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Energy Security and Climate Change Policy in the OECD:
The Political Economy of Carbon-Energy Taxation by
Érick Lachapelle
A thesis submitted in conformity with the requirements
for the degree of Doctor of Philosophy
Graduate Department of Political Science
University of Toronto
Copyright by Érick Lachapelle 2011
2011-02-16
ii
Energy Security and Climate Change Policy in the OECD:
The Political Economy of Carbon-Energy Taxation
by
Érick Lachapelle
A thesis submitted in conformity with the requirements
for the degree of Doctor of Philosophy
Department of Political Science
University of Toronto
February 2011
Abstract
Why do countries tax the same fuels at widely different rates, even among similarly
situated countries in the global political economy? Given the potentially destabilizing
effects of climate change, and the political and economic risks associated with a reliance
on geographically concentrated, finite fossil fuels, International Organizations and
economists of all political stripes have consistently called for increasing tax rates on
fossil-based energy. Despite much enthusiasm among policy experts, however, politicians
concerned with distributional consequences, economic performance and competitiveness
impacts continue to be wary of raising taxes on carbon-based fuels.
In this context, this thesis investigates the political economy of tax rates affecting the
price of fossil fuels in advanced capitalist democracies. Through an examination of the
political limits of government capacity to implement stricter carbon-energy policy, as
well as the identification of the correlates of higher carbon-based energy taxes, it throws
new light on the conditions under which carbon-energy tax reform becomes politically
possible. Based on recent data collected from the OECD, EEA and IEA, I develop an
estimate of the relative size of implicit carbon taxes across OECD member countries on
six carbon-based fuels and across the household and industrial sectors. I exploit large
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cross-national differences in these carbon-energy tax rates in order to identify the
correlates of, and constraints on, carbon-energy tax reform. Applying multiple regression
analysis to both cross-section and time-series cross-sectional (TSCS) data, this thesis
leverages considerable empirical evidence to demonstrate how and why electoral systems
matter for energy and environmental tax policy outcomes.
In particular, I find considerable empirical evidence to support the claim that systems of
proportional representation (PR), in addition to the partisan preferences of the electorate,
work together to explain differential rates of carbon-energy taxation. By opening up the
ideological space to a broader spectrum of “green” parties, I argue that PR systems create
a favourable institutional context within which higher rates of carbon-energy taxation
become politically possible. After specifying a key causal mechanism within different
types of electoral systems – the seat-vote elasticity – I argue further that, voters in
disproportional systems actually have more leverage over politicians, and that an increase
in environmental voting can have an impact on rates of carbon energy taxation, even in
the absence of PR. While the accession to power of green political parties in PR systems
is more likely to lead to higher rates of carbon energy taxation, voting for green parties in
highly disproportional systems creates incentives for other parties to adopt “green”
policies, leading to a similar outcome. In this way, the effect of green votes and green
seats will have the opposite effect on policy according to the type of electoral system in
use.
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Acknowledgements
I am extremely grateful to several people that provided generous help and support over
the course of this PhD journey. In particular, I owe much to Professor Stephen Clarkson,
without whom I would not have found myself at the University of Toronto, and Professor
Richard B. Day, an intellectual inspiration early on in my University of Toronto
academic career.
A very big thanks goes to the members of my committee: Louis W. Pauly, Neil Nevitte,
and Rodney Haddow. As my supervisor, Professor Pauly provided excellent guidance
and support, both intellectually and professionally. Always pushing me to clarify my
thinking, Professor Pauly proved to be a great help as a pedagogical and professional
advisor. Professor Nevitte proved to be an excellent mentor, educator and supporter,
while my research benefited a great deal from many stimulating discussions with
Professor Haddow. It was an honour to work with these excellent scholars.
Beyond my committee a number of other professors offered generous time and feedback
along the way. At the University of Toronto: Steven Bernstein, Christian Breunig, Don
Dewees, Danny Harvey, Matt Hoffman, Larry LeDuc, Doug Macdonald and Grace
Skogstad deserve particular mention. Other members of the academic community were
also kind enough to read my work and provide very helpful comments. I am especially
indebted to John Allan, Kathy Harrison, Mike Kraft, Caroline Kuzemko, James
Meadowcroft and Barry Rabe. These scholars provided generous comments and their
own work was a tremendous source of inspiration. Finally, I should also like to thank my
new colleagues at l’Université de Montréal for immediately making me feel welcome in a
leading Canadian research institution.
If a journey is best measured in friends than in miles, my time at the University of
Toronto ranks as one of the best in my life. I cannot acknowledge all of them here, but
should make particular mention of Chris Alcantara, Amar Athwal, Sebastian Baglioni,
Chris Cochrane, Joëlle Dumouchel, Gabe Eidelman, Bill Flanik, Vic Gomez, Josh
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Gordon, David Houle, Mike Painter-Main, Vincent Pouliot, Mark Purdon, Reuven
Schlozberg, Anthony Sealey, Deb Thompson, and Ruben Zaiotti. Thanks to Matt Cripps,
Marcus Coutou, Joe Fagioli and Chris Palis for keeping me grounded through it all.
I also gratefully acknowledge financial support from the Social Sciences and Humanities
Research Council of Canada, the Ontario Graduate Scholarship Program, the School of
Graduate Studies, the Royal Bank of Canada, and the Department of Political Science at
the University of Toronto. This support provided me with the means to finance my
research and was thus instrumental in the completion of this project. I should finally like
to thank Laine Russ of the Data Library Services at Robarts Library for all her assistance,
as well as Joan Kalis, Carolynn Branton, Leanne Thomas and all of the administrative
support offered by the Department of Political Science. The essential work of these
individuals too often goes unrecognized in a large institution like the University of
Toronto, and they deserve my special thanks. I am happy to count these wonderful people
among my friends.
Finally my deepest gratitude goes to my immediate family – mom, dad, sister and her two
amazing boys – who loyally supported me throughout all of my academic studies. In
particular, my parents have consistently been a wonderful source of inspiration and
taught me to never give up. I dedicate this work to them – my dear mother and father –
among the most hard working and honest people I know, without whose care and
encouragement none of this would have ever been possible.
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Table of Contents
Abstract………………………………………………………….……………………….ii Acknowledgements……………………………………………………………………...iv List of Tables…………………………………………………………………………...viii List of Figures…………………………………………………………………………….x Acronyms………………………………..……………………………………………....xii
1. ENERGY SECURITY, CLIMATE CHANGE, AND THE POLITICAL ECONOMY OF TAXING FOSSIL FUELS 1
1.1. CONTEXT: COMPLEX PROBLEMS AND COMMON CHALLENGES IN THE OECD 1 1.1.1. COMMON SOLUTIONS TO THE PROBLEMS OF ENERGY SECURITY AND CLIMATE CHANGE 4 1.1.2. THE POLITICAL LIMITS TO TAXING CARBON 7 1.2. PUZZLE: CROSS-NATIONAL DIFFERENCES IN FOSSIL FUEL TAXATION 11 1.3. TOPIC, RESEARCH QUESTIONS AND PURPOSE 12 1.4. SCOPE 13 1.5. LITERATURE REVIEW 16 1.5.1. THE COMPARATIVE POLITICS OF CARBON TAXATION – WHAT DO WE KNOW? 17 1.5.2. THE ROLE OF POLITICAL INSTITUTIONS 24 1.6. THEORETICAL FRAMEWORK AND ASSUMPTIONS 27 1.7. THEORETICAL ARGUMENT 34 1.8. CHAPTER SUMMARY 39
2. THE ECONOMICS OF PRICING CARBON 40
2.1.1. FOSSIL FUEL EXTERNALITIES: CLIMATE CHANGE 43 2.1.2. FOSSIL FUEL EXTERNALITIES: ENERGY SECURITY 55 2.2. INTERNALIZING EXTERNALITIES: PRICING CARBON 57 2.2.1. OPTIONS FOR PRICING CARBON 59 2.2.3. CARBON TRADING 65 2.2.4. COMPARING TAX AND TRADE 66 2.3. ISSUES IN THE DESIGN OF A CARBON TAX 69 2.4. THE POLITICAL ECONOMY OF INSTRUMENT CHOICE 75
3. THE POLITICAL LIMITS TO IMPLEMENTING CARBON TAXES 79
3.1. TAKING STOCK OF EXPLICIT CARBON TAXES IN THE OECD: A CRITICAL APPRAISAL 81 3.2. TRENDS IN EXPLICIT CARBON TAXES 83 3.3. CASE STUDY: MAJORITARIAN ELECTORAL SYSTEMS AND THE BRITISH COLUMBIA CARBON TAX 96
4. ENERGY TAXES AS IMPLICIT CARBON TAXES: EXPLORING CROSS-NATIONAL DIFFERENCES 110
4.1. ENERGY TAXES VS. CARBON TAXES 112 4.2. ENERGY TAXES AS IMPLICIT CARBON TAXES 114 4.3. WHY STUDY IMPLICIT CARBON TAXES? 118 4.3.1. THEORETICAL IMPORTANCE FOR POLITICAL SCIENCE 120 4.3.2. PRACTICAL IMPLICATIONS FOR POLICY 122
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4.4. ESTIMATING IMPLICIT CARBON TAXES 127 4.5. DESCRIPTIVE ANALYSIS 132 4.5.1. DIFFERENCES ACROSS FUELS 135 4.5.2. DIFFERENCES ACROSS SECTORS 137 4.6: THE PUZZLE: DIFFERENCES IN IMPLICIT CARBON TAXES ACROSS COUNTRIES AND OVER TIME 139 4.6.1: CROSS-NATIONAL DIFFERENCES IN IMPLICIT CARBON TAXES 141 4.6.2: IMPLICIT CARBON TAXES OVER TIME 143 4.6.3: THE REAL PUZZLE 145
5. EMPIRICAL ANALYSIS: THE POLITICAL ECONOMY OF TAXING FOSSIL FUELS 147
5.1: ARGUMENT 148 5.2: HYPOTHESES 150 5.3: DATA AND METHODS 151 5.4: EMPIRICAL ANALYSIS AND EVIDENCE 155 5.5: IMPLICIT CARBON TAXES ON FUELS USED BY INDUSTRY 156 5.5.1:STEAM COAL 157 5.5.2: HEAVY FUEL OIL 177 5.6. IMPLICIT CARBON TAXES ON FUELS USED BY HOUSEHOLDS 195 5.6.1: DIESEL 206 5.6.2: GASOLINE 221 5.7: SUMMARY AND DISCUSSION 237
6. CARBON-ENERGY POLICY AT A CROSS-ROADS: PROSPECTS FOR THE FUTURE 243
6.1. KEY FINDINGS 244 6.2. CONTRIBUTIONS 248 6.3. THE WAY FORWARD 250
APPENDIX 1: VARIABLE DEFINITIONS 253
APPENDIX 2: OPERATIONALIZING THE DEPENDENT VARIABLE 258
APPENDIX 3: EMISSION FACTORS 266
BIBLIOGRAPHY 267
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List of Tables Table 1.1: Electoral system and the number of years with at least one
green party member in the elected legislature (1978-2006)..........35 Table 2.1.1.1: Highlights of possible climate impacts discussed by Stern……...52 Table 2.1.2.1: Crude oil imports (2006)..………………………………………..55 Table 2.2.4.1: Main features of carbon tax vs. cap-and-trade………………...…67 Table 3.2.1: Carbon taxes in selected OECD jurisdictions……………………86 Table 3.2.2: Carbon tax rates by fuel type, in current USD/tonne of CO2…….95 Table 3.3.1: Summary of tax departures………………………………………97 Table 3.3.1: Electoral competition in key coal and natural gas districts:
vote shares (in percentages)…………………………………….108 Table 4.4.1: Tax rates on Unleaded Gasoline in Canada (in CAD dollars)….128 Table 4.4.2: Tax rates on Natural Gas in Switzerland (in Swiss Francs)…….129 Table 4.4.3. Emission factors………………………………………………...130 Table 4.5: Implicit carbon tax (constant USD/tCO2) by fuel type (2006)....134 Table 4.5.1: Average implicit carbon taxes across OECD (2006), constant
USD/tCO2………………………………………………………136 Table 5.5.1.1: Summary statistics for coal tax regression models……………..164 Table 5.5.1.2: Coal tax regression models testing the ideological space
hypothesis (H2)…………………………………………………165 Table 5.5.1.3: Implicit carbon taxes on coal by left wing cabinet portfolios
and PR…………………………………………………………..169 Table: 5.5.1.4: Coal tax regression models testing the disproportional
constraints hypothesis (H3)……………………………………..171 Table 5.5.1.5: Robustness checks for (H2) in regression models of
square root coal tax with robust standard errors………………..175 Table 5.5.1.6: Robustness checks for (H3) in regression models of coal tax
with robust standard errors……………………………………..176 Table 5.5.2.1: Summary statistics for HFO tax regression models………….…183 Table 5.5.2.2: HFO tax regression models testing the ideological space
hypothesis (H2)…………………………………………………184 Table 5.5.2.3: Implicit carbon taxes on HFO by left wing cabinet portfolios
and PR….……………………………………………………….188 Table 5.5.2.4: HFO tax regression models testing the disproportional
constraints hypothesis (H3)……………………………………..189 Table 5.5.2.5: Robustness checks for (H2) regression models with
robust standard errors…………………………………………...193 Table 5.5.2.6: Robustness checks for (H3) regression models with
robust standard errors…………………...………………………194
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Table 5.6.1: Summary of variables and hypothesized relationships…………203 Table 5.6.2: Summary statistics for motor fuel tax regression models………204 Table 5.6.1.1: Diesel tax regression models testing the
ideological space hypothesis (H2)……………………………...209 Table 5.6.1.2: Diesel tax regression models testing the
disproportional constraints hypothesis (H3)……………………213 Table 5.6.1.3: Diesel tax regression models testing the electoral incentives
hypothesis (H4)…………………………………………………218 Table 5.6.2.1: Gasoline tax regression models testing the
ideological space hypothesis (H2)…………………………...…225 Table 5.6.2.2: Gasoline tax regression models testing the disproportional
constraints hypothesis (H3)…………………………………….229 Table 5.6.2.3: Gasoline tax regression models testing the electoral incentives
hypothesis (H4)…………………………………………………233 Table 5.7.1: Performance of primary research hypotheses across fuels……..240
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List of Figures Figure 1.1: World primary energy demand by fuel type in the IEA Reference
Scenario………………………………………………………………...…2 Figure 2.1.1.1: Changes in temperature, sea level and Northern snow cover……………44 Figure 2.1.1.2: Radiative forcing components…………………………………………...47 Figure 2.1.1.3: Temperature and CO2 concentration in the atmosphere…………………48 Figure 2.1.1.4: Atmospheric concentration of carbon dioxide…………………………..49 Figure 2.1.1.5: Global anthropogenic GHG emissions…………………………………..50 Figure 2.1.1.6: Global GHG emissions by source……………………………………….50 Figure 2.1.2.1: World price of oil (Brent Sweet Crude spot price)……………………...55 Figure 2.3.1: Setting the optimal carbon tax level……......…………………………….72 Figure 3.2.1: Percentage of fossil energy in electricity production……………….…...89 Figure 3.2.2: Change in nominal tax rate over time……………………………………93 Figure 3.2.3: Change in real tax rate over time………………………………………...93 Figure 3.3.1: Tax rates applied under BC’s carbon tax by carbon content of fuels……99 Figure 3.3.2: Share of natural gas in BC mineral production…………………………102 Figure 3.3.3: Support for environmental taxation…………………………………….105 Figure 3.3.4: Geographical distribution of coal and gas in BC……………………….106 Figure 4.3.2.1: Gasoline price and tax differentials, in current USD (2008)…………..125 Figure 4.3.2.2: Total gasoline price by tax rate in current USD/L (2008)……………..126 Figure 4.5.1: Average implicit carbon taxes (USD/tCO2) by fuel, OECD (2006)…...137 Figure 4.5.2: Mean tax rate across sectors in constant (2000) USD/tCO2……………138 Figure 4.6.1: Implicit carbon tax rates for selected OECD countries (2006)…………142 Figure 4.6.2: Implicit carbon taxes on coal, in selected OECD countries…………….144
Figure 5.3: Mean income of OECD countries (2006)………………………………154 Figure 5.5.1.1: Implicit carbon tax rate on steam coal used by industry……………….158 Figure 5.5.1.2: Total coal production………………………………………………...…159 Figure 5.5.1.3: Implicit carbon tax on steam coal by level of corporatism…………….161 Figure 5.5.1.4: Implicit carbon tax rate on steam coal by electoral regime (H1)………162 Figure 5.5.1.5: The marginal effect of left party cabinet portfolios under PR (H2)……168 Figure 5.5.1.6: The marginal effect of left wing cabinet portfolios in disproportional
systems (H3)……………………………………………………………172 Figure 5.5.2.1: Implicit carbon tax rate on heavy fuel oil used by industry……………178 Figure 5.4.2.2: Net crude oil exports in selected OECD countries……………………..179 Figure 5.5.2.3: Implicit carbon tax on HFO by level of corporatism…………………..181 Figure 5.5.2.4: Implicit carbon tax rate on HFO by electoral regime (H1)…………….182 Figure 5.5.2.5: The marginal effect of left party cabinet portfolios under PR (H2)……187 Figure 5.5.2.6: The marginal effect of left wing cabinet portfolios in disproportional
systems (H3)…………………………………………………………....190
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Figure 5.6.1.1: Implicit carbon tax on diesel fuel for household consumer use………..206 Figure 5.6.1.2: Implicit carbon tax rate on (non-commercial) diesel fuel by
electoral regime (H1)…………………………………………………...207 Figure 5.6.1.3: The marginal effect of green parties in the legislature under PR (H2)...211 Figure 5.6.1.4: Marginal effect of green seat share in disproportional systems (H3)….215 Figure 5.6.1.5: Marginal effect of green/new-left votes in
disproportional systems (H4)…………………………………………..220 Figure 5.6.2.1: Implicit carbon tax rate on gasoline for private household use………..222 Figure 5.6.2.2: Implicit carbon tax rate on gasoline by electoral regime (H1)………...223 Figure 5.6.2.3: The marginal effect of green/new left party cabinet portfolios
by electoral regime (H2)……………………………………………….227 Figure 5.6.2.4: The marginal effect of green/left cabinet in
disproportional systems (H3)…………………………………………..231 Figure 5.6.2.4: Marginal effect of green votes in disproportional systems (H4)………235
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Acronyms BC British Columbia Btu British thermal unit CO2 Carbon dioxide CBO Congressional Budget Office EIA Energy Information Administration EC European Commission ETS Emissions Trading Scheme EU European Union FE Fixed effects FPTP First past the post GCF Gross calorific value GDP Gross Domestic Product GHG Greenhouse gases GWh Gigawatt hour HFO Heavy fuel oil IEA International Energy Agency IPCC International Panel on Climate Change IMF International Monetary Fund kcal Kilocalories kt Kilotonne ktoe Kilotonnes of oil equivalent kWh Kilowatt hour LDV Lagged dependent variable LFO Light fuel oil LOSU Level of scientific understanding LSDV Least squares dummy variable Mtoe Million-tonnes of oil equivalent m3 Cubic metres NCV Net calorific value NGO Non-Governmental Organization NRC National Research Council NRTEE National Roundtable on the Environment and the Economy OECD Organization for Cooperation and Economic Development OLS Ordinary least squares PCSE Panel-corrected standard errors Pg Pico grams ppm Parts per million PPP Purchasing Power Parity PR Proportional representation Qbtu Quadrillion British Thermal Units SMP Single member plurality Tg Terra gram toe Tonnes of oil equivalent UNFCCC United Nations Framework Convention on Climate Change W m2 Watts per square metre
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Chapter 1: Introduction
1. Energy security, climate change, and the political economy of taxing fossil fuels
1.1. Context: complex problems and common challenges in the OECD
Meeting growing energy needs while minimizing the environmental impact of fossil fuel
dependence is one of the central governance challenges of the 21st century. Economic
growth, industrialization, rising population levels and the increased use of electronic and
other energy-consuming devices are fueling rapid increases in energy consumption the
world over. According to the IEA’s Reference Scenario,1 global energy demand is
expected to increase 40 per cent, from 12,000 million tonnes of oil equivalent (Mtoe) in
2007 to 16,800 Mtoe in 2030, with fossil fuels accounting for more than three quarters of
this growth (IEA, 2009b: 42 and 74). Unless governments dramatically change course,
global demand will place additional pressure on already strained energy delivery
infrastructure and finite supply, inevitably raising the price of fossil fuels, the continued
use of which promises to add millions of additional tonnes of CO2 into the current
atmospheric stock. The 2009 IEA Reference Scenario, and the projected dominance of
fossil fuels, is depicted in Figure 1.1.2
1 The IEA reference scenario presents a baseline picture of how global energy markets are likely to evolve in the absence of changes to existing government policies. It thus presents a forecast of trends under a “business as usual” scenario. 2 The dotted line, “WEO-2008” is the Reference Scenario developed in 2008. The 2009 Reference Scenario has slightly revised the forecast in energy demand in light of the impact of the global recession.
2
Figure 1.1: World primary energy demand by fuel type in the IEA Reference Scenario
Source: IEA (2009b: 75) As can be seen in Figure 1.1, global energy demand is expected to increase about 40%
over the next twenty years as emerging economies in China and India continue to
industrialize at unprecedented rates. Even after the recession of 2009 is accounted for,
revised estimates are just a few percentage points lower than the WEO 2008 Reference
Scenario, indicated by the dotted line in Figure 1.1. Thus, in the business-as-usual
scenario such scarce fossil fuels as oil and gas make up an increasing share of the total
energy mix, while the use of coal also continues to rise.
In light of global energy challenges, like peak oil (Campbell, 1997; Deffeyes, 2001) and
peak gas (Darley, 2004) this reliance on finite fossil fuels to meet growing energy
demand is disconcerting. From an energy security perspective, economic and
geopolitical concerns regarding continued dependence on imported energy, and the
concentration of proven reserves in unstable regions of the world (IEA, 2005:56),
constitute a strategic weakness for energy intensive and energy-importing states (Adelle
et al. 2009; Yergin, 2006). As noted by Hughes (2006) – a geologist with Natural
Resources Canada – the issue is not just one of scarce resources, but also one of
deliverability. Even if Canada quadrupled production of its tar sands, for instance, the
added production would only represent 5% of the IEA’s projected demand. Thus, the real
3
questions are how fast can oil resources be converted to supply in the face of growing
demand, and at what cost? In addition, most of the remaining reserves are not found in
Canada, and some fear that a dependence on external sources of supply, particularly from
the Middle East and parts of Africa, challenge a variety of “national interests” held by
Western governments. For instance, energy supply disruptions threaten continued
economic growth, and funneling currency to petro-states could threaten the
democratization and counterterrorism objectives of the U.S. and its Western allies
(Deutch and Schlesinger, 2006; Downs, 2006). Such concerns are particularly acute in
energy dependent parts of Europe and the U.S., prompting former U.S. President George
W. Bush to say, “I’ve often said one of the worst problems we have is that we’re
dependent on foreign sources of crude oil, and we are […] we need alternative sources of
energy” (quoted in Collina, 2005, emphasis added).
From an environmental perspective, the continued reliance on fossil fuels, especially an
increase in the use of coal, presents an additional risk. Although coal is the one fossil fuel
for which the world has comparatively large remaining reserves, continued use of this
relatively cheap polluting fuel threatens to emit millions of additional tonnes of carbon
dioxide to the existing stock, which according to some is already too high (Chandler,
2009; Hansen et al. 2008; Harvey, 2010). For this reason, global climate change
continues to attract much attention as potentially one of the most significant economic
and environmental threats facing humanity today (IPCC, 2007b; Stern, 2006).
Notwithstanding some of the recent controversy over a series of leaked emails from the
University of East Anglia, in which climate scientists were caught in a maelstrom of
accusations regarding hidden and manipulated data (Katz, 2010),3 over 97 per cent of
actively publishing climate scientists agree with the main conclusion of the IPCC;
namely, that human activity is responsible for observed increases in mean global
temperatures (Anderegg et al. 2010). Moreover, thousands of the world’s leading climate
scientists who make up the IPCC are calling for massive and immediate reductions to
greenhouse gas (GHG) emissions in order to avert tipping points (Lenton et al. 2008) and
3The subsequent public inquiry into the “Climategate” ordeal has since cleared climate scientists of any wrongdoing (Adam, 2010).
4
the potentially catastrophic consequences of climate change (IPCC, 2007b; Hansen et al.
2008; Meinshausen et al. 2009). As a result, reducing the primary cause of human-
induced emissions – from burning fossil fuels – is now commonly identified as an
important objective of governments – at all levels – around the world (Pew, 2010).
1.1.1. Common solutions to the problems of energy security and climate change
Although energy security and climate change pose very different problems for
governments, they converge on the solutions commonly proposed to address them (c.f.
Adelle et al. 2009; IEA, 2007a; IMF, 1994; 2008). For instance, policies that discourage
the demand for fossil fuels promote energy conservation (and a reduction in dependence
on energy imports) greater efficiency (and technological innovation) as well as a
reduction in emissions from fossil fuel combustion. For these reasons, economists of all
political stripes – who otherwise rarely agree on anything – have become fervent
advocates of increasing the price of fossil fuels, and almost uniformly, support a carbon
tax.
Among the most prominent carbon tax proponents is former chief economic advisor to
George W. Bush, Gregory Mankiw, who in 2006 proposed an increase in the gas tax of
$1 per gallon which is equivalent to a carbon tax of over $100 per tonne of CO2, or
roughly $367 per tonne of carbon (Mankiw, 2006).4 Evidence of a “carbon tax
consensus” can be found on Mankiw’s pro-carbon tax blog, The Pigou Club, which lists
such prominent economists as William Nordhaus, Martin Feldstein, Alan Greenspan,
Gary Becker, Paul Krugman, Thomas Friedman, Richard Posner, Joe Stiglitz, Robert
Samuelson, Paul Volcker, and Lawrence Summers, among others, as supporters of
increasing taxes on fossil fuels. Adding to the list, a recent poll of economists by the
Wall Street Journal found a majority of economists agreed that a carbon tax is the best
4 Authors own calculation based on an emission factor of 8.8 kg of carbon dioxide per gallon of gasoline using mission factor from the U.S. Environmental Protection Agency (EPA, 2005). To convert from a tax on carbon dioxide to an equivalent tax on carbon, multiply the former by the molecular ratio of CO2 to carbon (44/12).
5
way to encourage investment in alternative energy (Izzo, 2007). Even the right-leaning
American Enterprise Institute (AEI) has published several endorsements of a carbon tax
(Green et al. 2007; Hassett and Metcalfe, 2006). Such evidence highlights the extent to
which an ideologically diverse group of economists – from Nobel Prize winning
conservative economist Garry Becker, to left-leaning economists Paul Krugman and
Joseph Stiglitz – have united under the banner of putting a tax on carbon.
To be sure, part of the reason for its intellectual appeal is rooted in the ability of the
carbon tax to contribute not only to environmental objectives, but to national security
goals as well. As noted by Becker (2009):
A tax on carbon emissions from business and household production would not only help reduce global warming […] but it would also lower the world prices of these fuels through reducing the demand for fossil fuels. Lower prices would cut the revenues received by Middle Eastern states from the sale of oil and natural gas. This is why a carbon tax receives support from many environmentalists and national security advocates.
Framed in terms of national security, carbon taxes garner additional appeal in energy-
dependent states. By raising the price of gasoline and other fossil fuels across the entire
economy (i.e. all sectors including households), some of the costs of foreign energy
dependence (e.g. vulnerability to supply disruptions, financing of the military to protect
infrastructure) can be internalized, all while encouraging energy conservation, investment
in domestic energy alternatives, fiscal room for governments and reductions in emissions
of CO2 (IMF, 1994). In addition, it is often suggested that a carbon tax provides a way of
diminishing OPEC’s rents, which accrue each time the price of fossil fuels rise, thus
diminishing the prospect of petrol dollars being used against Western interests (Liski and
Tahvonen, 2004).5
In addition, increasing tax rates on fossil fuels appeals to environmentalists. Indeed,
many popular voices in the environmental community have been converted to the free-
5 It would take an equivalent carbon tax of close to $400 USD/ tonne of CO2 to match the sharp rise in gasoline prices experienced in the U.S. between February 2008 and July 2008 (about $3.5 per gallon).
6
market fundamentalism of economists, and have joined the choir advocating an increase
in taxes on energy and fossil fuels (e.g. Brown, 2003; Suzuki and DesRosiers, 2007;
Hansen, 2008). According to its proponents, a revenue-neutral carbon tax shift is the
most “rational” policy (Newbery, 2005), holding the promise of encouraging investment,
innovation and productivity (Lanoie et al. 2008; Martin and Kemper, 2010), more jobs
(Goodstein et al. 2010), all while improving the environment and making the tax system
more efficient. As a result, it is sometimes argued that, if properly designed, carbon taxes
can yield a strong “double dividend” in terms of realizing net welfare gains in addition to
environmental benefits (Bento and Jacobsen, 2007). For all these reasons, advocates
claim that carbon taxes are simply the right thing to do.
Despite their broad intellectual appeal and near universal support from economists –
sometimes perceived as having substantial influence on policy (Babb, 2001; Blyth, 2002;
Fourcade, 2006; Hall, 1989) – governments have been markedly less enthusiastic about
implementing carbon taxes, energy taxes, or other types of climate policy, for that matter.
Indeed, while carbon and energy tax shifts are the most frequently advocated response to
climate change and energy security,6 relatively few jurisdictions across the OECD have
implemented the recommended tax reforms,7 and several high profile energy tax
proposals have failed, oftentimes quite miserably.8 Moreover, as documented in Chapter
3, even those countries that have implemented carbon tax proposals with some degree of
success generally fail to apply uniform rates on carbon economy wide, the sin qua non of
a pure carbon tax. Such a state of affairs raises the question: why is the most frequently
advocated, straightforward and rational policy response to climate change also the
most difficult? 6 In addition to the wealth of supporting evidence provided on the web (see Mankiw’s Pigou Club Manifesto), several studies on expert opinion empirically document the preference of economists for carbon taxes. See for instance GAO (2008), Haab (2009); Holliday et al. (2009), Izzo (2007). 7 To date, only six OECD jurisdictions have implemented the economists preferred policy of a broad-based, revenue-neutral carbon tax; Finland (1990), Sweden (1991), Norway (1991), Denmark (1992), the Netherlands (1996) and British Columbia (2008) fall into this category. Other examples of broader environmental tax shifts include Germany (1999) and the United Kingdon (2001). 8 Notable cases of ill-fated carbon/energy tax proposals include U.S. President Clinton’s proposed Btu tax (1993), Italy’s suspended carbon tax (2000), New Zealand’s abandoned carbon tax following the re-election of a minority government (2005), the dismal election performance of Canadian Liberal Party Leader Stephen Dion, who campaigned and lost on a carbon tax propsosal (2008), and the recent French constitutional court decision to strike down President Sarkozy’s carbon tax plan.
7
1.1.2. The political limits to taxing carbon Underestimating the political difficulty of responding to climate change and of
implementing a carbon price is common in social science (Rabe, Lachapelle and Houle,
forthcoming), and the case of energy taxation is no exception. To be sure, the
conventional wisdom on the problem of climate change is that it is, first and foremost, a
global problem, in both its causes and consequences, thus requiring an international
solution. However, this approach raises problems of collective action and thorny
questions regarding how to equitably share the mitigation burden (Stern, 2006). Unlike
localized transboundary pollution issues, climate change is truly a global problem, insofar
as a tonne of CO2 emitted will have the same effect on global climate, regardless of
whether it originated from Shanxi or Alberta. Since it is total CO2 emissions from all
countries that is relevant for the climate, coordinated emission reductions are required
around the globe; otherwise, unilateral actions have no substantive impact on the global
stock of atmospheric levels of CO2.9 But cooperation on this issue at the international
level poses a major challenge in terms of getting a large number of sovereign states –
each with varying vulnerabilities to climate change and emission trajectories – to agree
(Hoffmann, 2005; Stern, 2006: 450). As argued by Olson (1965), the larger the group, the
smaller the likelihood of meeting the need for collective goods through voluntary (or
unilateral) actions alone.10 Ceteris paribus, as groups grow in size, the benefits of action
become smaller for individual members, decreasing the incentives for unilateral or
collective action.11 Applied to the global public good nature of a stable climate, rational,
self-interested countries will have an incentive to free-ride on the mitigation policies of
9 As argued by Pezzey (1992) and others, unilateral carbon taxes are largely ineffective, even if coordinated among the OECD, given the relatively small and decreasing share of emissions originating from these countries. 10 Though from a different ontological position, Hoffmann (2005) makes a similar point, arguing that universality enhances the chances of political stalemate due the multiplicity of actors and interests at the negotiating table. 11 In his later work, Olson (1971) points out that the resulting under-supply of collective goods is particularly a problem at the international level. Astutely anticipating the outcome of the recent “Copenhagen Accord,” where states decided to change tracks on multilateral negotiation of mitigation targets, opting instead for a bottom up approach where countries unilaterally set targets and “opt in” to the regime, Olson points out that international cooperation largely occurs through “independent contributions,” or a two-stage process where countries agree in principle to cooperate for some purpose, and then determine the extent of cooperation individually (Olson, 1971: 868).
8
others, and have absolutely no incentive to take unilateral action in the absence of a
coordinated global response.12
In this sense, responding to climate change can be likened to a prisoner’s dilemma,
forcing governments into a trade-off between collective and individualistic strategies
(Midttun and Hagen, 1997). To the extent that an increase in carbon energy taxation will
place domestic industry at a competitive disadvantage, unilateral action will penalize first
movers, and reward non-cooperation. Thus, even where public support for climate action
is high, governments are constrained by what they can unilaterally implement
domestically by this dilemma. On the other hand, dissimilarities at the international level
– in terms of abatement costs, support for environmental initiatives and ecological
vulnerabilities – will make unanimous multilateral agreements extremely difficult to
achieve (Midttun and Hagen, 1997). From this perspective, the effect of reducing local
emissions in the absence of collective action is to impose the environmental externalities
generated in other countries on one’s own population, and to impose political costs on
domestic political actors who are unlikely to accept them (Pardy, 2007). In these lights,
the question of why energy tax reform is so difficult is turned on its head. Why would
any country unilaterally raise taxes on fossil fuels in the first place?
In addition to the problem of collective action at the international level, governments also
face a series of domestic constraints. Responding to the threat of climate change is
politically complex because the causes (and effects) of climate change (policy) are
inextricably tied to modern lifestyles (consumption habits) and to the functioning of the
modern industrial economy. Given the link between fossil fuel consumption and
economic development, policy-makers have had a century-long interest in promoting the
discovery and use of fossil fuels, with a favourable mix of large subsidies and
disproportionately low taxes. By making fossil fuels cheaper and allowing individuals
12 The requirement of global coordinated action has served as the primary factor used by governments in Canada and the U.S. to legitimate a very slow policy response, and weak emission reduction commitments, to address climate change. For instance, while the U.S. is unwilling to commit to emissions reductions unless China does, Canada has said in the absence of U.S. action, Canadian mitigation efforts are futile (Prentice, 2009).
9
and firms to emit millions of tonnes of CO2 into the atmosphere without cost,
governments have effectively subsidized the use of carbon-based fuels and encouraged
their over-consumption (Rivers and Sawyer, 2008).13 As a consequence, these policies
have generated path-dependent dynamics like those described by Pierson (2000), creating
vested interests (constituencies) and economic incentives that militate against path-
departing processes and policy shifts like raising taxes on carbon.14 Thus, existing
government policy will be constrained by domestic interests that profit from the
consumption of fossil fuel energy, and other domestic interests that have become
dependent on relatively cheap forms of heavily polluting fuels.
Domestic energy producers and users, for instance, have an interest in keeping energy
taxes low, in order to control costs and maintain their share in international and domestic
markets. Indeed, the need to protect the competitiveness of domestic industry is one of
the most frequently cited economic barriers to unilateral implementation of higher taxes
on fossil fuels.15 In addition, some argue that unilateral carbon constraints can distort
competition in global markets, leading to “carbon leakage”16 and the proliferation of
emissions from pollution havens. According to this line of reasoning, there is no point in
unilaterally implementing climate policy in a single country, or a group of countries, if
such policy leads to the relocation of CO2 emissions to non-complying regions of the
world (Hoel, 1996). Finally, since carbon regulation policy necessarily imposes
concentrated costs on a small group of energy intensive and fossil fuel producing sectors,
these groups have greater incentive (and capacity) to mobilize against carbon tax
13 For instance, Boyd et al. (1995) find that given estimated damage costs, the price of fossil fuels are much lower than optimal. 14 Though external shocks may disrupt the “equilibrium,” and radically alter the course of policy development, policies create powerful economic and political constraints (in the form of constituencies and transaction costs) that complicate reform. According to this logic, such “feedback effects” from existing policies favour the enactment of path-dependent or path-consistent changes that seldom depart from existing institutional logics. This line of reasoning raises the theoretical question of under what conditions path-departing changes (like large increases in energy taxes) might occur? 15 See for instance: Baranzini et al. 2000: 401; Demailly and Quirion, 2005; Ekins and Barker, 2001:348-351; Ekins and Speck, 1999: 386; OECD, 2001: 71; OECD, 2006; Reinaud, 2008; Zhang and Baranzini, 2004: 512. 16 Carbon leakage refers to the potential for firms to relocate production to “pollution havens” in response to asymmetric carbon constraints and cost structures across countries.
10
increases, as compared to the broader (inter-temporally distributed) interests that would
share the benefit from a more stable climate (Svendsen et al. 2001).
Governments are further constrained by widespread public opposition to taxes, which is
in fact common across the OECD. Taxes impose visible costs on voters (Barthold, 1994)
who consistently express an aversion toward taxes (Steinmo and Tolbert, 1998). To the
extent that governments are primarily interested in maximizing electoral gains (Mayhew,
1974), increasing tax rates on fossil fuels is from this perspective politically difficult. For
this reason governments might be expected to eschew tax increases and avoid the
“politics of pain” (Pal and Weaver, 2003).
In sum, several factors at the domestic and international levels combine to constrain the
ability of governments to raise taxes on fossil fuels, and might lead to the expectation of a
convergence toward low rates of carbon energy taxation, particularly among advanced
industrial economies that have historically benefited from the exploitation of fossil fuels.
Concerns over international competitiveness further militate against abnormally high
taxes on common industry inputs, and incentives to free-ride suggest no country should
unilaterally raise the price of carbon-based fuels in the hopes of decreasing its own
emissions. Domestically, powerful industry groups and tax-weary voters are likely to
make increases in fossil fuel taxation politically difficult, especially if we assume self-
interested politicians are primarily interested in maintaining political power. Thus, from
economic (cost) environmental (emissions) and political (votes) perspectives,
governments are constrained in their ability to unilaterally raise taxes on fossil fuels, and
we should expect to see more convergence than divergence in tax rates applied to carbon
(especially among similarly situated – i.e. advanced industrial – countries in the OECD).
Indeed, for all these reasons, we should expect to see consistently low tax rates on
commonly used fossil fuels across the OECD.
11
1.2. Puzzle: cross-national differences in fossil fuel taxation
In light of the substantial domestic and international incentives to do nothing about
climate change and to keep energy prices low, and if a public choice view of
governments solely motivated by electoral incentives is assumed, one might expect to see
no real increase in taxes on fossil fuels in response to climate change or the energy
security issue. Given the general public’s aversion to taxes (Steinmo and Tolbert, 1998:
167), and the “pathological hatred” for taxes on motor fuels in particular (Hsu et al.
2008), one might expect to see no real differences in the taxation of commonly used fuels
across countries, and attempts to raise them should be politically very difficult.
Nonetheless, some countries have unilaterally imposed broad-based carbon taxes, raising
the total effective tax rate applied to various fossil fuels (See Chapters 3 & 4). Moreover,
effective tax rates on the same, commonly used fossil fuels vary enormously, even among
similarly situated countries in the OECD (Chapter 4).17
What factors explain the very large cross-national differences in tax rates applied to the
same fossil fuels? What drives (or enables) certain countries to implement higher energy
taxes? Conversely, what are the political barriers and constraints that prevent energy tax
reform? Are net energy-importing countries more likely to have higher tax rates on
particular fossil fuels, as the national security discourse suggests? Do domestic fossil
fuel energy producers constitute a barrier to higher taxes on particular carbon-based
fuels? Precisely how and why countries differ in the tax rates they impose on carbon-
based fuels is the empirical focus of this dissertation.
17 These non-trivial differences are further explored in subsequent chapters.
12
1.3. Topic, research questions and purpose
In the context of common pressures (to do something about climate change or hedge
against rising fossil fuel scarcity) and common constraints (in terms of incentives to
maintain the status quo and free-ride), this dissertation explores the political determinants
of large cross-national differences in tax rates applied to carbon-based fuels, the
combustion of which is the single largest source of aggregate GHG emissions, and the
reliance on which is increasingly seen as a strategic weakness for importing states.
Applying a comparative analysis framework to exploit cross-national differences in tax
rates on fossil fuels, the goal is to answer the two following questions:
1. How are fossil fuels taxed in the OECD? 2. Why are the same fossil fuels taxed at widely different rates, even among
similarly situated countries in the global political economy?
Moving beyond the existing literature, which is often limited by small n country
comparisons or a focus on just one (usually gasoline) fossil fuel, I examine the role of
electoral systems in shaping the incentives and ability of political parties to implement
increases in rates of carbon energy taxation. This answer helps to shed some light onto
the broader issue of why – despite overwhelming advocacy from high-ranking
economists – energy tax reform appears so difficult, or conversely, why – given
international and domestic incentives to keep taxes low and free-ride on the Earth’s
climate – countries unilaterally impose higher tax rates on fossil fuels in the first place.
To be sure, the empirical core of the analysis employs mostly quantitative techniques,
allowing for an identification of trends in the data. The purpose is thus to search for
general patterns – common obstacles and conditions – that might facilitate the imposition
of taxes on fossil fuels. With a larger number of cases, the analysis is able to gain
leverage on numerous independent variables than has so far been attempted in the carbon
tax literature. But this analytical breadth does come at the cost of decreased depth, and
careful attention to detail, context and complexity. While much of the detailed analytical
case study work has already been completed in the literature, the findings of this project
13
contribute by bringing some theoretical parsimony to the comparative study of carbon
taxes, and by suggesting new cases deserving of closer study.
In the context of common challenges, like the revived discussion on energy security, and
the new discourse around climate change, this dissertation speaks to one of the classic
questions in comparative and international political economy. Indeed, like the work of
Gourevitch (1986), Katzenstein (1978) and Weiss (2003), I seek to explain why, in the
presence of common external policy challenges, individual countries respond in different
ways. The objective is to obtain a better sense of the general patterns in tax rates that
systematically emerge across a large number of countries, and to develop probabilistic
generalizations rather than a comprehensive account of the historically contingent and
context specific factors that converge in any one particular case.18 The ultimate purpose
of this research is to garner a better understanding of the political determinants – of the
general forces that shape and constrain taxes on fossil fuels – which can provide insight
into the “big questions” – under what conditions can we expect to successfully overcome
barriers to raising taxes on fossil fuels, and what kind of politics is required in order to
change the tax structure so that it is more consistent with economic efficiency and
compatible with efforts to reduce GHG emissions?
1.4. Scope
This project is concerned with the political economy of carbon taxation.19 It seeks to
explain differential rates in carbon energy taxes across countries, not the particular tax
mix (which is actually used as an independent variable). The focus is not on the politics
18 Being one of the first systemtic, comprehensive accounts of implicit carbon energy taxation, I leave the detailed tracing of causal mechanisms for future work. 19 In terms of scope, the analysis is restricted to a focus on energy taxes affecting the price of carbon-based fuels. Although other types of policies, like subsidies, affect the price of carbon, due to time constraints, and for reasons of data availability, energy subsidies for fossil fuels are left out of the present analysis. Apart from time, the primary reason for this decision is based on the fact that, at present, systematically collected, cross-national data on fossil fuel energy subsidies that is comparable across countries is currently unavailable. Indeed, governments are especially reluctant to disclose information on subsidies to the fossil fuel industry, like tax exemptions, though recently some advances have been made in collecting this type of information (Earth Track; IEA, 2010; OECD, 2010; World Bank et al. 2010). Given the size of fossil fuel subsidies and their importance for energy and fossil fuel prices, future work in this area is highly desirable and can compliment the present research.
14
of instrument choice, although this topic is briefly considered in a discussion of carbon
taxes and carbon trading in Chapter 2 and raised in the Conclusion. Rather, the primary
concern is with the politics and economics underlying one type of market-based
instrument (MBI) that is most often used by all governments – consumption taxes. To the
extent that taxes on energy consumption have important implications for other areas of
public policy – e.g. social and economic policy – a study of carbon energy taxation can
link and speak to debates surrounding globalization (Hays, 2003; Swank, 2006), the
politics of redistribution (Garrett and Mitchell, 2001; Iversen and Soskice, 2006), and the
financing of the welfare state (Kato, 2003). In terms of environmental and climate policy,
energy taxes are relatively understudied in the literature, even though they have important
economic and environmental effects (Giddens, 2009).20 For these reasons, the dissertation
focuses primarily on the tax approach to pricing carbon.
According to experts, taxation of carbon energy is the simplest and most efficient way of
reducing emissions and fossil fuel dependence, and is the most frequently advocated
policy instrument advocated by economists (Mankiw, 2007; Nordhaus, 2007),
climatologists / environmentalists (Hansen, 2008; Brown, 2003), International
Organizations (EC, 1991; IMF, 2008; OECD, 1997; World Bank, 2010) and even some
members of the business community (Hyndman, 2009; Clark, 2009), who otherwise
make strange bedfellows. Yet for the reasons mentioned above, it is also the most
politically difficult instrument to implement, as evidenced in both the relative
infrequency with which governments adopt carbon taxes, and in the significant
exemptions granted, if successfully implemented at all. From a political science
standpoint, the tax approach to pricing carbon thus raises fascinating questions regarding
20 It can be argued that tax rates on fossil fuels provide a reasonably good proxy for overall environmental policy in countries (c.f. Broz and Maliniak, 2007; Fredriksson and Millimet, 2007; Ward and Cao, 2010), especially when compared to other problematic indexes of environmental sustainability used in the literature (e.g. Cao and Prakash, 2010; Whitford and Wong, 2009). Even in cases where countries engage in emissions trading (e.g. EU-ETS), energy taxation provide a useful indicator of the price of carbon across different sectors of an economy. For instance, the EU ETS imposes a carbon price on a portion of the economy covering several thousand (i.e. about 10,000) installations in the energy and industrial sectors, while taxes on fossil fuels apply to all energy users. Second, the EU ETS is relatively new (implemented in 2005). This time point barely overlaps with the longer coverage provided by the study of energy taxes, which span a much longer time period.
15
the politics of imposing direct costs on social actors by raising effective rates of carbon
energy taxation.
Unlike most other political science research on carbon taxes, and for reasons that will
become clear in Chapter 4, I examine all energy taxes affecting the price of fossil fuels,
not just those explicitly labeled “carbon taxes.” Indeed, carbon taxes currently
implemented in OECD jurisdictions are not pure Pigouvian taxes, and upon closer
scrutiny, lose their distinctiveness vis a vis more commonly found energy taxes. The
latter have similar economic and environmental effects in terms of raising the relative
price of carbon based fuels, and can thus be analyzed as a de facto carbon tax. In
addition, examining all taxes on fossil fuels provides a more comprehensive, valid
measure of the “effective” tax rate on carbon, allowing for a quantitative analysis of a
much larger number of countries, since all countries tax fossil fuels (to varying degrees).
The analysis of carbon energy tax data is divided into two main parts. In the descriptive
component (Chapter 4), I analyze tax rates on six fossil fuels in all countries for which
data are available from the IEA, which includes the 29 OECD member states.21 The
subsequent empirical analysis of the determinants of cross-national differences in these
tax rates (Chapter 5) is limited to four of the most commonly consumed fossil fuels by
industry (coal and heavy fuel oil) and households (diesel and gasoline) across a smaller
sub-set of these countries. The four fossil fuels were selected based on their uniform use
across all countries in the sample.22 The decision to restrict the empirical analysis to the
traditional 21 advanced industrial economies most frequently analyzed in the
comparative/international political economy literatures (Swank, 2006; Winner, 2005) is
done for reasons of data availability (for key independent variables), and in the interest of
comparing countries sharing a similar history involving a number of similar economic
21 The 29 OECD countries are: Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Korea, Luxembourg, Mexico, the Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. 22 All of the advanced industrial democracies use coal, heavy fuel oil, diesel and gasoline to varying extents. Light fuel oil and natural gas are more popular in some cases than others, posing some problems for comparison across all industrialized countries. A study of the four most common fossil fuels across industry and household sectors was also more feasible given the amount of analysis invested.
16
transformations occurring since the late 1970s. Moreover, a focus on the advanced
capitalist democracies holds potential income effects constant, while avoiding the
problem of comparing vastly different countries whose particular economic
circumstances can confound an analysis of the determinants of energy tax policy. A
further justification of the case selection is found in Chapter 5.
Finally, the analysis is temporally bounded between 1978-2006, a period for which most
of the data are available. The year 1978 provides a good starting point insofar as it
corresponds to the end of the second oil shock of the 1970s. The period 1978-2006 also
covers a number of temporally defined developments – e.g. economic recessions,
globalization, Rio Conference, Kyoto – that are potentially important in a study of tax
policy. In addition, the time period under study ends just as the EU-ETS emission trading
system began operations in 2005. Analyzing tax rates over this time period thus avoids
the complicated question of how energy tax structures interact with carbon trading
policies like the EU cap and trade regime.
1.5. Literature review
The politics of carbon energy taxation are covered by an enormous literature spanning a
broad range of academic disciplines. Rather than review all of this work, the following
section identifies two primary literatures of particular relevance to the present research
project – the comparative politics of carbon taxation (1.5.1), and the role of political
institutions (1.5.2). Insights from these literatures are used to inform the theoretical
framework (1.6) argument (1.7) and primary research hypotheses (1.8), presented below.
17
1.5.1. The comparative politics of carbon taxation – what do we know? Much of what we know about carbon taxes comes from the work of economists. Central
to this research is the question of optimal tax design for reducing emissions at least
aggregate social cost (e.g. Hoel, 1996; Oates, 1995; Parry, 1995; Sandmo, 1975; 1976) or
for balancing the tradeoff between economic efficiency and political feasibility
(Daugbjerg and Pedersen, 2004; Felder and Schleiniger, 2002). To this end, the economic
literature has primarily examined the likely effects of carbon taxes on, for instance:
aggregate emissions (Botteon and Carraro, 1993; Bruvoll and Larsen, 2004; Cournede
and Gallon, 2003; Enveldsen, 2005; Mathiesen and Mæstad, 2004; Speck et al. 2003);
industrial competitiveness (Demailly and Quirion, 2005; Jenkins et al. 2002; Mæstad,
2003); social incidence (Johnson et al. 1990; Zhang and Baranzini, 2004; Wier et al.
2005; Creedy and Sleeman, 2006); technological diffusion (Jaffe and Stavins, 1995;
Gerlagh and Lise, 2005; Vollebergh, 2007); and, overall economic cost (Andersen and
Ekins, 2009; Carraro and Siniscalco, 1993; Weyant and Hill, 1999; Barker and Ekins,
2004; Wissema and Dellink, 2007). Much of this work is primarily descriptive in nature,
describing carbon energy tax policy and commenting on environmental and economic
effects (Vehmas, 2005; Vehmas et al. 1999). Reflecting a preoccupation with economic
efficiency, and a normative commitment to prescribing policy that is consistent with this
ideal, this literature has also heavily debated the “Porter Hypothesis” (Porter, 1998;
Porter and Van Der Linde, 1995) as well as the potential for a “double dividend” (Pearce,
1991; Goulder, 1995; Bovenberg and de Mooij, 2001), which concerns the extent to
which carbon-energy taxes can lead to an improvement in social welfare in addition to
environmental benefits, by shifting the tax burden from income to environmental
externalities.
Rather than treat the effects of taxes as the main outcome to be explained, other work
models the primary causes of carbon energy taxes, in terms of both their design and
implementation. This literature spans both economics and political science and can be
sub-divided in three main traditions.
18
The first broad tradition is inspired by theories of public choice (Buchanan and Tullock,
1962; Downs, 1957; Olson, 1965) and the political economy of interest group politics
(Becker, 1983). This literature is primarily concerned with a seminal question asked by
Robert Hahn (1989) regarding how the patient followed the doctor’s orders. Writing at
the end of the 1980s, Hahn noted that despite the many books and articles written by
economists on the relative merits of incentive-based policy instruments, few governments
had actually used them, and even where implemented, their design significantly departed
“…from the role which economists have perceived for them” (Hahn, 1989: 96).
Sometimes called “execution deficits” (Schneider and Volkert, 1999) or “tax departures”
(Vehmas, 2005), this gap between economic prescriptions and political implementation
has turned Hahn’s original inquiry on its head, spawning an entire body of work asking,
“why did the patient not follow the doctor’s orders” (Kirchgassner and Schneider, 2003).
To answer this question, a typical public choice analysis first identifies four main actors
in the environmental policy field – voters, politicians, bureaucrats and industry groups –
and proceeds to examine their interests in the application of different policy instruments,
which is then taken as an explanation for a particular policy outcome.
This is the approach of a seminal paper by Buchanan and Tullock (1975) who provide a
formal model to show why command and control instruments are preferred to market
based instruments by business groups and bureaucrats. In a similar tradition, Svendsen et
al. (2001) employ Olson’s (1965) logic of collective action to explain differences in tax
rates applied to large and weakly organized consumer interests compared to the smaller
and more concentrated interests of industry groups. Their theoretical predictions are then
applied to the experience with carbon taxes in Scandinavian countries, with an emphasis
on Norway. Taking a slightly different tack, Pearce (2006) builds on Becker (1983) to
show that differences between public and private social welfare functions explains why
the UK government opted not to implement a true carbon tax, implementing instead the
Climate Change Levy as economically less efficient but politically more popular in its
design. Though much of the evidence is anecdotally drawn from a relatively narrow
sample of cases, this literature helps to specify the nature and role of government,
bureaucratic, voter and industry interests in the field of environmental policy. In so doing,
19
it also provides theoretically informed accounts of why energy tax reform is so difficult,
and why, given the political interests involved, carbon-energy taxes may be designed and
implemented inefficiently.
Like the public choice literature, political scientists have also tackled the question of why
carbon-energy taxes are never implemented true to the Pigouvian ideal, and the role of
industry interests play a key role in their analyses. Unlike the public choice literature,
however, political scientists pay much more attention to the role of institutions, political
parties and ideas. But while the political science research is relatively more empirically
focused, and is more causal/descriptive rather than prescriptive in its aims, it too tends to
focus on a relatively small number of carbon tax countries in its comparative analysis.
For instance, one of the first studies on the comparative politics of carbon taxes by
political scientists seeks to explain the first mover phenomenon, asking why (and how)
the Nordic governments in Sweden, Denmark, Norway and Finland unilaterally
implemented carbon taxes, in the absence of an international agreement to partition the
burden (Midttun and Hagen, 1997). Building on Rokkan (1966) Midttun and Hagen argue
that electoral incentives (particularly rising environmental concern and political parties
with a green profile) are responsible for pushing the Nordic governments to take an avant
garde position on environmental issues,23 while corporatist channels allowed industry to
substantially modify the design of carbon tax proposals. Together, both factors explain
how the Nordic countries were first to implement environmental policies while not
sacrificing their economies. In a similar vein, Kasa examines the gap between “ambitious
proclamations and less heroic practices” in terms of the numerous exemptions granted to
mainland carbon-intensive industry in Norway (2000). Preferring the analytical lens of
policy-networks to the relatively broader notion of corporatism, Kasa provides a more
detailed descriptive account of the privileged access to decision-makers these networks
provided, allowing mainland industry to block a proposed broadening of the Norwegian
carbon tax on three separate occasions (Kasa, 2000).
23 Midttun and Hagen (1997) refer specifically to the party platforms of Socialist, Social Democratic and Labor parties in Finland, Sweden, Norway and Denmark (290-291).
20
Building on the network approach, Daugbjerg and Pedersen (2004) expand on Kasa and
apply the main theoretical argument to a comparative analysis of pesticide and CO2
taxation in Denmark, Norway and Sweden. This more comparative research design
attempts to explain variation within first movers – i.e. in the particular tax designs among
three carbon tax countries – thus considerably improving on the work of Kasa by
introducing variance in the dependent variable. Interestingly, the study highlights the role
of social democratic parties in proposing the new green taxes in all cases examined. And
while the detailed analysis of pre-existing policy networks in all three case studies is
compelling, unlike the work of Midttun and Hagen, Daugbjerg and Pedersen fail to
provide adequate analysis of the electoral incentives and environmental concern that
converged to place the taxation issue on the agenda in the first place.
This latter issue is taken up in Kathryn Harrison’s (2010) recent piece on the comparative
politics of carbon taxes, which compares instances where countries have implemented
carbon tax proposals (Finland and Denmark) with two cases in which such proposals
have failed (Canada and Germany). In contrast to the work of Scandinavian political
scientists, Harrison applies a broader theoretical framework to the issue, eschewing a
corporatist/network approach and instead examining the role of good policy motives,
electoral incentives and political institutions across the four cases. Employing this
framework, Harrison specifically documents a key role for green and leftist political
parties as enthusiastic entrepreneurs whose environmental platforms, which received
increasing electoral support, helped to “green” traditional parties and push environmental
taxation onto the political agenda (Harrison, 2010; Hatch, 1995). Even in Germany,
where the Greens opposed an explicit carbon tax because it would encourage nuclear
energy, the Green party was instrumental in pushing a broader based tax reform to
increase the cost of all energy, including fossil fuels (11-12). Thus, in addition to the role
of corporatism in pulling toward a particular policy design (Midttun and Haggen, 1997;
Daugbjerg and Pedersen, 2004), Harrison identifies a role for electorally-driven political
parties in the initial “push” for carbon/energy taxation. Harrison’s analysis also points to
proportional representation as a facilitating factor in the implementation of carbon taxes,
21
highlighting its role in promoting the emergence of small environmentally focused parties
onto the political scene.
While making important contributions in their own right, both economic and political
science scholarship in the area of carbon taxation are inherently limited because of their
small n. For instance, the public choice literature has contributed much in terms of
specifying the micro incentives of particular groups for mobilizing in opposition to
increases in rates of carbon taxation, providing an explanation for the gap between carbon
tax theory and practice found in the OECD (Chapter 3). However, insights from this
theoretical modeling is rarely tested across a large number of countries in the public
choice literature, and often ignores the institutional setting in which interests are formed
and with which interests must work to have an influence on tax policy outcomes.
Nevertheless, these insights into the political role of interests can be readily formulated as
testable hypotheses guiding cross-national empirical work.
Similarly, the qualitative work undertaken by political scientists provides another source
of explanatory hypotheses to be tested in broader cross-national comparative research. To
be sure, the great contribution of scholarship in this tradition has been to specify the
contextual factors that converge to explain how and why particular governments in small
open economies – e.g. the Nordic countries – were able to reconcile domestic pressure for
environmental regulations while also protecting domestic industry exposed to
international competition. What remains to be seen, however, is whether the same
insights are applicable across a broader number of countries to explain differences in
rates of taxation applied to fossil fuels, as is proposed here. As highlighted by Kasa’s
(2005) recent review of the existing literature, comparative carbon tax scholarship could
benefit from more attention to differences in the economic structure and growth of
countries, as well as external economic pressures such as those resulting from trade
(Kasa, 2005: 92). The existing political science research can thus benefit from models
and methods that are better suited for adjudicating among numerous explanatory
variables measured at the domestic and international level, and further specifying the
22
particular role of political parties, institutions, and electoral incentives across a broader
number of countries.
To this end, recent quantitative work on green taxation has made some important
advances. For instance, a recent paper by Ward and Cao (2010) seeks to explain cross-
national differences in the “green tax burden,” which they operationalize as revenues
from green taxes as a percentage of per capita gross domestic product. Employing spatial
econometric tools to a panel data set, Ward and Cao find that the energy producer lobby
(energy production / GDP) is associated with significantly lower green tax burdens, and
to their surprise, find that higher income tax burdens are positively associated with
significantly higher green tax revenues. Most of their models also find a significant
relationship between the presence of green parties in the legislature and higher green tax
burdens, and separate trade measures (dyadic trade and aggregate flows) produce
significant results consistent with the expected directions. In a separate paper, Ciocirlan
and Yandle (2003) similarly examine revenues from green taxes. Like Ward and Cao,
Ciocirlan and Yandle find evidence of trade effects, with green tax revenues inversely
related to trade openness. Though consistent with expectations, it should be noted that the
dependent variable in both studies, revenues from green taxes, provide only an indirect
proxy for tax level, and so these results should be interpreted with caution. Drawing
specifically on the public choice literature, Ciocirlan and Yandle test a number of
independent variables not included by Cao and Ward, including the number of
exemptions granted to industry and a country’s level of carbon emissions. Reporting
results for just one model, Ciocirlan and Yandle (2003: 213) find some support for their
claim that green taxes “…are not set with a specific concern for the environment; their
purpose is largely to generate revenue.”
In contrast to a focus on tax revenues, other work has specifically examined tax rates. For
instance, a recent PhD dissertation from the Claremont Graduate University examines the
Political Economy of Energy Taxation in the OECD, 1973-1995 and is similar to the
present project in its breadth, method and scope (Morozova, 2005). A limitation in this
work, however, is that Morozova’s statistical analysis deals exclusively with tax rates
23
imposed on the manufacturing sector, leaving analysis of consumer taxes on fossil fuels
open for further research. This being the case, Morozova’s dissertation provides
interesting insight into the question of comparative environmental taxation. Her primary
hypothesis concerning corporatism, for which she finds only limited empirical support, is
included in the analysis of tax rates on industry fuels in the empirical analysis (Chapter
5).
Also focusing on tax rates, this time on consumers, Hammar et al. (2004) examine
gasoline taxes across a sample of 21 OECD countries over the period 1978-2000, and
generate some interesting (if problematic) results. For instance, one of their main
findings is that gasoline consumption per capita has a substantial and statistically
significant, negative effect on gasoline tax (Hammar et al. 2004:10).24 This finding
seems obvious, and also raises a key problem of causality; are low fuel taxes the result of
higher levels of consumption (and thus increased pressure against higher taxes), or vice
versa? In addition to this endogeniety, Hammar et al. (self-admittedly) fail to incorporate
the potentially crucial role of organized business interests in their model, while the
potential mediating role of different political institutions is not even discussed. This
shortcoming is partially addressed in a recent paper on the political determinants of
environmental taxation. Using gasoline price and tax data from the IEA, Broz and
Maliniak (2009) find that malaportioned electoral systems – i.e. electoral systems where
some “geographical units have shares of legislative seats that are not equal to their share
of population” (9-10) are significantly associated with lower gasoline prices. To the
extent that rural voters are more dependent on gasoline, this argument is plausible.
However, the malapportionment logic seems considerably less well suited to explain
variation in taxation on such other fossil fuels as coal and heavy fuel oil, which are more
often used by industry in urban districts, for instance.
In sum, while the quantitative literature has helped bring some theoretical parsimony to
the question of environmental taxation, it appears as though the empirical range of this
24 Other independent variables examined in Hammar and Sterner’s model include vehicles per capita, income level, pre-tax of gasoline, taxation as a share of GDP, and governmental debt.
24
literature has so far remained limited. Indeed, no single study has attempted to cover tax
rates on both industry and households. The primary culprit, it would appear, is a lack in
the availability of good data. For instance, some research relies on revenue data (Cao and
Ward, 2010; Ciocirlan and Yandle, 2003), which is problematic, since revenues are tied
to consumption, or that which environmental taxation is intended to deter.25 Thus, if the
objective is to explain cross-national differences in levels or the stringency of green
taxation, tax rates appear to be a more valid measure.
Where tax rates have been used, studies remain relatively focused on either industry fuel
taxes (Morozova, 2005), gasoline prices (Broz and Maliniak, 2009), or are otherwise
handcuffed by methodological issues (Hammar et al. 2004). A more satisfactory analysis
would test the efficacy of a coherent political argument against other plausible causes of
differential rates of environmental taxation, across numerous fossil fuels, not just
gasoline, and over time. The existing quantitative literature does not provide a theory that
might plausibly be applied to different fuels for this purpose. As it happens, a burgeoning
literature on the policy consequences of electoral systems exists, and seems well suited to
this task.
1.5.2. The role of political institutions
Inspired by the work of comparative political scientists (e.g. Cameron, 1978; Crepaz,
1998), a recent and growing tide of theoretical research in economics has addressed the
question of cross-national variation in the size of government and government spending
across countries. The basic argument is that electoral rules systematically shape economic
policy, government expenditures and the size of the welfare state (Persson and Tabellini,
2008). Employing Downsian logic, these studies argue that majoritarian (as opposed to
25 As pointed out by Barde and Braathen (2007: 58), tax revenues should not be taken as an indicator of the effectiveness or stringency of environmental tax policy. Revenues from green taxes will be strongly associated with levels of consumption. This is problematic because the green tax component of total tax revenue will rise and fall with levels of consumption, irrespective of what happens to policy. As such, if the goal is to mesure policy, actual tax levels should be preferred.
25
proportional) electoral systems produce greater competition among parties in key
marginal districts, leading to more targeted policy and fewer public goods (Persson and
Tabellini, 1999). In contrast, parties competing in proportional systems are more likely to
target benefits for the broader population, since a percentage of legislative seats are
determined by the national vote. Though largely focused on developing formal theory
and the specification of micro political incentives, this literature has also begun to
empirically tests model predictions. In particular, numerous studies have found that,
consistent with expectations, majoritarian elections lead to smaller governments, smaller
transfer payments, and smaller welfare states (Milesi-Ferretti et al. 2002; Persson and
Tabellini, 1999; 2002; 2004).26
To be sure, political scientists do not ignore such institutional effects, though they also
pay close attention to the politics of coalitions that electoral systems produce. For
instance, emphasizing the importance of government partisanship in explaining cross-
national differences in redistribution (e.g. Blais et al. 1993; 1996), Iverson and Soskice
(2006) argue that electoral systems affect coalition behaviour, leading to differences in
the partisan composition of governments, and hence redistribution. In a similar vein,
Manow (2009) has argued that majoritarian electoral systems (and associated party
systems) have lead to a “residual-liberal” welfare state, while the interaction of
proportional electoral rules, and the ideological makeup of coalitions, explain the
development of Nordic (red-green) and continental (red-black) welfare states,
respectively. Tackling a somewhat different question, Martin and Swank (2008) trace the
origins of corporatist and pluralist employers’ associations, once again, to the electoral
system and the party systems they foster. Finally, Rogowski and Kayser (2002) find that
national-level prices are strongly influenced by the type of electoral system in use, which
tilt the balance in favour of either consumer (lower prices) or producer (higher prices)
interests.
26 The logic underpinning these findings is firmly based on the micro incentives of actors, and is discussed at greater length in the Argument section of this dissertation (1.7).
26
At present, this emerging literature on the political and economic effects of electoral
systems has rarely addressed tax policy. In one exception, Steinmo and Tolbert (1998)
examine the impact of dominant party government on shaping cross-national differences
in tax burdens across industrialized democracies. Citing the importance of striking long-
term compromise on taxing and spending in dominant coalitions, and the incentives for
governments to “behave” (i.e. not raise taxes) in majoritarian systems, Steinmo and
Tolbert argue that electoral rules impact tax burdens through the production of three
dominant governing outcomes. Majoritarian elections typically produce majoritarian
governments vulnerable to small changes in vote shares, and thus produce an incentive to
keep taxes low. In contrast, Proportional systems can lead to higher or lower taxes,
depending on whether dominant or shifting coalitions are the norm. Where party
coalitions are relatively stable, long-term compromises on taxing and spending are
common (resulting in higher taxes), while shorter time horizons in shifting-coalition
polities tends to keep taxes low (Steinmo and Tolbert, 1998). While making an important
contribution to the study of tax policy, the institutional logic of Steinmo and Tolbert is
devoid of political agency, which presumably matters for (environmental) tax policy
outcomes.
Emphasizing a different causal logic, a more recent study by Fredriksson and Millimet
(2004) explicitly models the effects of electoral institutions on policy. Following Persson
and Tabellini (1999), Fredriksson and Millimet point out that a party vying for power in a
majoritarian system requires only 25 % of the popular vote to win a majority (50% of the
vote in 50% of the districts), whereas in proportional systems, a party requires at least
50% of the national vote. From this, they argue that parties in majoritarian systems will
have an incentive to develop local policies targeted toward key marginal districts, while
parties in proportional systems will have an incentive to target broader, national welfare
goals. Testing their hypotheses against a series of environmental policy indicators,
Fredriksson and Millimet find broad support for their argument, suggesting electoral
systems may have an influence over environmental policies with diffuse benefits, too.
27
In light of the robust findings across the electoral institutions literature, the argument
developed (1.7) and tested (Chapter 5) in this dissertation draws heavily on this political
institutional framework. I thus attempt to combine insights from the literature on the role
of electoral institutions with those emerging from the literature on the comparative
politics of environmental taxation. The general theoretical framework (1.6) and argument
(1.7) are further discussed and elaborated in the next sections. To be sure, the present
study fills an important gap in the literature just summarized, by testing the efficacy of
electoral systems to explain cross-national differences in rates of fossil energy taxation,
across a broad number of the advanced industrial economies in the OECD.
1.6. Theoretical framework and assumptions
Drawing on what we already know about the comparative politics of environmental
taxes, and the role of political institutions, the general theoretical approach adopted here
suggests that levels of carbon-energy taxation are determined by the primary type of
electoral system used to translate vote shares into seat shares, the electoral preferences of
voters, the ideological stripe of the parties in power, the revenue needs of government,
the size of industry opposition, and the exposure of the domestic political economy to
international trade. As discussed in the review of the literature above, broadly similar
approaches are shared by several studies in the recent literature on comparative
environmental policy, though none explicitly lays out their framework in precisely this
way. Moreover, existing studies often fail to include one or more of the variables
commonly found to be important in the literature taken as a whole.
Following the now common taxonomy in comparative and international political
economy scholarship (Hall, 1997; Harrison and Sundstrom, 2010), I group these
explanatory factors into three broad categories – interests, ideas and institutions – and
comment on each before presenting my theoretical assumptions, argument, and primary
working hypotheses, to be tested in Chapter 5.
28
Interests
Of all politically salient interests, the role of organized business is often found to play a
key role in explaining public policy outcomes (Layzer, 2007; Quinn and Shapiro, 1991).
Yet contra Marxian notions of a monolithic capitalist class, recent research has shown
that business is not a single interest (Hart, 2004). Rather, important fissures exist within
the business community (Falkner, 2009), and different industrial sectors possess both
different policy preferences and varying incentives to mobilize in an attempt to influence
a given policy outcome. In the area of fossil fuel energy taxation, the relevant interests to
consider include fossil fuel energy producers, energy intensive industry (e.g. in
manufacturing), trade-exposed sectors of the economy, and producers of renewable
energy. Of these primary interests,27 the trade exposed and fossil fuel energy producers
are likely to be the most motivated opponents of fossil fuel energy taxation.
The fossil fuel industry has an inherent interest in keeping the price for its products low,
so as to ensure continued demand for fossil fuels and the profitability of its operations. If
government were to increase the cost of fossil fuels by raising taxes on carbon, producers
of fossil fuels stand to bear the highest and most concentrated burden, since the market
for their product is directly threatened. These concentrated interests thus have the largest
incentive to mobilize against an increase in fossil fuel taxation, and possess a wealth of
resources (e.g. money) to mount well-organized and well-financed campaigns in
opposition to an increase in taxes on fossil fuels (Carpenter, 2001; Layzer, 2007). In
addition, producers of fossil fuels also possess a certain amount of structural power, in
the sense that governments of fossil fuel rich countries are often dependent on this
industry as a major source for wealth creation, jobs, and government revenue (Carter,
2010). The relative size of the fossil fuel industry is thus an important variable to
27 I make a distinction here between “primary” and “secondary” interests. By primary interests, I refer to the interests of those firms whose profitability is directly affected by an increase in tax rates on energy products. In contrast, secondary interests refer to the interest of other firms in the supply chain, which rely on energy producers and energy-intensive industry as consumers and suppliers of their products and services. For simplicity, I consider only primary interests here. It is also reasonable to expect that primary interests are the most politically salient, in that these interests have greater incentives to mobilize, since they are most directly affected.
29
examine when considering an interest-based explanation for differences in tax rates on
fossil fuels.
Like producers of fossil fuels, large consumers of energy also have an interest in keeping
tax rates on fossil fuels low, though their motivation for doing so is somewhat (if mildly)
less pronounced. Indeed, firms in energy-intensive industry have an interest in
controlling input costs (Svendsen et al. 2001: 392), but they do not necessarily have an
inherent interest in keeping the price of fossil fuels low. All else being equal,28 energy
intensive firms should not have a preference for energy derived from fossil fuels, if they
can obtain the same level of energy from renewable sources, at a similar price. Unlike
producers of fossil fuels, raising taxes on carbon-based energy does not directly threaten
the products and services produced by firms in the energy intensive industry, and
estimates of pollution control typically range between 2-3% of total operation costs,
producing much weaker incentives to mobilize against taxes on carbon (Goodstein, 1999;
Macdonald, 2007; Olewiler, 1994). In addition, some manufacturers producing energy
efficient products, and those interested in maintaining a “green” public image, have an
interest in reaping legitimacy gains from publicly supporting (or at least not opposing)
policies that reduce energy consumption and associated levels of pollution (Layzer,
2007). For these reasons, energy-intensive industry is less likely than the fossil fuel
sector to mobilize against an increase in tax rates on fossil fuels. There are also
important methodological reasons for not including energy-intensive industry in the
empirical analysis.29
In the long term, energy-intensive firms have less of an interest to oppose fossil fuel
taxation, or any other policy designed to decrease greenhouse gas emissions. In the short
term, however, energy-intensive firms in trade-exposed sectors of the economy possess
greater incentives to expend resources and mobilize against an increase in tax rates on
28 Including the cost of capital stock turnover. 29 A commonly used proxy for the relative size of energy intensive industry is total energy consumption per unit of GDP. Including this kind of variable in the model, however, introduces a problem of endogeniety, since tax rates on fossil fuels are just as likely to influence levels of energy consumption/unit of GDP as vice versa.
30
fossil fuels. As is often argued by firms in trade-exposed sectors of the economy, any
unilateral increase in energy taxation directly affects their cost of doing business,
potentially weakening their international competitiveness (Ekins and Speck, 1999).
Although sometimes questioned in the theoretical and empirical literatures (e.g. Andersen
and Ekins, 2009; Bovenberg and Goulder, 2002a; Jaffe et al. 1995; Jenkins et al. 2002
Porter and van der Linde, 1995), this oft-cited claim resonates with government decision-
makers and the electorate, who are both sympathetic toward any argument invoking the
fear of job losses and self-imposed economic hardship. Indeed, the fear over a tax’s
impact on international competitiveness is the most frequently cited argument against the
unilateral imposition of a carbon tax (OECD, 2001; 2006). Other research has also found
evidence of tax competition, or a “race to the bottom” in open economies (Bretschger and
Hettich, 2002; Genschel, 2002; Winner, 2005).30 As a result, it is important to include the
extent to which a country’s economy is exposed to international competition.
A final group of interests to consider relates to those of the renewable energy sector.
Though relatively new and small in number, producers of renewable energy and
renewable energy technology constitute a constituency of growing importance in several
OECD countries. Their inherent interest in creating a “level playing field” for their
products and services is diametrically opposed to producers of fossil fuels, who currently
benefit from years of investment in a carbon-based infrastructure, low tax rates for their
goods and government subsidies. Most firms in this industry want to see effective action
on climate change, especially those that raise the price of fossil fuel energy. Capturing
the relative size of the renewable energy sector can help to ascertain the political
importance of this emerging industrial sector, as well as to control for the fact that
countries differ in the level of domestically available alternatives to fossil fuel energy.
However, fossil energy taxes are sometimes used to encourage the development of the
green energy sector, and a measure of this variable would thus be endogenous to fossil
energy tax rates. As a result, it is not included in empirical tests in Chapter 5.
30 Interestingly, the effects of trade openness are mixed, with other studies citing larger governments (e.g. Cameron, 1978).
31
Ideas
In addition to producer group interests, the analytical framework proposed here also
suggests that social values – and in particular, environmentalism – should be associated
with higher rates of carbon energy taxation. More environmentally conscious publics will
prefer such policies and demand stricter environmental regulations. This might also make
it easier for governments to impose taxes on their public, when the taxes can be sold as
environmental, and the public is already highly sensitive to environmental issues. On the
supply side, it is reasonable to expect that the ideological orientation of government will
impact the types of policies implemented. For instance, green parties have been known to
pursue stricter environmental policy.
The problem with the environmentalism argument is that it is difficult to measure ideas,
particularly environmental ones. Lacking sufficiently comparable cross-national public
opinion data covering the time period of interest here (i.e. 1978-2006), one approach is to
use green party seat and vote shares as proxies for the level of “environmentalism” in a
country. To be sure, there are some issues with such indicators. First, environmentalism
cannot always be reduced to green party votes, since some countries don’t have green
parties, yet do have a history of environmentalism (e.g. the U.K., see Rootes, 2003).
Moreover, a decline in the vote for greens may not necessarily be attributable to a decline
in an interest for environmental protection. For instance, Papadakis (1989; 1986) has
argued that the electoral setback of the German Greens in 1990 was at least partially due
to the ability of established parties to co-opt the green agenda.31 In these respects, relying
on electoral data provides an imperfect measure of environmentalism across countries. At
the same time, however, green seat and vote shares are often the indicator of choice in
cross-national, large n comparative research, and are generally accepted as the best of
available measures for this purpose (e.g. Neumayer, 2003). In the empirical analysis to
follow in Chapter 5, I use the share of green party votes as an indicator of public demand
for environmental regulation.
31 Dalton (1994) has noted that traditional (social democratic) left-wing parties often adopt environmental policy preferences in an attempt to court new social movements.
32
In addition to using electoral data to measure the electorate’s preferences, other studies
have been interested in examining the extent to which party ideology can affect policy.
Beginning with Downs’ (1957), scholars have debated whether parties in general, and
party ideology in particular, matters for policy outcomes (e.g. Blais et al. 1993; 1996).
More recently, several studies have found interesting relationships between the
ideological makeup of government and tax and fiscal policy (e.g. Cusack, 1999; Hart,
2010). As hypothesized by Jahn (1998) and Neumayer (2003) in their cross-national
studies of environmental performance, green and left parties should most likely be
associated with significantly better environmental outcomes, if partisanship matters at all.
It is thus plausible to expect an increase in the electoral and political strength of green
parties (at the polls, in the legislature and in government) to have an effect on rates of
carbon energy taxation. I thus include societal demand-side (i.e. green votes) and political
supply-side (i.e. green seats and cabinet posts) factors in the analytical framework
proposed here, and test for their effects in the empirical analysis of Chapter 5.
Institutions
As noted earlier, it is frequently suggested that certain types of political institutions – like
the electoral system – have implications for public policy. In particular, scholars draw a
key distinction between majoritarian and proportional systems, which shape party
preferences and mediate the relationship between governments and voters. In
majoritarian systems, a party can win an election with just 25 per cent of the popular vote
(50 per cent of the vote in 50 per cent of districts), encouraging politicians to target key
marginal districts that may be decisive in an election (Fredriksson and Millimet, 2004;
Persson and Tabellini, 2008).32 Due to this property, majoritarian elections usually lead to
a disproportionate allocation of seats given a particular distribution of votes, and a small
change in vote can thus have relatively large political consequences. Combined with the
related tendency for majoritarian systems to lead to large majority governments, parties 32 By majoritarian system, I refer to the simple plurality, first-past-the post of counting votes to determine which candidate wins an election, usually in a single-member-district (SMD). I refer to majoritarian, plurality and SMD systems interchangeably.
33
are more vulnerable under such systems, and thus have an incentive to “please” voters by
appealing to local interests, especially in key districts (Persson and Tabellini, 2008). In
contrast, proportional systems involve various ways of allocating seats in proportion to
the percentage of the popular vote. Though not all proportional systems lead to perfectly
proportional outcomes (hence the importance of measuring disproportionality), they tend
to allocate legislative seats in proportion to the national vote (Gallagher, 1991). As a
result, it is often argued that parties in proportional systems are more likely to adopt
policy preferences targeted to broader, national social welfare goals, like environmental
health and quality, in order to maximize electoral gains (Fredriksson and Millimet, 2004).
For these reasons, I test for the role of electoral systems, and specifically, the effect of
disproportionality, on rates of carbon energy taxation.
In sum, the analytical framework comprises an analysis of the interests, ideas and
institutions that can affect rates of carbon energy taxation across countries. While not
ignoring the role of economic constraints, I argue that the political ideology of parties
interacts with the degree of proportionality in electoral systems as a driver of
environmental and energy tax policy outcomes (1.7). In constructing this argument, I
make a few key assumptions.
First, I assume that the fossil fuel and trade exposed industry, voters and political parties
are the primary units of analysis, and that they are rational actors pursuing their interests.
I assume industry’s preference in the fossil fuel-producing sector and trade-exposed
sectors of the economy are for lower taxes on fossil fuels. I also assume voters in rural or
less densely populated areas will prefer lower taxes, since they presumably have to drive
further distances and are more likely to operate heavy machinery, and are thus more
dependent on fossil fuels. Following other studies in the literature, I assume votes for
green parties indicate support for environmental policy, and that individuals who vote for
green parties are more likely to support environmental taxation. I further assume that
green and left parties support higher taxation of energy products, in accordance with the
findings of other studies (e.g. Damania, 1999; Daugbjerg and Pedersen, 2004; Harrison,
2010). Following Schumpeter (1950), I assume electoral competition is the essence of
34
representative democracy, and this implies that political parties compete for the support
of heterogeneous voters with a suite of policies. While not denying that parties
(especially small issue-oriented ones) carry out ideological programs, they are ultimately
driven and constrained by their primary interest in obtaining political power. It follows
that the primary objective of governments, and power-seeking politicians in political
parties, in addition to implementing their ideological program (where they have one) is in
re-election. Finally, I assume that in general, the probability of receiving electoral support
is negatively affected by the imposition of new taxes on fossil fuels, except in the case of
green voters.
1.7. Theoretical argument
In what follows I develop the argument that proportional electoral systems facilitate the
imposition of energy taxes, and in particular, lead to higher rates of implicit carbon
taxation in advanced capitalist democracies. I argue further that electoral systems matter
to the extent that they interact with voter preferences and party politics. This argument is
tested along with elements of the theoretical framework discussed above, in Chapter 5.
This empirical analysis treats the party system and choice of electoral system
exogenously.33
First, I argue that green political parties, and parties of the left, generally support higher
rates of fossil fuel taxation. This argument is not directly tested here, but accords with
previous research. Damania (1999) notes that Green parties in Europe, Australia, New
Zealand and elsewhere support environmental taxes. This observation is further
supported in the recent work of Harrison (2010), which discusses the role of green parties
and their preferences for higher rates of energy taxation. Daugbjerg and Pedersen (2004)
also note that in all cases where carbon taxes were implemented, social democratic (i.e.
33 Though they are related, one could write an entire dissertation on the choice of electoral system or the development of the party system. See for instance: Pilon’s dissertation (York University). Other studies on electoral system choice include Bawn, 1993; Boix, 1999; and Cusack et al. 2007).
35
traditional left-parties) were in the coalition.34 Traditional left-wing parties may be
expected to support higher rates of environmental taxation in order to court new social
movements to their party (Dalton, 1994; Kitschelt, 1993) and finance a progressive
welfare state (Kato, 2003).
Second, I argue that PR systems are good for parties of the left and greens. To be sure,
the effect of electoral systems and issue dimensions on the “effective” number of political
parties is now well-established (Duverger, 1954; Taagepera and Grofman, 1985). More
recently, Iversen and Soskice (2006) show that proportional electoral rules lead
systematically to a greater number of left governments. In Table 1.1, I show that
proportional electoral systems also lead to systematically greater representation of Greens
in parliament.
Table 1.1: Electoral system and the number of years with at least one green party member in the elected legislature (1978-2006) Green party representation
No greens
Greens
Proportion of years with greens in parliament
Electoral system
Proportional
237
186
0.44
Majoritarian
190
25
0.12
Source: Data from Armingeon et al. (2009)
As is clear from Table 1.1, electoral systems are not politically neutral. They influence
the ideological makeup of the legislature and government, and determine which groups in
society are more likely to see their interests represented in the legislature and in
government policy. For instance, green party representation in the legislature is over three
34 Future work should empirically test this claim using data from the Comparative Manifesto Project.
36
times more likely in PR (Table 1.1). Similarly, in separate tests now shown, it was found
that green/new-left parties are twice more likely to participate in government under PR
systems (compared to majoritarian systems). Moreover, electoral systems also determine
how well voters can hold governments and politicians accountable for their actions. In so
doing, electoral systems may be expected to shape policy outcomes by (i) creating the
ideological space within which political parties are more/less able to implement their
policy programmes; and, (ii) generating incentives that shape the policy preferences of
vote-maximizing political parties.
Ideological space
Proportional electoral systems create the ideological space for green parties, and those of
the traditional left (i.e. social democratic parties) to increase rates of carbon energy
taxation. By definition, proportional systems produce more proportional outcomes
between a party’s share of legislative seats and its share of the votes. This tends to
increase the number of “effective” parties (Rae, 1967; Taagepera and Shugart, 1989;
Lijphart, 1990). As the effective number of parties increases, so does the ideological
range of parties, and the issues claimed to be their own. To the extent that such systems
favour smaller, issue-oriented parties, it can be expected that environmental issues will
increase in political importance.
Moreover, it has also been found that proportional systems are more likely to produce
multi-party coalition government (Taagepera and Shugart, 1989; Strom, 1990), increasing
the chances of smaller parties forming government. Responsibility over government
cabinet portfolios can be expected to increase the influence of smaller green parties, as
well as their intra-coalition negotiation power. Coalition government also makes it harder
for voters to know who to blame for unfavourable policy (e.g. tax increases), as lost votes
for poor governing performance are shared among coalition partners (Persson and
Tabellini, 2008; Powell, 2000), thus decreasing the political costs of tax increases. In
contrast, the lines of accountability in majoritarian systems are clearer, since they tend to
produce majority governments. This will encourage “good behaviour” among
37
governments fearful of the electoral consequences of increasing taxes (Persson and
Tabellini, 2008). For this reason, green/left parties will be constrained in their ability to
increase taxes under majoritarian (disproportional) systems where majority governments
are the norm.
Electoral incentives
Electoral systems are not neutral, and create incentives for political parties, regardless of
ideological stripe, to do certain things and avoid others. For instance, proportional
electoral systems encourage politicians to seek a broader national constituency with their
policy, since parties compete for national seats, and the minimal coalition of voters
required to win an election is 50 per cent plus one. Parties thus have an incentive to give
greater importance to nation-wide, public goods issues, and consider the welfare of the
entire population, in order to maximize votes and associated seats. As Persson and
Tabellini (2008) note, “proportional representation diffuses electoral competition, giving
the parties strong incentives to seek electoral support from broad coalitions in the
population through general public goods” like environmental policy (Fredriksson and
Millimet, 2004). In contrast, majoritarian systems typically focus electoral competition in
pivotal districts, producing an incentive for parties to target local interests at the expense
of broader welfare goals (Persson and Tabellini, 2008; Fredriksson and Millimet, 2004).
Moreover, compared to systems of proportional representation, majoritarian systems can
translate small changes in voter sentiment into larger changes in legislative seats
Sometimes referred to in the literature as the “seat-vote elasticity” (Rogowski and
Kayser, 2002) or “seat-vote proportionality” (Powell, 2000), such disproportionality
produced by the electoral system leverages the effect of votes and “strengthens the
incentives of politicians to please voters” (Persson and Tabellini, 2008). Combined with
the fact that disproportional electoral systems typically produce majority governments
where the lines of policy accountability are clear, a high seat-vote elasticity will constrain
the ability of government, no matter which political stripe, to increase taxes on carbon
based energy. This is because governments in such disproportional systems will be more
38
vulnerable to voters. By the same logic, given the incentives to seek votes, changing
voter preferences under highly disproportional systems will encourage parties to adjust
policy preferences in order to win new votes. Thus, while green seats and green
government will be constrained in their ability to increase taxes under disproportional
systems, green votes are expected to have exactly the opposite effect as the degree of
disproportionality increases.
Summary of hypotheses
These arguments can be distilled in four primary working hypotheses, which will be
tested in Chapter 5.
H1: The PR hypothesis: Relative to majoritarian electoral systems, countries with PR will impose higher implicit tax rates on carbon. H2: The ideological space hypothesis: Relative to majoritarian electoral systems, greater representation from parties of the left and greens will be positively associated with significantly greater implicit carbon tax rates under PR. H3: The disproportional constraints hypothesis: Relative to proportional systems, greater representation from parties of the left and greens will not be positively associated with greater implicit carbon tax rates under more disproportional systems, as these parties will be constrained in their ability to raise tax rates, regardless of their ideological program or policy preferences. H4: The electoral incentives hypothesis: Relative to more proportional systems, increasing support for green parties will lead to an increase in rates of implicit carbon taxation under more disproportional systems, as parties/governments have greater incentive to respond to mounting electoral threats where the seat-vote elasticity is high.
39
1.8. Chapter summary
The general outline of this dissertation is as follows. Chapter 2 examines the economic theory of carbon-energy taxation and answers the question: why tax carbon? Chapter 3 examines the empirical record of carbon-energy taxation and demonstrates key political shortcomings when economic ideas are put into political practice. It also offers an initial analysis of why this gap exists, applying insights from the theoretical argument about electoral systems to the case of the British Columbia carbon tax. Chapter 4 expands the analysis to consider other forms of carbon-energy taxation and develops the argument that these “implicit” carbon taxes warrant closer empirical study. Chapter 5 develops an empirical analysis to assess the political determinants of cross-national variation in rates of taxation for coal, heavy fuel oil, diesel and gasoline. The analysis finds broad support for hypotheses H1 to H4, as the interaction between parties and electoral systems consistently emerges as a robust predictor of carbon energy taxation. Chapter 6 concludes.
40
Chapter 2: Carbon taxes in theory
2. The economics of pricing carbon Economic models have long demonstrated that market-based approaches to pollution
abatement are generally more cost-effective than are subsidies, voluntary programs, and
regulation (Baumol and Oates, 1985). More recently, countless government and NGO
studies from the climate policy community now espouse the relative merits of putting a
price on carbon (NRTEE, 2007; Metcalf, 2007; CBO, 2008; Demerse and Bramley, 2008;
Mintz and Olewiler, 2008; Rivers and Sawyer, 2008). Apart from “getting the prices
right,” market-based approaches strike at the core of the climate change issue and energy
security issues; namely, they target the need to “decarbonize” the economy and de-couple
economic growth from the use of scarce fossil fuels like crude oil.
By adjusting prices so that they better reflect the environmental and social costs of fossil
fuel use, policy-makers can help re-shape deeply entrenched patterns of production and
consumption by making emissions-intensive goods and practices relatively more
expensive, while making environmentally superior choices relatively less costly. In
addition, there is now a broad-based, cross-cutting consensus among economists,
environmentalists, and members of the business community that a carbon tax is, in
theory, the most efficient and in many circumstances the most effective policy instrument
to price carbon, and by association, reduce the use of fossil fuels and man-made
emissions of greenhouse gasses (GHG).
For these reasons member countries in the Organization for Economic Cooperation and
Development (OECD) have generally come to accept the need to “put a price” on carbon
(OECD, 2001; 2006; 2009).35 At the same time, pricing carbon has proven to be a
35 As discussed in Chapter 3, carbon taxes have been implemented in several jurisdictions across the OECD, and carbon markets have been established or are in the process of being established in Europe, parts of North America, and the South Pacific (e.g. Australia, Japan).
41
politically difficult sell, engendering debate over appropriate policy instruments and their
design.
The following chapter sets out the theory of carbon pricing and answers the question,
“why tax carbon”? The first section of this chapter discusses the economic concept of
externality (2.1), and demonstrates how the burning of fossil fuels imposes substantial
environmental and social costs in the form of climate change (2.1.1) and the costs
associated with continued dependence on increasingly scarce fossil fuels (2.1.2). Next,
the chapter outlines two options for internalizing such costs (2.2), which involve putting a
price on carbon – either directly, through an emissions tax (2.2.1), or indirectly, through
an emissions cap and permit trading system (2.2.2). After comparing the two pricing
options (2.2.3) and key design issues that affect the nature and effectiveness of a carbon
tax (2.3) the chapter concludes with a discussion of the political economy of instrument
choice (2.4).
2.1. External economies It is somewhat ironic that economists, often criticized for some of the social ills afflicting
society, have long developed answers to the related problems of public goods and social
cost. Following Marshall’s (1890) pioneering work on external economies, Pigou (1920
[1932]) developed the concept of externality as a divergence between private and social
cost. According to Pigou, economic activity can generate both positive and negative
externalities, that is, costs and benefits external to an economic transaction that affect the
welfare of third parties in negative or, in positive ways.36 Such costs and benefits are
external insofar as: (i) they are borne not by participants in an economic transaction but
by third parties; and (ii) they are not reflected in price signals and thus fail to be
considered by economic agents as they make private production and consumption
decisions in the market. To the extent that external costs and benefits are not reflected in
price signals, the market mechanism will not lead to a Pareto Optimal competitive
equilibrium. Private agents may engage in too much (or too little) of an activity,
36 A positive externality involves a private transaction resulting in net benefits, while a negative externality imposes net costs, on third parties.
42
ultimately leading to a mis-allocation of resources and market failure. For instance, by
not having to pay for the pollution/costs caused by an industrial activity (a negative
externality), a firm responding to distorted market signals will have an incentive to
produce more than the socially optimal amount of their product, thus reducing the
availability of public goods like clean air, water or un-congested highways.37
The classic example of a negative, production-based38 externality is the case of a smoke-
emitting factory whose economic production fails to account for the smoke emitted into
the atmosphere (Coase, 1960). In the absence of appropriate price signals, a firm will
over-exploit the social capital stock of clean air (without cost), which may negatively
affect (i) the production possibilities of firms in other industries relying on clean water
and air (e.g. fishing), or (ii) the public health of nearby communities. In either case, a
negative externality is created. Since air pollution may harm other firms or individuals in
society, and since this cost imposed onto third parties is unaccounted for in the price or
production function of the factory, a negative externality results.
When prices fail to reflect the “true” social and environmental costs of an activity or
good, markets are distorted, leading to perverse incentives to produce more (or less) than
the socially optimal amount of a good, which leads to an inefficient allocation of
resources. Economists refer to such a mis-allocation of resources as a market failure in so
far as resources are used inefficiently and outcomes are sub-optimal (Sandmo, 2005: 34).
Under such conditions, economists have advocated “full cost pricing,” which may
involve government intervention (e.g. pollution taxes), to force polluters to internalize
37 In the case of a positive externality, the opposite may be true. For instance, since the benefit to society of an educated population is not considered in the economic transaction between a paid teacher and his or her pupil, education tends to be under-supplied relative to the social optimal output, which might call for a corrective subsidy to bring the private benefits and costs of education in line with the social benefits and costs of an educated population. Since the central problem of the present research is assessing policy responses to the economic and social costs of climate change, the focus is on negative externalities here. 38 In addition to there being positive and negative externalities, requiring different kinds of policy response, externalities can either be production or consumption based. An example of a consumption-based externality is the number of cars on the road. Car travel brings private utility but also decreases the quality of air and roads, and increases pollution and traffic congestion. Since individuals that drive fail to consider the costs imposed onto others by their driving, by for instance creating traffic or pollution, driving can impose a negative, consumption-based external cost not considered when individuals opt to drive instead of taking public transit (Sandmo, 2005).
43
social costs. It follows that, in the absence of corrective taxes, “an economy with
externalities is not efficient, since the externality itself creates a distortion” (Salanié,
2003, emphasis added).
2.1.1. Fossil fuel externalities: Climate change Despite attempts by special interests to confuse the debate (Hoggan and Littlemore, 2009;
Michaels and Monforton, 2005), and the uncertainties inherent in scientific inquiry
(Cooke, 1991), the science of climate change is now well established. To be sure, all
science is based in probabilities, and some areas of climate science are better understood
than others. That average global temperatures are increasing, for instance, is now
established as scientific fact (IPCC, 2007b, NRC, 2010). Moreover, notwithstanding
some of the recent controversy over a series of leaked emails from the University of East
Anglia, over 97 per cent of actively publishing climate scientists agree with the main
conclusion of the Intergovernmental Panel on Climate Change (IPCC); namely, that
human activity is responsible for observed increases in mean global temperatures
(Anderegg et al. 2010). As a result, thousands of the world’s leading climate scientists
are calling for massive and immediate reductions to greenhouse gas (GHG) emissions in
order to avert tipping points (Lenton et al. 2008) and the potentially catastrophic
consequences of climate change (IPCC, 2007b; Hansen et al. 2008; Meinshausen et al.
2009). Although the consequences of climate change are difficult to model (given that the
climate system is complex and adaptive), its effects pose significant risks to human lives,
as evidenced in what has already been observed that is attributable climate change.
To be sure each successive report of the IPCC – a collaboration of climate scientists from
around the world working on the physical basis of climate change – has established with
increasing levels of certainty that the Earth is warming, and the US National Academy of
Sciences agrees (NRC, 2010). For instance, Working Group 1 of the Fourth Assessment
Report of the IPCC concluded that, “[w]arming of the climate system is unequivocal, as
is now evident from observations of increases in global average air, and ocean
temperatures, widespread melting of snow and ice and rising global average sea level”
(IPCC, 2007b: 5, emphasis added). This conclusion is based on the latest measurements
published by the IPCC, which clearly depict the global warming phenomenon in three
main areas (Figure 2.1.1.1).
Figure 2.1.1.1: Changes in temperature, sea level and Northern snow cover
Source: Figure SPM.1. (IPCC, 2007b) As depicted in Figure 2.1.1.1, global average temperatures have been rising since the
beginning of the industrial revolution, and three independent lines of eviden
the IPCC’s scientific claim of a warming climate: (a) rising global average temperatures
in the sea and air; (b) widespread melting of snow and ice; and, (c) the concomitant rise
published by the IPCC, which clearly depict the global warming phenomenon in three
es in temperature, sea level and Northern snow cover
Source: Figure SPM.1. (IPCC, 2007b)
As depicted in Figure 2.1.1.1, global average temperatures have been rising since the
beginning of the industrial revolution, and three independent lines of eviden
the IPCC’s scientific claim of a warming climate: (a) rising global average temperatures
in the sea and air; (b) widespread melting of snow and ice; and, (c) the concomitant rise
44
published by the IPCC, which clearly depict the global warming phenomenon in three
As depicted in Figure 2.1.1.1, global average temperatures have been rising since the
beginning of the industrial revolution, and three independent lines of evidence support
the IPCC’s scientific claim of a warming climate: (a) rising global average temperatures
in the sea and air; (b) widespread melting of snow and ice; and, (c) the concomitant rise
45
in global average sea level. In fact, the IPCC has found that since 1850, eleven of the last
twelve years between 1995 and 2006 are among the 12 warmest years on record. It is
estimated (and commonly agreed amongst accredited climate scientists) that the total
temperature increase between the pre-industrial and present era is approximately 0.76
[0.57 – 0.95] degrees C (the difference between current mean global temperatures and
that of the last ice age is roughly 5 degrees C, which is why some call for an urgent
reduction of emissions to limit warming to 20).39 In addition, scientists fear a “snow ball”
effect whereby even small temperature differences can cause small events (e.g. loss of
permafrost and release of methane) that lead to much larger changes and exponential
warming (Lenton et al. 2008). To be sure, the rate at which the planet is warming is
unprecedented, and is nearly double the rate over the last 50 years relative to the last 100
(IPCC, 2007: 5). Observed declines in mountain glaciers, hemispheric snow cover, and a
concomitant rise in global average sea level (about 3.1 mm per year between 1993 –
2003, up from 1.8 mm per year during the period 1961 – 2003) is also consistent with
global warming science and now threatens the livelihood of the nearly 40% of world
population that live within 100 km of the coast.
To be sure, scientists who study climate change have a good understanding of the
mechanics and underlying cause. For close to two hundred years, scientists have
understood the “greenhouse effect” – i.e. the process by which carbon dioxide and other
gases form an insulating blanket around the Earth’s atmosphere. As their name suggests,
these “greenhouse gasses” trap some of the heat generated by solar radiation, which
would otherwise be reflected back towards space (Drake, 2000; Harvey, 2000; Houghton,
2004). This concept was first identified by French mathematician and physicist Joseph
Fourier in 1824, and further developed by Swedish scientist and chemist Svante
Arrhenius at the turn of the century. Arrhenius estimated that a doubling of atmospheric
concentrations of CO2 released from the combustion of fossil fuels would result in a
warming of approximately 2.1 degrees Celsius (when water vapor feedback was taken
39 See Jaeger and Jaeger (2010).
46
into account), which is very close to the most recent “climate sensitivity”40 estimates of
approximately 1.5 – 4.5 degrees Celsius (Harvey, 2000; Hoggan and Littlemore, 2009;
IPCC, 2007b).
Since this early work, scientists have continually refined and built confidence in the idea
of anthropocentric (i.e. human-induced) climate change. In fact, consistent with this
early work, the most recent and authoritative IPCC publication concludes:
Most of the observed increase in globally averaged temperatures since the mid- 20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations. This is an advance since the [Third Assessment Report’s] conclusion that “most of the observed warming over the last 50 years is likely to have been due to the increase in greenhouse gas concentrations.” Discernable human influences now extend to other aspects of climate, including ocean warming, continental-average temperatures, temperature extremes and wind patterns (IPCC, 2007b: 10).
Successive IPCC reports have thus built confidence in the likelihood that humans are
primarily responsible for the observed changes in climate. Indeed, the IPCC has
increased its level of confidence in anthropocentric causes of warming from likely
(carrying a > 66% probability) to very likely (>90% probability), and have concluded that
it is very likely that the observed warming is not due to known natural causes alone
(IPCC, 2007b: 10). According to the IPCC, key among the human drivers of climate
change are global atmospheric concentrations of greenhouse gases, which have rapidly
increased as a result of industrialization and economic growth. In particular, carbon
dioxide has been singled out as the key greenhouse gas with the highest radiative forcing,
i.e. the gas most responsible for trapping heat inside the Earth’s atmosphere and thus
altering the balance between inward and outward solar radiant energy flows (Figure
2.1.1.2).41
40 Equilibrium climate sensitivity is commonly understood as being an estimate of equilibrium global average warming for a doubling of CO2. 41 The IPCC (2007b) defines radiative forcing as “a measure of the influence that a factor has in altering the balance of incoming and outgoing energy in the Earth-atmosphere system and is an index of the importance of the factor as a potential climate change mechanism. Positive forcing tends to warm the surface while negative forcing tends to cool it.” See the IPCC glossary for further details.
47
Figure 2.1.1.2: Radiative forcing components
Source: Figure SPM.2 (IPCC, 2007b)
Figure 2.1.1.2 illustrates radiative forcing values for 2005 relative to pre-industrial
conditions and is expressed in watts per square metre (W m2). As can be seen, carbon
dioxide is the leading GHG with the relatively largest, positive radiative forcing impact,
meaning it has a warming effect on the Earth’s climate. Moreover, as indicated by the
right hand column, the level of scientific understanding (LOSU) for this mechanism is
high. From this perspective, it is not surprising that scientists have found a direct, positive
correlation between emissions of CO2 – the most important greenhouse gas – and
changes in global average temperature (Matthew et al. 2009). Others have found an
equally striking relationship between atmospheric concentrations of carbon dioxide and
temperature changes, as depicted in Figure 2.1.1.3.
48
Figure 2.1.1.3: Temperature and CO2 concentration in the atmosphere
Source: Petit et al. (1999)42
As can be seen in Figure 2.1.1.3, temperature changes over the past 400,000 years are
tightly correlated with CO2 concentrations. Although the data in the Figure end at 1950,
this relationship appears robust over time. More recently, patterns of industrialization and
economic growth since 1950 have fueled an exponential increase in the concentration of
CO2 and other GHG, raising concern over the impact of such emissions for the global
climate (Figure 2.1.1.4).
42 http://www.earthingfaith.org/2010/01/25/is-climate-change-natural-3/
Figure 2.1.1.4: Atmospheric concentration of carbon dioxide
Source: Reay and Pidwirny 200643
Figure 2.1.1.4 plots the rise in CO
time using data from the Mauna Loa Observatory in Hawaii and ice core data for earlier
years. As can be seen, the atmospheric concentration of CO
industrial revolution, and has increased exponentially in the post World War II period,
reaching 379 ppm in 2005. The primary culprit contributing to this rise is the b
fossil fuels, upon which modern industrial countries and the global economy depends
(Figures 2.1.1.5 and 2.1.1.6).
43 http://www.eoearth.org/article/carbon_dioxide
mospheric concentration of carbon dioxide
Figure 2.1.1.4 plots the rise in CO2 concentrations (measured in parts per million) over
time using data from the Mauna Loa Observatory in Hawaii and ice core data for earlier
ars. As can be seen, the atmospheric concentration of CO2 has risen steadily since the
industrial revolution, and has increased exponentially in the post World War II period,
reaching 379 ppm in 2005. The primary culprit contributing to this rise is the b
fossil fuels, upon which modern industrial countries and the global economy depends
arth.org/article/carbon_dioxide
49
concentrations (measured in parts per million) over
time using data from the Mauna Loa Observatory in Hawaii and ice core data for earlier
has risen steadily since the
industrial revolution, and has increased exponentially in the post World War II period,
reaching 379 ppm in 2005. The primary culprit contributing to this rise is the burning of
fossil fuels, upon which modern industrial countries and the global economy depends
Figure 2.1.1.5: Global anthropogenic GHG emissions
Source: SPM.3. IPCC (2007b)
Figure 2.1.1.6: Global GHG emissions by source
Source: Emission Database for Global Atmospheric Research (2009)
44 http://energy.antp.co.kr/epbrd/bbs/board.php?bo_table=bbs5&wr_id=48&page=10
Figure 2.1.1.5: Global anthropogenic GHG emissions
Figure 2.1.1.6: Global GHG emissions by source
Source: Emission Database for Global Atmospheric Research (2009)44
http://energy.antp.co.kr/epbrd/bbs/board.php?bo_table=bbs5&wr_id=48&page=10
50
51
Figures 2.1.1.5 and 2.1.1.6 illustrate the role of fossil fuels as the primary source of GHG
emissions and concomitantly, a key cause of climate change. As can be seen, since the
1970s yearly GHG emissions have grown steadily, topping 45 pico grams of CO2
equivalent in 2005 (i.e. over 45 billion metric tonnes of CO2 in a single year).45 The
majority of this increase (approximately 60 per cent) is attributable to fossil fuel
combustion (Figure 2.1.1.6). In particular, emissions of carbon dioxide – the primary
greenhouse gas identified in Figure 2.1.1.2 – have grown by approximately 80 per cent
between 1970 and 2004 (Figure 2.1.1.5). Therefore, it is not just GHG, but anthropogenic
(i.e. man-made) emissions that are causing climate change.
According to the available science, the emissions patterns just described pose significant
threats to the physical and biological systems that help sustain life on earth. For instance,
as a result of a changed climate, scientists fear increasing negative effects in the areas of
fresh water availability, bio-diversity loss, increased intensity and frequency of violent
storms, increased flooding and drought, declining agriculture yields (in large regions of
the world), and concomitant problems for human health, nutrition and disease (IPCC,
2007: 10). In addition, increased concentrations of carbon dioxide, a key driver of
climate change, have led to the world’s oceans becoming more acidic, which is expected
to negatively impact marine shell-forming organisms like corals, upon which much ocean
life depends (IPCC, 2007: 9). Many of these risks are discussed in Stern’s (2006)
economic review of the risks and costs associated with climate change, summarized in
Table 2.1.1.1.
45 In order to compare different greenhouse gas emissions from individual sources and gases, it is common to convert emissions to CO2 equivalents.
52
Table 2.1.1.1: Highlights of possible climate impacts discussed by Stern
Source: Stern (2006: 57)
The basic message in Stern’s review of the potential impacts of climate change – and
associated human and social costs – is that climate change is a serious issue that will also
impose serious economic costs. While such costs to the environment and human health
are very difficult to measure in quantitative terms (c.f. Ekins and Barker, 2001: 329),
Stern (2006) uses an integrated assessment model (PAGE2002) to estimate the damage
costs of climate change, which the Review finds could range between 5 and 20% of
global GDP if no action is taken to stabilize emissions between 450 and 550 ppm.
53
Applied to the issue of climate change, it becomes apparent that current patterns of
energy production and consumption constitute a large, negative externality of the kind
discussed in section 2.1. In fact, current patterns of energy production and consumption
impose external environmental and social costs in the form of an unstable climate and the
concomitant risks associated with rising global average temperature. The risks of a
warming climate, such as increased droughts, flooding, violent storms, and their
associated impacts on living organisms, can be interpreted as costs borne not by
individual emitters of GHG but as collective costs borne by society and the environment.
The potentially devastating costs of such risks, and their known anthropogenic causes,
have prompted Stern (2006) to call climate change the single largest market failure the
world has ever known.46 According to this view, government policies and price supports
have systematically distorted energy markets, making the price of fossil fuels artificially
low, encouraging the burning of fossil fuels at the expense of other, cleaner forms of
energy, ultimately leading to a mis-allocation of resources. Though difficult to quantify,
especially when considering the future value of a stable climate, the risks posed by
climate change are likely to impose substantial economic costs in the future (c.f. Stern,
2006).
In economic terms, these costs are externalities in the sense discussed in section 2.1, but
with important qualifications (Stern, 2006: 310). First, the nature of climate change
makes it an inherently global problem. Unlike other environmental externalities like acid
rain, climate change is not a transboundary issue. A tonne of CO2 emitted into the
atmosphere in one part of the world will have the same environmental impact as a tonne
of CO2 emitted in another. Second, the environmental harm done by the emission of
GHG involves a pure public good – the earth’s climate. Together, the global
characteristic of the climate change externality, combined with its public good nature,
produce incentives for countries to free-ride on the GHG abatement policies of other
46 In addition to bringing the climate change externality onto the political agenda, the Stern report is also famous for turning the climate change policy debate on its head. Rather than discuss the cost of climate change mitigation, the report examines the costs of climate change, and concludes that the costs of inaction (e.g. the collapse of the eco-systems upon which the environment depends) significantly outweigh the cost of measures taken to significantly reduce anthropogenic emissions of GHG.
54
countries. International coordination is therefore a central requirement to address climate
change, however cross-national differences in GHG abatement costs have so far made
such cooperation extremely difficult.
A further distinguishing characteristic of the climate change externality is that it is also a
generational issue. If current trends in anthropogenic GHG emissions are allowed to
continue, scientists anticipate irreversible and substantial economic and environmental
consequences in the future (IPCC, 2007: 7). The lag between the externality-generating
activity, on the one hand, and the visibility of negative impacts, on the other, means that
the economic and environmental costs from the burning of fossil fuels will be imposed
not only on current, but especially future, generations (Stern, 2006). The time lag
between the causes of climate change and its effects raise thorny issues concerning how
to assess future benefits from mitigation policy implemented today (i.e. the so-called
‘discount rate’ debate).47
A final remark concerning the external costs of fossil fuel use is worth noting. Climate
change is a politically complex issue precisely because its causes and effects are
inextricably linked to the functioning of modern industrial economies. Given the link
between fossil fuel consumption and economic development, governments have had a
century-long interest in promoting the discovery and use of fossil fuels, with a favourable
mix of large subsidies and disproportionately low taxes. While important for economic
growth, by making fossil fuels relatively less expensive, such a policy framework helps
sustain distortions in energy markets, and systematically discriminates against the
adoption of climate friendly energy products and production processes. As a result, the
current policy framework creates perverse incentives to over-consume fossil fuels, and
increase emissions of carbon dioxide into the atmosphere.
47 This debate largely revolves around critics of the Stern review, which suggest Stern’s discount rate is set too low. See: Stern (2006); Tol and Yohe (2006); Byatt et al. (2006); Nordhaus (2007).
55
2.1.2. Fossil fuel externalities: Energy security Excessive use of fossil fuels is also related to another problem facing many OECD
countries – access to secure and stable sources of energy supply. In the case of energy
security, dependence on foreign sources of petrol can be interpreted as both a negative
externality and a strategic weakness for importing states (Bohi and Toman, 1996). In this
latter case, the externality generated by dependence on foreign sources of petroleum is
the cost of securing resources in geo-politically unstable regions of the world (e.g.
through the financing of wars), or the social costs resulting from energy shortages and
associated price hikes, which impose additional costs on consumers. Figure 2.1.2.1
depicts the volatility in crude oil spot prices while Table 2.1.2.1 summarizes the extent of
crude oil dependency for selected OECD member countries.
Figure 2.1.2.1: World price of oil48
Source: IEA (2009) Table 2.1.2.1: Crude oil imports in 2006 Importing country 1000 bbl/day Population in millions 1000 bbl/year per capita
United States 10,118 298 12 Japan 4,075 128 12 Germany 2,213 82 10 France 1,653 61 10 Italy 1,768 59 10 Spain 1,220 44 10 Netherlands 954 16 21 Great Britain 1,039 61 6 Source: EIA (http://tonto.eia.doe.gov/cfapps/ipdbproject/IEDIndex3.cfm)
48 Series refers to Brent, a high-grade light sweet crude that can be used as an international benchmark.
0
20
40
60
80
100
120
1982 1986 1990 1994 1998 2002 2006 2010
USD
/bbl
Nominal
Real
56
As can be seen in Figure 2.1.2.1, spot prices for crude are highly volatile, at times
increasing rapidly in a manner of months. Table 2.1.2.1 summarizes crude oil import data
for 8 OECD countries. As can be seen, on a per diem basis, the U.S. is by far the country
most dependent on oil imports, and is therefore most vulnerable to external supply
disruptions and price hikes. When countries are compared on a per capita basis, the U.S.
case is less exceptional. The point is that several countries are heavily dependent on
crude oil imports, and this reliance on external supplies constitutes a key vulnerability
and strategic weakness for these economies.
Though use of the term externality here may be “stretching” the concept somewhat
(Sartori, 1970), energy remains under-theorized in the political science literature. As a
result, an assessment of energy policy might benefit from analysis via a lens more attuned
to political forces rather than simply to economic ones. In this sense, interpreting energy
security as an externality seems to apply. To take one example, Russian actions in the
area of its natural gas exports to Eastern and Western Europe have introduced enormous
volatility in energy prices in the region, just as was the case during the oil shocks of the
1970s. Although these actions necessarily play out through price signals (and thus do not
follow the traditional definition of a market externality), they also create uncertainty for
market actors, as well as inefficiencies and distortions in the energy market.49 In this
broader sense, increased energy imports from unstable regions can be interpreted as costs
(distortions) that can be internalized through forward-looking policy that seeks to
mitigate such negative effects. In fact, following the first and second oil crises of the
1970s, some countries began increasing energy taxes as a means of decreasing their
dependence and vulnerability towards external sources of supply. While most notably
done in places like Sweden, even countries like Canada increased excise taxes on motor
fuels in an attempt to reduce demand, and thus vulnerability to external shocks.50
From both a climate and energy security perspective, therefore, excessive dependence on
fossil fuels can be understood as creating external costs. Ironically, existing government
49 Thanks to Caroline Kuzemko for her assistance in helping me think through this point. 50 Private conversation with former official with Finance Canada, John Allan.
57
policy, currently biased against climate friendly and domestic sources of alternative
energy, has further entrenched this dependence on fossil fuels.51 Indeed, allowing
polluters to use the atmosphere as a free dumping ground amounts to an indirect subsidy
for fossil fuels. Moreover, as discussed in Chapters 4 & 5, tax rates are systematically
biased in favour of more carbon-intensive forms of energy. Consequently, the issue of
pricing carbon is not just about internalizing external costs associated with the burning of
scarce fossil fuels, but also one of correcting systematically distorted energy markets and
policies.
2.2. Internalizing externalities: Pricing carbon
The burning of fossil fuels – a cornerstone of modern industrialized economies – thus
generates significant external costs that are collectively borne by the environment and the
human societies embedded within it. Current price structures for fossil fuel energy allow
firms and individuals to dump thousands of tonnes of carbon dioxide and other GHG into
the atmosphere, free of charge, thus encouraging over-consumption. If polluters were
forced to pay for the disposal of their emissions, as is usually the case with other types of
human-made waste, then polluters would have an incentive to emit less (Rivers and
Sawyer, 2008). Over-consumption of fossil fuels, like crude oil and natural gas, also
constitute a strategic weakness for states that are dependent on external sources of supply.
If prices on these fuels were higher, users would have an incentive to consume less,
51 Given the dependence of modern industrial economies on fossil fuels, it is no surprise that mitigating the adverse effects of climate change through GHG reduction is a politically contested issue, for at least three reasons. First, and most relevant to the present study, the root cause of anthropogenic climate change – emissions of carbon dioxide – are deeply entrenched in current patterns of consumption and production, buttressed by a distortionary mix of low taxes and large subsidies for fossil fuels. Current policy and price structures have created a condition of fossil fuel dependence – a cornerstone of modern industrial society – raising the difficult challenge of decoupling economic growth from emissions of CO2. Second, climate change is shrouded in uncertainty – both with respect to its causes and especially its predicted effects. As pointed out by the IPCC, however, recent changes to the earth’s climate are unequivocal, and are highly correlated with the exponential increase in atmospheric concentrations of GHG emissions since the industrial revolution (IPCC, 2007b). In light of such evidence, climate change skepticism is often used as a political smokescreen used to justify the status quo. Finally, climate change is a man-made problem, and in particular, a problem created by the industrialized North. As such, calls for costly mitigation in the global South raise issues of international fairness. While a carbon tax plays into the North-South debate, such issues are beyond the scope of the present analysis.
58
invest in more efficient technology, and substitute for domestically available alternatives
(assuming the latter were somehow made to be cheaper). For this reason, a growing
number of economists (e.g. Mankiw, 2007; Nordhaus, 2007), International organizations
(e.g. EC 1991; OECD, 2001; 2009; IMF, 2008; World Bank, 2010), and NGO’s (e.g.
Pembina, Friends of the Earth) advocate putting a price on carbon emissions as a central
plank in efforts to reduce consumption of fossil fuels and mitigate the adverse effects of
climate change.
The appeal of market instruments to price carbon lies in their ability to satisfy three of the
most oft-cited objectives of environmental policy (Corfee-Morlot and Jones, 1992: 15).
First, market instruments used in climate policy are cost-effective in that the benefits they
bring (reductions in GHG, reduced dependence) outweigh their cost, and the abatement
achieved occurs at minimum cost to society. Second, most studies find market
instruments to be environmentally effective in that their implementation actually reduces
emissions of GHG. Finally, important design features can help satisfy the criterion of
equity, in order to ensure that economic instruments are perceived as being fair. In
addition, carbon taxes present important theoretical advantages over other methods of
pricing carbon52 in terms of encouraging technological progress and being
administratively less complex.
To be sure, decision-makers in the real world must balance these competing objectives,
and there are many obstacles to the proper implementation of market-based instruments.
In particular, valuing the benefits of reduced GHG emissions is especially contentious.
As Corfee-Morlot and Jones (1992: 16) point out, even if we could somehow agree on the
future value of a stable climate, at what level should we discount these values in order to
compare them with present day costs? In addition, GHG emissions can be difficult to
measure, and the cost of a changing climate is difficult to quantify, making
straightforward calculations of the cost-and-benefit of climate policy especially difficult.
Economic instruments also affect the distribution of production and consumption in an
52 For instance, regulation (law enforcing expenditure on mitigation and therefore imposing an emissions price) or an emissions cap and permit trading system.
59
economy, raising thorny questions regarding social equity. Finally, given the global
public good nature of the earth’s climate, an optimal policy response would be
undertaken at the international level. However, given the distribution of costs and
benefits and incentives to free ride, international climate policy coordination is
notoriously difficult to implement, and governments are apparently unwilling to
surrender control of even a small percentage of their domestic tax base to an international
body (Corfee-Morlot and Jones, 1992).
2.2.1. Options for pricing carbon
Notwithstanding these issues, market-based policies are increasingly seen as the most
promising instruments available for addressing externalities in energy markets (Rivers
and Sawyer, 2008; Baumol and Oates, 1985). In fact, the history of climate policy has
evolved from an emphasis on voluntary mechanisms in the 1990s, to the more recent
focus on “coercive” measures like regulation and carbon pricing (Macdonald et al. 2006;
Houle and Macdonald, 2009). To be sure, a carbon price can be set implicitly through
regulation (i.e. a law forcing expenditure on mitigation and therefore imposing a price on
emissions); however, across the OECD the debate has evolved into one that is more
narrowly focused on using market-based instruments (Hahn, 1989; OECD 2001; 2006;
2009).53
There are two basic ways of using the market price to “internalize” the external costs
associated with fossil fuel use. As described by Weitzman (1974), governments can set a
price on pollution either directly, through the tax instrument (i.e. a price-based approach),
or indirectly, through an emissions cap and permit trading system (i.e. a quantity-based
approach). Both harness market prices to internalize some of the external costs associated
with the burning of fossil fuels, and upon further analysis, the two approaches are much
less different than is sometimes portrayed (Fischer et al. 2008). By adding a price to
53 The main advantage of market instruments over regulation lies in their flexibility. Regulations require continuous updating to reflect changes in the latest technology, while market instruments produce a constant incentive to continually invest in efficiency.
60
emissions of carbon dioxide, both instruments force market prices to better reflect the
environmental, social and economic harm associated with fossil fuel use, creating an
incentive for polluters to reduce their emissions.
2.2.2. Carbon tax
In strict terms, a carbon tax is a direct charge levied on all fossil fuels, proportionate to
the carbon content (or carbon emissions) of each fuel.54 Since the carbon content of every
fuel is relatively well known, estimates of the amount of carbon dioxide (CO2) released
from the burning of each fuel can be derived.55 It is thus possible to tax energy sources
based on their specific climate-change potential, usually in terms of their carbon content
or carbon dioxide equivalent (Baranzini et al. 2000). Accordingly, under a pure carbon
tax, coal should be taxed at the highest rate, then oil, then natural gas, since coal emits
more CO2 when burned, and natural gas, the least.56 This feature of adjusting the tax rate
proportionate to carbon content is what I refer to as the principle of differentiation, i.e.
the tax differentiates across tax bases (fuels) according to their associated emissions of
carbon dioxide. For all intents and purposes, this feature is the defining characteristic of
a pure carbon tax. To the extent that other energy sources (like wind, solar, hydro and
nuclear) are carbon free, they are exempt from a pure carbon tax. Thus, a carbon tax is
effectively a tax on fossil fuels (Carbon Tax Centre, 2009).
Conceptually, a carbon tax has much in common with selective excise taxes levied on
specific goods. In this case, however, the tax base is the carbon content of a particular
54 Some authors (Baranzini et al. 2000) distinguish between a tax on the carbon content of fuels (a carbon tax) and a tax on emissions of carbon dioxide from the burning of different fuels (a CO2 tax). This distinction is technical and involves a conversion using a carbon to carbon dioxide ratio of 12/44. The present research uses carbon tax, CO2 tax, carbon levy, carbon tariff, and emissions tax interchangeably. 55 Simply multiply carbon content by the carbon to CO2 ratio (12:44) after factoring in that amount of carbon which is un-oxidized during combustion (IPCC, 1996). 56 The carbon content of coal is 25.1 grams of carbon per 1,000 British Thermal Units (BTUs); 20.3 for oil; and, 14.5 for natural gas (Pearce, 1991: 939). It should be noted that of the three main fossil fuels, the carbon content of coal is the most variable. See IEA (2008); and EIA Annex B “Method for Estimating the Carbon Content of Fuels (B-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2001), p.A.47. http://www.epa.gov/climatechange/emissions/downloads09/Annex2.pdf.
61
fuel, or the associated emissions of carbon dioxide.57 In this way, carbon taxes are
qualitatively distinct from other taxes on energy products more commonly found across
the OECD, such as ad valorem taxes (VAT), which are based on the value of a good or
service, “energy taxes,” which apply to energy consumption regardless of environmental
effect, and excises levied on particular energy sources, such as coal or motor fuels
(Pearce, 1991; Baranzini et al. 2000). Notably, while these latter taxes affect the price of
carbon-based energy, their rates are not set in proportion to the carbon content/emissions
of each fuel, and are thus not a “carbon tax.”58
Carbon taxes create an incentive to reduce emissions of CO2 by forcing individuals and
firms to pay a fee for every tonne of carbon dioxide they emit into the atmosphere. Goods
and services that cause very high emissions become relatively more expensive, and
polluters are forced to either reduce emissions through behavioural change or
technological innovation, or else pay the tax. A carbon tax thus addresses the externality
(more CO2 in the atmosphere) by directly adding a cost proportionate to the carbon
content of, or emissions from, a particular fuel. In this way, carbon taxes are a relatively
simple, direct and straightforward mechanism for “internalizing” the environmental and
social costs of burning fossil fuels.59
At the conceptual level, carbon taxes have certain theoretical advantages that make them
a preferred policy instrument among many climate policy experts (Nordhaus, 2007;
Hansen, 2008; Hyndman, 2009). These advantages can be summarized in terms of
meeting three key policy criteria: efficiency, equity, and effectiveness. They can also be
used as criteria against which existing carbon tax policy can be assessed (Chapter 3).
57 Since the correlation between the carbon content of a particular fuel and carbon emissions of that fuel is very high, a tax on the carbon content will have a similar impact on anthropogenic GHG as a tax on emissions. 58 It is important to note that taxes on energy can be considered an “implicit” or “defacto” carbon tax. This point is elaborated on in chapter 4. 59 Pigouvian tax theory suggests that the “optimal tax” level should be equal to the external costs associated with an externality. To be sure, assigning a monetary value to environmental goods and human health is highly controversial (Ekins and Barker, 2001: 329). From a practical standpoint, however, the notion of internalizing the costs of climate change is less to set an accurate price on the externalities associated with fossil fuel use than increasing the relative price of fossil fuels in order to reduce GHG emissions.
62
Cost-efficiency. A carbon tax is “cost-effective” in the sense of minimizing the aggregate
social costs of abatement (Pearce, 1991). By imposing a uniform price on carbon that is
applied economy-wide, the marginal cost of emissions reductions is equalized across all
sectors of the economy (a condition for cost-effectiveness), ensuring that those in an
economy with a low marginal cost of abatement (i.e. those for whom the cost of
abatement is lower than the price to pollute) have an incentive to reduce emissions (i.e.
increase abatement).60 The choice of whether to emit and pay the tax, or reduce emissions
(through energy conservation, investing in more efficient technology, or substituting for
less carbon-intensive fuels), thus falls on individual polluters, each possessing their
unique marginal cost function for pollution abatement. Each polluter weighs the cost of
emission control against the cost of emitting and paying the tax, and will invest in climate
friendly technology when the cost of such actions is less than what it would cost to
continue emitting (IPCC, 2007a: 755). Assuming actors are rational,61 low marginal cost
polluters will make greater abatement efforts (since the cost of abatement is less than the
price to pollute), achieving the intended reduction in pollution at the lowest aggregate
cost to society (Pearce, 1991: 941; Baranzini et al. 2000: 396; Grafton et al. 2004: 64).
Equity. The key feature of a carbon tax that makes it cost-effective – a uniform rate
applied economy-wide – also makes a carbon tax potentially regressive, in the sense that
it might impose a relatively larger cost on low-income families. Since lower income
families spend a disproportionate amount of their income on energy, an increase in
energy prices for non-luxury goods will have a relatively greater impact on the disposable
income and welfare of the poor. However, unlike other forms of pricing carbon – either
through an emission cap and permit trading system, or regulations (i.e. standards that
impose a defacto price on emissions) – a tax is also inherently revenue raising.62 With
60 As Hahn (1989: 96) explains, “If all firms are charged the same price for pollution, the marginal costs of abatement are equated across firms, and this result implies that the resulting level of pollution is reached in a cost-minimizing way.” See also: Hahn (1986); Hoel (1996); and IPCC (2007a: 755). 61 Since the debate over climate policy centres primarily on issues of cost, the “rational actor” assumption seems plausible. Applying a price to emissions, however, may have the unintended effect of legitimating the act of polluting, and of increasing emissions (c.f. Danhof 2008). 62 Though there are many theoretical advantages to auctioning permits, in practice, all emissions trading schemes allocate permits based on past emissions, free of charge. Such practice makes it difficult to reward early action, creates barriers to entry for new firms, and does not raise revenue for governments.
63
the judicious use of revenues, the regressive effects of carbon taxes can largely be offset
if revenues are used progressively, as is done in many Scandinavian countries where
regressive taxes are used to finance a progressive welfare state (Kato, 2003). Thus, the
regressive effects of a carbon tax can be offset with various mechanisms, raising some
debate about how best to use revenues derived from a tax, which can be directed toward
the general government budget, earmarked for other environmental programs, or used to
decrease other taxes and achieve the goal of “revenue neutrality.”63
Environmental Effectiveness. Theoretically, carbon taxes are thought to be effective in
terms of reducing emissions in that they generate monetary incentives to produce energy
efficient goods from low-carbon energy on the supply-side, as well as incentives to
consume such alternatives on the demand side. In fact, more so than any other
instrument, a carbon tax creates on-going incentives to reduce emissions. To be sure,
regulations tend to be technology-based (e.g. fuel efficiency standards), and encourage
emitters to adopt particular technologies. Under such a framework, there is little
incentive for emitters to reduce emissions beyond the prescribed standards, unless
governments continually adjust regulations so that they are slightly above the best
available technology (OECD, 2006; Zhang and Baranzini, 2004: 508). Similarly, an
emission cap and permit trading system also lacks such “dynamic efficiency,” since
permit prices are likely to fall over time as climate friendly technology is diffused,
eliminating the incentive to continue with emission reductions (Baumert, 1998). In
contrast, a carbon tax provides a permanent incentive to innovate and adopt new
technologies, for as long as carbon-based fuels are used (Pearce, 1991: 942). Such
permanence helps to ensure on-going reductions in GHG, ostensibly the primary
motivation underlying any appropriately labeled “carbon tax.”
63 Carbon tax revenues can be used for a variety of policy objectives, and these may not necessarily be environmental. For instance, Scandinavian countries adopting a carbon tax stress the importance of not only decreasing emissions of GHG, but also of making the tax structure more efficient (i.e. the “double-dividend hypothesis”). Others suggest that some of the revenue should be dedicated to ensure that the less well off in society are not systematically disadvantaged by the tax (c.f. Sadik, 2008).
64
In practice, experience with the direct taxation of CO2 suggests that carbon taxes are in
fact effective instruments for reducing emissions of CO2 and the associated risks of
climate change. Although empirical studies of “environmental effectiveness” are limited
in number and marred by methodological difficulties (Baranzini et al., 2000: Ekins and
Barker, 2001: 345), all of the available evidence suggests that carbon taxes are correlated
with reductions in either absolute emissions of carbon dioxide, or with reductions in the
emissions intensity of production. In addition, it should also be noted that the long-term
environmental impact of a carbon tax is likely to be greater than its short-term impact,
since the price signal given by a rising carbon tax might affect investment decisions
concerning capital stock turnover, which occurs over a longer time-horizon (Baranzini et
al, 2000: 406).
Summarizing the available literature, Baranzini et al. find broad support for the
environmental effectiveness of carbon taxes (2000: 407), as does the IPCC (IPCC, 2007:
756). For instance, emissions of carbon dioxide decreased by 6% in Denmark between
1988 and 1997, while the economy grew by 20 per cent, and Danish emissions dropped 5
per cent between 1996 and 1997, the year the Danish carbon tax was raised (IPCC, 2007:
756). In another oft-cited study, Bruvoll and Larsen report that while emissions did not
decrease since the implementation of the Norwegian carbon tax, emissions intensity
(emissions per unit of GDP) witnessed a significant reduction (2004).64 Even quasi-
carbon taxes, such as the UK’s “Climate Change Levy,” have been found to be effective
in terms of reducing emissions of GHG (IPCC, 2007: 756).
64 It should be noted that the modest success of the Norwegian carbon tax has been attributed to extensive exemptions for energy intensive sectors, and to inelastic demand for carbon-based fuels (Bruvoll and Larsen, 2004).
65
2.2.3. Carbon trading
An alternative, potentially complimentary,65 means of internalizing the costs associated
with fossil fuel use is the cap-and-trade system.66 Under cap-and-trade, policy-makers
create scarcity for emissions permits by setting a fixed limit (or “cap”) on the total
amount of CO2 emissions for included sectors of the economy. The cap (usually
measured in mega-tonnes of CO2) is then divided into a number of allowances or credits,
and such permits are then issued to emitters by free allocation or auction.67 The number
of permits cannot exceed the cap, and polluters cannot emit beyond their allowances,
ensuring that a given target is met.68 A market is then set up to allow the trading of
permits. Heavy polluters can chose to invest in technology to decrease total emissions, or
must purchase credits from other regulated entities that pollute less. When heavy emitters
purchase credits, they effectively pay a charge for polluting, and reward the seller, who
pollutes less. A cap-and-trade system thus creates property rights for pollution, and the
right to emit becomes a tradable commodity.
As is the case with a carbon tax, the trading of permits imposes a uniform carbon price
for regulated entities under the regime, ensuring that GHG reductions are achieved in a
cost-effective manner. Those for whom the marginal cost of abatement is cheaper will
reduce emissions and sell excess credits to those emitters for whom abatement is
65 Cap-and-trade systems are generally more applicable for regulating large heavy emitters, usually covering roughly half of an economy, while a carbon tax should in principle be applied economy wide. As a result, proponents of carbon pricing sometimes point out synergies in the two approaches, as they can be combined (c.f. Lee et al. 2008). 66 Cap-and-trade is sometimes referred to as emissions trading, carbon trading, and the permit system. These terms are used interchangeably in the present analysis. 67 The auctioning of permits has important advantages over free allocation. First, auctioning generates government revenue that can be used for progressive purposes. Second, auctioning eliminates barriers to entry for new firms that must pay for allowances that were initially given away at no cost under the free allocation design. Third, auctioning gives “credit for early action,” effectively rewarding those firms that undertook early abatement in that they will have to purchase a smaller number of credits. Finally, auctioning avoids the problem of firms ramping up production prior to the free allocation of permits, in anticipation of their being “grandfathered” according to past emissions. Despite these theoretical advantages, however, credits are usually always allocated freely based on a “grandfathering” formula, which makes it politically easier to implement cap-and-trade. 68 In theory, the cap should be reduced over time in order to achieve continued reductions. In practice, removing permits from the system is politically difficult.
66
relatively more expensive. Thus, in theory, pollution is reduced at the lowest possible
cost. Unlike a carbon tax, however, a well-functioning trading system depends crucially
on an effective monitoring and enforcement regime that imposes penalties at a level
substantially higher than the prevailing price for permits (IPCC, 2007: 759-9).
In practice, cap-and-trade systems have been implemented with some success. The most
often-cited examples include the sulfur-dioxide market in the U.S., and the European
Emission Trading System (ETS) developed under the Kyoto framework.69 The U.S.
experience with sulfur dioxide (SO2) trading is generally cited as a successful case of
market-based policy. Although it took nearly five years to set up, once implemented, the
U.S. sulphur market helped generate very large reductions in sulfur emissions (Sorrell
and Skea, 1999; McLean, 2007). In contrast, the European ETS was implemented in a
relatively short three year time period, but its first phase of implementation (2005 – 2007)
has since been criticized for over-allocating allowances and excessive price volatility. To
be sure, there has always been a sense that the first phase was more of an experiment, and
efforts have been made to improve the European ETS in the second phase (MacKenzie,
2007; Skjærseth and Wettestad, 2008). Recent evidence from Point Carbon indicates that
abatement efforts are now beginning, and overall, analysts suggest the improved EU
system will result in larger GHG reductions in the future (Grubb et al, 2005; Betz et al,
2005; Betz and Sato, 2006).
2.2.4. Comparing tax and trade
Both carbon taxes and emissions trading are examples of market-based approaches to
climate policy. As such, both instruments put a price on carbon, internalizing some of the
external costs associated with the burning of fossil fuels, and both create incentives to
reduce the use of carbon-based energy and become more energy efficient. The main
features of the tax and trade options are summarized in Table 2.2.4.1.
69 The EU ETS is the world’s largest tradable permits system, applying to approximately 11,500 heavy emitters across the EU’s 25 Member States, responsible for about 45% of the EU’s total CO2 emissions.
67
Table 2.2.4.1: Main features of carbon tax vs. cap-and-trade
Carbon Tax Cap-and-Trade
Price Fixed
(price certainty)
Volatile
(price uncertainty)
Emissions Reduced
(quantity uncertain)
Capped
(quantity certain)
Coverage Economy wide (exemptions for
sensitive industry)
Heavy emitters (sector specific,
initially, high transaction costs)
Economy-wide if applied
upstream (fuel distributors)
Revenue Generates revenue for tax cuts or
expenditures (can be used to
offset regressive effects if spent
progressively)
Only if permits are auctioned
Administration/
Implementation
Less complex, can be readily
implemented in less time and
with existing administrative
bureaucracy
Highly complex, requires
protracted negotiation around
design and creation of new
institutions
Political
feasibility
More visible to consumers
(politically less popular)
Costs are hidden, passed on to
consumers
(politically preferred)
Design Issues Tax base (coverage)
Collection point
Price level
Coverage
Point of obligation (upstream or
downstream)
Cap level
Initial allocation
Price ceiling/floor
Monitoring & enforcement
Note: this table builds on Olewiler (2008)
68
In theory, the main difference between the two instruments lies in setting the price versus
quantity of emissions (Weitzman, 1974). Taxes are “price-based” instruments, meaning
that the price of carbon is fixed, and the quantity of emissions adjusts according to
decisions made by private actors in the market (i.e. whether to change their emission-
generating behaviour, or pay the tax).70 Conversely, emission trading is “quantity-
based,” meaning that the quantity of emissions is capped by government (or some
authority) at a certain level, creating scarcity, allowing the price of emissions to fluctuate
within a market, through trading or auctions (where heavy emitters buy permits from the
government of from those polluting less). Theoretically, the choice between the two
creates a tradeoff between price certainty (important for investment decisions) and
emissions certainty (important for environmental considerations). For this reason, taxes
are sometimes preferred because they provide emitters with cost certainty, crucial when
making long-term investment decisions, while environmentalists sometimes prefer
trading, because its outcome is more certain with regards to achieving a given reduction
in emissions (Ekins and Barker, 2001: 331).
Despite the differences outlined in Table 2.2.4.1, however, tax and trade options are
broadly equivalent (Elkins and Barker, 2001: 329-330). Indeed, Fischer and Hinchy
(2004) demonstrate that both approaches can be equally cost-effective, if certain
assumptions regarding the design of cap-and-trade are met. For instance, when permits
are auctioned and the system is applied economy-wide, the two approaches are
functionally equivalent. Consistent with the “polluter pays” principle, emitters are forced
to decrease emissions, or else pay a fee. But while the fee is fixed under a tax, and set by
government, it can fluctuate under cap-and-trade according to supply and demand, and in
this sense, a cap-and-auction system is essentially a privatized carbon tax (Hyndman,
2007).
70 A central authority (i.e. government of international organization) sets a price for carbon, and emitters chose how much to emit, according to their marginal abatement costs and future investment decisions.
69
Crucially, from a policy perspective, the two options face many of the same issues when
considering their design; decisions made on the particular design of either a tax or trading
system can erode the distinctiveness of either approach. For instance, policy-makers
interested in implementing either a tax or cap-and-trade must first decide on what sectors
of the economy will be affected, and what sectors are exempt, and this choice can
minimize a commonly cited difference between the two in terms of coverage (economy-
wide versus sector-specific).71 Similarly, if permits are auctioned under cap-and-trade, it
too can raise government revenue, which can be used to offset any potential regressive
effects, (a carbon tax is inherently revenue raising). To take another example, commonly
cited problems with cap-and-trade, such as price volatility and the associated difficulty
business has with making investment decisions under price uncertainty, have given rise to
discussion of establishing a so-called price-collar (i.e. price ceilings and floors).72 One
option, the “safety-valve,” allows emitters to purchase permits from the government at a
specified trigger price (Jacoby and Ellerman, 2004), effectively removing the “cap” from
cap-and-trade. If implemented, innovations like the safety-valve generate more certainty
regarding price, but at the cost of less certainty regarding whether a particular emissions
level can be met. In these lights, when the pure form of either the tax or trading options
are implemented in actual policy, important design characteristics can blur the theoretical
distinction between “price versus quantity” discussed above (c.f. Fischer et al. 2008).
2.3. Issues in the design of a carbon tax
Although carbon taxes meet the criteria of efficiency, equity and effectiveness in theory,
from a practical standpoint, policy-makers must balance these sometimes-competing
policy objectives. Given the politics of implementing any policy that generates winners
and losers, governments must make compromises and tradeoffs when designing policy
71 Because they are more straightforward to implement, carbon taxes tend to be applied economy-wide. In practice, cap-and-trade systems are usually sector specific, targeting heavy emitters, since it would be administratively complex and increase transaction costs to a prohibitive level were they to cover all emitters. 72 Such innovations are referred to as “hybrid models” in the literature.
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instruments. Concerning their implementation, four design issues are of central concern;
tax base, incidence, collection point, and level.
Tax base (What to tax). The first key issue when designing a carbon tax concerns the
relevant tax base, or what to tax. Although the Kyoto Protocol covers six GHG, each with
its own effect on atmospheric warming per unit of emissions, the focus of climate policy
tends to be on carbon dioxide, the most significant contributor to anthropogenic GHG.73
Accordingly, policy-makers can levy a tax on the quantity of carbon embodied in a
particular fuel (i.e. a “carbon tax”), or on the specific amount of CO2 emitted when a fuel
is burned (i.e. a “CO2 tax”).74 The choice of whether to tax carbon content or emissions
is a technical issue, and a tax rate on carbon can easily be transformed to a tax on
emissions using the well-known ratio of carbon to CO2 (44:12). In either case, the tax
base is essentially the carbon content of a particular fuel, and in this way carbon taxes
should differentiate among different fuels according to their environmental effects. This
principle of differentiation is the key distinguishing feature of a pure carbon tax, but as
demonstrated in Chapter 3, is inconsistently applied across all jurisdictions with a so-
called “carbon tax.”
Incidence/coverage (Who to tax). Unlike the relatively straightforward question of what
to tax, policy-makers interested in implementing a carbon tax face the politically
contentious issue of social incidence and coverage, i.e. who should pay? In principle, a
carbon tax should apply equally to all uses (e.g. household and industrial) of the same
fuels, without any exemptions so that they are imposed economy-wide. To be sure, the
ability of existing tax agencies to apply a new tax across all sectors of the economy,
without creating any new institutions or bureaucracy, is a key advantage of the carbon tax
over carbon trading proposals.
73 When considering taxes on other GHG, policy makers can use carbon dioxide equivalents, which provide a standardized measure of atmospheric warming per unit of emissions for different GHG. 74 An alternative tax base proposed by the Carbon Tax Centre, a non-profit carbon tax advocacy NGO established in 2007, is to tax in terms of per million BTU heat content for each fuel. Baranzini et al. (2000: 397) point out that taxing in BTU is more common for energy taxes than for carbon taxes.
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Applying a uniform rate across all sectors of the economy is important for two key
reasons. First, all things being equal, a uniform price applied to all sectors of the
economy will be more environmentally effective, since all sources of CO2 emissions are
regulated. By covering all emitters, incentives are created for consumers to demand less
carbon intensive goods and services (because they are made cheaper by the tax) and for
producers to satisfy this demand (on the supply side). Second, universal coverage is also
important for the theoretical efficiency of a carbon tax. As discussed in section 2.2.2, if a
uniform price on the use of a particular fuel is imposed across all emitters, then the
marginal cost of abatement is equated across all polluters, ensuring that only those for
whom the marginal cost of abatement is lower than the tax will make efforts to reduce
their emissions, at lowest cost to society. However, as demonstrated in Chapter 3, the
principle of universal coverage is often sacrificed in order to ease the burden of
implementation, satisfy the demands of import-competing and energy-intensive industry,
and to increase the political acceptability of a new carbon tax more generally.
Collection point. Another question is where to tax, i.e. whether the tax should fall on
producers or consumers. Textbook economic theory suggests that a Pigouvian tax should
be imposed at the point of the externality-generating activity, usually “downstream,”
where the fossil fuels are actually combusted (Pearce, 1991). By taxing at the point of
externality, policy-makers ensure the tax achieves its intended consequence. For
instance, in the case of fossil fuels, petroleum is used in the manufacture of plastics.
Were petroleum to be taxed “upstream,” at the point of production, then plastic
manufacturers would be paying a higher price for their inputs, despite not causing any
emissions. Moreover, a tax levied “upstream,” on production, would essentially be a tax
on extraction, which could disproportionately affect net carbon importers if
internationally applied. As argued by Pearce (1991: 945) and others, (e.g. Zhang and
Barnzini, 2000: 509), if the point is to reduce GHG emissions, then the tax should be
consumption based. Others argue that there are advantages to taxing “upstream” (Carbon
Tax Centre, 2009; Barthold, 1994: 139). Since there are fewer producers and retailers
than fossil fuel energy consumers, a tax administered between producers and retailers
would minimize the collection points for the tax, making collection administratively
simpler. In addition, by imposing a price at the source, it wou
producers from employing environmentally harmful practices in the production of fossil
fuels, like gas-flaring in Alberta’s oil sands. Regardless of government choice on this
matter, experience suggests prices are ultimately passed on
Price level (What price). A further
carbon tax is deciding on the level that will produce the required level of emissions
reduction (i.e. fully internalize the externality)
carbon price, though they disagree on how high it should be.
optimal level of a carbon tax is relatively straightforward. Economists often use a highly
simplified model to illustrate that an efficient level
refining) is reached when the marginal private cost of pollution abatement equals the
marginal benefit (Figure 2.3.1
Figure 2.3.1: Setting the optimal carbon tax l
Source: Freebairn (2000)
simpler. In addition, by imposing a price at the source, it would discourage energy
producers from employing environmentally harmful practices in the production of fossil
flaring in Alberta’s oil sands. Regardless of government choice on this
matter, experience suggests prices are ultimately passed onto consumers.
A further difficult and controversial issue when designing a
carbon tax is deciding on the level that will produce the required level of emissions
(i.e. fully internalize the externality). Economists call this level the “optimal”
carbon price, though they disagree on how high it should be. In theory, setting the
optimal level of a carbon tax is relatively straightforward. Economists often use a highly
simplified model to illustrate that an efficient level of a given polluting activity (e.g. oil
refining) is reached when the marginal private cost of pollution abatement equals the
.1).
.1: Setting the optimal carbon tax level
72
ld discourage energy
producers from employing environmentally harmful practices in the production of fossil
flaring in Alberta’s oil sands. Regardless of government choice on this
difficult and controversial issue when designing a
carbon tax is deciding on the level that will produce the required level of emissions
l this level the “optimal”
In theory, setting the
optimal level of a carbon tax is relatively straightforward. Economists often use a highly
of a given polluting activity (e.g. oil
refining) is reached when the marginal private cost of pollution abatement equals the
73
Figure 2.3.1 illustrates the theory underlying the optimality of carbon taxes.75 The model
assumes that there is a direct proportional relationship between output in this particular
industry and pollution discharge, represented on the horizontal axis. Let us assume that
the sector in question is for gasoline production, and that the demand elasticity is
somewhat elastic, as the slope of D would suggest. The demand curve (D) represents the
demand for gasoline, and reflects the intuitive idea that as the price begins to rise, the
quantity demanded (and associated pollution) will decrease. The upward sloping supply
curve, S, reflects the private cost of producing gasoline, in terms of, for instance, land
labour and capital. This curve also represents the intuitive idea that as the price of
gasoline goes up, so will the quantity produced. Finally, the marginal social cost curve
(SS) represents the marginal external (or social) cost of each additional unit of pollution
emitted. The SS curve is therefore an estimate of the cost imposed on the environment
and society (the marginal external cost, i.e. the externality), or what economists call the
“damage cost” (i.e. a measure of society’s loss of wellbeing that results from the damage
imposed by an externality-generating activity), quantified in monetary terms.
According to textbook economic theory, the intersection of curves S and D represents a
market failure insofar as the competitive market equilibrium (quantity Q) ignores the
marginal social or external cost (MEC) of pollution. Under such conditions, the price of
the externality-generating activity is kept artificially low (P), leading to excess economic
activity and higher levels of pollution (in this case, GHG emissions). If a carbon tax is
levied in an attempt to account for MEC, then the private marginal cost rises from S to S1
= S + T, where T is the per unit carbon tax (e.g. $100/tonne of CO2). With the imposition
of the tax, competitive markets choose the quantity where S1 and D intersect, that is, at
quantity Q*, which is, in theory, the socially optimal level of production for this good.76
Assuming the tax is equal to the marginal external cost of pollution associated with fossil
fuel production and consumption,77 the private market chooses the socially optimal
75 Figure 2.3.1 and its interpretation are based on Freebairn (2000). 76 At this level, the price of gasoline increases, while the quantity produced/consumed and associated emissions fall. 77 The empirical validity of this assumption is discussed below.
74
quantity Q*, where the marginal cost of pollution abatement is equal to the marginal
benefit. As noted by Freebairn (2000), “setting the pollution tax at a rate equal to the
marginal external cost internalizes the externality into private sector decisions.” The task
is to determine the socially optimal level of the good to be maintained (e.g. setting a
target on GHG emissions) and the level of tax required to achieve the intended target
(e.g. setting tax rates on carbon-based energy).
If the goal is to internalize the external costs of a polluting activity, then ideally, the level
of tax should be equal to the marginal external cost (MEC). However, try as they might,
economic estimates of damage costs, and assigning a monetary value to environmental
goods and human health, are highly controversial (Ackerman and Heinzerling, 2004).
Since the true damage cost of emissions can never be known (Ekins and Barker, 2001;
Owen, 2004), economists take the “second best” approach of using “control costs” (i.e.
the costs of abatement) as a surrogate for the damage imposed by pollution, and call the
“optimal” tax the one that minimizes the cost of reaching a given level of GHG
reductions. Setting an optimal tax on emissions of carbon dioxide, therefore, does not
necessarily require an accurate estimate of the damage costs of fossil fuel use. All that is
required is an acceptable standard (target level of GHG) so that pricing options can then
be compared in terms of the relative cost of abatement they impose (Owen, 2004). From
a practical standpoint, the notion of internalizing the costs of climate change is less to set
an accurate price on the externalities of fossil fuel use than increasing their relative price
in order to discourage the use of certain types of energy and reduce GHG emissions.
In practice, setting the tax level is much more an exercise in politics than one of applied
economic theory. As a result, some observers fear that fixing a price on carbon through
tax is too arbitrary – if set too high, a tax might hurt economic growth; if too low, a tax
might not lead to the intended reductions in emissions (McMahon, 2008). Such fears,
however, appear misplaced. As pointed out by carbon tax proponents, unlike technology-
based standards, which are less flexible, taxes can be adjusted more readily as observed
effects of existing price levels on emissions and economic growth come to light. While
this may be politically difficult, governments can also legislate trial periods and
75
automatic tax increases over time, as is often done in practice. Such flexibility is crucial
given the rapidly changing nature of both economic circumstances and the science of
climate change (Pearce, 1991: 942). To make taxes more politically acceptable and in
order to ease the cost of adjustment, governments are likely to set the level low and
gradually increase the rate. The gradual increase is crucial if the tax is to reflect the
rising costs of atmospheric CO2 concentrations over time. Moreover, a continuous,
legislated and automatic increase in the tax ensures that the real tax rate is not eroded by
inflation, and provides an incentive for innovation and early adoption of efficient
technology as firms and individuals anticipate rising costs of emissions. Thus, a carbon
tax can encourage the desired behavioural change even at lower levels of the tax as
individuals and firms adjust early in anticipation of higher prices (Zhang and Baranzini,
2004; c.f. Cadot and Sinclair-Desgagné 1995).
As will be discussed in Chapters 3 & 4, the price at which CO2 is currently taxed varies
widely across countries and across fuels. In many countries, coal is not taxed at all, while
other fuels are taxed at rates up to as high as $400 USD per tonne of carbon dioxide.
However, these rates are not applied to all fuels. In contrast, the IPCC projects that a
global carbon price of about 30 to 40 Euros will be required by 2020 to achieve
stabilization of atmospheric greenhouse gas concentrations at 450 to 550 ppm (Andersen,
2009).
2.4. The Political Economy of Instrument Choice
For all their similarities, a cap-and-trade approach to pricing carbon has enjoyed
relatively more success in the political arena (Keohane et al. 1998; Andrew et al. 2010).
At the international level, cap-and-trade was included in the Kyoto framework under the
so-called “flexibility mechanisms,” giving rise to the establishment of the world’s largest
carbon market in the European Emissions Trading System (ETS). Although Kyoto
leaves room for (and in fact encourages) domestic actions like carbon taxes, no
jurisdictions has unilaterally implemented a carbon tax since ratification of Kyoto in 1997
76
(the exception is British Columbia). In contrast, cap-and-trade systems for carbon
dioxide emissions have flowered across Europe since the signing of Kyoto, and plans to
establish national cap-and-trade systems are currently being discussed in Australia and
Japan, among others. In addition, regional initiatives have taken place in North America
(WCI, RGGI), and cap-and-trade proposals currently dominate domestic climate policy
discussions in the U.S. and to a lesser extent, in Canada. Meanwhile, across the Anglo-
Saxon world, carbon tax proposals have faced resistance in such countries as Canada, the
U.S., Ireland, Australia and New Zealand.
A key reason for the adoption of cap-and-trade over carbon tax proposals at the global
level has to do with the interests and power of the U.S., which insisted on the inclusion of
flexibility mechanisms under the Kyoto framework. Initially, the European Union
preferred a system of harmonized carbon taxes to promote low-carbon technologies, but
eventually conceded to U.S. pressure for carbon trading (Christiansen and Wettestad,
2003; Ellerman et al. 2007). To be sure, the success of the sulfur-dioxide market in U.S.
acid rain policy shaped how the Clinton Administration approached Kyoto (MacKenzie,
2007). However, the U.S. preference for trading over taxes can also be explained with
reference to the U.S. energy and emissions profile (Baumert, 1998). Relative to other
countries, the U.S. is characterized by energy inefficiency and high per capita emissions.
As a result, a carbon tax would penalize the U.S. relative to other countries that are less
dependent on fossil fuels. Industry in the U.S. has thus tended to lobby against taxation
and in favour of trading, which would allow U.S. firms to purchase allowances from
other countries and avoid having to reduce emissions through costly GHG reduction
strategies implemented at home. Even though the U.S. eventually backed out of Kyoto,
carbon trading has been institutionalized at the international level, and the EU has opted
for creating an international system for GHG reductions that the U.S. can eventually
join.78
78 In addition to U.S. pressure, deep divisions within the EU itself, and the institutional characteristics of the European Union make a European-wide carbon tax relatively more difficult to implement than carbon trading. Under EU decision-making rules, tax measures require unanimity, while emissions trading falls under environmental policy where decisions can be made under less stringent “qualified majority voting” rules. European plans for a Europe-wide harmonization of carbon taxes thus floundered in 1993 and 1994 in the face of opposition from industry and especially the U.K., which was able to play a veto role. For
77
A second reason for the relative popularity of trading over taxes has to do with more
general characteristics of the two approaches in terms of visibility and magnitude of
costs. As argued by Barthold (1994: 143), the choice of market-based instrument
presents policy-makers with a choice between hiding and declaring costs. Moreover, as
argued by Weaver and Pal (2003), governments will generally eschew policies that may
cause “pain,” or visible harm to their constituents. In contrast to taxes, which directly
impose costs, existing cap-and-trade systems almost always allocate permits freely, based
on the past emissions of each regulated entity (so-called “grandfathering”).79 Although
such practice creates barriers for new firms entering the industry (since they are forced to
buy permits that were initially given away), and does not create government revenue (as
auctioning the permits would), the practice of free allocation is used in order to make
cap-and-trade more politically acceptable. To be sure, grandfathering allows firms to
ramp up emissions prior to permit allocation, which can lead to over-allocation and
ensures that business can avoid taking costly action to reduce emissions. In addition, a
system of cap-and-trade ensures that some firms will be “winners” in the sense that they
will have excess permits to sell on the carbon market. In this way, grandfathered permits
gives firms something of value, which can be traded, and the costs of reduction can be
passed indirectly to consumers, who believe cap-and-trade makes industry pay. In
contrast, taxing has the appearance of only creating “losers” in the sense that all emitters
subject to the tax are forced to pay.
Notwithstanding the apparent popularity of emissions trading over carbon taxes, the
following chapters examine the politics and economics of carbon taxes exclusively. This
focus is partially the result of limitations in terms of time and space. A review of both
types of instruments is not possible within the confines of this in-depth study of taxation.
Carbon taxes have also been selected as the focus because climate policy experts
other accounts of why the EU abandoned the climate energy tax proposal, see Zito 2002; Haigh 1996; Klok 2002 and MacKenzie, 2007. 79 The relatively new experience of auctioning withing the Regional Greenhouse Gas Initiative is an exception. Discussions around the Western Climate Initiative also indicate that some permits will be auctioned.
78
frequently advocate them as the simplest and most direct way to put a price on carbon,
yet governments vary widely in terms of how they tax carbon. Finally, the fact that
carbon-energy taxes are used by all OECD jurisdictions, despite the inherent difficulties
in implementing any type of tax reform, provides an excellent opportunity for an analysis
of the comparative politics of carbon taxation.
79
Chapter 3: Carbon taxes in practice
3. The political limits to implementing carbon taxes
As highlighted in Chapter 2, a carbon tax (and some forms of cap-and-trade) can reduce
GHG emissions at least cost to society. As a result, countless government and NGO
studies from the climate policy community now embrace market-based approaches to
climate policy, and espouse the relative merits of putting a price on carbon (NRTEE,
2007; 2009; Metcalf, 2007; CBO, 2008; Demerse and Bramley, 2008; Mintz and
Olewiler, 2008; Rivers and Sawyer, 2008). In addition, there is now a broad-based,
cross-cutting consensus among economists (e.g. Mankiw, 2007; Nordhaus, 2007),
environmentalists (e.g. Hansen, 2008; Brown, 2008), and even some members of the
business community (Hyndman, 2009; Clark, 2009),80 who otherwise make strange bed-
fellows, that a carbon tax is the most efficient and in many circumstances the most
effective policy instrument to price carbon, and by association, reduce consumption of
fossil fuels and associated emissions of greenhouse gasses (GHG).
Despite the overwhelming enthusiasm for carbon taxes among experts, however,
governments have been somewhat reluctant to unilaterally implement domestic carbon
taxes at home. Indeed, relative to such alternatives as carbon trading, carbon taxes have
proven to be a politically difficult sell, witnessed in both the frequency with which
jurisdictions decide on implementing a carbon tax, and in terms of fundamental flaws in
their design, once implemented. Moreover, carbon tax proposals have failed in several
parts of the world, sometimes miserably. Notable cases of ill-fated proposals include U.S.
President Clinton’s proposed Btu tax (1993), Italy’s suspended carbon tax (2000), New
Zealand’s abandoned carbon tax following the re-election of a minority government
(2005), the dismal election performance of Canadian Liberal Party Leader Stephan Dion,
who campaigned and lost on a green tax shift proposal (2008), and the recent French
constitutional court’s decision to strike down President Sarkozy’s carbon tax plan (2009).
80 Exxon Mobile in the United States, and the Canadian Association of Petroleum Producers, are among some of the business organizations to make public their preference for a carbon tax.
80
Such experience with failed tax proposals has shown that important domestic and
international political factors can prevent carbon taxes from being implemented
(Harrison, 2010). In addition to the general aversion to implementing new taxes, and to
“the politics of pain” more generally (Pal and Weaver, 2003), concerns over
distributional consequences (like equity and regressivity) as well as concerns regarding
economic competitiveness, make implementation politically difficult (OECD, 2001;
2006; Weir, 2004; Zhang and Baranzini, 2004). Moreover, and in contrast to such other
policy instruments as emission trading, taxes impose direct and visible costs on society,
which further makes for a tough political sell (Barthold, 1994).
Nevertheless, a few European countries and sub-national jurisdictions in North America
have gone ahead and implemented their own version of a “carbon tax,” though these
taxes are yet applied across the economy with uniform rates for sectors and fuels
(Andersen, 2008; Ciocirlan and Yandle, 2003). Moreover, upon further analysis,
important design characteristics, which are adopted to make tax proposals politically
palatable, severely undermine the theoretical advantages of carbon taxes, and blur the
distinction between a textbook carbon tax and other types of more commonly found
energy taxes.
The purpose of this chapter is to “take stock” of the current state of carbon taxes that
have so far been implemented in jurisdictions across the OECD. Building on the
discussion in Chapter 2, this chapter summarizes key defining characteristics of a carbon
tax that may act as criteria against which actual carbon tax designs can be assessed (3.1).
Next, the chapter highlights common trends and key differences (3.2) in the design of
existing carbon taxes. After highlighting significant departures from economic theory, the
chapter assesses the plausibility of the electoral system argument outlined in Chapter 1
for explaining an important limitation of the British Columbia carbon tax (3.3).
81
3.1. Taking stock of explicit carbon taxes in the OECD: A critical appraisal
Implementing a carbon tax is no easy task. New carbon tax proposals face opposition
from entrenched fossil fuel interests and energy-intensive, trade-exposed sectors of the
economy. In addition, voters are often suspicious of new tax reforms, and seem
categorically opposed to increases in tax rates on motor fuels (Hsu et al. 2008). Given
the politics associated with their implementation, political trade-offs must be made, and
such design characteristics can significantly detract from the theoretical advantages of
carbon taxes discussed in Chapter 2.
If one were to evaluate the carbon taxes currently in place according to the theoretical
ideal (Chapter 2), one might consider at least four key criteria. First, carbon taxes should
differentiate the tax rate imposed on different fuels, according to their carbon content or
associated emissions of carbon dioxide. Second, if a carbon tax is to meet the criteria of
being cost-effective, it should apply a uniform price economy-wide, with no exemptions
in terms of coverage, so that those in society with a low marginal cost of abatement (i.e.
those for whom the cost of abatement is lower than the price to pollute) have an incentive
to reduce emissions (i.e. increase abatement). Both principles of differentiation and
broad coverage also have implications for the third key criterion; namely, environmental
effectiveness. If carbon taxes are to have their intended effect on reducing emissions of
CO2, they should be applied at a relatively high level, gradually increased over time, and
apply to all sectors of the economy so that all sources of pollution are regulated. Finally,
to ensure that taxes meet the criterion of equity and political feasibility, carbon taxes
might be designed so as to be revenue neutral (i.e. not dedicated solely to government
budgets), so that part of the revenues raised can be used to offset any regressive effects.81
Although in principle a simple and straightforward idea, carbon taxes differ substantially
across jurisdictions, and political factors largely determine the final design and substance
81 Economists generally prefer revenue neutral carbon taxes on the basis of their enhanced efficiency – the revenue can be used to increase efficiency in the tax system by reducing other distortionary taxes. Some environmentalists, however, prefer that revenues be earmarked for other GHG reduction measures and programs, so there is a debate here.
82
of particular carbon taxes as they are implemented in OECD jurisdictions (Daugbjerg and
Pedersen, 2004; Pearce, 2005). In particular, carbon taxes differ in terms of the rates
applied to different tax bases (coal vs. oil vs. natural gas), who pays the tax (sectoral
coverage), and how the revenues are used (affecting social incidence). Though important
for making them politically palatable, certain design features can significantly undermine
the theoretical cost-efficiency and environmental effectiveness of a carbon tax.
To date, several jurisdictions across the OECD have successfully implemented an explicit
form of carbon tax, approximating the theoretical ideal with varying degrees of success.
Finland (1990), Sweden (1991), Norway (1991), Denmark (1992) and the Netherlands
(1996) were among the first countries to do so in the 1990s. Later, a second-wave of
incomplete and pseudo carbon taxation emerged in the OECD with Italy (1999),
Germany (1999) and the UK (2001) implementing their own brand of energy/carbon tax,
in some cases under the broader rubric of ecological or environmental tax reform
(ETR).82 More recently, the City of Boulder, Colorado (2007), and the Canadian
provinces of Québec (2007) and British Columbia (2008) have implemented sub-national
forms of a carbon tax in their effort to meet Kyoto targets for the reduction of GHG
emissions.
Upon further review, however, it is clear that some of these reforms should not be
considered a carbon tax in the sense described in Chapter 2. Indeed, a closer look reveals
that several considerably miss the mark of being a true tax on emissions of CO2. The
Italian carbon tax was controversial from its inception in 1999, and has since been
suspended in light of growing inflation in that country. Its future status is currently
unknown. The same is true of the French carbon tax proposal, which in December of
2009 was struck down by the country’s Constitutional Council on the basis that the initial
plan contained too many exemptions for industry (Parussini, 2009). The Italian and
82 Italy’s controversial carbon tax reform in 1999 has since been subject to suspension in light of concern over rising inflation in that country. Its future status is currently unknown. As such, the Italian carbon tax is excluded from the present analysis. In addition, the present analysis excludes the German and UK cases, since both are better interpreted as energy taxes – i.e. taxes on energy consumption – than an attempt to impose a tax on the carbon content/emissions of different fuels.
83
French carbon taxes are thus not considered here, as they have yet to be fully
implemented.
In such other places as Germany and the UK, environmental tax reform was successful,
but the final product yielded a new energy tax, as opposed to an explicit price on
emissions of carbon (Pearce, 2006; Harrison, 2010). In the case of Boulder, Colorado,
despite its name, the carbon tax implemented in 2007 is essentially a tax on electricity
consumption. It is levied on the consumption of electricity only, and fails to apply a
uniform price on carbon across all sectors. Although such taxes on electricity and energy
consumption will (indirectly) affect the price of carbon dioxide, they do not explicitly
target the carbon content of fuels as their tax base, providing no real incentive to
substitute for less carbon intensive fuels, and therefore, should not be categorized as a
carbon tax. They are energy taxes, to be sure, but they are not a tax on carbon.
The following sections are primarily concerned with carbon as opposed to energy
taxation, and are thus limited to analysis of jurisdictions coming closest to the theoretical
textbook carbon tax, in Finland, Sweden, Norway, Denmark, and British Columbia. Due
to data limitations, and in the interests of making results easier to replicate, the carbon tax
in Québec83 is excluded from more thorough analysis. In addition, the low tax rate is
largely symbolic, and was not presented as a comprehensive, revenue-neutral carbon tax,
as was the case in BC
3.2. Trends in explicit carbon taxes
In general, successful carbon tax proposals in the OECD share a few characteristics in
common.84 First, nearly all carbon taxes in existence were implemented incrementally,
by increasing the rate over time, or by gradually extending coverage (and removing 83 The province of Québec’s carbon tax covers hydrocarbons (petroleum, natural gas and coal) on 50 energy-producing refiners (including Ultramar, Petro-Canada, and Shell Oil) as well as wholesale distributers (including Imperial Oil, Irving Oil, and independent retailers). To be sure, this fits nicely with the view that, in the interests of broader coverage, a carbon price is best applied “upstream” (e.g. Parry and Pizer, 2007). However, data limitations prevent a more complete analysis of this tax here. 84 As the experience of failed proposals suggest, this is not to say that the following characteristics guarantee success.
84
exemptions and/or rebates for sensitive industry). For instance, tax rates in Finland were
introduced at a relatively modest level (approximately $1.4USD/tonne of CO2) in 1990,
and increased (to approximately $22USD/tonne of CO2) in 1998. Initially limited to heat
and electricity production, the Finish tax was also broadened over time to cover
transportation and heating fuels (Barde and Braathen, 2007: 54). In other jurisdictions,
an increase in carbon tax revenues is generated through the progressive reduction of
exemptions, an approach taken by Sweden and Denmark in the early 1990s. Finally,
increases to the carbon tax can be automatic, as in BC’s annual carbon tax increase of
$5.00 CDN each year, rising to $30CDN in 2012 (British Columbia, 2008).
Gradual implementation is important for several reasons. First, a low initial tax rate, and
allowing both the tax rate and tax base to increase over time, is often required to make
carbon taxes politically palatable. Second, an initially low rate (or initially large but
gradually decreasing refunds) allows emitters time to adjust. For instance, amidst
concern from business, industry in Denmark was granted a 100% rebate on the carbon tax
applied to low sulphur fuel oil, when the tax was first implemented in May 1992. The
rebate was subsequently decreased over time to 50% (1993), 40% (1997), 30% (1998),
20% (1999), to just 10% (2000) where it stands as of first quarter 2008 (IEA, 2008:
117).85 In addition, legislated increases in the tax can help alleviate concern that
governments adjust the tax for self-interested reasons. Automatic adjustment also sends a
clear price signal for longer-term investment decisions, and encourages behavioural
change even at lower tax rates, as emitters anticipate higher costs in the future. Finally, a
legislated, automatic and gradual increase effectively adjusts the tax rate for inflation,
ensuring that real tax revenues are not compromised.
A second common trend in carbon taxes in the OECD relates to who is taxed, and how
much of the economy is covered. Contrary to the theory of Pigouvian taxation, which
stipulates a tax should be uniform across all sectors of the economy, most carbon taxes
apply different rates to different uses of the same fuel (e.g. commercial versus household 85 A similar staggered refund system was implemented for light fuel oil used by industry (IEA, 2008: 118). As of 1 January 1993, the rebate granted to industry using steam coal was cut in half from 100% to 50%, where it remains as of First Quarter 2008.
85
use), and all carbon tax countries in the OECD provide special tax rebates, reductions or
exemptions for certain sectors of their economy.
Due to the difficulty in implementing harmonized carbon taxes on a regional or global
scale, and the accompanying concern of losses to international competitiveness, sectoral
exemptions appear necessary in order to make carbon tax proposals politically palatable.
Unilateral carbon taxes are often implemented in such a way as to minimize their impact
on sensitive industries, by providing a complex mix of tax loopholes, refunds and
exemptions (Daugbjerg and Pedersen, 2004). Although necessary for political feasibility
(Midttun and Hagen, 1997), however, specialized exemptions violate the spirit of carbon
taxes, undermine their environmental effectiveness, and blur the distinction between
“carbon taxes” and other taxes levied on the same energy products. As a result of major
exemptions for industry, the majority of the tax burden imposed by carbon taxes, like
energy taxes more generally, falls on oil for transport and for household use (Haugland et
al., 1992; Barde and Braathen, 2007; Svendsen et al. 2001).
In the absence of an international system of harmonized taxes, and given the perceived
negative impact of carbon taxes on international competitiveness, different countries will
apply different rates, and will exempt different industries from carbon tax obligations,
depending on the domestic constellation of interests opposing such taxes, and pre-
existing business-government networks, which privilege certain industries over others
(Kasa, 2000; Daugbjerg and Pedersen, 2004; Pearce, 2006). As a result, carbon tax
designs vary substantially across the OECD. Key distinguishing features include: time of
implementation; tax level; rebates and exemptions; and, how the revenues are used,
whether allocated to the general government budget, recycled back to the economy, or
earmarked for tax cuts or government expenditures. These differences are summarized in
Table 3.2.1.86
86 In addition, carbon tax schemes can also be distinguished in terms of: the purpose and motivation of the tax; how the proposal was implemented – on its own or as part of a broader tax reform; fuels covered and varying rates applied to each fuel; and, the sectors of the economy to which the tax applies. Where possible, these differences are discussed below.
86
Table 3.2.1: Carbon taxes in selected OECD jurisdictions
Year
Initial tax rate8
7 Coverage
Revenue
Finland
1990
$2.63 USD
/tCO2
(24.5 FIM/tC)
All fossil fuels. Exempt: fuels used in electrical
generation (due to separate electricity tax) and fuels
in industrial processing
About 5 b. in 2008 (6.3% total tax rev)
allocated to gen. gov budget w
ith som
e reductions
in other taxes
Sweden
1991
$66 USD
/tCO2
(27 Euro/tCO2)
All fossil fuels. Exempt: fuels used in electrical
generation. M
anufacturing initially given 75%
rebate, reduced to 50%
in 1997.
About 25.7 b. SEK in 2008 (1.7% total tax rev)
allocated to budget and som
e offsetting of other
taxes
Norway
1991
$30 USD
/tCO2
($21 USD
/tCO288)
Most fossil fuels. Exempt: coal and coke in cem
ent
and lim
e industry; fuels in international m
arine/air
travel; fuels used in oil/gas refining. Electricity not
affected (hydro). About 64%
of emissions covered.
About 7.118 b. N
OK (0.9% total tax rev.)
allocated to general governm
ent budget w
ith
some effort to tax shift away from
income tax
Denmark
1992
$28 USD
/tCO2
(100 DKK/tCO2)
All fossil fuels incl. fuels used in electricity gen.
Rebates: for industry. Progressively lowered from
100%
in 1992 to 50%
(coal) and lower depending
on fuel.
About 5.1 b DKK in 2008 (0.6% of total tax rev)
recycled back to industry
Netherlands
1992/
96
$5 USD
/tCO2
(5.16 DGL/tC
O2)
All fossil fuels (initially). New regulatory energy
tax (50%
energy 50% CO2) introduced in 1996
covers only fuels used in “small scale” energy
consum
ption.
Exempt: Fossil fuels used in electricity gen,
industry and greenhouse horticulture. Coal, heavy
fuel oil and motor fuels covered by “env. fuel tax”
and excise, respectively.
About 3.2 b in 2004 (close to 3% of total tax
rev.) for mixed purposes.
Revenue from
old environmental fuel tax
allocated to gov. budget for revenue purposes;
new regulatory tax (1996) recycled through tax
relief and a portion is earmarked for programs to
prom
ote energy saving and environm
ental
behaviour.
British
Colum
bia
2008
$8 USD
/tCO2
(10 CDN/tCO2)
All fossil fuels. Exempt: bio-fuels, fugitive
emissions from
industrial processing, fuels used in
inter-jurisdictional air and marine travel, fuels for
export. Electricity not affected (hydro). About 70%
of emissions are covered.
About 338 m CDN$ in expected revenue (roughly
1.9%
total tax revenue) returned through various
personal and business income tax cuts.
Source: Barde and Braathen (2007); Truc (2009); Bruvoll and Larsen (2004); W
ier et al. (2005); Environmental A
gency (Governm
ent of Japan); Ministry
of Environment (Finland); M
inistry of Taxation (Denmark); Ministry of Housing, Spatial Planning and Environment (Netherlands); Tax Statistical
Yearbook of Sweden (2009); Statistics Norway; British Colum
bia (2008).
87 The initial (starting) tax rates are converted into real (2005) USD
per tonne of CO2 to allow for more meaningful cross-time comparison. O
riginal (nominal)
data are in parentheses. Where necessary, data are converted to real 2005 $U
SD using OECD country-specific consum
er price data (energy items), current
exchange rate, and a carbon to carbon dioxide ratio of 12/44. See methodological appendix for more details.
88 Bruvoll and Larsen (2004) estimate of the average carbon tax rate across all fossil fuels in 1999.
87
As can be seen from Table 3.2.1, many discrepancies exist between the theoretical ideal of a
carbon tax, on the one hand, and actual carbon tax policy implemented in the OECD, on the
other. The first major departure that will be discussed has to do with coverage – both in terms of
what is taxed, and who is liable to pay.
Recall that for carbon taxes to be cost-effective, they must apply a uniform price on emissions
that applies to all products and all uses of fossil fuels equally. In OECD jurisdictions with a
carbon tax, however, this is rarely, if ever, the case. Table 3.2.1 briefly summarizes the
numerous exemptions and rebates offered. A close look reveals that carbon tax jurisdictions in
the OECD apply different rates to different sectors (or uses) of the same fuel, and all jurisdictions
grant exemptions and rebates to particular sectors of the economy, effectively violating the
principle of comprehensive coverage. Sweden, the country with the highest carbon tax rate in the
OECD, is a case in point. For instance, as of 1 January 2006, the carbon tax on light fuel oil in
Sweden was 50% higher in the household sector compared to the same tax on the same fuel used
by industry, once the 50% rebate granted to Swedish industry is applied. Similarly, Denmark
varies its carbon tax rate according to whether a fuel is used for space heating (80 /tonne of
CO2), “light industrial processes” (12 /tonne of CO2), or “heavy industrial processes” (3 /tonne
of CO2). In both instances, an important feature of carbon tax theory – a uniform price applied
economy-wide – is violated in practice.
Other carbon tax jurisdictions apply the same rate to different sectors; however, after rebates and
exemptions are accounted for, the result is much the same, if not greater. In Finland, for instance,
the carbon tax imposed on households can in some cases be 100% greater than that imposed on
industry, given that fossil fuels used for industrial purposes are fully exempt in that country.
Similarly, although the tax rate applied to industrial and household use of steam coal in Denmark
is identical (242 DKK/tonne), industry is refunded 50% of what is paid in the tax. To take
another example, Norway granted a full exemption to the cement and lime industry, which is
responsible for 90% of coal consumption in that country (Vehmas et al. 1999). Eventually, coal
was simply taken off the list of taxable fuels under the Norway carbon tax (Norway Ministry of
Finance). Finally, even where carbon taxes are viewed as comprehensive, emissions from some
industrial processes are exempt from paying the carbon tax, resulting in 30% of the provincial
88
economy being unregulated by the BC carbon tax (British Columbia, 2008).89 While these
exemptions are understandable given the difficulty of measuring “fugitive emissions”90 and in
ascribing “responsibility” to inter-jurisdictional travel, they could be reduced with a tax designed
upstream, which would then be passed down to all uses of carbon in an economy.
Besides the problem of uniform sectoral coverage in a downstream tax, carbon tax policy in the
OECD also departs from the theoretical ideal in terms of the object of taxation (i.e. what is
taxed). In some instances, particular fossil fuels are singled out for a complete exemption. Thus,
Norway exempts natural gas from its carbon tax, and since 2003, has abolished the carbon tax
applicable to coal and coke. As a result, the Norwegian carbon tax now covers only the use of
petrol, automotive diesel, and mineral oils (heavy and light fuel oils), and these rates do not apply
to protected sectors (e.g. fisheries). Similarly, the complex carbon tax system in the Netherlands
applies only to a select few fossil fuels. Notable exemptions include heavy fuel oil, coal and
motor fuels, which are covered by other taxes explicitly for the purpose of generating revenue. In
these respects, Denmark, Finland, Sweden, and British Columbia stand out as the most
comprehensive carbon taxes in place, in terms of imposing tax rates on all fossil fuels. However,
it should be noted that fuels used in electrical generation in Denmark, the Netherlands, Finland
and Sweden are exempt from the carbon tax, and a separate tax is instead levied on the
consumption of electricity. Vehmas (1999: 346) reports that in the case of Finland, electricity-
generating companies successfully received the exemption by arguing that, in a liberalized
electricity market, increasing the price of energy inputs would pose disproportionate costs on
domestic electricity production. Another reason for the exemption may also relate to the relative
importance of fossil fuels in the domestic electricity generation mix (Figure 3.2.1). Of all carbon
taxes in the OECD, it should be noted that the BC tax is the most comprehensive.
89 According to the government of BC, the exemptions are for “the time being.” The idea is that unregulated industries (e.g. landfill and agricutlture) will eventually fall under plans for some form of inter-jurisdictional cap-and-trade. 90 These emissions refer to where carbon dioxide is emitted as a result of a chemical reaction (e.g. cement manufacture) rather than through on site-combustion. I am grateful to Kathy Harrison for pointing this out.
Figure 3.2.1: Percentage of fossil
Source: World Bank, World Development Indicators As can be seen in figure 3.2.1, three of the four carbon tax jurisdictions that grant an exemption
to carbon-based fuels in power generation also have very high percentages of fossil fuels in their
domestic electricity fuel mix (Fin
generators, competing in a liberalized European market,
largely explain why the exemptions were granted. From the perspective of climate change
policy, however, these exemptions are
fossil-fuel use in electricity production, it is reasonable to assume that a large portion of
emissions in these countries are generated from the power producing sector.
compromise solution - a consumption tax on electricity
penalizes renewable electricity generation, despite the latter’s
some countries, like Denmark and Finland, of
fossil energy in electricity production
Development Indicators
1, three of the four carbon tax jurisdictions that grant an exemption
based fuels in power generation also have very high percentages of fossil fuels in their
domestic electricity fuel mix (Finland, the Netherlands and Denmark). The political role of p
competing in a liberalized European market, and national energy security interests,
explain why the exemptions were granted. From the perspective of climate change
however, these exemptions are concerning. Indeed, with such high concentrations of
fuel use in electricity production, it is reasonable to assume that a large portion of
emissions in these countries are generated from the power producing sector. Moreover, while the
a consumption tax on electricity - may encourage conservation, it equally
ctricity generation, despite the latter’s carbon-free status. And while
some countries, like Denmark and Finland, offer other incentives to make renewable electricity
89
1, three of the four carbon tax jurisdictions that grant an exemption
based fuels in power generation also have very high percentages of fossil fuels in their
the Netherlands and Denmark). The political role of power
rgy security interests,
explain why the exemptions were granted. From the perspective of climate change
. Indeed, with such high concentrations of
fuel use in electricity production, it is reasonable to assume that a large portion of
Moreover, while the
may encourage conservation, it equally
free status. And while
fer other incentives to make renewable electricity
90
more competitive relative to fossil fuel electricity generation, a tax on fossil fuel would seem a
much more efficient and straightforward approach to promoting renewable power.91
A second major tax departure illustrated in Table 3.2.1 relates to how carbon tax revenues are
spent. In general, revenues from environmental taxation can be used in several ways, including:
allocated to the general government budget; earmarked for government programs/expenditure; or
used to reduce existing distortions in the tax system. Vehmas et al. (1999) report that revenues
from carbon taxes in Finland, Norway and Sweden go directly into the general government
budget, although Sweden and Norway have each introduced measures aimed at offsetting the tax
burden from business and personal income taxation. Similarly, the carbon tax in BC is
essentially revenue neutral, with revenues going to a host of tax deductions for business and
individual tax payers (BC, 2008). In Denmark, revenues are recycled back to industry in order to
ease the burden of implementation (Danish Ministry of Finance, 1995). Finally, the Netherlands
has taken a mixed approach. The “Environmental Fuel Tax,” now levied only on coal, is
explicitly a revenue-generating tax, while revenues from the newer energy regulation tax is both
used to offset reductions in other taxes applied to business and consumers, and to finance
programs aimed at increasing energy savings and conservation behaviour (Ministry of Housing,
Spatial Planning and Environment).
For reasons of efficiency, economists generally disapprove of new taxes geared toward increasing
government revenue or earmarked for government programs and subsidies, as is explicitly done
in the Netherlands. Rather, their preference is for revenue-neutral designs where funds are used
to reduce other distortionary taxes, which may actually work to increase the overall efficiency of
the tax system and create net welfare gains. Indeed, it is argued in the economic literature that an
environmental tax shift may potentially yield a “double-dividend” in the form of realizing
economic benefits (i.e. a more efficient tax system) that are additional to the environmental
improvements derived from an environmental tax (c.f. De Mooij, 2000; Goulder, 1995;
Bovenberg, 1999). At the same time, use of revenues has important implications for the
regressive effects of carbon taxes. While reducing distortions can make economies more
91 The Netherlands applies a preferential electricity tax rate for electricity generated from renewables. Once in the grid, however, it is impossible to know where electrons came from, and since electrons do not contain any carbon, a tax on carbon inputs seems a much simpler and straightforward approach.
91
efficient, the end result may be to reduce taxes on business as opposed to labour, depending on
where distortions are greatest in a particular tax system (Zhang and Baranzini, 2004: 510).92
Thus, in some instances, there may be a tradeoff between using revenues to meet two opposing
ends – a reduction in distortionary taxes (efficiency) vs. using revenues to offset any regressive
impacts of the tax (equity). In practice, the balance between these two potentially competing
objectives is settled politically. Indeed, governments use revenues in order to make taxes more
politically acceptable, allocating funds to assuage concerns expressed by the most influential
groups in society, including industry (Daugbjerg and Pedersen, 2004). To date, analysis of a
government’s inclination to use revenue for equity vs. efficiency vs. political gain is lacking, and
while some governments go to great lengths to ensure revenue neutrality (e.g. BC), evidence of
any systematic attempt by governments to identify and reduce only the most distortionary taxes
in their political system is limited. As a result, whether existing carbon tax reforms meet the
criteria of economic efficiency or social equity, or whether revenues are purely used out of
government self-interest, is a context-specific question requiring further investigation (c.f. Wier
et al. 2004; Ciocirlan and Yandle, 2003).
A final group of tax departures analyzed in this paper have to do with tax levels and rates. Recall
that from an ideal type perspective, rates per tonne of CO2 should be set relatively high, be
progressively increased over time, and differentiate according to the carbon content of the
different fuels covered.
Levels. To be sure, ascertaining the “optimal rate” is shrouded in methodological and ethical
controversy. Indeed, it is very difficult (if not impossible) to measure the “social cost” of carbon,
since the true cost of emissions is unknown (Ekins and Barker, 2001: 329; Owen, 2004), and
since the benefits (and costs) from a (un) stable climate will be felt well into the future. In
addition, it is questionable whether individuals can objectively agree on the monetary value of
environmental public goods, like clean air and a stable climate, since we all attach a different
value to environmental goods. Nevertheless, economists have attempted to estimate the “optimal
92 Depending on the existing structure of the tax system, using revenues to make the tax system more efficient may systematically disadvantage the poor. For instance, if taxes on capital are more distortionary than income taxes, as they are in the U.S., seeking a “double dividend” from a carbon tax will lead to a reduction in taxes on capital, which does nothing to offset any regressive effects of a carbon tax.
92
carbon price,” and this exercise has been facilitated by the COP-15 agreement, which sets an
upper limit on global average temperature change to 2 degrees Celsius warming. The task of
setting a commensurate tax rate is facilitated with this number, as designers can now work
backward and come up with a more realistic estimate of what level of tax is required in order to
reduce emissions to a point where a maximum 2 degree warming is probabilistically assured.93
Cross-national comparisons, however, remain difficult. Indeed, in the absence of a global carbon
price, or system of harmonized carbon taxes, domestic carbon prices must be set relative to
prevailing economic and environmental conditions at the domestic level. As a result, estimates of
the optimal carbon price vary across jurisdictions based on projected levels of emissions with and
without a carbon price, and on country-specific demand elasticities. Rather than compare
existing carbon tax levels to some abstract ideal, therefore, a better approach is to compare
carbon tax levels to country-specific estimates of what is required to meet a particular country’s
emission targets. Lacking these numbers, the following briefly compares carbon tax levels
relative to each other, and places greater emphasis on both the speed with which they have been
increased, and the extent to which rates are set in proportion to the carbon content of different
fuels.
As indicated in Table 3.2.1 and further demonstrated in Figures 3.2.2 and 3.2.3, carbon tax
schemes currently implemented in OECD jurisdictions vary widely in terms of the average tax
imposed on per tonne of CO2, that is, the tax rate per tonne of CO2 averaged across all fuels. On
average, carbon tax rates are highest in Sweden, which currently reflect a rate of 93 $USD per
tonne of CO2, or about 80 $USD in constant (2005) prices. In nominal prices, Sweden is
followed by Finland (about 60 $USD) and Norway (about 40 $USD). If real tax rates are
compared, the Netherlands emerges with the second highest average carbon tax. At the other end
of the scale, carbon tax rates are lowest in Denmark and British Columbia, in both real and
nominal prices. In the case of British Columbia, this is to be expected, given that the carbon tax
was just implemented in 2008, and is set to rise by 5 $CDN each year, reaching 30 $CDN in
2012 (British Columbia, 2008). In contrast, the carbon tax in Denmark was brought in at an
93 Of course, assumptions regarding price elasticities and climate sensitivity are still required, so it remains an imperfect science.
initially low rate, where it has stayed the same, in nominal terms, and actually
terms, since being introduced in 1992.
Figure 3.2.2: Change in nominal tax rate over time
Source: See Table 1 and data from IEA Figure 3.2.3: Change in real tax rate over time
Source: See Table 1 and data from IEA
initially low rate, where it has stayed the same, in nominal terms, and actually decreas
terms, since being introduced in 1992.
2: Change in nominal tax rate over time
Source: See Table 1 and data from IEA Energy Prices and Taxes, 3 Quarter 2009.
: Change in real tax rate over time
Source: See Table 1 and data from IEA Energy Prices and Taxes, 3 Quarter 2009.
93
decreased, in real
94
Large differences in carbon taxes can be seen in Figures 3.2.2 and 3.2.3. The order of countries
changes between the two because some countries (e.g. Denmark) fail to increase nominal tax
over time, leading to a net decline in tax rates when examined in real terms. Conversely, large
increases in the nominal tax rate over time produces similar increases in real terms, as tax rates
are increased at a higher rate than inflation (e.g. the Netherlands, Finland and Sweden). Indeed,
as a function of percent change, the Dutch carbon tax grew by over 90%, the Finnish tax by 85%,
and the Swedish tax by about 15% when real tax rates are examined. The real tax rate in Norway
grew moderately (about 3%), while the Danish tax shrunk, in real terms, by about 75%, since the
overall carbon tax rate was left unchanged.
To be sure, part of the reason for such high average tax rates in Sweden, the Netherlands, and
Norway has to do with the disproportionate burden imposed on household energy use. Indeed,
tax rates imposed on things like motor fuels and fuels for household heating are much larger in
these countries, despite being less carbon intensive than other fuels like coal. Therefore, Figures
3.2.2 and 3.2.3 are somewhat misleading, masking the sometimes large and potentially
inconsistent differences in the carbon tax structure, which are analyzed further in Chapters 4 &5.
Differentiation. It has already been shown that carbon taxes in the OECD fail to impose a
uniform price across the entire economy. But how well do existing carbon taxes perform in
terms of applying a different price according to the carbon content, and associated emissions, of
different fuels? To answer this question, tax data need to be transformed into the equivalent tax
on emissions of carbon dioxide, using standard emission coefficients.94 Table 3 summarizes the
transformed data, across different fuels.
94 The figures quoted in table 3 are calculated using standard EIA emission coefficients. For details on the emissions factors used and calculations performed, please refer to the methodological appendix.
95
Table 3.2.2: Carbon tax rates by fuel type, in current USD/tonne of CO2 Carbon
content95 British Columbia
Denmark Finland Netherlands Norway Sweden
Coal
26 $6.79 $17.99 $27.38 $6.82 $34.03 $25.98
Heavy Fuel Oil
21.5 $9.52 $16.51 $27.01 (not covered)
$28.37 $25.20
Light Fuel Oil
19.95 $9.45 $16.86 $27.59 $77.89 $34.39 $145.46
Diesel
19.6 $9.45 $16.86 $27.54 (not covered) * $145.46
Gasoline
19.3 $9.41 $17.51 $27.90 (not covered) $58.68 $124.75
Nat. Gas
14.5 $9.44 $20.87 $14.31 $110.21 (not covered) *
Cor (r=) -0.76 -0.57 0.73 -0.98 -0.48 -0.80 Source: IEA (2008) and British Columbia (2008). *Data unavailable at this time. The data in Table 3.2.2 are derived from IEA and official government statistics on carbon taxes
in selected OECD countries. Based on the most recent data available, taxes have been
transformed from tax rates per base unit of fuel (e.g. tax in $/litre) to the corresponding tax rate
per tonne of CO2. Such a transformation gets to the heart of the issue; namely, what is the
corresponding tax rate on emissions of carbon dioxide, and allows for a comparison across fuels
with different carbon contents and measured in different base units (e.g. litres of gasoline vs.
cubic metres of natural gas). These data are also expressed in current US dollars, using market
exchange rates, in order to allow for cross-national comparison. For illustrative purposes, fuels
in the table are arranged from most to least polluting in descending order, accompanied by
estimates of their corresponding carbon content (in Teragrams of carbon per quadrillion Btu).
If governments applied a uniform carbon tax across fuels in proportion to the carbon contained
and released when a fuel is combusted, we should expect to see a constant tax rate as we move
down each column from carbon intensive (i.e. coal) to less carbon intensive (i.e. natural gas)
fuels. However, it is apparent from Table 3.2.2 that the equivalent tax per unit of carbon dioxide
is not uniform across fossil fuels, as would be the case in the presence of a pure carbon tax.
95 EIA Annex B “Method for Estimating the Carbon Content of Fuels” (B-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2001); p.A.47. Available online at http://www.epa.gov/climatechange/emissions/downloads09/Annex2.pdf
96
Rather, more carbon intensive fuels appear to be taxed at a lower rate, on a per tonne of CO2
basis.96 For instance, in some instances, coal is among the least taxed fuel, and in such
jurisdictions as Denmark, the Netherlands and BC, natural gas is taxed at a higher rate per unit of
carbon dioxide than coal. This inverse relationship between carbon content of fuels and the rate at
which a fuel is taxed is summarized in the simple bivariate correlation, used for illustrative
purposes only, of the general pattern that exists between carbon content and carbon tax rate. If the
purpose of a “carbon tax” really is to decrease atmospheric concentrations of GHG, including
carbon dioxide, then these findings indicate that the design of existing carbon taxes seems
flawed. With the exception of Finland, and potentially BC, the logic of carbon taxes is
inconsistently applied across all jurisdictions with a carbon tax.
3.3. Case study: Majoritarian electoral systems and the British Columbia carbon tax
To summarize, it appears as though no jurisdiction has successfully implemented a true carbon
tax. Indeed, the foregoing analysis has identified several important “tax departures,” or
discrepancies between Pigouvian theory and actual carbon tax design. These tax departures,
summarized in Table 3.3.1, can be grouped in terms of (i) failing to apply to all fossil fuels,
regardless of fuel type or application; (ii) providing rebates and exemptions, in violation of the
principle of uniform coverage; (iii) departures from the efficient use of revenue; (iv) stagnant or
declining tax rates, in real terms; and (v) weak correspondence between carbon content of fuels
and the applicable tax rate.
96 To be sure, different agencies report slightly different emission factors, which may affect the calculation of tax rate per tonne of CO2. I used several emission factors and consistently found the same result – inconsistent application of carbon taxes – though there was some minor variation in the precise differences. I am currently working on my own emission coefficients, which take into account different qualities of fuels used in different countries.
97
Table 3.3.1: Sum
mary of tax departures
Tax base
(Covers all fossil fuels)
Coverage
(No exemptions)
Revenue recyclin
g (For social goals)
Tax level
(Relatively high)
Differentiation
(Acc. to carbon
content)
BC
All fossil fuels.
Bio-fuels, fuels used in
inter-jurisdictional travel
and fuels for export exempt.
Broad-based
Industrial processing
exempt.
Revenue neutral tax
deductions, double-
dividend?
Scheduled moderate
increase to 2012
Inverse relationship.
Coal under-taxed
relative to other fuels
depending on which
emission factor is
used
Denmark
All fossil fuels.
Fuels for elec gen. exempt
Rebates for industry
reduced to 50%
(coal)
and 10% (other fuels)
Recycled back to
industry (earmarked)
Declined in real terms
Moderately negative
relationship.
Natural gas over-
taxed relative to other
fuels
Finland
All fossil fuels.
Fuels for elec gen. exempt
Exemptions for
industrial processing
Allocated to general
government budget
Rapid increase in real
terms
Positive relationship.
Consistent rate
applies according to
carbon content
Netherlands
Coal, heavy fuel oil and
motor fuels now covered by
excise. Fuels for elec gen
exempt
Exemptions for
sensitive sectors (e.g.
horticulture)
Mixed – partially
revenue raising;
reductions in other
taxes, and earmarked
Rapid increase in real
terms
Strong negative
relationship. Coal
under-taxed, natural
gas much higher.
Norway
Natural gas and coking coal
now exempt.
Exemptions for
sectors (e.g. fisheries)
Allocated to general
government budget
Stagnant
Moderate negative
relationship. M
otor
fuels over-taxed.
Sweden
All fossil fuels.
Fuels for elec gen. exempt
Rebate to
manufacturers now
50%
Allocated to general
government budget,
some offsetting
Moderate increase in
real terms
Strong negative
relationship. M
otor
fuels and home
heating over-taxed.
98
To be sure, the reasons for the incongruence between the ideal carbon tax found in
introductory economics textbooks, and the carbon taxes in practice, are primarily
political. For instance, the need to protect the competitiveness of domestic, energy-
intensive and trade-exposed industry is often used as a justification by governments for
maintaining at least one of the tax departures identified here; namely, exemptions for
certain sectors of the economy (e.g. Norwegian Ministry of Finance).97 However, these
arguments do not directly translate into a justification for taxing more carbon-intensive
fuels at a lower rate, the last tax departure described in Table 3.3.1. Similarly, while the
existing literature does a good job of explaining why tax exemptions exist, in terms of the
influence of domestic lobbies and their connection to government decision-makers (Kasa,
2000; Daugbjerg and Pedersen, 2004; Pearce, 2006), such studies overlook and fail to
account for the inverse relationship summarized in Table 3.2.2. What accounts for the
weak and in some sense inverse relationship between the carbon content of fuels and
corresponding tax rates?
As a preliminary assessment (or “plausibility probe”) of the theoretical argument outlined
in Chapter 1, I briefly consider the role of electoral rules in accounting for some of the
exemptions and apparently weaker tax on coal in British Columbia. The case of BC is
very recent and is the only OECD jurisdiction with a carbon tax where a majoritarian
electoral system is used. It is also the first carbon tax to be implemented in a non-
European setting, and has so far not been analyzed in the carbon tax literature (with the
exception of Harrison, 2010). Moreover, of particular interest is the fact that BC is one
of Canada’s leading producers of both natural gas and coal. In this light, the discrepancy
between the carbon tax rate applied to coal, and that applied to natural gas, is particularly
puzzling (Figure 3.3.1).
97 Some studies cast doubt on the competitiveness argument, suggesting these justifications should be scrutinized carefully. See, for instance, Ekins and Speck (1999).
99
Figure 3.3.1: Tax rates applied under BC’s carbon tax by carbon content of fuels
Source: BC (2008) and EIA (2005) As can be seen in Figure 3.3.1, the carbon tax in BC seems biased in favour of coal when
an emission factor of 2.77 tonnes of CO2 per tonne of coal is applied to the BC carbon tax
rate on HHV coal. As can be seen, the primary discrepancy is between the tax rate
applied to coal (approximately $6.79 USD), on the one hand, and the tax rates on all
other fuels (approximately $9.50 USD), on the other. To be sure, this apparent
inconsistency in the relationship between carbon content and tax rate is not unique to
British Columbia’s carbon tax (Table 3.2.2). In fact, the BC case is illustrative of a
general pattern – with the exception of Finland, jurisdictions with carbon taxes
inconsistently apply the logic of differentiated rates. With a Pearson’s r correlation
coefficient of r = -0.98 and -0.80, the Netherlands and Sweden are similar in this regard.
In fact, 5 out of the 6 carbon tax jurisdictions in Table 3.2.2 apply rates under the carbon
tax that are inversely related to the carbon content of fossil fuels, raising the question:
what accounts for this discrepancy? In the case of BC, which we can take as
representative, why is coal taxed at a lower rate?
100
Emission Factors. First, it might be the case that individual jurisdictions use average
carbon content rather than actual carbon content when determining tax levels to be
applied to different fuels. As a result, the tax rates set by governments and/or those
summarized in Table 3.2.2 might be the product of differential emission factors. To be
sure, this explanation is not trivial and requires careful consideration, as anyone who has
worked with emission factors knows they are variable. The carbon emitted from the
combustion of a tonne of coal, for instance, can vary by a factor of 60%, when comparing
high quality anthracite (black) with low quality lignite (brown) coal (IEA, 2008). Given
the variability of coal qualities (ranked in terms of heat content) used cross-nationally,
some emission factors may be more or less well-suited for coal in some countries rather
than others, and care must be taken to avoid using inappropriate emissions factors,
particularly for coal. This being the case, the majority of coal burned in most
industrialized countries tends to be bitumen or sub-bitumen. The corresponding emission
factors for these coal types is closer to 15-20 per cent (Harvey, 2010). Although the
chemical composition of other fuels also varies cross-nationally, the differences are
relatively minor.
In order to correct for the sensitivity of tax rates to the emission factor used, and to guard
against the possibility that Table 3.2.2 might lead to false conclusions, I apply two sets of
emission factors and find roughly the same results. The emission factors, taken from the
U.S. Energy Information Agency, and the IPCC, both authoritative sources, can be found
in the methodological appendix. The EIA factors apply a consistent emission factor to
the tax data (and assume bituminous coal), while the default carbon content data from the
Revised 1996 IPCC Guidelines for National Greenhouse Gas Reporting are the de facto
international standard. In addition, the IPCC factors were adjusted for country-specific
Net Calorific Values of the most commonly used coal in the country (IEA, 2008). In
contrast, correspondence with BC officials indicate that the emission factors used to
determine the BC carbon tax rates on coal correspond to an average of the three emission
factors for coal in BC reported by Canada’s National Inventory Report, which also vary
substantially (NIR, 2008). While more research could help reduce uncertainty in the
estimates provided in Table 3.2.2, they provide as accurate a depiction as possible given
101
the information available. In addition, the large differences in tax rates across fuel types
– for example, between motor fuels and coal – are very likely real and not the product of
using different emission factors. That the choice of emission factors used by the
government in calculating the tax rate may be politically driven is a distinct possibility.
Interests. A second potential explanation is to be found in the literature on carbon tax
exemptions. Much of the literature on the political economy of carbon taxes in European
and Nordic countries, for instance, takes an interest-group/policy-network approach
(Kasa, 2000; 2005; Daugbjerg and Pedersen, 2004; Pearce, 2006). Applied to the present
problem, we might hypothesize that the tax rates do not correspond to carbon content,
because producers and large scale consumers of more carbon-intense fuels have greater
influence on government, and were somehow involved, or at least consulted, when the
carbon tax was being designed, and the rates set. On the surface, evidence confirming the
interest group explanation for the discrepancy in the BC carbon tax is mixed. On the one
hand, a carbon tax was introduced by the BC Liberals, a political party less known for its
environmental credentials than for its business-friendly demeanor. In fact, the left-
leaning New Democratic Party has consistently attacked the BC Liberal party for its
previous support of expanding oil and gas production in the province, and elections BC, a
non-partisan government agency responsible for administering elections in the province,
lists several large companies, including some in the area of natural resource and mining,
as contributors to the Liberal party in its last electoral campaign. If the “privileged
access” of business interests inside the BC Liberal government is true, then, given the
structure of the BC tax, which favours coal at the expense of natural gas, we should
expect that the coal industry is somehow more important to the provincial government or
economy of BC. But a closer look at the economic profile of British Columbia reveals
just the opposite.
In fact, natural gas is in several respects more important for the overall provincial
economy, and the domestic use of coal appears quite limited. While BC is Canada’s
largest exporter of coal, contributing 1.8 billion $CDN to provincial GDP, the value of
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provincial natural gas production was roughly three times larger, or 5.9 billion $CDN in
2005 (BC Stats, 2006).
Figure 3.3.2: Share of natural gas in BC mineral production
Source: BC Stats (2006) As can be seen in Figure 3.3.2, natural gas production accounted for the majority (56%)
of revenues derived from BC’s mineral economy in 2004, which is over 5 times the share
of coal. Similarly, in terms of power generation, natural gas is the second largest source
of primary energy in BC’s provincial electricity mix, after hydro. Here again, the
contribution of natural gas is relatively more significant, contributing more power to the
provincial grid than coal. In 2007, for instance, natural gas was used to generate 2,950
GWh of relatively clean electricity, while no coal was used at all (NIR, 2009: 490).
Finally, as a source of industrial energy, natural gas is used in more industrial settings
than coal. This is due to the relatively small contribution of such coal intensive industries
as aluminum, cement and lime. Based on all of these indicators, it would appear that
relative to coal, natural gas is more important to the provincial economy as a source of
energy. Based on its relative importance, and following the logic of the interest group
account, we should expect larger, more vocal opposition to a carbon tax from the
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producers and users of natural gas. Yet the carbon tax in BC is systematically biased in
favour of coal. The reason must lie somewhere else.
Political Institutions. A third possible explanation for the discrepancy between the tax
applied to coal and that on all other fuels under the BC carbon tax can be found in a
recent literature exploring the relationship between political institutions and
environmental policy (Harrison & Sundstrom, 2010). From this perspective, researchers
are encouraged to look at the institutional context as a potential mediating variable,
conditioning the influence of interests and ideas on policy outcomes. Building on the
argument developed in Chapter 1, we might expect the majoritarian electoral system in
BC to play a role. First, and most broadly, electoral systems are one of the mechanisms
through which social preferences are aggregated and articulated to governments, which
can be particularly influential during elections. Second, electoral systems shape the
character of party systems and the nature of party competition, and produce an incentive
for parties in majoritarian systems to target local interests, especially in key ridings
(Persson and Tabellini, 2008). Applied to the case of the BC carbon tax, one might
expect that the distribution of resources across the province’s electoral districts, and the
political competition within those districts, will have an influence on shaping the ultimate
design of the BC carbon tax.
As previously mentioned, the BC carbon tax was implemented by a party commonly
viewed as right of centre and with a less than stellar environmental record. But by 2007,
in the context of rising environmental concern shown at the polls and in a province with
an already heightened level of environmental consciousness,98 the BC Liberal party,
under Gordon Campbell, launched one of the most progressive climate policy agendas in
the country at the time. In a government throne speech in early 2007, the Premier
announced a host of new policy initiatives, including new emissions reductions targets,
promises to “green the grid,” and to work with other jurisdictions (notably California) on
other initiatives to “reduce net greenhouse gases in the Pacific Coast Region” (Office of
98 British Columbia has consistently been among the provinces with the highest percentage of votes for the Green Party in Canadian federal elections.
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the Premier, 2007). Later that year, the government began consulting on the idea of a
carbon tax, which was enthusiastically supported by a host of NGOs and academics
working in the climate policy community, as well as notable opinion leaders like David
Suzuki (Harrison, 2009). Taking a page out of the Green Party’s policy platform, the
Liberals forced the rival New Democratic Party (NDP) to criticize a path-breaking (for
North America) policy proposal in the provincial election of 2008, to the dismay
environmentalists, who had traditionally supported the more environmentally conscious
NDP, and felt betrayed by the seemingly opportunistic “axe the tax” campaign. Initially,
the proposal also received broader public support (Environics, Harrison, 2009), until the
price of gasoline rose, an issue that was subsequently eclipsed by economic recession. In
these lights, the BC carbon tax appears to have been as much good policy as it was good
politics. Indeed, reaching a low in 2000, support for environmental taxation in British
Columbia was on the rise when Campbell introduced his tax reform (Figure 3.3.3).99 In
the end, Campbell survived the election of 2008, and drew a new constituency to his
party. And while most attribute the victory to the confidence voters had in his
competency as an economic manager (Harrison, 2009), rather than to a resounding
approval of his carbon tax plan, Campbell’s environmental turn also reflected a new kind
of politics, where a right-leaning conservative party embraced the virtues of free-market
environmentalism, uniting free-market economists with environmentalists alike.
99 This particular question probes support for an environmental tax with revenues to reduce pollution, something that was not specifically done in BC. It is used here as a proxy to show support for environmental taxation in general.
105
Figure 3.3.3. Support for environmental taxation: Percent agreeing with the statement “I would agree to an increase in taxation if the money raised were used to reduce pollution”
Source: World Values Surveys
In addition to the impact elections have on the development of party platforms and party
politics, expanding the limits of the possible at times, electoral “rules of the game” and
electoral boundaries more particularly, also condition the room for political maneuver.
For instance, as argued in Chapter 1, highly disproportional systems, typical of
majoritarian elections like those in BC, produce incentives for politicians to target policy
in line with public opinion, since small shifts in the popular vote can translate into
relatively large shares in seats. Moreover, political institutions, like electoral rules,
systems, and boundaries, shape how interests are represented. Thus, in addition to the
relative size or importance of the natural gas industry, the geographical distribution of
resources must also be taken into account. Figure 3.3.4 provides a visual representation
of electoral districts in British Columbia, overlaid with the location of coal mines and gas
fields in the province.
50
55
60
65
70
75
1990 1992 1994 1996 1998 2000 2002 2004 2006
British Columbia Canada
106
Figure 3.3.4: Geographical distribution of coal and gas in BC
Source: GIS data from Elections BC; Ministry of Energy, Mines and Petroleum Resources; BC Oil and Gas Commission
107
Figure 3.3.4 illustrates the geographic distribution of coal and gas in the province of BC,
using geological GIS files, overlaid with a political map of electoral districts in the
province. Coal mines are represented in black, and natural gas fields in yellow. As can
be seen, natural gas fields are concentrated in North Eastern British Columbia,
exclusively. In contrast, there are several coal mines geographically dispersed across the
province. Crucially, the coal mines cover more electoral ground, so to speak, in that coal
is actively mined in several electoral ridings. In contrast, natural gas fields are found in
only two electoral districts (Peace River North and South), and in both cases, coal is also
prominent.
Interestingly, the 8 electoral districts with active coal production were well represented
by members of the Liberal Party at the time when the carbon tax was proposed and
designed, with several high ranking and relevant positions in the provincial cabinet. The
representatives included Minister of Energy, Mines and Resources, Richard Neufeld
(Peace River North), Minister of Community Development, Blair Lekstrom (Peace River
South), Minister of Agriculture, Stan Hagan (Comox Valley), Minister of State for
Mining, Bill Bennett (Kootney East), and Caucus Liason to the Minister of State for
Mining, Dennis Mackay (Stikine). In total 4 of the 5 members of the provincial
legislature were in cabinet, and the fifth held a special liaison position with the Minister
of State for Mining. Needless to say, districts with active coal mines are well represented
not only the Liberal caucus but also in cabinet. Although lacking access to the levers of
power, coal mines in the remaining districts are also able to make their views on the
carbon tax known through members of the opposition, and in the context of electoral
competition and criticism of the carbon tax, it appears as though some of these voices
were heard.
Moreover, of the 8 districts actively producing coal, 4 were considered to be “tight” races
(i.e. with a projected vote difference of less than 4%) in the months leading up to the
provincial general election of 2009.100 Based on seat projections, a shift in just 6 districts
100 See http://bc2009.com/ridings/
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could lead to a majority NDP government.101 In this way, coal districts could be
perceived as being pivotal, especially in light of the campaign, in which Campbell’s
carbon tax was hotly debated. The electoral success of the two largest parties (i.e. the BC
Liberals and NDP) is summarized for the two most recent general elections in Table
3.3.1.
Table 3.3.1: Electoral competition in key coal and natural gas districts: vote shares (in percentages) 2005 2009 BC Liberal NDP BC Liberal NDP Comox Valley 43 46 47 43 Fraser Nicola102 40 49 43 49 Kootenay East 48 44 51 36 Nanaimo 34 52 36 53 North Island 43 45 39 52 Peace River N 59 27 43 14 Peace River S 58 33 63 27 Stikine103 48 40 45 50 Source: Elections BC As is clear from Table 3.3.1, only two of the primary coal and gas ridings can be
considered “safe” for the BC Liberal party, based on the vote shares accruing to the
largest parties in 2005.104 Interestingly, the safe ridings of Peace River North and Peace
River South are also the two districts actively producing natural gas in North Eastern BC,
which might explain why the BC Liberal government was able to impose a relatively
higher tax rate on natural gas. In contrast, the vote difference in ridings where coal is
actively mined is considerably smaller. These latter districts are those that could be
considered pivotal for winning the next election, producing an incentive for the BC
Liberals to target these constituencies with favourable policy.
101 Based on data from the 2005 provincial election and overlaying the new districts, BC Liberals were expected to win 48 compared to 37 for the NDP. 102 This riding was substantially re-arranged between 2005 and 2009 by the Electoral Boundaries reform in 2008. I use electoral data for Yale-Lillooet for 2005. 103 This riding was also substantially redrawn by the Electoral Boundaries Act. Data for 2005 are for Bulkey Valley-Stikine. 104 By “safe” I mean a vote difference of greater than 10%.
109
In light of the above, it would thus appear as though the BC Liberal government
consciously designed the carbon tax in such a way as to not jeopardize their electoral
chances in coal-producing districts, which are also among the largest and least populated
(increasing the weight of individual votes in these districts).105 This is consistent with the
theory outlined in Chapter 1, which suggests that majoritarian systems will target policies
so as to benefit (or at least not harm) narrow constituencies that may be pivotal in an
election.
In sum, one might explain the structure of the BC carbon tax with reference to the
political economy of coal and natural gas in the province. There are many unionized coal
mines across BC, which overlap numerous electoral ridings. In contrast, the natural gas
industry is much less labour-intensive, is non-unionized, and is concentrated in just two
electoral ridings in North Eastern British Columbia, that are electorally “safe” for the BC
Liberals. It might be argued, therefore, that the natural gas industry has much less
political clout, and that the majoritarian electoral system, combined with the distribution
of resources across the provincial districts, biases policy in favour of coal, reflected in a
lower tax and exemptions on coal exports. This argument is distinct from the currently
dominant explanation found in the literature on carbon taxation, which identifies a key
role for corporatism and policy networks in the design of carbon taxes.
Having found some support for the theoretical argument in Chapter 1, the following
chapters develop a more comprehensive analysis of the extent to which electoral systems
matter for carbon-energy taxation. As discussed in the literature review, relatively less
attention has focused on analyzing and explaining the factors behind the more general
energy tax structure – including all taxes affecting the price of CO2. The following
chapters attempt to begin filling gaps in this literature, and analyze carbon-energy taxes
in a large-n, cross-national setting.
105 For instance, Stikine is the largest riding in British Columbia, and also the least populated.
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Chapter 4: Measurement and description
4. Energy taxes as implicit carbon taxes: exploring cross-national differences Much thinking around climate policy now focuses largely on explicitly labeled “carbon
taxes” and “cap-and-trade” programs as a means of putting a price on emissions of
carbon dioxide (CO2). The analysis of carbon taxes in Chapter 3, however, demonstrates
that no government has successfully implemented a pure carbon tax, in the strict
Pigouvian sense. Indeed, existing carbon taxes in OECD jurisdictions either fail to
differentiate across fuels based on associated emissions of carbon dioxide, or fail to apply
a uniform rate economy wide, or in nearly every instance, fail to do both. Similarly,
existing cap-and-trade systems are often limited to certain emitters and sectors of the
economy.
At the same time, all countries levy taxes on different fossil fuels, and these taxes affect
the overall price of carbon in a country, and associated CO2 emissions, even if this is not
their stated intent. For instance, all countries levy taxes on the use of motor fuels and oil
for heating, and these taxes impact the consumption of fossil fuels and, as a result, final
CO2 emissions. This underlying tax structure produces a less visible framework of
incentives and constraints that has important implications for climate policy, and thus
warrants closer analysis. It is also important for policy-makers to understand the existing
tax structure when developing climate policy.
The following Chapter will argue that, contrary to conventional wisdom, the carbon taxes
examined in Chapter 3 are less distinct, in both their design and effects, when compared
to more commonly found energy taxes in the OECD. As a result, if a researcher wants to
ascertain the effective “price of carbon” across countries, then it makes sense to analyze
energy taxes on fossil fuels in addition to carbon taxes, both of which affect the price of
carbon. Indeed, an analysis of these “implicit” carbon taxes paints a more comprehensive
and accurate picture of cross-national variation in the price of carbon, insofar as both
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energy and carbon taxes are taken into account. In addition, if researchers want to better
understand the determinants of taxes on fossil fuels, they can benefit from a measure that
allows for deeper and broader comparative analysis across a larger number of countries,
across different sectors of the economy (like household, transport and industrial sectors),
across different fossil fuels, and across time. A better understanding of implicit (or
indirect) carbon taxes, and of why they vary so much across countries, can help to
provide crucial insight into the factors that may facilitate and constrain energy tax reform,
specify the conditions under which higher taxes on fossil fuels are politically possible, as
well as help identify barriers to energy tax reform more generally. These insights can
then be further examined in future work on carbon taxes and climate policy.
To be sure, pre-existing fossil fuel taxes have important implications for climate policy.
For instance, tracking the structure of implicit carbon taxes across countries can assist
policy-makers in: (i) determining the cost of abatement in particular countries; (ii)
deciding on which policy instruments to implement and how they should be designed in
light of pre-existing taxes; and, and, (iii) evaluate the effectiveness of instruments (e.g.
carbon taxes) once implemented. Despite such implications for climate policy goals and
objectives, however, the actual energy tax structure is not well understood (Baranzini et
al. 2000; Giddens, 2009). Although researchers sometimes lament the fact that energy
taxes are poorly adapted to the problem of climate change, no study has yet examined the
energy tax structure in terms of the way in which different countries tax carbon-based
fuels (and associated emissions of carbon dioxide), let alone try to explain these
differences.
The following Chapter develops an estimate what shall be referred to as the implicit
carbon tax for six fossil fuels commonly consumed in OECD jurisdictions – coal, heavy
fuel oil (HFO), light fuel oil (LFO), diesel, gasoline, and natural gas. Estimates are based
on energy price and tax data from the International Energy Agency (IEA) and cover 29
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OECD countries over the period 1978-2006.106 The Chapter begins by setting out the
main theoretical distinction between explicitly labeled carbon taxes, on the one hand, and
energy taxes, on the other (4.1) before developing an argument in favour of
conceptualizing energy taxes as implicit carbon taxes (4.2). Building on the carbon tax
literature, the Chapter then develops a justification for examining implicit carbon taxes
(4.3) and reviews the procedure for their estimation across 29 OECD countries over the
period 1978-2006 (4.4). After describing trends in implicit carbon taxes in the OECD
(4.5), the Chapter proceeds to specify the puzzling differences that exist across countries
and over time (4.6), the empirical analysis of which are the subject of Chapter 5.
4.1. Energy taxes vs. carbon taxes
Economists (Pigou, 1920; Sandmo, 1975) and international organizations (EC, 1991;
IMF, 2008; OECD, 1997; World Bank, 2010) have long advocated carbon taxes as a
cost-effective instrument for reducing greenhouse gas (GHG) emissions. Indeed, it is
now well established in economic theory that – by equalizing the marginal cost of
abatement across an economy – a carbon tax can bring about a given level of emissions
reductions at least cost (Baumol and Oates, 1971). In addition, if the objective is to
reduce emissions of CO2, then a carbon tax (i.e. a tax on carbon content) is preferred to
an energy tax (i.e. a tax on energy consumption), on cost-efficiency grounds (Zhang and
Baranzini, 2004; Manne and Richels, 1993).
For a given level of GHG reductions, a carbon tax is more efficient than an energy tax
because it creates incentives for both reducing energy consumption (i.e. the conservation-
effect107) and switching to less carbon intensive fuels (i.e. the substitution-effect108).109 In
106 By the implicit tax on carbon, I refer to the sum of all taxes (e.g. excise + VAT + specialized taxes) on each carbon-based fuel just mentioned. 107 By “conservation-effect,” I refer to the incentive to reduce consumption of a taxed good. Applied to energy, a tax will increase the cost of energy consumption, and produce an incentive to conserve. 108 By “substitution-effect,” I refer to the incentive to substitute for less carbon-intensive fuels, which are taxed at a lower rate. 109 Andersen (2008) refers to a “demand” and “substitution” effect.
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contrast, an energy tax does not set rates in proportion to carbon content, and the second
incentive for fuel switching is therefore weakened.110 As a result, an energy tax achieves
GHG reductions primarily through its influence on price-induced conservation, and
ceteris paribus, must be set at a higher level (implying higher abatement costs) in order to
achieve the same level of reduction as a carbon tax (Zhang and Baranzini, 2004).
In practice, the difference between carbon and energy taxes is not so clear-cut. As
demonstrated in Chapter 3, carbon taxes currently implemented in OECD jurisdictions
often apply rates that are inconsistently related to the carbon content of particular fuels,
and often include numerous exemptions for industry. In other words, the carbon taxes in
place do not equalize the marginal cost of carbon abatement across the economy, and
provide only weak (and in some cases perverse111) incentives for fuel substitution. Thus,
existing carbon taxes cannot be considered a “pure” tax on carbon emissions, in the strict
Pigouvian sense (c.f. OECD, 2001: 56; Ciocirlan and Yandle, 2003). An implication is
that “carbon taxes” currently implemented in the OECD lose much of their
distinctiveness vis a vis other, more common forms of energy taxation. Indeed, under
these circumstances, the theoretical cost-efficiency advantages and the substitution-
effects of a carbon tax are weakened, and the distinction between energy taxes, and
carbon taxes proper, is effectively blurred.112
110 An energy tax on electricity consumption does not usually distinguish between electricity generated from coal vs. electricity generated from nuclear sources. 111 I use the term perverse here from an environmental perspective. The explicit goal of a CO2 tax is to reduce carbon emissions. However, under existing carbon tax regimes, coal is systematically taxed at a lower rate relative to other fuels. As a result, a perverse incentive is created – to continue burning coal – which is diametrically opposed to the stated intent of a carbon tax. 112 Only when the marginal cost of emitting an additional unit of CO2 is equalized across all sectors of an economy will emissions reductions occur at lowest aggregate social cost. Application of a uniform carbon price (e.g. $10 per tonne of CO2) ensures that, a) economic actors will have an incentive to switch to less carbon-intensive fuels; and, b) economic actors for who the marginal cost of abatement is lower will have an incentive to take greater efforts at reducing emissions. In the absence of a uniform carbon price, the carbon tax will not be efficient (in the sense of minimizing aggregate abatement costs) and may be expected to increase the macroeconomic cost of reducing carbon emissions (Ekins and Barker, 2001: 341).
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4.2. Energy taxes as implicit carbon taxes
Compared to the relatively few jurisdictions with explicitly labeled “carbon taxes”
discussed in Chapter 3, energy taxes are much more commonly found in OECD
jurisdictions. In fact, all OECD jurisdictions levy taxes on the consumption of such fossil
fuels as gasoline, diesel, oil, and natural gas.113 These energy taxes are sometimes
referred to as “indirect environmental taxes” (Albrecht, 2006: 92), or “implicit carbon
taxes” (Hoeller and Coppel, 1992; Baranzini et al. 2000; Yokoyama, 2000), in the sense
that they affect the price of energy products and associated emissions, even though such
effects are not their stated intent.
In a recent study on the political struggle to address climate change, Anthony Giddens
(2009: 149) argues that,
…we should not focus only on carbon taxes as such, but upon the consequences
of a given fiscal system as a whole for outputs that are relevant to climate change. We should recognize that existing taxes which have not been devised for environmental purposes may nevertheless in some part serve them – in that sense, they are carbon taxes.
Following Giddens, I adopt a similar approach to the issue of environmental/carbon
taxation. To be sure, existing fossil fuel energy taxes are not necessarily introduced to
reduce CO2 emissions, and are instead justified on the basis of other reasons, including
government revenue requirements, reduced foreign energy dependence, improved local
air, noise and water quality, decreased urban congestion and traffic accidents, and road
maintenance, to name a few. Nevertheless, existing energy taxes on fossil fuels have the
unintended benefit of reducing GHG because they increase the price of fossil fuels
(decreasing demand for these fuels and encouraging conservation). These effects on
consumption are precisely the reason why some prominent economists advocate higher
taxes on things like motor fuels (e.g. Mankiw, 2006).
113 Coal is almost always exempt.
115
At the same time, even formal “carbon taxes,” explicitly imposed to reduce emissions,
inconsistently apply rates to carbon content (c.f. Ciocirlan and Yandle, 2003: 207), and
have yet to be applied economy-wide (Andersen, 2008), thus weakening their status as a
pure “environmental” or Pigouvian tax. To the extent that rates under a carbon tax are
inconsistent with carbon content (as is often the case), incentives for fuel substitution are
weakened, and a carbon tax’s emission reduction effects derive exclusively from price-
induced conservation, just like an energy tax. Thus, irrespective of their label or
environmental rationale, poorly designed carbon taxes implemented in the OECD lose
some of their distinctiveness vis a vis more commonly found energy taxes, in terms of
their (theoretical) environmental effectiveness.
Moreover, upon closer analysis, a second distinguishing characteristic of carbon taxes is
effectively muddied in the real-world application of carbon taxes; namely, the cost-
efficiency advantages of a carbon tax relative to energy taxes. It has already been
suggested that inconsistent rates set by carbon tax regimes reduce the incentives for fuel
switching, necessitating higher overall tax rates to achieve a given level of abatement.
This argument can be pushed further in light of the exemptions commonly granted under
carbon tax regimes. Just as “implicit” carbon taxes “are not efficient, in the sense of
equalizing the marginal cost of carbon abatement across the tax base” (Ekins and Barker,
2001: 340), carbon taxes also fail to meet this distinctive criterion. Indeed, all carbon tax
regimes contain exemptions, violating the necessity of having a uniform carbon price
across all sectors of an economy (a condition for cost-effectiveness). In the absence of a
uniform carbon price, the carbon tax will not be efficient (in the sense of minimizing
abatement costs) as lack of this feature may be expected to increase the macroeconomic
cost of reducing emissions (c.f. Ekins and Barker, 2001: 341). Thus, in practice, the
distinction between carbon and energy taxes – in terms of both economic efficiency and
environmental benefits – is not as pronounced as is commonly assumed.
In fact, in the absence of a uniform carbon price on CO2 emissions applied economy
wide, energy or fiscal taxes imposed upon carbon-based energy will have the same
economic and environmental impact as those levies explicitly labeled “carbon taxes,”
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provided that the tax rates on the different tax bases (i.e. fuels) are the same (OECD,
2001: 56).114 This is due to the simple fact that standard energy taxes increase the
relative price of the fuels to which they are applied, but like carbon taxes which fail to set
rates in proportion to carbon content, provide no incentive to substitute for less carbon-
intensive fuels, reducing emissions only via price-induced conservation. The end result is
that, regardless of label, rationale, or stated intent, excise, VAT, and other specialized
taxes are functionally equivalent to “carbon taxes” when the latter fail to impose a
uniform rate in proportion to the carbon content of fuels.
To be sure, it is not always obvious whether an energy tax or a tax on a particular fossil
fuel can be considered environmental. Indeed, there is some controversy over what
constitutes an “environmental tax” in the literature, and this debate has some bearing on
the question of whether it is appropriate to consider energy taxes on fossil fuels as
“implicit” carbon taxes, as is done here. Two distinct lines of argument fall into two
general camps. On the one hand, some researchers adopt a formalist view, arguing that
only those taxes justified on the basis of an explicit environmental purpose should be
considered “environmental” (Bruvoll, 2009). From this perspective, a formal distinction
is made between fiscal (i.e. revenue-raising) taxes on the one hand, and environmental
levies (i.e. with an explicit environmental purpose), on the other. Thus, Vehmas (2005),
following Määttä, (1997), excludes motor fuel taxes from their definition of an
environmental tax, on the basis that such taxes are not solely (or even primarily) raised
for environmental purposes (Vehmas et al. 1999: 345). Similarly, the U.S. tax code does
not include the tax on gasoline under its four main categories of “environmental taxes,”
since revenues are often used to fund transportation projects and not dedicated for
explicitly environmental purposes (EPA, 2001). However, as pointed out by Gayer and
Horowitz (2005: 66-67), the same U.S. tax code does label its excise tax on crude oil an
114 To be sure, carbon taxes retain their theoretical advantages, and properly designed and implemented, are to be preferred over broader “energy taxes” as instruments of climate policy (Zhang and Baranzini, 2004: 508-509). The point is that existing carbon taxes fail to be implemented as theory suggests, and so their theoretical advantages, and distinctiveness, is effectively blurred.
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“environmental tax,” even though it is much smaller and has almost identical effects as
the U.S. federal tax on gasoline (not considered an “environmental tax”).115
On the other hand, international statistical agencies like Eurostat, the OECD and the IEA
take a consequentialist view of environmental taxes, defining a tax as environmental
“…based on the potential environmental effects of a given tax, which is determined by
the impacts of the tax on the producer and consumer prices in question, in conjunction
with the relevant price elasticities” (OECD, 1999: 57). This broader view of
“environmentally-related” taxation acknowledges the fact that pollution taxes are often
“piggybacked onto existing taxes on energy consumption and motor transport” (Ward
and Cao, 2010: 3), and thus environmental taxes are conceptually and practically
“intertwined,” something even proponents of the formalist approach explicitly recognize
(c.f. Bruvoll, 1999). In fact, previous research has suggested that even “green taxes” are
“…not set with a specific concern for the environment; their purpose is largely to
generate revenue” (Ciocirlan and Yandle, 2003: 213) and that all taxes, whether labeled
environmental or not, are fundamentally fiscal in nature, helping governments to raise
revenue and only labeled “environmental” in an attempt to legitimate them in the eyes of
the public (Svendsen et al. 2001: 497). From this, broader, consequentialist perspective,
scholars like Fredriksson and Millimet (2007) use gasoline taxes as a proxy for the
overall environmental policies of a country, while Broz and Maliniak (2009: 2)
conceptualize gasoline taxes as being environmental, in the sense that they “…influence
the level of environmental externalities both nationally and internationally.” I adopt a
similar, consequentialist view of environmental taxation and consider energy taxes as
implicit carbon taxes for the reasons given above. To be sure, this is largely a semantic
issue, however, since the findings of the present research – in terms of the political
determinants of fossil fuel energy taxation – apply equally to “energy taxes” as they do to
“implicit carbon taxes.”116
115 The U.S. gasoline taxes “…implicitly target the same externality as the crude oil tax and are larger in magnitude, but their revenue is not assigned to an environmental fund. They therefore are not labeled as environmental taxes by statute” (Gayer and Horowitz 2006: 67). 116 The data are converted with a fuel-specific emission factor. The coefficients on both transformed (CO2) and untransformed (base unit) data are therefore identical. Though results are insensitive to this
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4.3. Why study implicit carbon taxes?
Given the apparent constraints associated with implementing a pure carbon tax, the
resulting similarity between carbon and energy taxes in terms of non-universal coverage,
a loose connection between tax rates and carbon content of fuels, and the resulting similar
effects in terms of pricing emissions of CO2, an analysis of total taxes on fossil fuels is
warranted. Indeed, if one’s purpose is to ascertain and explain cross-national differences
in the effective “price of carbon,” then it makes sense to compare countries in terms of
both “implicit” and “explicit” carbon taxes, which together constitute the energy tax
structure affecting the price of fossil fuels. In addition, if one wishes to uncover the
correlates and constraints (or barriers) to environmental taxation, then taking a deeper
and broader approach to the study of carbon taxes increases the researcher’s leverage
over various potential explanatory factors, while maintaining ample degrees of freedom.
To be sure, previous research has explicitly recognized the importance of implicit carbon
taxes for climate change policy and politics. One of the earliest studies on the implicit
carbon tax examined its role in determining cross-national variation in energy prices
across OECD countries, the economic costs of superimposing carbon taxes on top of
existing energy taxes, and the prospects for restructuring taxes on energy to achieve a
reduction in emissions of CO2 (Hoeller and Coppel 1992). This important study by
Hoeller and Coppel was one of the first to develop concrete estimates of implicit carbon
taxes, which documented the tendency for OECD countries to tax mineral oils and oil
products at a higher rate than coal and natural gas. Though limited in considering
implicit carbon taxes for a single year (1988) and by its grouping together oil and oil
products, the study broke new ground by emphasizing the importance of existing energy
taxes for broader climate policy objectives, and for advancing the argument that the
introduction of new and explicitly labeled “carbon taxes” should be accompanied by a
reform of the existing energy tax structure (Baranzini et al. 2000).
transformation, the conversion is done out of theoretical interest for interpreting tax rates in terms of the price they place on emissions.
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Building on this work, one emerging research agenda assesses the prospects for “green
tax reform,” which can be seen as the process of integrating environmental concerns in
the pre-existing tax and fiscal systems (OECD, 1997) by, for instance, converting implicit
carbon taxes to a common carbon price (in dollars per tonne of CO2 equivalent), and
uniformly applying this price to all carbon-based fuels. Recent work, for instance, has
proposed a conversion of implicit carbon taxes to a common carbon price, thereby
“rationalizing” the energy tax system for consistency with environmental and climate
policy objectives (e.g. Albrecht, 2006; Yokoyama et al. 2000). In one particularly
interesting study, Jack Mintz and Nancy Olewiler (2008) develop a strong case for
replacing the Canadian federal excise tax with a broad-based carbon tax to cover other
fuels.117 Using the existing federal excise tax on gasoline consumption in Canada, the
proposed tax amounts to roughly $42 Canadian dollars per tonne of CO2. Importantly,
the proposed tax would not impact the price of gasoline – it would rather bring other,
more heavily polluting fuels, like coal, under the same level of tax that consumers already
pay each time they fuel up at the pump – thus alleviating one potential source of political
opposition.
The existing studies on implicit carbon taxes share in common the view that considerable
progress can be made, in terms of pricing carbon and reducing GHG emissions, by
adjusting existing energy taxes. In so doing, these studies make a considerable
contribution to what appears to be a stalled political discussion on carbon taxes, which
too often ignores the important and multi-faceted role of implicit carbon taxes.118
Existing studies are limited, however, in terms of their inability to differentiate between
tax rates applied to similar fossil fuels with different carbon content – like diesel and
gasoline – as well as changes in the implicit carbon tax rate over time. For instance,
117 Mintz and Olewiler advocate a broadening of the Canadian federal excise tax on gasoline (equivalent to approximately $42/tonne of CO2) to cover other fossil fuels in an effort to reduce emissions of greenhouse gases and other air contaminants. 118 It now appears that President Obama will not be successful in passing a comprehensive climate bill in this Congress, and the Canadian government is unlikely to unilaterally impose a domestic carbon price. Yet short of an explicit carbon tax or emissions cap and permit trading system, governments in both countries could go some way in jointly undertaking a more straightforward rationalization of their respective energy tax systems.
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Mintz and Olewiler (2008: 22) base their estimates of implicit carbon taxes on the work
of Hoeller and Coppel, which does not distinguish among the unique tax rates applying to
different mineral oils and oil products. Where they do offer a more detailed analysis of
energy taxes disaggregated by fuel, Mintz and Olewiler (2008: 20) do not convert tax
data (in Canadian dollars per base unit) to a common base (e.g. CO2), thus making cross-
fuel comparison difficult.119 Finally, Mintz and Olewiler extrapolate the Hoeller and
Coppel estimates (developed for 1988) to 1997 and 2005 by adjusting the tax data for
inflation using consumer price indices, making the assumption that no change in nominal
tax rates occurred over this period.
At best, the implicit carbon price has been calculated for a particular fuel in a particular
country (e.g. Mintz and Olewiler, 2008), or for numerous countries and numerous energy
products, but for just a single year (e.g. Hoeller and Coppel, 1992; Baranzini et al. 2000).
While making important contributions, these studies are limited in terms of providing
data that can be analyzed cross-nationally and/or over time. Cross-nationally and
temporally comparable data are necessary if one were to answer the “interesting” and
relevant question of “…the factors explaining the actual tax structure and the obstacles to
its reform” (Baranzini et al. 2000: 397n11). To date, “…it seems that no country has
attempted a full-scale carbon tax audit” of the tax system (Giddens, 2009: 155). Thus, a
comprehensive analysis of the actual energy tax structure, and the correlates of and
constraints on high implicit carbon taxes, is important for several reasons, both
theoretical and practical.
4.3.1. Theoretical importance for political science
At present, economists dominate the literature on energy taxes (e.g. Andersen and Ekins,
2009; Baranzini et al. 2000). With few exceptions (e.g. Fredriksson and Millimet, 2007),
119 For instance, the difference between a 0.10 $/litre tax on a litre of gasoline in Canada, and a $75 tax on 107 kilocalories of natural gas in Denmark, is not immediately recognizable unless data are converted to a common base unit.
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this literature rarely considers important political and institutional variables in its
treatment of the energy tax and price structure (e.g. Hammar et al. 2004). While there
exists substantial potential for political science to bring fresh insights into questions
surrounding energy tax policy, political scientists have only just begun to examine
institutional factors underlying the environmental tax structure (Broz and Maliniak, 2009;
Ward and Cao, 2010). As a result, a large data set on energy taxes such as the one
collected allows the political scientist to answer some fundamental questions, including:
why do implicit carbon tax rates vary so widely across countries and across sectors?
What are the political determinants of energy taxes? Why is energy tax reform so
difficult?
Insights from political science can help shed new light on these fundamental questions.
Indeed, taxes – whether levied on environmental externalities, energy
consumption/production, or personal and corporate income – are fundamentally about
redistribution, the “essence of politics” (McGillivray, 2004). Difficulties in raising energy
taxes provide an interesting case of the politics of cost distribution (Svendsen et al. 2001),
and political science scholarship potentially has a great deal to offer in terms of
explaining and understanding cross-national differences in energy taxes. For instance,
insights from the comparative politics of electoral systems literature, and the international
political economy of taxation, have already made substantial contributions to the
understanding of how advanced capitalist states finance their welfare regimes, and why
cross-national differences exist (Kato, 2003; Steinmo and Tolbert, 1998). These
literatures hold the promise of shedding new light on the issue of energy taxation in
cross-national perspective, allowing researchers to test hypotheses and theories developed
by political scientists in other areas of the discipline. In this context, researchers can
better ascertain the generalizability of current theories of tax policy in new domains, and
further explore the extent to which insights from political science can help to explain
cross-national variance in energy taxes.
In testing hypotheses familiar to the political scientist, this type of research can also help
to refine existing theories in political science, and to formulate new hypotheses to be
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tested in future work on climate policy. It has been noted elsewhere that cross-national
variation in the implicit price of carbon “…is one of the main problems to implementing
internationally co-coordinated [climate policy]” (Baranzini et al. 2000: 397). Indeed, to
the extent that energy prices affect the relative cost of abatement across countries
(Hoeller and Coppel, 1992), the existing level of energy taxation will make it more or
less costly for countries for to implement a price on carbon domestically (i.e. existing
energy taxes may produce differential incentives for national action on climate change).
As a result, the current dependent variable in this study, implicit carbon taxes, may prove
to be an important independent variable in future analyses of climate policy. For
instance, existing energy taxes may structure the incentives and determine country
positions on whether to adopt an internationally harmonized carbon price, or agree to new
international norms and rules governing the climate (i.e. low energy tax countries may
have incentives to free ride on international agreements). Any hope at international
agreement will have to take these differential costs into account and propose an
appropriate mechanism of burden sharing. But these costs must first be determined, and
analysis of the existing energy tax structure is a crucial piece of the puzzle.
4.3.2. Practical implications for policy
In addition to its theoretical importance, the study of implicit carbon taxes is also of
practical interest as well. A better understanding of implicit carbon taxes is important for
policy-makers, for two primary reasons. First, such information can help identify the
potential scope for “green tax” or “environmental tax” reform (OECD, 1997) via, for
instance, the undertaking of a comprehensive “carbon audit” of the tax system (Giddens,
2009). Much can be learned from descriptive statistics on implicit carbon taxes in terms
of how the existing tax structure produces incentives to consume particular fuels, and
“[m]any existing taxes can be changed so as to benefit the environment” (Barde and
Braathen, 2007: 45). Data on implicit carbon taxes can help determine how consistent
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energy taxes are with overall climate policy objectives, and identify where reforms are
most urgently needed.120
Moreover, as pointed out by climate policy experts, assessing “initial” carbon taxes is an
important prerequisite for the eventual implementation of an explicit carbon price, at both
the domestic and international level (Gupta et al. 2007: 756). For instance, Nordhaus
(2007: 40) responding to Victor (2001: 86) stresses the need to measure “net carbon
taxes,” that is, the size of a carbon tax (proposal) relative to pre-existing fiscal policies
like taxes and subsidies affecting the price of fossil fuels. Collecting energy tax data and
estimating the corresponding implicit tax on carbon is an important part of such an
endeavor, providing policy-makers with crucial information for deciding on how to
account for initial taxes in the design of a carbon tax (c.f. Yokoyama et al. 2000).
Information on implicit tax levels is also important for efforts to internationally
harmonize carbon taxes as well. As Nordhaus (2007: 42) points out, given the disparity
in energy taxes between some North American countries and those in Europe (discussed
below), “…it would make no economic sense to require Europe to add even higher
carbon taxes on top of its existing ones before other countries impose even modest carbon
taxes.”121
Second, understanding the current energy tax structure can help determine what level of a
carbon tax is needed, if one is to be implemented. For instance, key questions for
governments considering a carbon tax concerns the costs (and benefits) it will impose on
the economy, and the level at which it should be set. Information on implicit carbon
taxes can thus feed into the estimation of the marginal cost of abating an additional unit
120 As argued in the literature, governments would benefit from exploring the potential for integrating environmental considerations in their fiscal system (OECD, 1997; OECD 2001). Such coordination would help to increase the overall coherence of the tax system with other environmental, economic and fiscal objectives. 121 A first step is to better understand the structure of the tax system, and how it relates to the economic and environmental objectives of the state. For instance, a carbon-tax audit, as advocated by Giddens (2009), would allow for a better understanding of how the existing tax structure creates incentives to over-consume particular fuels, and under-consume other, more climate-friendly alternatives. Such an audit would require an analysis of the tax system in terms of how the current tax structure affects, for instance, the price of emissions of CO2. The present research provides a rich source of data for such an audit.
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of CO2, as well as the design of a carbon tax. While many economic studies examine the
so called “tax-interaction effect” (Goulder 1998; Goulder et al. 1999), and the prospects
for a “double-dividend” (Bovenberg, 1999; De Mooij, 2000; Bento and Jacobsen, 2007),
relatively less attention has been paid to the important question of how existing energy
taxes are to be accounted for in international agreements and domestic reform (Nordhaus,
2007).122
It is well-known that the marginal cost of abatement differs substantially across countries
and over time (Zhang and Baranzini, 2004: 509), and that the marginal cost of abating
CO2 emissions is a function of the availability and rate of development of non-carbon
fuels, the flexibility of an economy, and the use of revenue derived from price
instruments like a carbon tax or an auctioned emissions permit trading system (Ekins and
Barker, 2001: 369). In addition to such factors, OECD models demonstrate that:
…the economic cost of a carbon-tax [or climate] policy and its effectiveness in terms of abatement reduction depends importantly on the existing level of energy prices […] Countries with high energy prices will require larger carbon taxes [or a larger carbon price] than low energy-price nations to achieve a certain degree of abatement (Hoeller and Coppel, 1992: 186).
Existing energy prices thus play an important role in determining the cost of abating
emissions of CO2, and presumably in the aggressiveness and timing of climate policy as
well. As a result, “[i]t is relevant, therefore, to analyse what factors explain the large
difference in energy prices per tonne of carbon across countries (Hoeller and Coppel,
1992: 186, emphasis added). And a key determinant of energy prices is the energy tax
applied to different fuels.
To see the importance of energy taxes in energy prices, and thus for the cost of abating
CO2, consider the relationship between prices and taxes for gasoline (Figure 4.3.2.1.).
122 While the tax-interaction effect is concerned with the interaction between an environmental tax and pre-existing factor taxes on land, labour and capital, the “double-dividend” adds consideration of how revenues are used. Both consider the optimal design of environmental taxes on efficiency grounds, but generally do not consider distributional impacts of environmental taxes and their interaction with pre-existing energy taxes in their analysis.
Figure 4.3.2.1: Gasoline price and tax differentials,(2008)
Source: IEA (2009a) As can be seen in Figure 4.3.2.
compared to differences in energy taxes (red). For instance, the tax component
differential between the U.S. and U.K. ($1.22/litre) is over 30 times larger than the pre
tax price differential ($0.03/litre). In fact, closer analysis suggests that cross
$0.00 $0.50
MXCUSACANAUSNZLGRCJPN
SWZSPACZELUX
HUNIRESVKPOLKORAUTSWE
FINITA
DENPORGERFRAGBRBELNETNOR
: Gasoline price and tax differentials, Unleaded Gasoline, in current USD
4.3.2.1, the pre-tax price differential (in blue) is small when
compared to differences in energy taxes (red). For instance, the tax component
differential between the U.S. and U.K. ($1.22/litre) is over 30 times larger than the pre
/litre). In fact, closer analysis suggests that cross
$1.00 $1.50 $2.00 $2.50
USD/litre
Ex-
Tax Component
125
in current USD
tax price differential (in blue) is small when
compared to differences in energy taxes (red). For instance, the tax component
differential between the U.S. and U.K. ($1.22/litre) is over 30 times larger than the pre-
/litre). In fact, closer analysis suggests that cross-national
-tax Price
Tax Component
126
differences in gasoline pump prices are largely attributable to differences in rates of
energy taxation (Figure 4.3.2.2).
Figure 4.3.2.2: Total Gasoline Price by Tax Rate in current USD/L (2008)
As can be seen in Figure 4.3.2.2, there is a near perfect correlation (Pearson’s r=0.975)
between the price of gasoline and the corresponding tax rate. Indeed, much of the cross-
national variance in total gasoline prices (i.e. ex-tax price plus tax component) is
explained by tax differentials (R-square =0.95). If, as suggested by Hoeller and Coppel
(1992), a better understanding of energy prices, and factors affecting energy prices, is
desirable (for determining such things as the marginal cost of abatement, level of a
carbon tax, or negotiating an international burden sharing agreement), then a
comprehensive understanding of the existing tax structure, and its political determinants,
is required.
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4.4. Estimating implicit carbon taxes
In order to get a better sense of the energy tax structure, data on fossil fuel tax rates from
the International Energy Agency (IEA) were collected over the period 1978-2006. From
these data, systematic estimates of implicit carbon taxes in 29 OECD countries were
estimated. I develop this estimate of the “implicit carbon tax,” defined as the sum total
of all taxes (i.e. excise + VAT + specialized taxes, per unit) levied on the most commonly
used fossil fuels. Because VAT is refunded to industry in all countries, estimates of the
effective implicit tax rate on fossil fuels used for industrial purposes do not include
VAT.123 All calculations are based on energy price and tax data published by the
International Energy Agency (IEA)’s quarterly publication, Energy Prices and Taxes
(various issues).124 The data cover the following fuels and sectors:
1) Coal i. Industry and Household data (combined due to under-reporting)
2) Heavy fuel oil (HFO)
i. Industrial use (HFO is only used for industrial purposes)
3) Light fuel oil (LFO) i. Industrial use ii. Household use
123 Aggregating different taxes, like VAT and excise, may be seen to introduce a certain degree of “noise” in the measure. Indeed, the politics driving VAT and excise taxes are potentially quite different. Nevertheless, I have opted to combine VAT and excise where applicable (i.e. where VAT is not refunded), and aggregate the estimate of the effective implicit carbon tax, for an important substantive reason. I’m interested in knowing what the energy tax structure as a whole looks like, and in particular, what the level of taxes paid on carbon based fuels is (i.e. what is the implicit tax/price on carbon). Aggregation is therefore necessary. In addition, I exclude VAT when it is refunded (i.e. in the case of industry). So, in the case of industry, only excise is examined, and interested readers can compare the results for taxes applied to industry versus taxes applied to households if there is concern over including VAT. It should be stressed that the decision to not include VAT in estimates of the implicit tax on industry was done for a substantive reason (business is refunded VAT, so the effective tax rate is only the excise), and not out of a methodological concern for the validity of the measure. 124 The IEA has developed a standardized protocol for collecting and aggregating yearly energy price and tax data. To maintain consistency, no attempt was made to fill missing data with that obtained from national statistical agencies.
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4) Diesel i. Commercial use (industry) ii. Non-commercial use (private transportation)
5) Gasoline
i. Household use (IEA data does not differentiate across sectors)
6) Natural gas i. Industrial use ii. Household use
For fuels commonly used for industrial and residential purposes, the data capture
differences in tax rates applied across sectors of the economy (e.g. industry vs. household
use of light fuel oil), allowing for an analysis of the tax incidence within countries.
Although data for the tax on fossil fuels used in electricity generation are also available
(e.g. coal and heavy fuel oil), I do not consider such tax rates in this analysis, since
electricity is also taxed downstream, raising complicated issues of dual taxation.
Moreover, the electricity fuel mix varies greatly from country to country (and even within
regions of a single country) as well as over time, making it very difficult to consistently
and reliably capture the CO2 content of electricity consumption across countries and over
time.
Original data were obtained from various volumes of the IEA’s quarterly publication,
Energy Prices and Taxes. A sample table from which the data are drawn appears below.
Table 4.4.1: Tax rates on Unleaded Gasoline in Canada (in Canadian dollars)
Regular Unleaded (92 RON) Gasoline (per litre)
X-Tax Price Excise Tax GST Total Tax Total Price 2003 0.437 0.252 0.048 0.300 0.737 2004 0.508 0.254 0.053 0.307 0.815 2005 0.612 0.254 0.060 0.314 0.926 2006 0.661 0.260 0.064 0.324 0.985 Source: IEA (2008)
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Table 4.4.2: Tax rates on Natural Gas in Switzerland (in Swiss Francs)
Natural Gas for Households (per 107 kilocalories GCV)
X-Tax Price Excise Tax GST Total Tax Total Price 2003 699.4 3.8 53.4 57.2 756.6 2004 704.2 3.8 53.8 57.6 761.8 2005 773.0 3.7 59.0 62.7 835.7 2006 887.1 4.3 67.7 72.0 959.1 Source: IEA (2008) These data are yearly averages calculated by the IEA and based on statistics collected
from national sources, expressed in terms of national currency, in this case, Canadian
dollars and Swiss Francs. The fact that these data are expressed in units of national
currency makes direct cross-national comparison difficult, unless market exchange rates
are used to convert to a common currency, like U.S. dollars, Euros, or international
dollars at purchasing power parity (PPP). Moreover, the data are expressed in base units
(e.g. litres, tonnes, kilocalories), which are not directly comparable. For instance, the
difference between a 0.324$ tax on one litre of gasoline in Canada, and a 72$ tax on 107
kilocalories of natural gas is difficult to grasp, given the different units of measurement
used by the IEA to quantify different types of energy products. In order to make the data
comparable across countries and across fuels, a common metric is needed, and the data
need to be transformed.
If one is interested in the relationship between the structure of energy taxes in a given
country and its implications for climate policy, it makes sense to transform the data in
Tables 4.4.1 and 4.4.2 into the equivalent tax per tonne of CO2. Such a conversion
allows for a more intuitive comparison of tax rates across fuels, in terms of a common
base unit, carbon dioxide. The conversion factors used for this purpose are derived from
the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories, the most
authoritative source for GHG emissions accounting. Additional data, like country-
specific Net Calorific Values (NCV) for fuels, were also used in the calculations from
mass to volume, ensuring that the emission factors are the most accurate available (IEA,
130
2008). The final emission factors used in the transformation to implicit carbon tax rates
are summarized in Table 4.4.3.125
Table 4.4.3. Emission factors Emission Factor Units Coal126 2.77 tCO2/tonne Heavy fuel oil127 2.955 tCO2/kilolitre Light fuel oil 2.642 tCO2/kilolitre Diesel 0.00269 tCO2/litre Gasoline 0.00232 tCO2/litre Natural gas 2.34 tCO2/107kilocalories (GCV) Source: IPCC (1996) and IEA (2008a) The above emission factors are used to convert tax data into the equivalent tax per tonne
of carbon dioxide, making the tax data comparable across fuels. In order to estimate the
implicit carbon tax on different fossil fuels across countries, converting tax rates to USD
(or PPP) on emissions of carbon dioxide makes the most sense, allowing for a
comparison of tax rates across fuels and across countries.128 Data for this purpose are
drawn from the Penn World Tables 6.3 (Heston, Summers and Aten, 2009). Moreover,
when making comparisons over time, I use inflation-adjusted data, using country-specific
consumer price indices for energy goods. These data are taken from the OECD’s Main
Economic Indicators (OECD 2009) Price Indices (base year 2000=100).129
125 For a detailed discussion of emission factors and the conversion of tax data, refer to the Appendices 2 and 3. 126 For coal, an emission factor for bituminous is used. Bituminous coal is the most commonly consumed type of coal in the OECD. 127 If converted to tCO2/tonne, the emission factor for HFO is 3.078. It is higher than the emission factor for coal due to the fact that HFO is a denser form of energy. Conversely, on an energy unit basis, which is the more common way to measure carbon content, coal is the dirtiest fuel, containing more carbon per TJ. On a per energy unit basis, coal is “dirtier” because more tonnes of coal must be burned in order to get the same amount of energy as from burning a tonne of HFO. For further details, please consult Appendix 1. 128 Different options for standardizing the IEA tax data were also considered. Please refer to the appendices for a more complete discussion. 129 This approach involves first standardizing tax rates in U.S. dollars (or PPP), using exchange rates (Heston, Summers and Aten, 2009), then deflating by country-specific consumer prices, if across-time comparisons are being made (OECD, 2009). Next, standardized tax rates (in current or constant USD/base unit) are divided by corresponding emission factors for each type of fuel (IPCC, 1996), in order to transform the data from a “tax per unit” to a “tax per tonne” of CO2. Refer to Appendix 2 for a detailed methodology of the tax data transformation.
131
The result of these transformations is an estimate of the implicit tax rate on a particular
fossil fuel, by year and by country, expressed in terms of US dollars per tonne of carbon
dioxide emitted. To guard against the influence of exchange rates, I compare results
across models in Chapter 5 using data converted to USD and Purchasing Power Parity.
When making comparisons across time, data are adjusted for inflation in real prices. The
resulting measure allows for meaningful comparison of implicit carbon tax rates across
countries, across fuels, across sectors, and over time. And while this approach is prone to
the possibility that estimates will be sensitive to fluctuating exchange rates,130 such a
conversion is standard practice (OECD, 2010), appears less harmful than alternatives
(discussed in Appendix 2), and provides several advantages.
First, converting tax rates into constant (2000) US dollars facilitates meaningful
comparison across countries, and over time. Converting to US dollars makes the data
meaningful across countries because, since the Second World War, the US dollar has
served as the international currency and thus provides a common frame of reference.
Regression results using data converted to USD can also be checked against results in
PPP for robustness.131 Once converted to USD, the data are also deflated according to
country-specific national consumer price data for energy (OECD 2009) in order to
facilitate comparisons of real tax rates over time.132 Where CPI data for energy products
is not available, I use the general CPI for all goods.133
130 It should be noted that some country differentials between national end-use prices and taxes expressed in US dollars will, to some extent, be influenced by exchange rates, which are determined by market forces (IEA, 2008: 48). In order to guard against the potential bias created by conversion to USD, I include the exchange rate as a control variable in regressions where tax data are reported in USD. Moreover, I compare results across models converting to USD and PPP as a check for robustness. 131 The OECD (2010) suggests using multiple base currencies as a check against bias created by market exchange rates. Comparing results across models using USD and PPP conversions is thus an important robustness check. In addition, though US dollars are more meaningful for interpretation, the rational for using PPPs is to obtain rates of currency conversion that eliminate differences between countries while also permitting volume comparisons (Ciocirlan and Yandle, 2003). 132 I first convert to USD, then adjust for inflation using country-specific CPI. 133 The Consumer Price Index for energy goods (OECD 2009) contains missing data in the following countries: Czech Republic (1991-1995); Greece (1978-1988); Hungary (1978-1989); South Korea (1978-1989); Mexico (1978-1979); Poland (1978-1994); Portugal (1978-1990); Slovak Republic (1978-1994); and Turkey (1978-1993). In these countries, tax data are inflation-adjusted using the general CPI – all goods, to avoid breaks in the CPI series. In all other countries, including Norway where one data point is missing (1978), the more energy-specific CPI measure is used.
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Second, given the primary interest in examining taxes on energy products as they pertain
to fossil fuel use and the associated emissions of carbon dioxide, converting rates to
tonnes of CO2 allows for direct comparison of taxes across different fuel types, according
to the GHG abatement incentives they embody. Expressing tax rates in terms of tonnes of
CO2, rather than base unit, is much more intuitive and facilitates comparison of tax rates
across fuels, sectors and countries. It also allows for some leverage on the question of
how well existing energy tax structures reflect the environmental harm of different fuels.
4.5. Descriptive Analysis
Table 4.5 summarizes estimates of the implicit carbon tax across different fossil fuels in
29 countries in the OECD. As explained in section 4.4, these estimates were derived
from my own calculations, which adjusted IEA tax data in USD with country-specific
consumer price indices for energy products, then divided by emission coefficients that
were developed consistent with the Revised 1996 Guidelines for National Greenhouse
Gas Inventories. The result is a tax rate on a given fuel, in constant (2000) USD, per
tonne of CO2 emitted, which allows for comparison across fuels. Unless otherwise
indicated, all data are reported in constant (2000) USD per tonne of CO2. For illustrative
purposes, the data in table 4.5 refer to the sector-specific implicit tax on steam coal
(industry),134 heavy fuel oil (industry),135 light fuel oil (households),136 diesel (non-
134 Steam coal is used primarily by industry and for generating electricity, though it is also used by households in parts of Europe as well. Steam coal was not used by industry in Mexico over the time period analyzed here. Coking coal was used instead. 135 Heavy fuel oil is primarily used for industrial purposes and electricity generation. The IEA data distinguishes between two types of heavy fuel oil – high sulphur fuel oil and low sulphur fuel oil. Both are in fact “heavy fuel oil,” i.e. residual fuel (No.’s 5 and 6) that are left over from crude after gasoline and the distillate fuel oils are extracted through distillation. Increasing concern with sulphur emissions led many to phase out high sulphur fuel oil used by industry and in electricity generation in the 1990s. My data refer to high sulphur fuel oil, which contains the most observations. However, for years where tax rates on high sulphur fuel oil are not available (i.e. for many countries post-1990s), I impute tax rates on light sulphur fuel oil. Given the similar carbon content in both types, this imputation is justified. Moreover, care was taken to ensure that imputations did not cause artificial jumps in the tax data. For instance, between 1995 and 1998, Austria taxed both types of heavy fuel oil equally, so the imputations are reasonable. Therefore, where tax rates between the two are similar, an imputation is made. In cases where the tax rates vary widely (e.g. Luxembourg), no imputation is made to avoid creating an artificial changes in the series.
133
commercial use),137 gasoline138 (non-commercial use),139 and natural gas (household
use).140
In most cases, data are for 2006. Otherwise, data are for the most recent year
available.141 Since not all data are drawn from the same year, tax rates in Table 4.5 are
reported in constant (2000) USD per tonne of CO2. A “.” indicates the data are not
available, while “n/a” indicates the data are not applicable.142
Finally, I compare results using the imputed data (USD) with non-imputed data (PPP) as a check for robustness. 136 These data are tax rates on light fuel oil for household use. The equivalent of light fuel oil is Kerosene in Japan and Korea. Mexico is the only country in table 4.4 for which the data refer to the tax imposed on industry, due to a lack of data for that country. This imputation in Table 4.4 is for illustrative purposes only. Later empirical analyses of tax rates on light fuel oil (Chapter 5) make no such cross-sector imputations, since tax rates between the two sectors tend to be quite different. 137 The Canadian tax rate is for commercial use of diesel. All others refer to private non-commercial use. 138 Since fuel grades bought and sold vary across countries, tax rates on the most commonly reported fuel grade are described and analyzed in this dissertation. From a climate perspective, this mixing of fuel grades is not problematic, as all fuel grades are roughly equal in carbon content. The data refer to regular unleaded 91 RON (Research Octane Number) for Australia, Austria, Canada, Denmark, Japan, Korea, Mexico, New Zealand, and the USA; mid-grade unleaded 95 RON for all others. 139 The IEA tax data on gasoline are reported only for private non-commercial use. No cross-sector comparisons are therefore possible on tax rates for gasoline. 140 All data refer to tax rates on household use of natural gas. Taxes on both sectors are analyzed separately in Chapter 5. 141 For coal, Australia (1989), Belgium (1991), Czech Republic (2002), France (2003), Germany (1994), Hungary (1998), the Netherlands (1991), New Zealand (1984), Portugal (2003), and Slovak Republic (1999) are the latest data available. For heavy fuel oil, Australia (1983), Greece (2005), Italy (2002), Luxembourg (1994), Portugal (2002) are latest available. For light fuel oil, Australia (1983), Greece (2005), Hungary (1994), New Zealand (1986) are the latest available. Due to data constraints, the Mexican tax rate on light fuel oil refers to the tax levied on industry use, while all others refer to households. For diesel, Greece (2005) is the latest available. The Canadian tax on diesel is for commercial purposes, while all others are for private household use. For gasoline, Greece (2005) is the latest available. For natural gas, Belgium (2000), Denmark (2005), Germany (2000), Greece (2005), Italy (1999), Japan (2004) and Luxembourg (2005) are the latest available. All others refer to tax rates in 2006. 142 For instance, the cell for natural gas in Norway reads “n/a,” since close to 99% of electricity consumed in that country is from hydro.
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Table 4.5: Implicit carbon tax (constant USD/tCO2) by fuel type, 2006 Coal HFO LFO Diesel Gasoline Nat.Gas Cor (carbon content) 26 21.5 19.95 19.6 19.3 14.5 (r=) Australia $0.00 $2.82 $3.20 $101.53 $115.61 . -0.62 Austria $18.42 $22.23 $85.81 $190.89 $266.08 $75.73 -0.35 Belgium $0.00 $4.92 $45.30 $194.44 $359.76 $35.82 -0.23 Canada $0.00 $8.68 $20.69 $58.77 $89.37 . -0.72 Czech Rep. $0.00 $5.92 $73.68 $209.11 $275.73 $32.34 -0.25 Denmark $6.07 $16.22 $189.88 $225.52 $355.50 $232.10 -0.68 Finland $16.91 $15.79 $74.01 $196.28 $370.34 $31.61 -0.19 France $0.00 $6.21 $63.72 $228.07 $352.58 $37.40 -0.24 Germany $0.00 $7.44 $49.27 $212.59 $329.08 $37.94 -0.24 Greece . $6.49 $95.23 $147.69 $194.79 $17.48 0.22 Hungary $0.00 $7.74 $23.52 $170.51 $226.73 $13.19 -0.19 Ireland . $4.01 $45.03 $187.93 $248.74 $33.66 0.09 Italy $0.00 $19.72 $228.01 $230.63 $342.77 $141.34 -0.50 Japan $1.02 $6.30 $11.24 $109.47 $203.95 $25.92 -0.24 S. Korea . $18.86 $86.40 $188.91 $330.59 $45.04 0.12 Luxembourg . $6.74 $23.97 $138.93 $235.96 $9.51 0.15 Mexico . $0.00 $0.00 $18.31 $29.57 $26.32 -0.65 Netherlands $2.24 $9.00 $116.16 $174.78 $335.45 $87.08 -0.38 New Zealand $0.38 $0.00 $41.79 $21.84 $123.95 $29.63 -0.34 Norway $18.95 $46.43 $91.21 $219.68 $324.89 na -0.72 Poland $0.00 $5.43 $73.69 $194.51 $253.80 $36.93 -0.27 Portugal $0.00 $7.79 $65.30 $202.10 $351.93 $17.41 -0.19 Slovak Rep. $0.00 $0.00 $18.90 $188.48 $228.61 $27.23 -0.24 Spain . $4.76 $65.21 $160.44 $235.09 $36.11 0.09 Sweden $16.26 $113.38 $192.13 $208.69 $299.36 . -0.92 Switzerland $0.00 $0.88 $16.20 $223.58 $249.00 $20.70 -0.21 Turkey $0.76 $12.66 $81.96 $87.07 $153.62 $7.73 -0.19 UK $2.32 $27.97 $43.11 $313.58 $360.03 $9.78 -0.16 USA $0.00 $3.47 $4.87 $28.78 $28.62 . -0.69 OECD avg $3.62 $13.51 $66.53 $166.66 $250.74 $44.50 -0.29 Source: adapted from IEA Energy Prices & Taxes (various editions); and Ministry of Housing, Spatial Planning and Environment
(Netherlands).
As can be seen in Table 4.5, the implicit tax on carbon varies widely across fuels
(horizontally) and across countries (vertically). Closer analysis reveals clear patterns in
the way OECD countries tax on fossil fuels, as well as less obvious, non-trivial variance
in the way different countries tax the same fuels.
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4.5.1. Differences across fuels
At one level, there are substantial within country differences in terms of how individual
fuels are taxed. For illustrative purposes, tax rates in Table 4.5 are arranged from most to
least polluting fuels in descending order (i.e. coal to natural gas), accompanied by
estimates of each fuel’s corresponding carbon content (in Teragrams of carbon per
quadrillion Btu).143 Reading across the rows in Table 4.5, it is clear that, generally
speaking, the more carbon intensive a fuel (i.e. carbon content), the lower the tax rate.
For instance, with the highest carbon level per quadrillion Btu, coal is the most carbon
intensive, yet least taxed fuel. On the other hand, relatively less carbon-intensive fuels
used in transport, tend to bear the highest implicit carbon tax in the OECD. Between the
two motor fuels, and consistent with this pattern, all OECD countries (save the United
States) tax diesel at a lower rate than unleaded gasoline, on a per tonne of CO2 basis,
despite the fact that diesel is more polluting. While diesel vehicles may cause lower CO2
emissions per kilometer driven (due to greater efficiency), this tax trend is concerning
from the perspective of climate change, as such fuel economy might actually encourage
additional consumption through the so-called “rebound effect,” also known as “Jevon’s
paradox” (OECD, 2001: 57; Jaccard and Bataille, 2000; Alcott, 2005).144
Further illustrating the tendency for more carbon-intensive fuels to be least taxed, the last
column of Table 4.5 reports Pearson’s correlation coefficient between implicit carbon
taxes for different fossil fuels and their corresponding carbon content. In all but 5 of 29
cases, implicit carbon taxes are inversely related to the carbon content of fossil fuels. In
some cases (e.g. Australia, Canada, Denmark, Mexico, Norway, Sweden, and the USA),
the correlation is rather large (i.e. > |0.6|), meaning that lower tax rates tend to be strongly
143 Carbon content of figures are taken from Table A-34: Carbon Content Coefficients (Tg Carbon/QBtu) in EIA Annex B “Method for Estimating the Carbon Content of Fuels” (B-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2001), p.A-47. 144 Perhaps the trucking industry, which relies on diesel fuel, may explain this difference, as the interests of this industry are more concentrated than the diffuse interests of consumers of gasoline. In their work on the Dutch policy experience with green tax reform, Vermeend and der vaart (1998: 80) discuss the role of the trucking industry in keeping diesel fuel taxes relatively low.
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associated with higher carbon content fuels in these countries.145 Most others fall within
the range of -0.2 to -0.59. While the implicit tax rate is positively correlated with carbon
content in five countries (Greece, Ireland, South Korea, Luxembourg and Spain), these
countries are exceptions to the general pattern, and the correlations are comparatively
weak (ranging from 0.09 to 0.22). Overall, it is clear from Table 4.4 that the tax structure
in OECD countries is biased in favour of fuels that are more carbon intensive. And
surprisingly, this pattern is equally apparent in countries with a carbon tax (e.g. Sweden
r = -0.92) as it is in non-carbon tax countries (e.g. USA r = -0.69). Table 4.5.1 and Figure
4.5.1 summarize this general trend for the OECD countries as a whole.
Table 4.5.1: Average implicit carbon taxes across OECD in 2006, constant USD/tCO2
Average Tax per t/CO2
Carbon Content Tg Carbon/QBtu
Coal $3.62 26 HFO $13.51 21.5 LFO $66.53 19.95 Diesel $166.66 19.6 Gasoline $250.74 19.3 Natural Gas $44.50 14.5 Source: adapted from IEA Energy Prices & Taxes (various editions)
r=-0.29
Average implicit carbon taxes for each fuel are reported in Table 4.5.1 and Figure 4.5.1.
The data are averaged across all 29 OECD countries for which data are available, for six
fossil fuels, in constant (2000) USD, for year 2006. Consistent with what is often the case
within countries, the general pattern is for more carbon intensive fuels like coal, to be
least taxed.
145 Such correlations are largely the result of extremely low tax rates on coal as compared to less carbon intensive fuels like motor fuels and natural gas.
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Figure 4.5.1: Average implicit carbon taxes (USD/tCO2) by fuel, OECD 2006
Source: adapted from IEA Energy Prices & Taxes (various editions)
With the exception of natural gas, Table 4.5.1 and Figure 4.5.1 illustrate how implicit
carbon taxes are inversely related to the carbon content of fossil fuels across the OECD.
In this respect, implicit carbon taxes, summarized in Tables 4.5 and 4.5.1, are similar to
the explicit carbon taxes described in Chapter 3.
4.5.2. Differences across sectors
In addition, the implicit carbon tax rate demonstrates a further similarity to what was
found in the analysis of carbon taxation (Chapter 3). As is the case with explicit carbon
taxes, the tax burden associated with implicit carbon levies tends to fall
disproportionately onto the household and transport sectors (c.f. Barde and Braathen,
2007: 48 & 58). Indeed, transportation fuels (diesel and gasoline) are consistently the
highest taxed fuels in all countries. With the notable exceptions of the USA, Canada, and
Mexico, motor fuel taxes in 2006 correspond to an equivalent carbon tax of over $100
USD/tonne of CO2. Ironically, the “carbon taxes” discussed in Chapter 3, levied with the
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explicit purpose of reducing GHG emissions, are comparatively smaller in magnitude.
The implicit carbon tax rate on motor fuels often exceeds $200 USD/tonne of CO2, while
taxes of over $300 USD/tonne of carbon dioxide are not uncommon.
In addition, households tend to pay much more in taxes on energy products than does
industry. This difference can be seen when comparing tax rates on heavy fuel oil (HFO)
used by industry, and light fuel oil (LFO) used for household purposes, like heating. In
most cases, the tax on LFO is substantially larger than the tax on HFO (e.g. $187.22 to
$51.93 in Sweden), despite the fact the HFO is more carbon intensive and polluting
(Table 4.5).146 Such differences are also present in tax rates on different uses of the same
fuel (Figure 4.5.2).
Figure 4.5.2: Mean tax rate across sectors in constant (2000) USD/tCO2
Source: adapted from IEA Energy Prices & Taxes (various volumes)
Figure 4.5.2 shows the mean tax rate on three fuels for which IEA data provide distinct
tax rates across the industrial and household sectors. The data represent the implicit
carbon tax rate by sector, and by fuel, averaged across all OECD countries for which data
146 The LFO data in Table 4.5 are for tax rates on households, allowing for a comparison between industry and household use of heavy and light fuel oil. The IEA tax data further distinguishes LFO for industry and household use. Comparing tax rates between industrial and household use of LFO reveals the same story – households face a much larger tax burden.
Mean tax rate across sectors in constant (2000) USD/tCO2
$32.79
$58.25
$113.56
$156.21
$2.11
$27.14
$0$20$40$60$80
$100$120$140$160$180
ind hh ind hh ind hh
light fuel oil diesel natural gas
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are available, over the period 1978-2006. As can be seen, households tend to pay much
higher energy taxes than industry for use of the same fuels. For light fuel oil, industry
tends to pay, on average, about $25 USD less in taxes than households, and this
difference is statistically significant.147 For diesel, the difference in mean tax is $42.65
USD per tonne of CO2, while industry pays about $25.03 less than households for natural
gas, on a per tonne of CO2 basis. In each case, the mean difference in the implicit carbon
tax paid by industry and households is statistically significant at a level of P<0.00005.148
These findings corroborate with other studies that show a tendency for the transport and
household sectors to pay a higher tax, though such studies usually do not examine
differences between distinct tax rates paid by industry and households for the same fuels
(c.f. Barde and Braathen, 2007). In addition, the findings confirm what others sometimes
assert without empirical documentation; namely, the tendency for implicit carbon taxes to
be inversely related to carbon content, thus penalizing low carbon content fuels on a per
tonne of CO2 basis (c.f. Baranzini et al. 2000; Baron, 1997). The description of energy
taxes in Tables 4.5 and 4.5.1 offers support on both counts, and provides one of the first
empirical documentations of the way in which the energy tax structure is biased in favour
of industrial use of more carbon intensive fuels.
4.6: The Puzzle: differences in implicit carbon taxes across countries and over time
While concerning from the perspective of climate policy, the structure of energy taxes
just described is not entirely surprising. To be sure, the cross-fuel and cross-sector
differences in implicit carbon taxes are readily explained from both an economic and
political perspective. From an economic vantage point, and as Baranzini et al. (2000:
147 The difference in mean tax rates between industry and households is thus real and statistically greater than 0. The t-test further gives a 95 per cent confidence interval around values of $18.34 and $28.70 USD per tonne of carbon dioxide. 148 Both mean differences in tax rates for diesel and natural gas are statistically significant at P <0.00005. On average, industry can be expected to pay between $34.92 to $39.80 USD less on taxes per tonne of CO2 for diesel than households, while the mean difference in taxes paid for natural gas is likely to fall between $18.55 to $22.78 USD, 95 times out of 100.
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397) point out, consumers of motor fuels bear a comparatively larger tax burden because
demand for these energy products is relatively inelastic. With inelastic demand, it is
easier for governments to extract revenues from such fuels. Tax rates on motor fuels
might therefore be expected to be higher, as they constitute an important tax base for
raising revenue (about 90% of “environmentally related” tax revenue, according to the
OECD, 2001). On the other hand, the theory of public choice might also lead to the
expectation of higher tax rates on certain fuels. In the language of Olson (1965),
households constitute a large group with diffuse interests, and thus have less incentive to
mobilize against taxes, relative to small groups bearing concentrated costs. Following
this logic, it is easier for governments to impose higher tax rates on the household sector,
compared to the small, well-organized interests of energy-intensive industry, which stand
to lose much from higher energy taxes (Svendsen et al. 2001). The energy tax structure is
thus consistent with what we might expect from the economic perspective of energy
demand elasticities, and with the classic problem of collective action described by Olson
(1965). Thus, cross-fuel differences in implicit carbon taxes are not very surprising.
More puzzling, however, is the fact that energy taxes are consistently biased in favour of
more heavily polluting fuels. As documented in Table 4.5, this is true even among
countries that have taken efforts to correct environmental externalities through green tax
reforms and the imposition of explicit carbon taxes. It thus appears as though reforming
the energy tax structure for consistency with climate policy objectives is even more
difficult than initially thought. Indeed, despite a handful of cases where energy tax
reform proposals were politically successful in terms of implementation, such success
stories are limited by what is shown in Table 4.5. Energy tax reform for climate policy is
thus extremely challenging, raising the question – why is it so difficult?
In order to offer insight into this question, much can be gained from an analysis of the
cross-national differences in the way different countries tax the same fuels. Indeed, the
cross-sector and cross-fuel comparisons described in sections 4.5.1 and 4.5.2 mask
important differences at the cross-national level. As documented in the next section,
fossil fuel energy taxes vary enormously across the OECD, even among similarly situated
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(i.e. advanced, industrial capitalist) countries in the global political economy, and this is
the real puzzle. Such cross-national differences exist despite incentives to keep energy
taxes low, pressures that are common to all countries (Chapter 1). At the same time, this
variance persists despite common and increasing international and domestic pressure to
reduce dependence on increasingly scarce and environmentally harmful fossil fuels. The
fact that taxes vary so widely, and change over time, suggests that some countries have
overcome common political barriers and there may be scope for reform. In addition, an
analysis of these cross-national differences may point to important correlates of and
constraints on raising taxes affecting the price of carbon-based fuels.
4.6.1: Cross-national differences in implicit carbon taxes
Returning to the main table summarizing implicit carbon taxes in 2006, it is clear that
different countries tax the same fuels at widely different rates. Reading down the
columns in table 4.5, it is apparent that carbon is taxed at a higher rate in some countries
than others, despite that fact that, as argued in Chapter 1, there are numerous reasons to
expect energy taxes among the advanced industrial democracies to converge downward.
For instance, implicit carbon taxes on coal vary from effectively $0 in several countries
to nearly $20 USD per tonne of CO2 in Austria and Norway, and this is true despite the
fact that Austria does not have an explicit “carbon tax.”
To further illustrate the substantial cross-country differences in the way countries tax
carbon energy, Figure 4.6.1 visually depicts implicit tax rates for six fossil fuels,
arranging countries in descending order, from highest to lowest energy tax rates.
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Figure 4.6.1: Implicit carbon tax rates for selected OECD countries, 2006
Source: IEA (2009) As can be seen in Figure 4.6.1, implicit tax rates levied on the same fuels vary widely
among advanced industrial democracies in the OECD. Though some countries first
appear to be consistently high implicit carbon tax countries, this is not always the case.
For instance, Norway and Sweden tax oil products and coal relatively heavily. Italy,
Sweden and Denmark have comparably high taxes on light fuel oil. Great Britain is
consistently among the highest in taxes on motor fuels, but one of the lowest for natural
gas. Denmark and Italy have some of the largest taxes on natural gas in the OECD, but
their taxes on heavy fuel oil are closer to the OECD average. On the other hand,
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Australia, New Zealand, Canada and the United States tend to have lower implicit carbon
tax rates, though not for all fossil fuels. Thus, no single country consistently appears in
the extreme case of abnormally high carbon taxes for all fossil fuels.
Looking more closely at the transportation sector, there are large and substantial cross-
national differences in the way countries tax motor fuels, and the reasons for these
differences are not obvious. For instance, in the case of diesel, countries as similar in
their cultural, political and legal traditions as Canada ($58.77 USD per tonne of CO2) and
Great Britain ($313 USD per tonne of CO2) lie at opposite ends of the implicit carbon tax
spectrum. In fact, the tax differential between the two countries is larger than 80 per
cent, and a carbon tax of over $200 USD per tonne of CO2 would be required in order to
harmonize the implicit carbon tax rate on diesel in Canada with that in the UK. More
broadly, these large differences in fossil fuel taxation persist even among countries at
similar levels of economic development. The implicit carbon tax on diesel in Norway
(real per capita GDP $46,729.19) is roughly seven times as large as that in the United
States (real per capita GDP $42,683) in 2006. Similarly, the implicit carbon tax on diesel
in Italy (real per capita GDP $28,410.67) is over ten times that which existed in New
Zealand (real per capita GDP $24,817.14) that same year. These large and non-trivial
differences among similarly situated countries in the OECD suggest that some countries
are more willing and able to overcome domestic barriers and incentives to keep taxes
low, and impose higher rates of taxation on carbon-based fuels.
4.6.2: Implicit carbon taxes over time
In addition to the large tax differentials across countries, temporal differences in implicit
carbon tax rates exist within countries. Indeed, some governments have increased tax
rates on certain fossil fuels over time, and such policy change can be seen in the
evolution of nominal tax rates. By examining temporal changes in the nominal tax rate on
different fossil fuels within countries, we can identify policy shifts, which provide
important windows through which insights regarding the conditions under which raising
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carbon taxes might be politically possible can be gleaned. For instance, despite common
pressures to keep taxes on industrial inputs low (for reasons of industrial
competitiveness), some countries have increased implicit tax rates over time. To take the
“tough case” of coal, apparently the most difficult fuel to tax, there are some cases in
which countries have been able and willing to increase implicit carbon taxes.
Figure 4.6.2: Implicit carbon taxes on coal, in selected OECD countries
Source: IEA 2009 Figure 4.6.2 documents the “tough case” of changing tax policy affecting the price of
coal, consistently the least taxed fuel across OECD countries. The data are in national
currency, which allows for a more accurate picture of tax policy change,149 but are
therefore not directly comparable across countries. For instance, the Swedish and
Norwegian taxes seem relatively large in comparison to Finland because the tax data are
149 The idea is to illustrate change in policy over time (i.e. a change in the nominal tax rate). Data are left in national currency to avoid year to year fluctuations caused by movements in exchange rates.
0
20
40
60
80
100
120
140
160
180
200
1980 1985 1990 1995 2000 2005
Evolution in implicit carbon tax on steam coalin national currency/tCO2
Canada Denmark Finland Norway Sweden UK USA
145
expressed in Swedish and Norwegian Crowns, as compared to Euros (Finland).
Moreover, the data are nominal, and thus provide no indication of the “real” tax rate, but
they do present a clear picture of when and by how much tax rates on coal changed.150
What is to be taken from the illustration is that tax policy changes have occurred in some
countries where they have decided to unilaterally increase the price of, in this case coal,
despite the kinds of pressures and constraints commonly thought to impair the ability of
countries to increase taxes on fossil fuels. Thus, contrary to pessimistic views, it is
possible to increase taxes on fossil fuels, even coal, and such temporal differences in
energy taxes provides analysts with a window to examine the conditions under which
such increases were politically possible.
4.6.3: The real puzzle
Thus, the real puzzle, and the area in which one can garner the most empirical traction
and gain the most theoretical insight, is to assess the substantial cross-national and within
country temporal variation that exists in the way advanced capitalist democracies in the
OECD tax fossil fuels. Analysis of cross-national differences and within country tax
policy change can provide insight into the barriers to energy tax reform, and help shed
light onto the conditions under which we may reasonably expect higher energy taxes to
be politically possible. Indeed, the large and substantial cross-national differences in fuel
tax policy, and within country changes over time, suggest that some types of political
conditions are relatively more conducive to higher rates of carbon taxation. These cross-
national and cross-time differences can be exploited in order to uncover some of the
correlates of, and constraints on, energy tax reform.
Ultimately, the goal of this research is to work toward answering the broader, more
fundamental questions of: what are the barriers to energy tax reform? Why is energy tax
reform so difficult? Why have some countries been able to increase taxes on fossil fuels?
What kind of politics is required for change in the energy tax structure, and under what 150 Note: though an effort was made to account for rebates and exemptions, data do not necessarily reflect the exemptions put in place to protect some industry. Moreover, it should be noted that the years in the graph (5 year interval scale) do not necessarily correspond to the specific year of tax policy changes.
146
conditions might one expect to see it happen in the future? In order to answer these
questions, Chapter 5 tests several hypotheses commonly found in the international and
comparative politics literatures, and documents empirical evidence to support the claim
that political institutions matter for rates of energy-energy and environmental taxation.
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Chapter 5: Empirical analysis
5. Empirical analysis: the political economy of taxing fossil fuels
As demonstrated in Chapter 4, implicit carbon taxes vary considerably across countries in
the OECD, and the reasons for such differences are not immediately obvious. No country
imposes consistently high or low tax rates on all fossil fuels, and substantial differences
exist even among similarly situated countries. For instance, countries as similar in their
cultural, legal and political institutions as Canada and Great Britain lie at opposite ends of
the implicit carbon tax spectrum. Even countries as similar as Canada and the United
States, both among the lightest taxers of energy, tax the same fuels at substantially
different rates. More broadly, countries at similar levels of economic development vary
considerably in the way they tax fossil fuels and associated emissions of carbon dioxide.
These differences are even found among countries that have successfully implemented an
explicit carbon tax, where surprisingly, more carbon-intensive energy continues to be
taxed at comparatively lower rates.
These cross-national differences in rates of carbon energy taxation invite a political
analysis to explain why the OECD’s most advanced industrial economies tax the same
fuels at widely different rates. In addition, the fact that implicit carbon tax rates continue
to be inversely related to carbon content even in countries with explicit carbon taxes begs
the question of why environmental tax reform is so difficult. And instances of countries
increasing tax rates invite analysis of the temporally and contextually specific conditions
under which energy tax increases are politically possible. In order to answer these
questions, I analyze cross-national and cross-time differences in implicit carbon tax rates
levied on different fossil fuels. In analyzing each fuel discretely, key explanatory
variables can be controlled, and cross-country differences can be leveraged, allowing the
researcher to uncover the factors that are generally associated with differential rates of
carbon energy taxation.
148
In what follows, this Chapter tests the theoretical argument outlined in Chapter 1 in a
series of empirical models. Considerable evidence to support the primary research
hypotheses concerning the role of electoral systems in shaping tax rates is found using
both cross-sectional and time-series cross sectional (TSCS) data, for different fossil fuels.
Given constraints of space and time, I analyze cross-national differences in 4 of the most
commonly fuels used in the OECD – industrial use of coal and heavy fuel oil; and,
household use of diesel and gasoline.
The chapter begins with a brief summary of the main argument (5.1). Next, I specify the
theoretical expectations as key primary hypotheses that will be tested (5.2). After
discussing data and methods (5.3) I examine the empirical evidence (5.4) through an
analysis of implicit carbon tax rates on fuels used by industry (coal and heavy fuel oil)
(5.5) and household use of motor fuels (diesel and gasoline) (5.6). I then summarize and
discuss results (5.7) before concluding in Chapter 6.
5.1: Argument
Building on the theoretical argument outlined in Chapter 1, this Chapter develops the
argument that proportional electoral systems facilitate the imposition of higher energy
taxes, and in particular, lead to higher rates of implicit carbon taxation in advanced
capitalist democracies. I thus expect to find higher implicit carbon taxes in countries
where PR is the primary method used to translate vote shares into seat shares.
Two causal logics underlie this expectation. First, I argue that PR systems create the
“ideological space” necessary for those parties predisposed to favour higher energy taxes
– i.e. parties of the left and green parties (which previous research has shown favour
higher rates of energy taxation) – to implement their political programs. This is due to the
well-documented fact that PR systems produce a larger number of “effective” political
parties (Duverger, 1954; Laakso and Taagepera, 1979; Lijphart, 1990) and a higher
149
incidence of coalition government (Taagepera and Shugart, 1989; Strom, 1990). The key
mechanism here is the greater degree of proportionality generated by PR systems – i.e. a
more faithful allocation of seat shares relative to vote shares – which implies, inter alia,
that a) dominant parties are less likely to win a majority; b) smaller parties (e.g. greens)
or those with broader social welfare goals (e.g. left-wing social democrats) will more
easily win seats in the legislature; and, c) these smaller parties will have a greater chance
of participating in coalition government. However, opening up the ideological range in
the party system is necessary but not sufficient for explaining higher rates of energy
taxation. I argue that the impact of PR is conditional on the ideological makeup of the
legislature and on the composition of government. Electoral systems thus open the door,
so to speak, but do not by themselves explain higher rates of carbon energy taxation.
Equally important is the presence of green/left parties – who favour energy tax increases
– in the legislature or government that enable these parties to implement their preferred
policies. This enabling effect stems from these parties being in power, or because
coalition partners will have an incentive to implement green/left programs (e.g. higher
energy taxes, higher spending) in exchange for political support, or in order to gain votes.
In this perspective, higher rates of energy taxation depend on both the presence of
green/left parties in the legislature/government combined with PR systems. We should
therefore expect to see larger implicit carbon taxes when green/left parties are represented
in the legislature and in government under systems of PR.
Second, I argue that electoral systems also create electoral incentives that can shape party
preferences. One of the ways through which electoral systems shape party preferences is
via the mechanism of government accountability, which increases under disproportional
electoral systems. Indeed, governments may be held more accountable in disproportional
systems because even a small change in the vote share can lead to relatively large
changes in a party’s share of legislative seats, making governments more vulnerable to
shifts in public opinion. Rogowski and Kayser (2002) call this the seat-vote elasticity,
though they never test its effects empirically. Moreover, to the extent that disproportional
systems tend to produce single-party majority governments, voters know precisely who to
punish for unfavourable policy (Persson and Tabellini, 2008). It follows that
150
disproportional systems increase transparency and government accountability, producing
an incentive for governments (and parties) to “please” voters, by for instance, not
increasing taxes. Thus, disproportional systems will tend to constrain the ability of
green/left parties to implement their political program, if this means higher energy taxes
that are politically unpopular. Power-seeking political parties know that they are more
vulnerable and accountable under majoritarian rules, and therefore will be constrained in
their ability to increase energy taxes when the seat-vote elasticity is high, as is the case in
disproportional systems.
Just as disproportional systems make governments and parties more accountable and
vulnerable, however, they also make parties and governments more responsive to small
changes in voter preferences. Indeed, while green/left parties might be constrained from
implementing their preferred tax and spending policies while in government, a rise in
support for a particular issue or issue-oriented party may very well result in the
implementation of policy consistent with this support, irrespective of which party is in
power. For instance, a sudden rise in support for green parties in disproportional systems
may lead to changes in policy, even if the green parties never actually gain power
(because of disproportional electoral results in majoritarian electoral systems). This is
due to the fact that parties competing for votes in an electoral system where the seat-vote
elasticity is high will have greater incentive to respond to the shift in popular sentiment,
in order to maximize vote gains and minimize vote losses. As a result, I expect to see a
rise in rates of implicit carbon taxation to follow a rise in popular support for green
parties, under highly disproportionate electoral systems.151
5.2: Hypotheses
The above logic can be reformulated in a series of empirically testable hypotheses. With
reference to the theory outlined above, the observable implications of the argument can
be distilled into four hypotheses, which are empirically tested in the sections that follow.
151 But a rise in the share of (cabinet) seats for greens and the left parties under disproportional systems will not lead to such an increase, since the incentive for all parties in such systems is to keep energy taxes low (H2).
151
H1: The PR hypothesis: Relative to majoritarian electoral systems, countries with PR will impose higher implicit tax rates on carbon. H2: The ideological space hypothesis: Relative to majoritarian electoral systems, greater representation from parties of the left and greens will be positively associated with significantly greater implicit carbon tax rates under PR. H3: The disproportional constraints hypothesis: Relative to proportional systems, greater representation from parties of the left and greens will not be positively associated with greater implicit carbon tax rates under more disproportional systems, as these parties will be constrained in their ability to raise tax rates. H4: The electoral incentives hypothesis: Relative to more proportional systems, increasing support for green parties will lead to an increase in rates of implicit carbon taxation under more disproportional systems, as parties/governments have greater incentive to respond to mounting electoral threats where the seat-vote elasticity is high.
5.3: Data and methods
In order to test these hypotheses, I develop a series of empirical models using both cross-
sectional and time-series cross-sectional (TSCS) data. The data are drawn from various
sources, including the IEA, OECD, World Bank (World Development Indicators), Penn
World Tables 6.3 (Heston et al. 2009), the Database of Political Institutions (Keefer,
2007), the Political Parties Data Set (Swank, 2007), and the Comparative Political Data
Set (Armingeon et al. 2009). Detailed data descriptions and summary statistics are
provided below and in the data appendix.
For the purpose of the present analysis, it was decided to focus on a particular sub-set of
OECD countries; namely, the advanced, capitalist, industrialized democracies that are
commonly studied together in the CPE and IPE literatures (Becher, 2010; Garrett and
Mitchell, 2001; Holzinger et al. 2008; Iversen and Stephens, 2008; Quinn, 1997; Swank,
2006; Swank and Steinmo, 2002; Winner, 2005). The number of countries and years
examined varies by the availability of data, but typically ranges between the 18 and 22 of
the richest industrial democracies in the OECD, over the period 1978-2006. Based on
152
their status as advanced industrialized democracies, and subject to data availability, the
countries in the sample include: Australia (AUS), Austria (AUT), Belgium (BEL),
Canada (CAN), Denmark (DNK), Finland (FIN), France (FRA), Germany (DEU),
Greece (GRC), Ireland (IRL), Italy (ITA), Japan (JPN), Luxembourg (LUX), the
Netherlands (NLD), New Zealand (NZL), Norway (NOR), Portugal (PRT), Spain (ESP),
Sweden (SWE), Switzerland (CHE), Great Britain (GBR) and the United States (USA).
Tax rates for all other countries described in Chapter 4 – including the Czech Republic
(CZE), South Korea (KOR), Hungary (HUN), Slovak Republic (SVK), Mexico (MEX),
Poland (POL), and Turkey (TUR) – are omitted from the empirical analysis developed in
this Chapter.152
Studying this particular sub-set of OECD countries carries with it numerous advantages
and can be justified on several grounds. First, the developed democracies included in this
analysis share a set of characteristics in common, rooted in a shared history involving a
number of similar economic transformations since the late 1970s. In addition, this group
continues to face common challenges (like financing their welfare states, renewed
concern over energy security, and addressing climate change), and share a limited range
of potential policy responses. As a result, these countries are more closely comparable,
while differences among them are of particular theoretical interest (c.f. Katzenstein,
1979).
Theoretically, the hypotheses tested in this Chapter draw from the literature on advanced
capitalist welfare states; as such, they are more applicable to these cases. Moreover,
much of the data required for testing these hypotheses are missing for the out of sample
cases, and there are substantive differences that suggest the hypotheses might not be
appropriate even if these data were available. As will be discussed in the Conclusion, the
focus on advanced capitalist countries in the OECD puts these countries front and centre.
Developed economies are the ones most commonly looked upon to provide leadership in
making the largest emission cuts to address global climate change, because of their
152 Note: country codes are based on ISO 3166.
153
historical emissions and because of their available resources. Thus, a focus on these
countries is pertinent, and pushes the present analysis to consider the conditions under
which the advanced OECD countries might take a lead role in making the GHG
reductions necessary to mitigate the adverse implications of climate change.
Finally, the restricted sample is also justified on methodological grounds as well.
Looking at only a subset of advanced capitalist OECD democracies allows the researcher
to control for level of economic development, thus holding national wealth effects and
regime type relatively constant. According to the literature on the Environmental
Kuznet’s curve, which postulates an inverted U shape function between economic
development and pollution, such control is important (Grossman and Krueger, 1995;
Raymond, 2004). Figure 5.3 lists the OECD countries in ascending order in terms of per
capita GDP.
Figure 5.3: Mean income of OECD countries in 2006
Source: World Bank (2009) The threshold for the present analysis is between New Zealand and Korea ($25,000 USD
per capita). Limiting the analysis to the richest OECD countries with established
democratic histories is important, since it is challenging to make sense of implicit carb
tax differences across, for instance,
democratic Canada, and the formerly Communist and relatively less affluent Czech
Republic, especially in light of the fall of the Soviet Union in the 1990s, and the hype
0 10000 20000
TURMEXPOLSVK
HUNPRTCZE
KORNZLGRCESPITA
FRAJPNFIN
DEUBELGBRSWEDNKAUTAUSCANNLDCHEIRL
USANORLUX
(constant 2005 international PPP)
Figure 5.3: Mean income of OECD countries in 2006
The threshold for the present analysis is between New Zealand and Korea ($25,000 USD
per capita). Limiting the analysis to the richest OECD countries with established
is important, since it is challenging to make sense of implicit carb
tax differences across, for instance, Japan and Korea, or consistently affluent and
democratic Canada, and the formerly Communist and relatively less affluent Czech
Republic, especially in light of the fall of the Soviet Union in the 1990s, and the hype
20000 30000 40000 50000 60000 70000
Per capita GDP in 2006(constant 2005 international PPP)
154
The threshold for the present analysis is between New Zealand and Korea ($25,000 USD
per capita). Limiting the analysis to the richest OECD countries with established
is important, since it is challenging to make sense of implicit carbon
consistently affluent and
democratic Canada, and the formerly Communist and relatively less affluent Czech
Republic, especially in light of the fall of the Soviet Union in the 1990s, and the hyper-
70000 80000
155
inflation among other economic challenges that occurred in many less developed
countries since the late 1980s.153
5.4: Empirical analysis and evidence
The following sections examine cross-national macroeconomic statistical evidence to
demonstrate the theoretical argument regarding the role of political institutions in shaping
tax policy outcomes. Aggregate data for each country are examined for statistical
relationships among key independent variables and tax policy levels. The analysis is
broken up into two main parts.
First, I examine tax rates on fuels used for commercial-industrial purposes; coal and
heavy fuel oil. Due to missingness in these data, I am unable to test all of the primary
working hypotheses in a panel model. Instead, I run OLS regression on a cross-section of
18 countries for which complete data are available. While multiple imputation of missing
values is sometimes advocated (King et al. 2001), this method requires that data be
missing at random.154 However, in the case of tax rate data for coal and heavy fuel oil,
long stretches of data are missing for each country. It was therefore decided to convert
the panel data structure to a simple cross-section by averaging yearly tax data over the
time period for which data are available, and regressing the country-specific mean tax on
key independent variables, also averaged over the same period. Although this data
structure considerably reduces degrees of freedom and does not allow for an analysis of
time trends and dynamics, it nevertheless can provide a sense of whether statistically
significant relationships exist among variables. Moreover, analysis of such data is often
used as a compliment to time-series cross-sectional techniques (e.g. Steinmo and Tolbert,
1998; Rogowski and Kayser, 2002).
153 It is worth emphasizing the fact that inflation rates are very similar across the sub-set of countries that make up the present analysis. In contrast, hyper-inflation occurred in several of the omitted countries. Had these countries not been omitted, large differences in tax rates among high and low inflation countries would artificially emerge where tax rates are adjusted for inflation (i.e. where cross-time comparisons are made). 154 Missing at random here implies that the probability of any observation for tax rate being missing should not be conditional on unobserved values of any of the variables used to impute incomplete values.
156
The second major component of the empirical analysis focuses primarily on fuels used by
ordinary energy consumers, with a particular emphasis on motor fuels. Due to the more
complete nature of tax rate data on the household sector, I construct a time series cross-
sectional (TSCS) data structure, which includes an annual time series for each of the
countries in the data set. This data structure is now common in the political science
literature, and the relatively larger n it yields produces lower bias and greater efficiency
in point estimates, due to its asymptotic properties. This allows me to include a larger
number of independent variables in empirical models without sacrificing degrees of
freedom. At the same time, certain technical issues are raised by the use of TSCS, which
are addressed in greater detail below.
5.5: Implicit carbon taxes on fuels used by industry
For the purpose of the present analysis, I divide implicit carbon tax rates in two groups –
taxation on fuels used primarily by industry, and taxation of fuels used primarily by the
non-commercial sector (i.e. households). To be sure, there are good reasons to believe
that the political dynamics inducing governments to push for higher/additional energy
taxation, or preventing them from doing so, will be somewhat different across the two
sectors. For instance, relative to households, energy-intensive industry is more sensitive
to international competitiveness concerns, while the energy-producing sector will oppose
taxes affecting the price (and competitiveness) of its primary products. In addition,
“industry” represents a small group with concentrated interests, and is therefore more
likely to overcome barriers to collective action and effectively mobilize against increased
fossil fuel taxation. For these reasons, one might expect different variables to influence
tax rates levied upon different fuels, different sectors, and different uses of the same
fossil fuels.
In one of the few previously existing large-n cross-national studies of energy taxation by
a political scientist, Morozova (2007) hypothesizes that tax rates on fuels used by
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industry should be strongly influenced by cross-national differences in levels of
corporatism. Building on the qualitative literature on the comparative politics of carbon
taxes, which suggests tripartite corporatist networks help to explain the ultimate carbon
tax design selected (Midttun and Hagen, 1997; Daugbjerg and Pedersen, 2004),
Morozova argues that corporatist decision-making networks decrease the bargaining
costs between business and government, leading her to expect higher carbon tax rates in
more corporatist countries. Empirically, she finds limited empirical support. An
alternative and not necessarily contradictory perspective developed here suggests that
electoral systems help explain the decision to implement higher energy taxes in the first
place, facilitating the political implementation of left wing and green party policy
programs, like increasing rates of energy taxation for the purpose of decreasing energy
use, decreasing pollution, and raising government revenue to finance a more progressive
welfare state. In order to test both hypotheses empirically, the following sections analyze
two types of fossil fuels most commonly used by heavy industry -- steam coal and heavy
fuel oil.
5.5.1:Steam coal As documented in Chapter 4, coal is the least taxed fuel in OECD countries. At the same
time, substantial cross-national differences exist in the way countries tax coal. Figure
5.5.1 illustrates large tax differentials across OECD countries on tax rates applied to
steam coal used for industrial processes.155 Data for Luxembourg, Ireland, Greece and
Spain are missing, resulting in an n of 18.
155 This analysis examines tax rates on steam coal used by industry. Other types of coal and coal derivatives, e.g. coking coal, are excluded, as are tax rates on coal used for electricity generation (for reasons mentioned in Chapter 4). Here I use the term coal and steam coal interchangeably, and the tax on coal refers to the tax on coal used for industrial purposes.
158
Figure 5.5.1.1: Implicit carbon tax rate on steam coal used by industry
Source: IEA Energy Prices and Taxes (various volumes) Note: Country codes are based on ISO 3166 The data in Figure 5.5.1.1 summarize the effective tax rate on steam coal used by
industry for 18 countries, in constant (2000) USD per tonne of CO2, averaged over the
years 1978-2006.156 As can be seen, large cross-national differences in the implicit tax
rate on coal exist. At one end of the spectrum, the United States, Portugal, Italy, France,
Germany, Canada, Belgium and Australia have no tax on coal between 1978-2006. All
of these countries, except for Portugal and Italy, are coal-producing countries. In contrast,
Sweden and Norway apply tax rates equivalent to over $10 USD per tonne of carbon
dioxide, while the Finnish tax averages to about $7 USD per tonne of CO2. Although we
might expect to see higher tax rates in countries that do not produce coal (e.g. Finland
and Sweden), Norway is a coal-producing country that nevertheless imposes one of the
156 Effective tax rate here refers to the total tax rate incurred by industry once rebates and exemptions are accounted for.
159
largest implicit carbon tax levels on coal in the entire OECD. Between these extremes,
Denmark, Austria, Switzerland, New Zealand, Japan, Great Britain and the Netherlands
are among the countries to impose taxes on coal, though their levies are comparatively
smaller, falling under $5 USD per tonne of CO2.
Figure 5.5.1.2: Total coal production
Source: EIA (2009) and Heston et al. (2009) Figure 5.5.1.2. summarizes the data on coal production across the sample of 18 OECD
countries for which tax data on steam coal used by industry are available. This measure
can be conceptualized as the power of the coal lobby in that it provides an indication of
the size of the coal producing sector (measured in tonnes of oil equivalent) expressed as a
percentage of real gross domestic product (in constant 2005 international dollars at
purchasing power parity). Thus, it can be used as a proxy for the relative size of the coal
producing sector in a particular jurisdiction, standardized in terms of the size of the
economy. It might be hypothesized that the level of implicit carbon tax applied to
160
industry use of steam coal will vary according to the size of the coal lobby.157
Interestingly, as suggested by Figures 5.5.1.1 and 5.5.1.2, the presence of coal producers
does not preclude taxes on coal, nor does the absence of a coal lobby guarantee them. For
instance, Italy produces no coal, nor does it apply a tax to industry use of steam coal. Of
the modest coal-tax countries (Figure 5.5.1.1), Great Britain, New Zealand and Belgium
produce relatively large amounts of coal, while Austria and Japan are also coal-producing
countries with moderate taxes on coal (Figure 5.5.1.2).
One potential reason for this particular distribution of coal tax rates across OECD
countries can be found in the work of Morozova (2007), who hypothesizes a relationship
between high levels of corporatism and higher tax rates on heavy fossil fuels. Applied to
the present study, the ability to impose higher tax rates on coal might be due less to the
absence of a coal lobby, than to the presence of corporatist decision making networks,
which decrease the cost of bargaining, and increase the potential for multi-stakeholder
compromise. A simple bivariate scatter plot provides some evidence in support of this
view.
157 Industries using steam coal might also be expected to mobilize against tax increases on coal, but including a measure of energy intensity in a statistical model raises an issue of endogeniety, therefore energy intensity is excluded. In its place, I substitute trade exposure for coal production, which yields similar results to those reported in the regression table below. The significant finding for the interaction between PR electoral systems and left cabinet governments is robust to this alternative specification.
161
Figure 5.5.1.3: Implicit carbon tax on steam coal by level of corporatism
Source: IEA Energy Prices and Taxes (various volumes) and Siaroff (1999)
As can be seen in Figure 5.5.1.3, there is a moderately strong, positive relationship
(r=0.66) between the implicit carbon tax rate on steam coal, averaged over the period
1978-2006, and Siaroff’s (1999) index of corporatism, though there is considerably more
variation at higher levels of tripartite coordination. An additional pattern is also to be
found when comparing the distribution of implicit carbon tax rates on steam coal across
the two primary categories of electoral systems (5.5.1.4).
162
Figure 5.5.1.4: Implicit carbon tax rate on steam coal by electoral regime (H1)
Figure 5.5.1.4 plots the distribution of implicit carbon tax rates on steam coal across the
two primary categories of electoral regime – single member plurality (i.e. majoritarian)
and proportional representation (i.e. PR) systems. As can be seen, both the median and
mean implicit carbon tax on steam coal used by industry is greater among countries
employing proportional electoral systems. Moreover, implicit carbon tax rates are
comparatively lower in countries employing single member plurality electoral formulae,
and a ttest of unequal variances confirms this difference as real at conventional levels of
significance (i.e. p<0.05). At the same time, however, the variation among PR systems is
rather large, suggesting that this variable, on its own, does not account for the large cross-
national differences in rates of implicit carbon taxation for steam coal. Indeed, while the
median under PR is higher than the median tax under majoritarian systems, some PR
countries have comparably low tax rates on coal.
163
In order to more closely analyze the political determinants of implicit tax rates on coal,
the 18 countries for which data are available are included in a series of regression models.
Following the theoretical framework discussed in Chapter 1, the models include measures
of business interests, political institutions and partisan ideology. Business interests are
operationalized with the variable coal_prod, which is a measure of the size of the coal
lobby, in terms of total coal production (in kilotonnes of oil equivalent) divided by real
gross domestic product. Data on coal production are taken from the EIA, and data for real
gross domestic product are from the Penn World Tables 6.3 (Heston et al. 2009). The
interests of trade-exposed, energy intensive sectors, who fear a loss of international
competitiveness from energy taxes, are operationalized by the variable openk, which is a
measure of trade openness (imports + exports / gross domestic product), taken from the
Penn World Tables 6.3 (Heston et al. 2009). Given the nature of the coal tax falling
specifically on the business community, I also include a measure of corporatism
developed by Siaroff (1999), which is expected to facilitate the imposition of taxes on
industry (Morozova, 2005). Another institutional variable of particular interest for the
theoretical argument analyzed here is called pr, which is a dummy variable indicating
whether the majority of legislative seats are allocated according to a proportional or
majoritarian formula (Keefer, 2007).158 To measure the role of left ideology, I include
left_cab, an indicator of left-wing representation in government, measured in terms of the
percent of cabinet portfolios occupied by members of traditional left-wing (i.e. social-
democratic) parties (Armingeon et al. 2009). Following insights from the qualitative
literature on carbon taxes (Daugbjerg and Pedersen, 2004; Harrison, 2010), I expect
green and left parties to be associated with higher rates of carbon energy taxation.
Finally, the theoretical argument outlined in 5.1 specifies that PR regimes are likely to
have an effect on tax rates because they mediate the political power of green/left political
parties. I therefore create two multiplicative interaction terms pr_leftc (left_cab*pr), and
left_diss (left_cab*dis_gall). Following the theoretical expectations outlined in 5.2, I
expect left party cabinet to lead to higher taxes under PR (H2), and this effect to be 158 The variable PR is a dummy variable indicating the way in which the majority of legislative seats are allocated in the lower legislature. The measure, adapted from Keefer (2007) is thus able to distinguish between electoral systems that contain both plurality and proportional formulae (e.g. Australia, Germany, and Japan).
164
constrained under disproportional systems (dis_gall) (H3). Summary statistics for these
variables are provided in Table 5.5.1.1.
Table 5.5.1.1: Summary statistics for coal tax regression models Variable Observations Mean Std. Dev. Minimum Maximum coal_tax 18 2.49 4.54 0 15.82 coal_prod 18 0.16 0.02 0 0.06 net_coal_xp 18 -46.83 74.54 -100 184 openk 18 57.00 25.73 18.6 131.8 corporatism 18 2.78 1.42 1 5 left_cab 18 32.83 19.87 0 72.41 pr 18 0.67 0.48 0 1 dis_gall 18 6.02 5.13 1.02 16.3 left_dis 18 188.5 222.9 0 728.44 pr_leftc 18 25.08 22.93 0 72.41 Notes: Refer to data appendix for detailed variable definitions Each independent variable in Table 5.5.1.1 is sequentially included in separate regression
models, beginning with the interests of coal producers and consumers, followed by
corporatism, the percent of all cabinet portfolios held by parties from the left, a dummy
for proportional electoral systems, and an interactive term between PR and left cabinet
portfolios. The variable net_coal_xp is a measure of a country’s import dependency or
export prowess (highly correlated with production) and is used later on with additional
controls in the robustness checks. The results of the primary models are summarized in
Table 5.5.1.2. In all models (1 to 6), the dependent variable is the average implicit carbon
tax rate on coal over the period 1978-2006, measured in constant (2000) USD.
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Table 5.5.1.2: Coal tax regression models testing the ideological space hypothesis (H2) (1) (2) (3) (4) (5) (6) coal_prod -15.52 -19.48 -2.427 -10.26 -10.98 -6.342 (18.62) (19.32) (15.63) (15.12) (16.36) (12.16) openk -0.0471 -0.0514 -0.0485 -0.0463 -0.0258 (0.05) (0.04) (0.04) (0.04) (0.03) corporatism 2.585*** 1.656 1.736 0.366 (0.74) (0.86) (1.03) (0.86) left_cab 0.0958* 0.0955 0.0110 (0.05) (0.06) (0.05) pr -0.434 -6.929** (2.73) (2.81) pr_leftc 0.260*** (0.07) _cons 3.833** 6.718* -1.585 -2.226 -2.271 0.810 (1.63) (3.78) (2.51) (2.35) (2.46) (2.04) N 18 18 18 18 18 18 Adj. R2 0.014 0.028 0.392 0.477 0.435 0.692 Standard errors in parentheses * p < 0.1, ** p < 0.05, *** p < 0.01 The basic results summarized in Table 5.5.1.2 support the hypothesis that PR electoral
systems shape rates of implicit carbon taxation by mediating the ability of left wing
parties to implement their green/energy tax policy preferences. Interestingly, however, a
few surprises emerge. Indeed, models including only business interests (1 & 2) reveal
little in terms of explaining why countries tax coal at different rates. However, building
on this base each successive model builds explanatory power. With six variables, the
final model (6) provides the best fit to the data, explaining close to 70 per cent of the
variation in coal taxes. It should be noted that an F test for Model 6 confirms the joint
significance of all the independent variables included.
166
Looking at each independent variable separately, evidence of interest group influence
over policy is limited, while evidence of the mediating role of political institutions is
more pronounced. Although higher tax rates on industrial use of steam coal are
negatively associated with larger coal lobbies and greater exposure to international trade,
the coefficients on coal production and trade exposure do not attain significance across
all models. Robustness checks explained later fail to reveal multicolinearity as a problem,
and when net_coal_xp is substituted for coal_production the models yield virtually
identical results.
In contrast to the relatively weak performance of economic interests, the political
variables perform much better. As expected, corporatism is positively associated with tax
rates on coal. Holding coal production and trade exposure constant, the degree of
corporatism is positively related to higher tax rates on coal, and this relationship is
significant at the p<0.01 level (Model 3). However, when other political predictors are
subsequently included (Models 4 through 6), the coefficient on corporatism loses
significance. As anticipated, the percentage of left cabinet portfolios is positively
associated with higher tax levels on coal, though this relationship achieves only modest
levels of significance (Model 4). Once the PR variable is entered into the model, both
left_cab and pr appear to have no impact. However, when both are included in a
multiplicative interaction term, the combined effect is highly significant (Model 6). More
precisely, left wing cabinet representation has no impact when pr is at zero (i.e. in
plurality systems), while pr is associated with significantly lower tax rates when there are
no left parties in cabinet. Consistent with the theory, the impact of PR is conditional on
the presence of left parties in government. Holding other factors in the model constant,
the combination of left wing party cabinet posts and PR leads to higher rates of implicit
carbon taxation on steam coal. Proportional electoral regimes are thus “good” for the
environment, but only where social democratic parties are in government, and vice versa.
Controlling for business opposition, exposure to international trade, and corporatist
decision-making networks, a 5 per cent increase in left party cabinet portfolios is
167
associated with an average increase in tax on coal of about $1.355 USD (i.e. 5 times 0.26)
per tonne of carbon dioxide in proportional systems. The inverse – where left parties are
in government under plurality systems, which sometimes occurs (e.g. Great Britain under
a Labour government), appears to have no effect, on average, as indicated by the
relatively large standard error.159 With only 18 cases and 6 independent variables, the
statistical significance of the interaction term in Model 6 is impressive. To be sure, both
the proportional representation and left cabinet variables are consistently strong
predictors of coal tax rates across alternative model specifications not reported here.160 In
fact, of the 6 independent variables included in the model, the standardized beta
coefficient for the interaction pr_leftc is nearly a full order of magnitude larger than the
next strongest predictor.161 These results persist even after additional model
specifications are introduced in robustness checks (below).
To better illustrate the interactive relationship between PR electoral systems and social
democratic parties, and associated levels of significance, Figure 5.5.1.5 graphs the
marginal effect of left wing party in government at different theoretical levels of PR.
159 The one exception to this pattern is Great Britain, whose Labour Government implemented a tax on coal as part of the UK Climate Change Levy (2001). 160 For instance, left cabinet portfolios is nearly always significantly associated with higher tax rates no matter what other independent variables are included in the model. 161 For simplicity I do not report the beta coefficients in regression tables.
168
Figure 5.5.1.5: The marginal effect of left party cabinet portfolios under PR (H2)
Figure 5.5.1.5 graphically depicts the marginal effect of increasing cabinet portfolios on
implicit carbon tax rates on steam coal. The dotted lines indicate the 95% confidence
interval and allows the reader to determine the conditions under which an increase in left
wing government participation has a statistically significant effect on implicit carbon tax
rates. While interpreting this graph, it is important to keep in mind that the marginal
effect is only significant when both the upper and lower bounds are above or below the
zero line. From this, we see that the marginal impact of left cabinet portfolios is positive
and significant in PR regimes (i.e. where PR is equal to 1), but that the marginal effect of
left party cabinet positions on coal taxation is not significant in countries where
majoritarian elections are used to elect governments (i.e. where PR is equal to 0). This
conditional relationship is exactly what we would expect from our theory regarding why
PR systems matter – they open up space for green/left-wing party policy preferences.
169
The substantive impact of this interaction on tax policy is further demonstrated in a
simple 2 by 2 table (Table 5.5.1.3).
Table 5.5.1.3: Implicit carbon taxes on coal by left wing cabinet portfolios and PR Majoritarian (smp)
Proportional representation (pr)
Left wing cabinet >40%
New Zealand ($0.83)162 Australia ($0.00) France ($0.00)
Sweden ($15.82) Norway ($11.49) Finland ($7.66) Austria ($2.04)
Left wing cabinet <40%
Japan ($0.66) Great Britain ($0.53)163 Canada ($0.00) United States ($0.00)
Denmark ($3.53) Switzerland ($1.90) Netherlands ($0.43) Belgium ($0.00) Germany ($0.00) Portugal ($0.00) Italy ($0.00)
As can be seen from Table 5.5.1.3, the data fit the theory quite nicely. As expected, left
wing cabinet composition makes little difference under majoritarian SMP systems.
However, in the third column (PR), the distribution of tax rates is clearly divided between
countries having had experience with relatively large left-wing cabinet government,
relative to those with comparatively fewer left wing cabinet posts. Substantively, 11 of
the 18 countries in the sample fall under this category of PR. Of these, several are also
characterized by strong representation from left wing parties, resulting in relatively
higher taxes on coal (e.g. Sweden, Norway, Finland, Austria). On the other hand, PR
countries with relatively lower left party cabinet representation (e.g. Germany, Belgium,
Italy, Switzerland) have had continuing difficulty in raising environmental taxes.164 The
only real outlier here is Denmark, and it levies only a moderate coal tax by comparative
standards. Conversely, greater (i.e. >40%) left wing party representation in plurality
162 In 1993 New Zealand adopted a more proportional electoral system. It is included in the SMP category here only because it was a plurality system for the majority of the 1978-2006 period. 163 A left-wing Labour government implemented the U.K. climate change levy in 2001. 164 As of 1999 the tax on steam coal in Switzerland is actually $0.00. Moreover, numerous fossil fuel tax proposals have met great political difficulty in Switzerland (e.g. Thalmann, 2004).
170
countries (e.g. Australia, New Zealand, Great Britain and France) has not resulted in
substantially higher tax levels on industrial use of coal, as expected. New Zealand is an
exception, where it recently changed its electoral system to PR in 1994, and Great Britain
introduced a moderate coal tax as part of the “Climate Change Levy” introduced by the
Labour government after Thatcher had dismantled the coal unions. Meanwhile, zero left
wing cabinet portfolios and plurality systems combine to explain non-existent tax rates in
Canada and the U.S. All of this lends considerable support to the idea that countries with
relatively high left-wing party representation in PR systems should have the highest taxes
on fossil fuels.
As a further test of the theory, and to ensure that the pr variable is really capturing the
effect of the electoral system, and not some other idiosyncratic differences, I substitute
dis_gall for pr. The dis_gall variable is Gallagher’s (1991) index of disproportionality.
Recall that the argument suggests PR should lead to higher taxes because it opens up
political space for smaller parties to implement their preferred policies. Conversely, it
follows that more disproportional systems should constrain the ability of small and left
wing parties to implement their policy programs. This is due to the fact that majoritarian
(disproportional) systems produce incentives to target geographically concentrated
interests in pivotal districts at the expense of targeting broader social welfare goals
(Persson and Tabellini, 2008; Rodden, 2007), like reducing GHG emissions and other air
and water pollutants associated the burning of fossil fuels. Moreover, disproportional
systems typically produce majority governments, thereby clarifying the lines of
accountability for unpopular policy, reducing the electoral threat of smaller green/left
parties, as well as their importance as coalition partners (Steinmo and Tolbert, 1998).
Finally, I argue that the ability of any party to increase taxes is constrained under
disproportional systems, since the public is likely to oppose an increase in taxes, and
governments are more accountable and vulnerable to small changes in vote share under
disproportional systems. If true, the observable implication is to expect lower tax rates in
disproportional systems, and the marginal effect of social democratic parties on tax rates
should disappear as electoral systems produce more disproportional results. These ideas
are tested and summarized in Table 5.5.1.4.
171
Table: 5.5.1.4: Coal tax regression models testing the disproportional constraints hypothesis (H3) (1) (2) (3) (4) (5) (6) coal_prod -18.71 -17.06 -2.427 -10.26 -10.47 -11.41 (18.23) (19.87) (15.63) (15.12) (15.75) (13.39) openk 0.0116 -0.0514 -0.0485 -0.0491 -0.0492 (0.0455) (0.0390) (0.0361) (0.0377) (0.0320) corporatism 2.585*** 1.656* 1.490 0.764 (0.743) (0.858) (1.230) (1.089) left_cab 0.0958* 0.101 0.250** (0.0528) (0.0616) (0.0818) dis_gall -0.0496 0.554 (0.253) (0.333) left_dis -0.0201** (0.00849) _cons 3.015** 2.328 -1.585 -2.226 -1.625 -4.460 (1.183) (2.955) (2.506) (2.350) (3.916) (3.536) N 18 18 18 18 18 18 adj. R2 0.003 -0.059 0.392 0.477 0.436 0.592 Standard errors in parentheses * p < 0.1, ** p < 0.05, *** p < 0.01 The disproportional constraints hypothesis is empirically supported in Table 5.5.1.4. As
expected, the coefficient on coal production is negatively associated with tax rates on
coal, though this variable never attains even a modest level of significance across Models
1 to 6. Similarly, trade exposure, measured by the variable openk, generally has the
expected sign (with the exception of Model 2), though it too never attains statistical
significance. Corporatism is positive and significant, as expected, in Models 2 and 3, but
loses its significance once dis_gall, the measure of proportionality, is included. Once
again, the last model including the interaction term provides the best fit to the data, and a
joint F test confirms that all independent variables in the model are jointly significant.
172
Model 6 tests the interactive hypothesis and finds an inverse relationship between social
democratic cabinet posts and implicit carbon tax rates on steam coal under
disproportional electoral systems. As expected, the marginal impact of left wing cabinet
portfolios decreases to insignificance as electoral systems produce more disproportional
outcomes. Figure 5.5.1.6 provides a graphical illustration.
Figure 5.5.1.6: The marginal effect of left wing cabinet portfolios in disproportional systems (H3)
As can be seen in Figure 5.5.1.6, the impact of left wing cabinet portfolios on rates of
implicit carbon taxation for coal is positive and significant at low levels of
disproportionality, just as the argument in 5.1 suggests. However, as disproportionality in
the electoral system increases, left wing parties are increasingly constrained in their
ability to implement higher energy taxes, and the marginal impact thus decreases with
increasing levels of disproportionality. Having substituted the simple pr dummy variable
with a measure that more adequately captures the key causal mechanism underpinning
173
the hypothesis of electoral constraints, the theoretical relationship postulated among
electoral systems, political parties, and carbon taxes garners further empirical support.
Robustness checks In order to build confidence in these results, I conduct a series of diagnostic and
robustness checks. First, correlation matrices and graphs are examined to check for
multicolinearity in the independent variables (see data appendix). Visual inspection of
these outputs provides no clear indication of collinearity issues, and this was confirmed
by low VIF scores, none of which exceeded the ‘rule of thumb’ threshold of values
greater than 10 (the largest was 8.70 for pr_leftc, which as an interaction term is expected
to be correlated with other independent variables). Theoretically, corporatism might be
expected to be correlated with left_cab. When corporatism is removed from the
regressions testing H2, the core results remain unchanged; pr_leftc retains its significance
at the p<0.01 level and the coefficient remains relatively unchanged (from 0.260 to
0.276). In addition, the adjusted R-square increases moderately to 0.713, as might be
expected when a non-essential independent variable is removed from the explanatory
model.
To check for heteroskedasticity (i.e. non constant variance in the error term), I plot the
residuals against predicted values of the dependent variable in a rvfplot. Some of the
residuals appear to cluster at values closer to zero, relative to higher values, indicating
some potential heteroskedasticity. A Breusch-Pagan / Cook-Weisberg test further
confirms the suspicion that the null hypotheses of homogenous variance should be
rejected.165 The heteroskedasticity in the errors suggests that the standard errors and
hypothesis tests might be invalid. The small sample size, and a few cases of large tax
rates relative to a cluster of countries with zero tax rates thus appear to pose a potential
problem. In order to guard against the possibility of influential outliers and observations
with greater leverage, I run a robust regression using Huber-White sandwich estimates of
165 This test is implemented in Stata with the command “estat hettest” following a regression. After estimating model 6, a hettest produces a value of 0.0086, suggesting the null of constant variance should be rejected in favour of the alternative.
174
standard errors (Huber and Ronchetti, 2009). After running models with this more
conservative estimator, both variables that were significant in the original model with
potential heteroskedasticity (i.e. pr and pr_leftc) remain significant. In fact, their
significance increases. The results are thus robust to different methods – principally
designed to deal with heteroskedasticity and influential observations – of estimating the
size of the standard errors.
As a final robustness check, I re-run the models with a transformed dependent variable,
use an alternative measure of the size of the coal producing sector, net_coal_xp, and
include several other control variables in the model, including average GDP per capita,
average central government debt (expressed as a percentage of GDP) and average
revenues from income taxes in GDP (Table 5.5.1.5). Although normality is not necessary
for OLS to produce unbiased estimates of regression coefficients, the dependent variable
is positively skewed due to most countries having low or no tax rate on coal, while a
handful have relatively large taxes.166 Erring on the side of conservatism and as a
robustness check, I transform tax rates by taking the square root of coal_tax, yielding a
distribution that more closely approximates normality. When the transformed tax rate is
regressed against the predictors in the original models, substituting net_coal_xp for
coal_production, adding controls, and using estimates of robust standard errors, the basic
results remain unchanged (Table 5.5.1.5).
The same is true in the robustness check of H3, summarized in Table 5.5.1.6. With
different estimators and model specifications, the coefficient on left wing government
under disproportional systems is consistently negative and statistically significant, just as
our theory predicts.
166 The normality assumption applies only to residuals and is important for hypothesis testing. Nevertheless, some researchers insist on the importance of normally distributed independent and dependent variables. I therefore run separate regressions using a transformed dependent variable that more closely approximates normality. The results between models using the original and transformed variables are virtually identical.
175
Table 5.5.1.5: Robustness checks for H
2 in regression models of square root coal tax with robust standard errors
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
pr
1.057*
1.057**
0.589
-1.654**
-1.981***
-1.749**
-1.701**
-1.711**
-1.877***
-1.585**
(0.570)
(0.472)
(0.456)
(0.572)
(0.573)
(0.763)
(0.632)
(0.668)
(0.561)
(0.519)
left_cab
0.0345**
0.00327
0.00861
0.00965
0.00631
0.00595
0.00304
0.00423
(0.0139)
(0.00802)
(0.0101)
(0.0109)
(0.0104)
(0.0167)
(0.0174)
(0.0128)
pr_leftc
0.0688***
0.0654***
0.0640***
0.0447***
0.0449***
0.0492***
0.0448***
(0.0129)
(0.0145)
(0.0159)
(0.0117)
(0.0140)
(0.0140)
(0.0127)
net_coal_xp
-0.00418
-0.00420
-0.00379
-0.00375
-0.00507
-0.00851*
(0.00285)
(0.00306)
(0.00305)
(0.00378)
(0.00423)
(0.00386)
openk
-0.00609
-0.00966
-0.00966
-0.00670
-0.00848
(0.0104)
(0.00657)
(0.00682)
(0.00497)
(0.00457)
corporatism
0.435**
0.441
0.391
0.190
(0.179)
(0.287)
(0.307)
(0.235)
avg_rgdpc
-0.00000199
-0.0000122
0.000000780
(0.0000556)
(0.0000548)
(0.0000447)
avg_debt
-0.00730
-0.0147*
(0.00753)
(0.00654)
itax_gdp
0.0958*
(0.0451)
_cons
0.350
0.350**
-0.520
0.268
0.173
0.365
-0.0548
-0.00540
0.611
-0.391
(0.446)
(0.163)
(0.481)
(0.246)
(0.127)
(0.372)
(0.314)
(1.435)
(1.596)
(1.491)
N
18
18
18
18
18
18
18
18
18
18
adj. R2
0.125
0.125
0.350
0.602
0.616
0.598
0.654
0.620
0.591
0.756
Standard errors in parentheses
* p < 0.1, ** p < 0.05, *** p < 0.01
176
Table 5.5.1.6: Robustness checks for H
3 in regression models of coal tax with robust standard errors
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
coal_tax
coal_tax
coal_tax
coal_tax
coal_tax
coal_tax
coal_tax
coal_tax
coal_tax
dis_gall
-0.0634
-0.0682
1.101
0.749*
0.533
0.782***
0.788***
0.787***
0.571
(0.0508)
(0.0522)
(0.742)
(0.355)
(0.304)
(0.120)
(0.131)
(0.143)
(0.382)
left_cab
0.0149
0.329**
0.346***
0.326***
0.290***
0.288***
0.288***
0.300**
(0.0137)
(0.0899)
(0.0661)
(0.0577)
(0.0294)
(0.0371)
(0.0409)
(0.110)
left_dis
-0.0355*
-0.0264**
-0.0253**
-0.0243***
-0.0243***
-0.0244***
-0.0213*
(0.0175)
(0.00873)
(0.00748)
(0.00305)
(0.00334)
(0.00373)
(0.0100)
net_coal_xp
-0.0140
-0.0120
-0.00921**
-0.00891
-0.00908
-0.0225
(0.0115)
(0.0101)
(0.00406)
(0.00501)
(0.00669)
(0.0191)
openk
-0.0532*
-0.0517***
-0.0516**
-0.0512**
-0.0509
(0.0287)
(0.0115)
(0.0125)
(0.0152)
(0.0406)
corporatism
1.674**
1.736**
1.720**
-0.249
(0.384)
(0.545)
(0.636)
(1.711)
avg_rgdpc
-0.0000150
-0.0000148
0.000269
(0.0000875)
(0.0000962)
(0.000256)
avg_debt
-0.000936
-0.0103
(0.0202)
(0.0558)
itax_gdp
0.163
(0.189)
_cons
1.019**
0.636
-7.970*
-9.096**
-3.905
-8.956***
-8.713**
-8.661**
-13.01
(0.397)
(0.645)
(3.854)
(2.934)
(2.830)
(1.210)
(2.344)
(2.850)
(7.705)
N
18
18
17
18
18
18
18
18
18
adj. R2
0.032
0.073
0.542
0.676
0.716
0.960
0.953
0.945
0.538
Standard errors in parentheses
* p < 0.1, ** p < 0.05, *** p < 0.001
177
As can be seen in Tables 5.5.1.5 and 5.5.1.6, the variables of theoretical importance for
H2 and H3 (i.e. pr_leftc and left_dis) retain their significance across all models. These
results are robust when an alternative measure of the size of the coal producing sector,
net_coal_xp (also a measure of coal dependence) is used. Interestingly, the adjusted R-
square measure decreases beginning at model 7 as might be expected when additional
variables are included without adding any explanatory power to the model.
In sum, the core finding – that a combination of proportional systems and left wing
governments produce higher fossil fuel taxes (H2) – is robust across the various model
specifications and operationalizations of the dependent presented here. Similarly, the
disproportional constraints hypothesis (H3) is further supported in the robustness checks,
at even higher levels of significance. Moreover, the results hold regardless of which
estimators are used, and in particular the findings are consistent even when using
alternative estimators specifically designed to deal with moderate levels of
heteroskedasticity, influential outliers and observations with greater leverage. These
findings increase confidence that the results are robust and insensitive to alternative
model specifications.
5.5.2: Heavy fuel oil As is the case with coal, the implicit carbon tax on heavy fuel oil (HFO) also tends to be
lower across OECD countries, in terms of the higher carbon content of this fuel (Chapter
4). Also commonly known as “residual” fuel oil, HFO refers to Number 5 and Number 6
fuel oils – the last of what remains of crude after gasoline and distillate fuel oils are
extracted. As the name implies, HFO is very dense, and is primarily burned in furnaces
and boilers for industrial processes and in the generation of heat power.167 Though tax
rates on heavy fuel oil are generally low, some rather large cross-national differences
167 This analysis examines tax rates on heavy fuel oil used by industry, exclusively. For reasons mentioned in Chapter 4, I do not analyze implicit carbon taxes on fossil fuels used for electricity generation.
178
exist across OECD countries. Figure 5.5.2.1 summarizes implicit carbon tax rates on
heavy fuel oil for industry in the 21 OECD countries for which data are available.168
Figure 5.5.2.1: Implicit carbon tax rate on heavy fuel oil used by industry
Source: IEA Energy Prices and Taxes (various volumes) Note: Country codes are based on ISO 3166 Figure 5.5.2.1 summarizes the effective industry tax rate on heavy fuel oil for 21 OECD
countries, in constant (2000) USD per tonne of CO2, averaged over the years 1978-
2006.169 For illustrative purposes, I include a vertical line at approximately $7 USD,
indicating the median tax. As can be seen, though several countries apply tax rates
equivalent to the median tax value of $7 USD per tonne of carbon dioxide, substantial
differences exist. In particular, Sweden, Norway and Greece apply very large taxes on
HFO, relative to all other countries in the sample. Portugal, Italy, the UK, Finland,
Austria and the Netherlands also apply tax rates substantially above the median. At the
168 I include all countries for which data are available here. 169 By the effective tax rate, I refer to the total tax incurred after rebates and exemptions (e.g. VAT) are accounted for.
179
other end of the spectrum, Australia, Japan the United States, Belgium, Switzerland,
Spain and Germany are somewhat below the median, while all other countries apply tax
rates that are relatively close to the $7 USD per tonne of CO2 median tax value.
To be sure, the reasons for these differences are not obvious. Countries at substantially
similar levels of economic development – e.g. the U.S. ($32,399 PPP mean income) and
Norway ($33,619 PPP mean income) lie at opposite ends of the HFO tax spectrum. In
addition, the largest oil producers (i.e. Norway, Canada, Great Britain, Australia,
Denmark, USA, New Zealand) tax HFO at widely different rates. Figure 5.5.2.2 arranges
countries in terms of net crude oil exports, a proxy for the size of the oil producing sector
(and import dependence), measured as the difference between exports of crude oil minus
imports, expressed as a percentage of total domestic crude oil consumption in a given
year.
Figure 5.5.2.2: Net crude oil exports in selected OECD countries
Source: IEA Energy Balances of OECD Countries (various volumes)
180
As can be seen in Figure 5.5.2.2, few rich OECD countries are net exporters of crude oil.
Large negative values indicate low crude oil production and increased dependence on
imports. Larger positive numbers indicate net exporters of crude. For instance, a value of
-100 indicates that 100% of the oil in a country is imported, while a value of + 50
indicates that a country exports 50% more oil than it consumes. As such, this measure
doubles as a proxy for both the size of the oil producing sector and its oil lobby, as well
as the dependence of a particular country on external sources of supply. In fact, this
measure is highly correlated with the measure of crude oil production also discussed later
in this analysis (r=-0.74) and the two can be used interchangeably as an indicator of the
size of the oil lobby.
Interestingly, the largest oil exporting countries in Figure 5.5.2.2 have substantially
different tax rates on HFO. For instance, Canada, Great Britain and Norway have
historically been among the rich OECD’s largest crude oil economies, yet they tax HFO
(and other oil products) at substantially different rates (Figure 5.5.2.1). Conversely, large
tax differentials exist among the most oil dependent countries. Contrary to the theory of
groups (Olson, 1965; Svendsen et al. 2001) countries with large oil producing sectors can
and do impose relatively large taxes on heavy fuel oil, while the absence of an oil
producing sector does not automatically translate into higher taxes on oil and its products.
Thus, differences in the implicit carbon tax rate on HFO cannot be explained with
reference to the availability of domestic resources and the interests of the oil-producing
sector alone.
Moreover, the simple bivariate relationship between HFO tax rates and levels of
corporatism also leaves much to be explained (Figure 5.5.2.3).
181
Figure 5.5.2.3: Implicit carbon tax on HFO by level of corporatism
As can be seen in Figure 5.5.2.3, the relationship between HFO taxes and corporatism is
weaker than the relationship between implicit carbon taxes on coal and level of
corporatism examined earlier. The correlation between the two variables is a modest
r=0.41. When regressed on coal, corporatism explains approximately 12 per cent of the
variation in tax rates on its own, leaving a substantial amount of the distribution in tax
rates unexplained.
Similarly, simple reference to the electoral system does not by itself explain differences
in implicit carbon tax rates on heavy fuel oil (Figure 5.5.2.4).
182
Figure 5.5.2.4: Implicit carbon tax rate on HFO by electoral regime (H1)
As can be seen from Figure 5.5.2.4, both the median and mean implicit carbon tax on
heavy fuel oil is greater among countries employing proportional electoral systems, while
implicit carbon tax rates are comparatively smaller in countries employing single member
plurality electoral formulae. However, a T-test (just barely) fails to confirm this
difference as significant.170 While less variance in the tax level under SMP suggests
carbon tax rates are more difficult to raise and change under majoritarian systems,
proportional representation does not by itself guarantee larger tax rates on heavy fuel oil
(or other fossil fuels). Indeed, the large variability in the box plot, and the cascading list
of countries in Figure 5.5.2.1, clearly show that some taxes are low, sometimes below the
median, even in countries with PR.
170 P value of 0.0609 in a test assuming equal variances (barely confirmed by robvar).
183
In order to more satisfactorily analyze and explain cross-national differences in implicit
tax rates on heavy fuel oil, and to empirically test key explanatory hypotheses, I include
21 OECD countries for which comparable data are available in a series of regression
models. Following the template established in 5.5.1, the models test the causal efficacy of
the same variables, including business lobbies (in this case, the oil producing sector), the
interests of trade exposed sectors, corporatist decision-making networks, the electoral
regime and its degree of proportionality, left party cabinet seats, and interactive variables
between left party and electoral regime/disproportionality. The summary statistics for
each variable are summarized in Table 5.5.2.1.
Table 5.5.2.1: Summary statistics for HFO tax regression models Variable Observations Mean Std. Dev. Minimum Maximum hfo_tax 21 12.69 15.28 0.47 66.79 crude_prod 21 0.048 0.130 0 0.599 net_oil_xp 21 -67.63 45.39 -100 42.79 openk 21 55.65 26.74 18.6 131.8 corporatism 21 2.55 1.41 1 5 left_cab 21 34.99 20.20 0 72.41 pr 21 0.67 0.48 0 1 dis_gall 21 6.08 4.77 1.02 16.3 left_dis 21 207.31 223.28 0 728.44 pr_leftc 21 26.59 23.97 0 72.41 Notes: Refer to data appendix for detailed variable definitions Following the same procedure that was used for analyzing tax rates on coal (5.5.1), each
independent variable summarized in Table 5.5.2.1 is sequentially included in separate
regression models, beginning with the interests of crude oil producers and consumers,
followed by corporatism, the percent of all cabinet portfolios held by parties from the left,
a dummy for proportional electoral systems, a measure of disproportionality, followed by
interactive terms between PR/disproportionality and left cabinet government portfolios.
The variable net_oil_xp is used later in the robustness checks. The results of each model
are summarized in Table 5.5.2.2.
184
Table 5.5.2.2: HFO tax regression models testing the ideological space hypothesis (H2) (1) (2) (3) (4) (5) (6) crude_prod 33.57 33.40 17.45 13.54 15.95 5.865 (25.76) (26.44) (26.58) (22.98) (23.96) (21.94) openk 0.0302 -0.116 -0.0628 -0.0897 0.00278 (0.129) (0.147) (0.129) (0.141) (0.134) corporatism 5.193* 2.902 2.386 1.906 (2.937) (2.681) (2.913) (2.617) left_cab 0.392** 0.366** 0.0370 (0.150) (0.161) (0.209) pr 4.321 -18.59 (8.194) (12.84) pr_leftc 0.647** (0.298) _cons 11.09*** 9.418 5.079 -5.575 -4.855 1.296 (3.501) (7.991) (7.946) (7.975) (8.274) (7.929) N 21 21 21 21 21 21 adj. R2 0.034 -0.017 0.091 0.323 0.291 0.432 Standard errors in parentheses * p < 0.1, ** p < 0.05, *** p < 0.01 The results of regression models 1 through 6 are summarized in Table 5.5.2.2. In each
model, the dependent variable is the implicit carbon tax rate on HFO, in constant (2000)
USD. As was the case with coal taxes, we find support for the hypothesis that PR
electoral systems condition the ability of left wing (social democratic) parties to
implement higher rates of energy taxation. Interestingly, we again find a few surprises.
As was the case with coal taxes, business interests provide a weak explanation for
variance in tax rates on HFO, while inclusion of political predictors produces increased
explanatory power. For instance, inclusion of left-wing party government substantially
increases the adjusted R-square moving from model 4 to 5, as does the inclusion of an
interaction between left-wing government and PR. However, the same model produces a
much better account of coal taxes (adjusted R2 of over 0.6) than of implicit rates of
185
carbon taxation on HFO (adjusted R2 of only 0.432). Although the framework as a whole
provides a markedly weaker account of variance in tax rates affecting the price of HFO,
the primary importance of the conditioning effect of electoral system appears to hold.
Moreover, a joint F test confirms the joint significance of all the independent variables
included in Model 6.
Looking at each independent variable on its own, we again find limited support for the
role of domestic interest groups. This is true regardless of whether crude oil production or
net crude oil exports is used as a proxy for the size of the fossil fuel lobby directly
affected by a tax on its product. Interestingly, crude oil production appears to be
positively associated with higher tax rates on HFO, though this variable fails to achieve
significance. In contrast, the coal production variable was consistently negative in the
coal tax regressions. Though never significant, the results do suggest that the coal lobby
is potentially a more effective or powerful constraint on the government’s ability to
impose taxes on its product. The fact that crude oil production consistently appears
positively (though insignificantly) associated with rates of implicit carbon taxation on
HFO is more consistent with a revenue-maximizing view of government than with a
general view of governments being responsive to fossil fuel producer interests.
Similarly, evidence of governments keeping taxes low to protect trade-exposed sectors of
the economy is also quite weak. This finding is consistent with the coal tax regressions.
Apart from the small sample size, one potential reason for this variable’s poor
performance is that the tax data do not fully account for exemptions granted to particular
industries. This shortcoming in the data might be corrected in future work with additional
research on tax exemptions for energy-intensive trade exposed industries.
As expected, the level of corporatism is positively associated with higher rates of HFO
taxation, and this relationship is significant at a level of p<0.1, though only when other
political variables are excluded from the model. When left wing party representation is
included, the coefficient on corporatism loses significance. Consistent with theoretical
expectations, the percentage of left cabinet portfolios is positively associated with
186
significantly higher tax rates, and this relationship disappears once we specify an
interaction between electoral system and left wing government, which is significantly
associated with higher rates of implicit carbon taxation on HFO, as expected. Holding all
other factors in the model constant, the combination of left wing parties in government
and PR electoral regimes leads to higher rates of implicit carbon taxation on heavy fuel
oil. Thus, it appears as though PR systems are associated with significantly higher taxes,
but only where left parties are represented in government. Controlling for business
opposition, exposure to international trade, and level of corporatism, a 5 per cent increase
in left party cabinet portfolios is significantly associated with an average increase in tax
on HFO of about $3.24 USD (i.e. 5 times 0.647) per tonne of carbon dioxide in
proportional systems. The inverse – where left parties are in government under plurality
systems, like Labour in the U.K. – appears to have no effect.
Of all independent variables included in model 6, the standardized beta coefficient for the
interaction pr_leftc is by far the best predictor of HFO tax rates in terms of both
significance and effect size.171 To better capture the nature of the interactive relationship,
Figure 5.5.2.5 plots the marginal effect of left wing party cabinet posts at different
theoretical levels of PR.
171 Note: beta coefficients are not reported in the regression tables.
187
Figure 5.5.2.5: The marginal effect of left party cabinet portfolios under PR (H2)
As can be seen in Figure 5.5.2.5, the same conditional relationship found in the analysis
of tax rates on steam coal is applies to HFO. From this, we see that the marginal impact
of left cabinet portfolios is positive and significant in PR regimes (i.e. where PR is equal
to 1), but that the marginal effect of left party cabinet positions on HFO taxation is not
significant in countries where members are elected based on a majoritarian formula (i.e.
where PR =0). This conditional relationship mirrors what was found in the analysis of tax
rates on steam coal for industry, and is exactly what might be expected from the
theoretical argument outlined in 5.1. By increasing the probability of left wing members
being elected, and by association, becoming members of government, PR systems
facilitate the implementation of higher tax rates on fossil fuels. The substantive impact of
this conditioning role of the electoral system on tax policy is further demonstrated in a
simple 2 by 2 table (Table 5.5.2.3).
188
Table 5.5.2.3: Implicit carbon taxes on HFO by left wing cabinet portfolios and PR
Majoritarian (smp)
Proportional representation (pr)
Left wing cabinet >40%
France ($7.34) New Zealand ($6.56) Australia ($0.47)
Sweden ($66.79) Norway ($35.57) Greece ($33.61) Finland ($11.43) Austria ($10.47)
Left wing cabinet <40%
Great Britain ($11.64) Canada ($6.92) United States ($2.73) Japan ($1.75)
Italy ($12.19) Netherlands ($9.17) Denmark ($8.03) Ireland ($6.64) Germany ($5.69) Switzerland ($5.48) Belgium($3.54)
The data in Table 5.5.2.3 fit with the theory, though one observation emerges as
potentially problematic. As we would expect, there appears to be no relationship between
left wing cabinet portfolios and tax rates under majoritarian systems. Indeed, countries
with lower left wing cabinet are just as likely to have relatively moderate rates of taxation
on HFO as those countries with higher levels of left wing government, under SMP. In
contrast, left wing government appears to have a greater effect under PR, consistent with
the theory. With the exception of Italy (which in fact does have a history of left wing
cabinet government), countries with both high levels of left wing cabinet posts and PR
electoral systems consistently tax HFO at higher rates, relative to countries with lower
levels of left wing cabinet government under PR. However, the Swedish tax rate on HFO
stands out as very large and may exert greater leverage in the regression analysis. This
hunch is examined further in a later section on regression diagnostics.
As a further test of the theory, and to ensure that the pr variable is in fact capturing the
effect of the electoral system and not some other difference, I substitute dis_gall for pr in
a separate series of regression models, as was done earlier in the analysis of taxation on
coal. Recall that dis_gall is Gallagher’s (1991) index of disproportionality, and that our
189
theory suggests left wing parties will be constrained in their ability to raise taxes in more
disproportional systems. If correct, the marginal effect of social democratic parties on tax
rates should decline as disproportionality in the electoral system increases. This
hypothesis is tested and empirical results are summarized in Table 5.5.2.4.
Table 5.5.2.4: HFO tax regression models testing the disproportional constraints hypothesis (H3) (1) (2) (3) (4) (5) (6) crude_prod 33.57 33.40 17.45 13.54 16.96 12.88 (25.76) (26.44) (26.58) (22.98) (24.79) (22.31) openk 0.0302 -0.116 -0.0628 -0.0640 -0.0484 (0.129) (0.147) (0.129) (0.132) (0.119) corporatism 5.193* 2.902 1.829 0.00988 (2.937) (2.681) (3.650) (3.379) left_cab 0.392** 0.407** 0.897*** (0.150) (0.157) (0.267) dis_gall -0.399 1.892 (0.893) (1.330) left_dis -0.0719** (0.0333) _cons 11.09*** 9.418 5.079 -5.575 -1.019 -13.26 (3.501) (7.991) (7.946) (7.975) (13.07) (13.02) N 21 21 21 21 21 21 adj. R2 0.034 -0.017 0.091 0.323 0.287 0.427 Standard errors in parentheses * p < 0.1, ** p < 0.05, *** p < 0.01 The general results found in the analysis of coal taxes is again replicated in this analysis
of implicit rates of carbon taxation on HFO. As can be seen in Table 5.5.2.4, the
disproportional constraints hypothesis is supported. Interestingly, the coefficient on crude
oil production is positive, indicating that oil producing countries tend to tax HFO at
higher rates, though this relationship is not significant. The sign on the coefficient for
190
trade exposure is consistent with expectations, yet it too fails to achieve significance
across all models. In contrast, the corporatism variable is consistently positive (as
expected) and significant in model 3, yet loses significance when other political
predictors are included. In particular, left wing cabinet posts are significantly associated
with higher tax rates on HFO. The sixth model tests the disproportional constraints
hypothesis, and findings are consistent with the theory. The interaction between social
democratic government portfolios and disproportional electoral systems is negative, as
expected. This relationship is depicted in Figure 5.5.2.6.
Figure 5.5.2.6: The marginal effect of left wing cabinet portfolios in disproportional systems (H3)
As can be seen, the impact of left wing cabinet portfolios on rates of implicit carbon
taxation for HFO is positive and significant at low levels of electoral disproportionality.
This impact decreases as electoral systems produce increasingly disproportional electoral
191
outcomes. At larger levels of disproportionality, the impact of left cabinet members on
HFO tax rates has no effect. Consistent with the disproportional constraints hypothesis
outlined in 5.2, Figure 5.5.2.6 clearly shows that left wing parties are increasingly
constrained in their ability to implement higher rates of carbon energy taxation as
disproportionality in the electoral system increases. Having substituted the pr dummy for
a variable that more adequately captures the key causal mechanism underlying the
importance of electoral systems for green taxes, we find additional support for an
important role for electoral systems in shaping energy tax policy outcomes, a finding
consistent with the earlier analysis of implicit rates of carbon taxation on steam coal used
by industry.
Robustness checks
As was done earlier, I run a series of robustness checks to build greater confidence in the
results. First, correlation matrices and graphs are examined to check for multicolinearity
in the independent variables (see data appendix). Visual inspection of this output failed to
identify any obvious collinearity issues, and this was confirmed by low VIF scores, none
of which exceeded worrisome values of 10. The two most correlated independent
variables in the models analyzed above are dis_gall and corporatism (r=0.67), which are
theoretically distinct concepts. When corporatism is removed from the model testing
disproportional constraints, the coefficients barely change, and the two significant
variables (left_cab and left_dis) become slightly more significant. In addition, the
adjusted R square increases to 0.46 from 0.42, as might be expected when an independent
variable with limited additional explanatory power is removed. None of this raises any
concern for the validity of the results.
Having ruled out multicolinearity as a problem, I proceed to check for heteroskedastic
errors. Visual examination of residuals reveals that they are quite normally distributed.
However, an rvfplot identifies Sweden as an outlier, and a Breusch-Pagan / Cook-
Weisberg test further confirms that there may be a mild problem of heterogeneously
distributed errors. Further tests (including leverage tests and a leverage versus residual
192
squared plot) suggest Sweden does not exert that much leverage.172 Nevertheless, I re-run
the models using robust estimates of the standard errors (Huber and Ronchetti, 2009), and
include additional control variables as was done in the robustness checks for coal. The
results are not substantively different across most models, as reported in Tables 5.5.2.5
and 5.5.2.6.
Unlike the case of the robustness checks on coal, the coefficient on the interaction terms
testing H2 and H3 lose significance in models 8 and 9 in Tables 5.5.2.5 and 5.5.2.6 when
debt and income tax variables are included. This might be expected given the reduced
degrees of freedom in models 8 and 9, which also lower the R-square. Given the
consistent significance across all other models, and the higher proportion of variance
explained in the restricted models, I conclude that the relationships found in the original
models are robust and significant.173
To summarize the results so far, the analysis of implicit carbon taxes on coal and heavy
fuel oil lend considerable support to both the ideological space (H2) and disproportional
constraints (H3) hypotheses. The distribution of tax rates on fuels used by industry – for
both coal and heavy fuel oil – differs systematically across the two primary electoral
systems used in the OECD. More precisely, the degree of disproportionality in electoral
systems appears to condition the ability of left wing parties to implement higher tax rates
on carbon based fuels used by industry. When disproportionality is low (i.e. in PR
regimes), left wing parties are associated with significantly higher tax rates on heavy fuel
oil. Conversely, when disproportionality increases, this effect disappears. Whether these
relationships can account for differences across other fossil fuels used by consumers is a
subject to which I now turn.
172 In fact, leverage tests indicate Norway and Canada are the most influential observations. 173 Finally, I rerun the model without Sweden in the sample. When this is done, all coefficients lose significance. However, a restricted model with all variables minus the interaction brings up a significant coefficient on pr. I conclude that PR retains a significant effect, regardless of Sweden. Moreover, given the small sample size and limited statistical evidence of Sweden’s influential status, I conclude that Sweden should remain in the analysis when testing the interactive hypothesis.
193
Table 5.5.2.5: Robustness checks for H
2 regression models with robust standard errors
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
hfo_tax
hfo_tax
hfo_tax
hfo_tax
hfo_tax
hfo_tax
hfo_tax
hfo_tax
hfo_tax
pr
11.02
4.696
-16.44*
-15.14
-17.76
-19.03
-24.84
-21.56
-22.00
(6.805)
(4.151)
(9.407)
(11.77)
(16.70)
(17.61)
(18.43)
(19.54)
(20.32)
left_cab
0.431**
0.0500
0.0479
0.0410
0.0328
-0.123
-0.0372
-0.0402
(0.204)
(0.0605)
(0.0588)
(0.0597)
(0.0716)
(0.136)
(0.172)
(0.177)
pr_leftc
0.670**
0.660*
0.691*
0.660*
0.781**
0.657
0.656
(0.281)
(0.312)
(0.360)
(0.327)
(0.345)
(0.397)
(0.423)
net_crude_xp
0.0222
0.0185
0.00668
0.0377
0.0503
0.0586
(0.0471)
(0.0525)
(0.0587)
(0.0538)
(0.0639)
(0.0799)
openk
0.0440
0.00193
-0.00943
-0.0626
-0.0590
(0.152)
(0.124)
(0.101)
(0.119)
(0.119)
corporatism
2.068
4.398
5.018
5.373
(3.343)
(4.134)
(4.339)
(4.949)
avg_rgdpc
-0.00107
-0.000820
-0.000864
(0.000659)
(0.000819)
(0.000850)
debt
0.119
0.122
(0.118)
(0.122)
itax_gdp
-0.150
(0.802)
_cons
5.349
-5.517
4.087**
5.077**
3.525
1.749
30.73*
18.86
21.72
(5.556)
(6.338)
(1.532)
(2.366)
(6.340)
(7.626)
(15.62)
(23.91)
(27.45)
N
21
21
21
21
21
21
21
21
21
adj. R2
0.075
0.340
0.500
0.473
0.443
0.429
0.450
0.437
0.388
Standard errors in parentheses
* p < 0.1, ** p < 0.05, *** p < 0.01
194
Table 5.5.2.6: Robustness checks for H
3 regression models with robust standard errors
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
hfo_tax
hfo_tax
hfo_tax
hfo_tax
hfo_tax
hfo_tax
hfo_tax
hfo_tax
hfo_tax
dis_gall
-0.705
-0.584
2.140*
2.133
2.052
2.131
2.086
2.062
2.043
(0.628)
(0.515)
(1.087)
(1.360)
(1.357)
(1.496)
(1.562)
(1.602)
(1.729)
left_cab
0.462**
0.932**
0.931**
0.938**
0.909**
0.879**
0.831*
0.836*
(0.193)
(0.331)
(0.368)
(0.375)
(0.369)
(0.391)
(0.384)
(0.410)
left_dis
-0.0752**
-0.0751*
-0.0759*
-0.0739*
-0.0729*
-0.0656
-0.0678
(0.0346)
(0.0395)
(0.0402)
(0.0384)
(0.0399)
(0.0399)
(0.0421)
net_crude_xp
0.000787
0.000451
-0.00504
0.00507
0.0298
0.0550
(0.0540)
(0.0560)
(0.0604)
(0.0622)
(0.0662)
(0.0855)
openk
-0.0462
-0.0590
-0.0680
-0.146
-0.140
(0.0874)
(0.0908)
(0.0869)
(0.117)
(0.115)
corporatism
0.835
1.375
3.061
3.442
(3.489)
(4.045)
(3.878)
(4.297)
avg_rgdpc
-0.000252
0.00000464
-0.0000945
(0.000598)
(0.000742)
(0.000758)
debt
0.205**
0.206**
(0.0901)
(0.0845)
itax_gdp
-0.361
(0.741)
_cons
16.99**
0.0919
-17.36
-17.26
-14.27
-15.95
-8.852
-23.72
-15.57
(6.666)
(4.176)
(10.33)
(14.81)
(15.15)
(18.43)
(21.75)
(30.24)
(37.39)
N
21
21
21
21
21
21
21
21
21
adj. R2
-0.002
0.355
0.509
0.478
0.450
0.414
0.373
0.440
0.404
Standard errors in parentheses
* p < 0.1, ** p < 0.05, *** p < 0.01
195
5.6. Implicit carbon taxes on fuels used by households
As demonstrated in the previous sections, implicit carbon taxes on the industrial use of
fossil fuels – steam coal and heavy fuel oil – vary systematically across countries
employing proportional and majoritarian electoral systems. In particular, the cross-
sectional data provide substantial evidence in support of the claim that electoral systems
condition the ability of left-wing party government to implement higher rates of energy
taxation. The following section extends this analysis by examining the role of electoral
regimes in shaping rates of implicit carbon taxation on other forms of energy most
commonly used by the non-commercial, household sector: motor fuels used in
transportation.
Due to the nature of data on motor fuels and the different interests at play, slightly
different models and tests are applied in this section. Indeed, the present analysis focuses
on tax rates imposed on a large group made up of diffuse and less well-organized
interests, i.e. consumers. As such, the corporatism variable drops out of the equation.174
In its place, I include additional controls for the plausible influence of central government
debt, population density, rural dwellers, election years, and the relative size of other types
of taxes that contribute to government revenue, namely, income taxes on personal and
corporate income.175 A larger number of observations of motor fuel tax rates allows for a
broader, more comprehensive empirical analysis including all of these variables.
It should also be noted that the transportation sector accounts for nearly half of total
world oil consumption (IEA, 2004: 84) and two thirds of GHG emissions (IPCC, 2007:
325). Taxes on motor fuels can thus be understood as being an important instrument for
mitigating emissions from the transport sector (Sterner, 2007) or decreasing dependence
on externally sourced crude oil (Becker, 2009). At the same time, motor fuel taxes are an
important source of government revenue. According to the OECD (2001: 55) roughly 90
174 Methodologically, the time-invariant nature of this variable makes it difficult to test using a panel data model structure (Plumper..). 175 These measures and the data sources are discussed in greater detail below as well as in the data reference appendix.
per cent of total revenues generated from “environmentally related” taxes are derived
from tax rates on motor fuels. Owing to a lack of substitutes, demand for motor fuels is
relatively inelastic, thus providing governments with a reliable source of revenue. At the
same time, taxes on motor fuels are systematically among the most disliked by
(Hsu et al. 2008). These factors add additional political dynamics to the energy tax
calculation, especially for governments facing growing levels of debt and emissions, and
who also face stiff electoral competition at the polls.
The tax data on motor fuels are collected from the IEA’s
quarterly publication, and cover the period 1978
complete, allowing for an analysis of a time
data analyzed here consist of 22 panels (rich OECD countries) over a time period of 29
years. Panel data taking this form
narrow panels, and are commonly analyzed by economists and political scientists
interested in explaining macro
allows for greater leverage and produces point estimates with less bias and more
efficiency, thanks to the asymptotic properties of a larger sample size. The models thus
include additional independent variables that were excluded from the earlier cross
sectional regressions, due to a lack of degrees of freedom. The cross
data also allow for the modeling of causal dynamics, which was not possible in the
previous coal and heavy fuel oil regressions.
For the empirical analysis using this TSCS panel data, I specify the general functional
form as:
where represents the general intercept,
represent the slope of each explanatory
The nature of this panel data structure
sectional units (i) over time (t)
per cent of total revenues generated from “environmentally related” taxes are derived
om tax rates on motor fuels. Owing to a lack of substitutes, demand for motor fuels is
relatively inelastic, thus providing governments with a reliable source of revenue. At the
same time, taxes on motor fuels are systematically among the most disliked by
(Hsu et al. 2008). These factors add additional political dynamics to the energy tax
calculation, especially for governments facing growing levels of debt and emissions, and
who also face stiff electoral competition at the polls.
motor fuels are collected from the IEA’s Energy Prices and Taxes
quarterly publication, and cover the period 1978-2006. This data is relatively more
complete, allowing for an analysis of a time-series cross-sectional (TSCS) data set. The
e consist of 22 panels (rich OECD countries) over a time period of 29
years. Panel data taking this form – where t exceeds n – are typically known as long and
narrow panels, and are commonly analyzed by economists and political scientists
laining macro-comparative trends. The larger number of observations
allows for greater leverage and produces point estimates with less bias and more
efficiency, thanks to the asymptotic properties of a larger sample size. The models thus
independent variables that were excluded from the earlier cross
sectional regressions, due to a lack of degrees of freedom. The cross-section time
data also allow for the modeling of causal dynamics, which was not possible in the
heavy fuel oil regressions.
For the empirical analysis using this TSCS panel data, I specify the general functional
represents the general intercept, X1 to Xn the explanatory variables,
represent the slope of each explanatory variable, and denotes the errors.
The nature of this panel data structure – combining repeated observations of cross
sectional units (i) over time (t) – enriches empirical analysis in ways not possible using
196
per cent of total revenues generated from “environmentally related” taxes are derived
om tax rates on motor fuels. Owing to a lack of substitutes, demand for motor fuels is
relatively inelastic, thus providing governments with a reliable source of revenue. At the
same time, taxes on motor fuels are systematically among the most disliked by consumers
(Hsu et al. 2008). These factors add additional political dynamics to the energy tax
calculation, especially for governments facing growing levels of debt and emissions, and
Energy Prices and Taxes
2006. This data is relatively more
sectional (TSCS) data set. The
e consist of 22 panels (rich OECD countries) over a time period of 29
are typically known as long and
narrow panels, and are commonly analyzed by economists and political scientists
comparative trends. The larger number of observations
allows for greater leverage and produces point estimates with less bias and more
efficiency, thanks to the asymptotic properties of a larger sample size. The models thus
independent variables that were excluded from the earlier cross-
section time-series
data also allow for the modeling of causal dynamics, which was not possible in the
For the empirical analysis using this TSCS panel data, I specify the general functional
the explanatory variables, to
combining repeated observations of cross-
enriches empirical analysis in ways not possible using
197
simple cross-section or time series data, producing several distinct advantages for
empirical research (Baltagi, 1995: 3-6). For instance, analysis of panel data allows
researchers to study the dynamics of change across units, and a fixed-effects model
allows researchers to control for unit-specific variables that are often difficult to measure
but of theoretical interest to empirical research (e.g. political culture). Despite these
advantages, however, many features of TSCS data (e.g. heterogeneous units, time series)
cause panel data regression models to depart from the statistical ideal of independent and
identically distributed (i.i.d.) error assumptions, a key requisite for Ordinary Least
Squares (OLS) regression techniques and the underlying mathematical properties that
justify statistical inference. Since panel data consist of repeated observations on the same
entity, unit heterogeneity becomes a distinct possibility, calling into question the i.i.d.
error assumption (Hamilton, 2006: 193).
In particular, panel data sets are often characterized by three features, which can violate
key assumptions in OLS. All three statistical problems relate to assumptions about panel
residuals, requiring more complex error specifications, and include groupwise
heteroskedasticity, contemporaneous correlation and serial correlation. After testing for
and decisively rejecting the null hypotheses of homoskedasticity and no serial-
correlation,176 I derive standard errors from Ordinary Least Squares (OLS) using
variance-covariance matrix panel corrected for contemporaneous correlation and cross-
sectionally heteroskedastic errors, and employ panel-corrected standard errors (PCSE) as
the primary estimator. As shown by Beck and Katz (1995), PCSEs provide more
consistent estimates when there is panel-specific heteroskedasticity, though they also tend
to increase the standard errors of estimates (and thus decrease their statistical
significance). Since the number of years (29) is larger than the number of panels (21), the
data structure is known as a “long narrow” panel, which further justifies the choice of
PCSE as the preferred estimator. In addition, the PCSE estimator is by now the most
widely used estimator for TSCS data in political science (Beck, 2001). 176 I used a modified Wald test for heteroskedasticity, and a Breusch-Pagan test for cross-sectional correlation. Both tests involved user-created commands in STATA by Chistopher Baum (xttest3 and xttest2). I also tested for serial correlation using the Wooldridge test (xtserial) described by Drukker (2003). All tests produced significant results, leading me to reject the null of no serial correlation and heterosckedasticity.
198
Recognizing the stickiness of tax rates over time, I also include a lagged dependent
variable (LDV). Although this approach does not completely “cure” the model from
serial correlation, I include the LDV for substantive reasons; namely, in an attempt to
control for the slow temporal dynamics of the processes I am attempting to model. As
Beck and Katz (2009) point out, this approach is also favourable to alternative ways of
modeling dynamics, on methodological grounds as well.177 Following the advice of Beck
and Katz (1995), I estimate the diesel and gasoline tax models using OLS with PCSE and
a lagged dependent variable (LDV). The LDV is included to control for serially
correlated errors over time. Correlograms indicate that imposing a first order Markov
process (AR1) on the model would be inappropriate given the dynamics in the DV, so I
include only the LDV, which as Beck and Katz suggest, should remove much of the
autocorrelation (as confirmed by low rho).
To be sure, some authors have challenged the “new orthodoxy” and suggest that
practitioners often use PCSEs without providing any evidence that they considered
alternatives or tested their suitability (Wilson and Butler, 2007).178 When panel data are
characterized by unit heterogeneity, as they are here, one of the alternatives suggested by
Kristensen and Wawro (2007) is to use OLS regression with cluster robust standard
errors and fixed effects (FEs), as proposed by Arellano’s update of White’s sandwich
estimates. They argue this approach is more suitable than PCSEs when unit effects are
particularly strong and when the number of time periods grows. As a robustness check
throughout my analysis, I estimate all models with this alternative estimator, which
produces standard errors that are robust to group-wise heteroskedasticity and
contemporaneous correlation. This method is used primarily as a robustness check, and
generally produces the same results, as demonstrated below.
177 Correlograms indicate that imposing a first order Markov process (AR1) on the model would be inappropriate for the dynamics in the DV. 178 Thanks to Rodney Haddow for assistance on thinking through the choice of estimator and on the overall methodological discussion presented here.
199
Finally, I estimate all models using unit fixed effects (FE).179 The fixed effects models
help control for unobserved differences across panels, which often exist across countries.
I thus control for slowly changing institutional differences, and such unobservable factors
as political culture, using unit fixed effects. The FE estimates make time-invariant
institutional variables (like federalism) redundant, and they are therefore excluded from
the analysis on such methodological grounds. In order to circumvent the problem of
including time-invariant variables with FE models (Bollen and Brand, 2008; Plumper and
Troeger, 2007), I include electoral system variables in interactive terms, which increase
over time variance and are thus permissible when using FE models, as shown by Trieman
(2009). Tests for unit roots are discussed in the Robustness section.
The hypotheses tested in this section are the same as those presented earlier, with an
additional hypothesis. At the risk of being repetitive, they are summarized here.
H1: The PR hypothesis: Relative to majoritarian electoral systems, countries with PR will impose higher implicit tax rates on carbon. H2: The ideological space hypothesis: Relative to majoritarian electoral systems, greater representation from parties of the left and greens will be positively associated with significantly greater implicit carbon tax rates on diesel and gasoline under PR. H3: The disproportional constraints hypothesis: Relative to proportional systems, greater representation from parties of the left and greens will not be associated with greater implicit carbon tax rates on diesel and gasoline under more disproportional systems, as these parties will be constrained in their ability to raise tax rates. H4: The electoral incentives hypothesis: Relative to more proportional systems, increasing support for new left and green parties will lead to an increase in rates of implicit carbon taxation on diesel and gasoline under more disproportional systems, as governments have greater incentive to respond to mounting electoral threats where the seat-vote elasticity is high. In order to test these primary working hypotheses, and build more confidence in the
results, I run a series of tests using time-series cross-sectional data. These statistical tools
allow me to test the primary hypotheses while also holding other potentially confounding
variables constant. Identical tests are repeated for both diesel and gasoline motor fuels.
179 A Hausman test confirms that a Random Effects model would be inappropriate due to systematic differences across panel units.
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The first hypothesis, H1, is tested with a simple ttest seeking to establish a statistically
significant difference in mean tax rates between countries employing PR and SMP
electoral regimes. Due to the slowly changing (time invariant) nature of this variable, it is
not tested using the TSCS data (Plumper and Troeger, 2007), but is included in
interactions, which are time variant and thus amenable to statistical analysis using TSCS
techniques (Bollen, 2009). Next, I build several models with the following variables to
test hypotheses H2 to H4. As done in the cross-sectional regressions, I include
crude_rgdp as a measure of the size of the domestic crude oil lobby. This variable is a
measure of total crude oil production in a country in a given year, divided by real gross
domestic product in 2005 international dollars at purchasing power parity.180 Consistent
with a public choice framework and the theory of interest group influence on policy, I
expect crude oil production to be inversely related to tax rates on motor fuels. Other
models substitute crude production with net crude exports, net_crude_xp, which captures
crude production levels and import dependency. Like crude production, I expect this
variable to be negatively correlated with tax rates. Next, I include openk as a measure of
exposure to international trade and the related competitive pressures to keep taxes low.
This variable, commonly used in the literature on tax policy to test for a “race to the
bottom,” is measured as the sum of imports and exports divided by GDP, in constant
national currency, and is taken from the Pen World Tables 6.3 (Heston et al. 2009).
Following the logic developed in the literature, I expect this variable to be inversely
related to tax rates on fossil fuels. The variable pr is a dummy variable for countries
employing electoral systems that can be categorized as proportional representation.
Recognizing that in some cases both plurality and proportional methods of assigning
legislative seats are used (e.g. Australia, Germany, Japan), countries are coded either PR
or majoritarian (SMP) according to the way in which the majority of seats are allocated in
the lower legislature. This measure is thus able to distinguish between electoral systems
that make use of both plurality (SMP) and proportional formulae, and is adapted from the
housesys variable in the Database of Political Institutions (Keefer, 2007).
180 Data on crude oil production is from the EIA, and real gross domestic product data is taken from Heston et al. 2009. See variable definitions for more information.
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Testing the disproportionality hypotheses H3 to H4 involves including Gallagher’s
(1991) index of disproportionality, a measure of the difference between a party’s share of
the popular vote and their share of total seats.181 The variable, labeled dis_gall, is
measured at an interval/ratio level and can be conceptualized as reflecting not just the
degree of disproportionality in a particular electoral system, but also the seat-vote
elasticity, which is often discussed but rarely examined in empirical tests (e.g. Steinmo
and Tolbert, 1998; Rogowski and Kayser, 2002). Given the greater disproportionality
between seats and votes generated by more disproportional electoral systems, all parties
in power will be constrained in their ability to raise taxes (since it increases the chances
of electoral defeat if the population does not want taxes). At the same time, small changes
in public opinion – like increasing support for green parties – will provide an incentive
for vote-maximizing parties in power to adopt part of the green program. As a result, we
should expect to see a greater willingness to increase energy taxes when the share of
green votes increases under disproportional systems.
Testing all of the electoral system hypotheses H2 to H4 involves including three variables
measuring the strength of left and green parties. Gov_left measures the cabinet
composition of government by expressing the percentage of cabinet portfolios held by
social-democratic and other left parties as a percentage of total cabinet posts, weighted by
days in government.182 The variables llc and llv measure the size and strength of “new
left” parties (as defined by Kitschelt, 1994) in terms of percentage of total cabinet posts
(llc) and share of total votes (llv). To be sure, green parties are included in the llc and llv
measures. Unfortunately, I do not have a measure for just green parties in cabinet. But
the llc and llv variables provide a reasonably good proxy, and are used in other studies
testing the role of green parties (e.g. Neumeyer, 2003). The variable green_dum is a
dummy variable indicating the presence or absence of green parties in parliament. The
variables greens and greenv measures the share of seats and votes received by parties
labeled “green” respectively, and are provided by Armingeon et al. (2009) following the
classification recommended by Lane, McKay and Newton (1997). The party variables
181 See data reference for the precise mathematical definition of this variable. 182 Adapted from Armingeon et al. 2009. See data references.
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are combined with disproportionality and PR scores to form multiplicative interaction
terms to test the conditional hypotheses H2 to H4. These include prgreen
(pr*green_dum), prgreens (pr*greens) prleft (pr*gov_left); prllc (pr*llc); disgreen
(dis_gall*green_dum); disgreens (dis_gall*greens) disllc (diss_gall*llc); disllv
(dis_gall*llv); and disgreenv (dis_gall*greenv).
A number of other variables are also included to control for the plausible influence of
several factors. First, all models include ln_rgdppc to control for potential income effects
and suggested by the literature on the Environmental Kuznet’s curve (Grossman and
Krueger, 1995; Raymond, 2004).183 I also control for a potential source of opposition to
motor fuel taxes coming from countries with a larger percentage of the population living
in rural areas with the variable rural_pop. Rural dwellers might oppose higher taxes on
gasoline and diesel because they are more likely to depend on fossil fuels to travel greater
distances by personal transportation and for machinery operated in rural areas (e.g.
generators, tractors, etc.). The same is true for less urbanized and less densely populated
countries where public transportation is less likely an option for personal travel, so I
include a control for population density, pop_den. To control for the possibility that
governments lower tax rates in an election year (as argued in the electoral cycle
literature), I include a dummy variable, electy, which is coded as 1 during years in which
an election is held.184 Finally, I control for public debt, other forms of taxation and
inflation. Consistent with a revenue maximizing view of government, especially in light
of the inelastic demand for fossil fuels, I expect greater public debt, debt_gdp to be
associated with higher rates of taxation. In contrast, I expect taxes on personal income,
itax_gdp, to be inversely related to implicit tax rates on gasoline and diesel, since the
latter can be used as a partial substitute for income taxes as a means of raising
183 The environmental Kuznet’s curve suggests a non-linear relationship between mean incomes and environmental outcomes. At low levels of economic development the environment is assumed to be a relatively low priority. However, with economic growth, environmental health is believed to take on growing importance. 184 From Swank (2007). For the United States, both Congressional and Presidential election years are coded; for Fifth Republic France, both Presidential and National Assembly elections are coded. For all other nations, national elections to the lower chamber of the national legislature are coded 1.
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government revenue.185 A control for inflation, inf_cpi_all is included to absorb the
influence of rising prices over time, and I also control for temporal autocorrelation with a
lagged dependent variable, lag_tax.
Table 5.6.1 lists all variables and identifies their label and expected relationship with
implicit carbon taxes. Further details on all variables analyzed below can be found in the
data references appendix.
Table 5.6.1: Summary of variables and hypothesized relationships Variable Label Expected relationship crude_rgdp crude oil production – openk exposure to trade – pr proportional representation + dis_gall disproportionality index – gov_left soc.dem party cabinet posts + leftv share of votes for soc.dem parties + llc new left government cabinet + llv share of votes for new left + green_dum dummy for green party rep + greens share of seats for green parties greenv share of votes for green parties + prleft left government in pr + prgreens green party seats in pr + prllc new left government in pr + disgreens green party seats in disproportional system – disllc new left government in disproportional system – disllv new left votes in disproportional system + disgreenv green party votes in disproportional system + ln_gdppc log per capita income + ln_sqgdppc186 log per capita income squared – electy election year – rural_pop rural population (% total) – pop_den population density (persons per square km) + debt_gdp total central government debt (% GDP) + itax_gdp taxes on personal income (% GDP) – inf_cpi_all general inflation rate + lag_tax lag of tax rate (t-1) + Source: see data references appendix. In order to better test the role of electoral regimes in shaping energy tax policy on motor
fuels, and to control for other variables, I run a series of regressions in separate empirical
185 In addition, we might expect citizens in countries with higher income tax rates to more forcefully oppose additional tax increases on energy. 186 Note: log per capita income squared is removed from all models analyzed in this chapter due to issues of multicolinearity. I instead analyze only the unsquared version of the variable.
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models containing a battery of independent variables. Summary statistics for all variables
are summarized in Table 5.6.2.187 These variables are variously employed in different
empirical models where the dependent variables are the implicit carbon tax rate on non-
commercial use of diesel (5.6.1) and gasoline (5.6.2).
Table 5.6.2: Summary statistics for motor fuel tax regression models Variable Observations Mean Std. Dev Min Max diesel_tax_usd 557 153.62 77.36 6.31 383.40 diesl_tax_ppp 557 160.22 80.65 7.52 385.44 gas_tax_usd 420 254.28 114.75 21.98 467.42 gas_tax_ppp 420 238.26 104.45 21.98 437.32 crude_rgdp 594 0.46 0.14 0 0.97 crude_oil_xp 583 -70.61 42.52 -100 44.96 openk 638 63.44 46.94 11.90 296.60 pr 638 0.66 0.47 0 1 dis_gall 638 5.98 5.26 0.37 24.61 green_dum 638 0.33 0.47 0 1 greens 638 1.74 2.91 0 13.33 greenv 638 2.26 3.29 0 14.4 llc 609 0.74 3.63 0 28.5 llv 609 3.48 3.76 0 18.2 gov_left 638 35.20 38.50 0 100 leftv 609 38.07 14.12 0 62 prgreen 638 0.29 0.45 0 1 prgreens 638 1.62 2.88 0 13.33 prgreenv 638 1.87 3.18 0 14.4 disgreen 638 1.24 2.97 0 23.22 disgreens 638 10.32 25.39 0 229.88 disgreenv 638 4.97 8.84 0 38.93 prllc 609 0.66 3.59 0 28.5 prllv 609 2.83 3.54 0 15.9 disllc 609 3.20 14.99 0 119.68 disllv 609 15.27 34.88 0 330.88 prleft 638 26.62 35.22 0 100 disleft 638 195.23 362.18 0 1870 ln_rgdppc 638 10.09 0.30 9.22 11.22 electy 638 0.29 0.46 0 1 pop_den 638 129.56 121.23 1.86 482.47 rural_pop 638 26.36 11.55 2.68 58 debt_gdp 509 49.98 29.70 0.822 163.83 itax_gdp 638 13.84 5.10 2.86 31.18 inf_cpi_all 638 4.89 4.81 -0.89 28.88 Each independent variable summarized in table 5.6.2 is included in various regression
models summarized and described in separate sections on diesel and gasoline. In
particular, I present results of several models in three distinct tables for each fuel, for a
187 Table reports data file totals. Regression models do not necessarily use all observations.
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total of 6 primary tables. Each model is estimated with two different estimators – panel-
corrected standard errors and clustered (robust) standard errors.
The first table in each section examines H2, the “ideological space hypothesis” and looks
to find a positive and statistically significant relationship between green and left party
representation and tax rates under PR, holding other factors constant. This hypothesis is
tested in several models using prgreen (the effect of at least one green member in the
lower legislature under PR); prgreens (the incremental effect of increasing the proportion
of green seats in parliament under PR); prllc (the impact of green/new-left cabinet
portfolios in government under PR); and prleft (the incremental effect of left party
cabinet government under PR).
The second table examines H3, the “disproportional constraints” hypothesis and looks to
find a negative and statistically significant relationship between green and left party
representation in government/legislature and tax rates under disproportional systems,
holding constant other variables in the model. This hypothesis is tested in several models
using the interaction terms disgreen (the effect of at least one green member in the lower
legislature interacted with disproportionality); disgreens (the effect of increasing the
share of total legislative seats held by green parties interacted with disproportionality);
disllc (the effect of increasing the share of cabinet posts to green/new-left parties
interacted with disproportionality); and, disleft (the effect of increasing the share of
cabinet posts held by left-wing parties interacted with disproportionality).
The third table examines H4, the “electoral incentives” hypothesis and looks to find a
positive and statistically significant relationship between the share of votes for green and
green/new-left parties and tax rates under disproportional systems, controlling for other
determinants of energy tax rates. This hypothesis is tested in different models using the
interaction terms disgreenv (the effect of increasing the share of votes to the green party
interacted with disproportionality) and disllv (the effect of increasing the share of votes to
new-left/green parties interacted with disproportionality).
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5.6.1: Diesel In contrast to fossil fuels used for industrial purposes, implicit carbon tax rates on non-
commercial use of diesel fuel are relatively large (with the exception of the U.S., New
Zealand and Canada, where diesel is taxed at a rate roughly equal to the average implicit
carbon tax on heavy fuel oil in Sweden). Like the tax rates levied on industrial fuels,
however, large cross-country differences exist. Figure 5.6.1.1 arranges countries from
high to low in terms of the average implicit carbon tax rate levied on diesel fuel used for
non-commercial use (i.e. private transport). 188
Figure 5.6.1.1: Implicit carbon tax on diesel fuel for household consumer use
Source: IEA Energy Prices and Taxes (various volumes) As can be seen in Figure 5.6.1.1, large tax differentials exist, even among similarly
situated countries in the global political economy. For instance, the average implicit
carbon tax on diesel in oil producing Norway (average real per capita GDP $33,619) is
188 Note: Canada refers to industry tax. Households for all others.
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roughly four times as large as that in oil exporting Canada (average real per capita GDP
$26,577). Although equally dependent on crude oil imports, the implicit carbon tax on
diesel in Japan is roughly half that applied in Switzerland. Part of the reason for these
differences appears to be accounted for by differences in political institutions, like the
electoral system (Figure 5.6.1.2).
Figure 5.6.1.2: Implicit carbon tax rate on (non-commercial) diesel fuel by electoral regime (H1)
As is clear from Figure 5.6.1.2, countries with proportional representation tax diesel fuel
at a higher rate than do countries with majoritarian electoral systems. The box plot on the
left compares the distribution of implicit carbon tax rates on diesel across the two
categories of electoral regimes. Consistent with H1, it is clear from this box plot that the
median tax rate under PR tends to be higher (close to $200USD/tonne of CO2) than the
median tax rate under majoritarian single member plurality systems (about
$100USD/tonne of CO2). Similarly, the bar chart to the right provides further evidence of
an institutional effect. The bar chart depicts the mean difference in tax rates on diesel, in
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constant 2000 USD per tonne of carbon dioxide over the period 1978-2006, across two
categories of electoral systems. The mean under PR ($168USD/tCO2) is substantially
larger than the mean implicit carbon tax rate on diesel under majoritarian systems
($125USD/tCO2). Moreover, a ttest of unequal variances confirms this difference as
being statistically significant at a level of p<0.0005, with majoritarian countries applying
an tax rate averaging between $28 and $58 USD/tCO2 less than those applied on the same
fuel under PR, 95 times out of 100. We thus find some empirical support for the
hypothesis that PR systems should impose higher implicit carbon taxes than majoritarian
regimes (H1). The next three tables test hypotheses H2 to H4, controlling for the
plausible effects of other variables.
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Table 5.6.1.1: Diesel tax regression models testing the ideological space hypothesis (H2) Model 1 Model 2 Model 3 Model 4 PCSE Cluster PCSE Cluster PCSE Cluster PCSE Cluster lag_rtax 0.702*** 0.702*** 0.743*** 0.743*** 0.750*** 0.750*** 0.756*** 0.756*** (0.0603) (0.0294) (0.0606) (0.0352) (0.0569) (0.0401) (0.0607) (0.0385) crude_rgdp 35.46 35.46 67.06 67.06 78.44 78.44 80.60 80.60 (129.3) (85.88) (131.8) (115.9) (130.4) (134.1) (130.0) (128.3) openk -0.587* -0.587** -0.590* -0.590** -0.374 -0.374 -0.447 -0.447* (0.274) (0.201) (0.270) (0.198) (0.289) (0.268) (0.261) (0.181) log_rgdppc 27.82 27.82 37.86 37.86* 38.44 38.44 40.26 40.26* (20.65) (18.68) (21.17) (17.24) (21.67) (21.27) (21.82) (18.03) debt_gdp 0.307*** 0.307* 0.244** 0.244 0.355*** 0.355* 0.311** 0.311* (0.0924) (0.128) (0.0895) (0.118) (0.0946) (0.132) (0.0964) (0.123) electy 2.250 2.250 2.325 2.325 2.384 2.384 2.891 2.891 (2.159) (2.143) (2.160) (2.285) (2.128) (2.302) (2.203) (2.276) inf_cpi_all -0.748 -0.748 -0.753 -0.753 -0.484 -0.484 -0.563 -0.563 (0.604) (0.568) (0.584) (0.714) (0.566) (0.753) (0.599) (0.717) pr -19.91** -19.91* -2.355 -2.355 -0.621 -0.621 4.709 4.709 (7.283) (7.357) (7.733) (6.452) (7.453) (5.555) (8.569) (5.503) green_dum -5.752 -5.752 (5.393) (5.517) greenpr 32.99*** 32.99*** (7.700) (8.387) greens -0.545 -0.545 (0.923) (1.279) greenspr 3.020** 3.020 (1.142) (2.060) llc -5.632** -5.632*** (1.784) (0.805) llcpr 5.204** 5.204*** (1.710) (0.931) gov_left -0.0204 -0.0204 (0.0449) (0.105) leftpr 0.0171 0.0171 (0.0456) (0.126) _cons -234.9 -203.8 -341.5 -317.3 -358.0 -341.9 -373.2 -357.1 (210.1) (183.0) (214.6) (169.5) (219.2) (203.8) (222.2) (176.5) N 377 377 377 377 362 362 377 377 R2 0.918 0.753 0.914 0.741 0.915 0.739 0.912 0.734 Standard errors in parentheses; panel coefficients excluded * p < 0.05, ** p < 0.01, *** p < 0.001
The basic results in Table 5.6.1.1 support the ideological space hypothesis. Indeed,
excluding the left-wing PR interaction, five of six coefficients on green party and PR are
significant at least the 0.05 level. In each model, the dependent variable is the implicit tax
rate on diesel fuel for non-commercial (i.e. household) consumer use, in constant 2000
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USD per tonne of CO2. Using different measures of green party representation and
green/left party cabinet, the argument that PR systems open up ideological space for the
imposition of higher diesel tax rates generally holds. Interestingly, the coefficient on
crude oil production is consistently positive, though it is never significant. Consistent
with expectations, the coefficient on trade exposure is consistently negative and
significant across most models. The controls for election year and inflation appear to
have no impact, while the size of the central government’s debt is consistently associated
with significantly higher tax rates on diesel fuel, as expected. As indicated by the
adjusted R-square, the models estimated with PCSE’s consistently perform better in
terms of explained variance.
Models 1 & 2 examine the impact of PR when green parties are represented in the
legislature. Holding constant crude oil production, exposure to trade, income levels,
central government debt, election year, levels of inflation and controlling for a temporal
lag, the marginal impact of green party representation is positively and significantly
associated with higher implicit carbon tax rates on diesel fuel in PR regimes. This is true
whether green party representation is measured with a simple dummy indicating the
presence or absence of greens in the legislature (model 1) or when the percentage of total
legislative seats held by greens is used (model 2). In each case, PR systems appear to
open up political space for the implementation of green taxes, as expected. The one
caveat – the cluster robust estimates are significantly less forgiving in one instance, and
using this estimator produces insignificant results in model 2.
Similarly, PR systems appear to condition the ability of green/new-left parties to
implement higher taxes on diesel, once in government. Models 3 and 4 present the results
of regressions when using green/new-left parties in cabinet (model 3) and social
democratic party cabinet posts (model 4), respectively. Controlling for all other variables
in the model, green/new-left cabinet posts are associated with significantly higher tax
rates on diesel under PR regimes, as expected. This result is robust across both types of
estimators used (model 3). However, the coefficients on social democratic cabinet posts
and PR (leftpr) fail to achieve significance. In contrast to what was found in earlier
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regressions on industry fuels, the impact of social democratic parties on diesel tax for
private household use is less clear. Interestingly, when the same model is fit to the same
data, but for industrial use of diesel, the social democratic and PR interaction becomes
significant. It thus appears as though left parties are more effective in imposing tax rates
on industry than consumers. Returning to consumer taxes, it is clear that the impact of
green and new/left green parties on household diesel tax rates under PR is consistently
significant. This interactive relationship is illustrated in Figure 5.6.1.3, using greens in
parliament under PR as an example.
Figure 5.6.1.3: The marginal effect of green parties in the legislature under PR (H2)
Figure 5.6.1.3 graphically depicts the marginal effect of green party representation on
diesel tax rates by electoral regime. As can be seen, the presence of green parties in the
legislature has a large positive effect on diesel tax rates in proportional systems (where
PR =1). As expected, this impact is decreasing and becomes insignificant moving from
PR to plurality SMP systems (PR=0). Under plurality systems, the dominant parties, who
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rarely require green party support to implement their preferred policy programs, can
safely ignore the policy preferences of greens. In such systems, therefore, the impact of
green party representation is muted, as suggested in Figure 5.6.1.3.
Having found some evidence to support H2, the ideological space hypothesis, I now turn
to a different measure of proportionality that more adequately captures the effect of
electoral systems. Recall that the argument in 5.1 predicts that more disproportional
systems should constrain the ability of smaller parties – e.g. green/new-left parties – to
implement their policy programs. This is due to multiple factors. First, it is often
remarked that disproportional systems typically favour large parties that depend on and
target the electoral support of geographically concentrated interests at the expense of
policies targeting broader welfare (Rodden, 2007; Fredriksson and Millimet, 2004).
Moreover, disproportional systems typically produce majority governments, thereby
reducing the electoral threat of smaller parties, as well as their importance as coalitional
partners (Steinmo and Tolbert, 1998). Finally, in light of its impact on the governing
regime, disproportional systems generate clearer lines of accountability between voters
and governments, making it easier for voters to “punish” governments who raise taxes
(Persson and Tabellini, 2008). For all of these reasons, we should expect the marginal
effect of green/new-left parties on tax rats to decline under more disproportional systems
(H3). The empirical validity of this hypothesis is examined in the models summarized in
Table 5.6.1.2.
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Table 5.6.1.2: Diesel tax regression models testing the disproportional constraints hypothesis (H3) Model 5 Model 6 Model 7 PCSE Cluster PCSE Cluster PCSE Cluster lag_rtax 0.696*** 0.696*** 0.721*** 0.721*** 0.721*** 0.721*** (0.0577) (0.0321) (0.0564) (0.0353) (0.0569) (0.0412) net_oil_xp 0.0320 0.0320 0.0439 0.0439 0.0982 0.0982 (0.0485) (0.0465) (0.0433) (0.0382) (0.0506) (0.0533) openk -0.546* -0.546* -0.650** -0.650** -0.605* -0.605* (0.238) (0.225) (0.244) (0.217) (0.274) (0.232) log_rgdppc 44.47* 44.47* 59.30** 59.30** 62.70** 62.70** (20.72) (21.01) (20.71) (19.03) (22.11) (20.39) debt_gdp 0.282** 0.282 0.220* 0.220 0.328** 0.328 (0.0995) (0.175) (0.0917) (0.163) (0.101) (0.180) itax_gdp -2.235* -2.235* -2.103* -2.103 -1.987* -1.987 (1.060) (1.027) (0.969) (1.075) (0.962) (1.106) electy 1.794 1.794 1.777 1.777 2.206 2.206 (2.308) (1.900) (2.225) (1.983) (2.326) (2.002) inf_cpi_all -0.844 -0.844 -0.749 -0.749 -0.595 -0.595 (0.765) (0.707) (0.704) (0.825) (0.693) (0.843) yr_dis_gall 0.423 0.423 0.811 0.811 -0.320 -0.320 (0.464) (0.663) (0.420) (0.763) (0.361) (0.895) green_dum 20.27*** 20.27** (6.114) (5.744) greendis -1.473* -1.473 (0.734) (0.839) greens 3.596*** 3.596* (0.752) (1.358) greensdis -0.926*** -0.926** (0.236) (0.297) llc 0.497 0.497 (0.372) (0.380) llcdis -0.203 -0.203** (0.105) (0.0637) _cons -373.2 -349.3 -530.8* -491.6* -559.6* -527.6* (217.8) (196.5) (212.7) (179.0) (224.4) (190.2) N 336 336 336 336 321 321 R2 0.891 0.768 0.890 0.766 0.888 0.760 Standard errors in parentheses; panel coefficients excluded * p < 0.05, ** p < 0.01, *** p < 0.001
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The results in Table 5.6.1.2 provide additional evidence of the conditioning effect of PR
electoral regimes for the relationship between small green parties and implicit carbon tax
policy outcomes. In all, four of six coefficients on the interaction terms are significant at
a level of 0.05, and all are significant at a level of 0.1. Again the dependent variable is the
implicit tax rate on diesel fuel for non-commercial private use, in constant 2000 USD per
tonne of CO2. I substitute net crude exports for crude oil production to see if results on
this variable change, and add an additional independent variable to measure the plausible
impact of other taxes – notably taxes on personal income and capital gains – on implicit
carbon tax rates for diesel. As can be seen, the evidence of a significant mediating role
for electoral institutions is fairly robust.
Substituting net crude oil exports for crude oil production changes little across all models.
As was the case with crude oil production, net oil exports is consistently positive, but
never significant. The coefficient for trade exposure continues to be moderately
significant and negative across all models, as expected. In models 5 to 7, average per
capita income also emerges as significant. Holding other variables in the model constant,
richer countries tax diesel at relatively higher rates. Central government debt is also
significant in models estimated using the PCSE estimator. On average and holding other
variables constant, larger debt results in higher diesel taxes. Conversely, as shown by the
income tax variable, countries with relatively higher taxes on personal income and capital
gains tend to tax diesel at a lower rate. This finding provides evidence that governments
balance revenue requirements with different mixes of income and consumption taxes. It
also suggests that individuals already paying relatively high income taxes will more
strongly oppose additional taxes on consumption. Finally, the variables measuring the
impact of an election year and inflation are not significant across all models tested in
Table 5.6.1.2.
Turning to the disproportional constraints hypothesis (H3), it is clear that the general
results are consistent with expectations of a conditioning role for electoral regimes.
Regardless of which measure is used – greens in parliament, share of total parliamentary
seats held by green party members, and share of cabinet posts held by green/new-left
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parties – more disproportional systems appear to constrain the ability of smaller, pro
environmental tax parties to impose higher tax rates on non-commercial use of diesel
fuel, as expected. Conversely, green party representation in parliament in proportional
systems (i.e. when disproportional is at 0) is associated with significantly larger tax rates
on diesel fuel (models 5 and 6). There are, however, two exceptions. First, when using
the Clustered estimate of standard errors in model 5, greendis is not significant at a level
of p<0.05. It is however, significant at a level of p<0.1. The same is true for the second
exception in model 7, llcdis, which is not significant at the conventional p<0.5, but is
significant at p<0.1. Figure 5.6.1.4 illustrates this reductive effect of disproportionality in
the electoral system.
Figure 5.6.1.4: Marginal effect of green seat share in disproportional systems (H3)
As can be seen from Figure 5.6.1.4, the marginal impact of increasing the share of green
seats in the legislature on implicit carbon tax rates for household use of diesel decreases
as disproportionality in the electoral system increases. Controlling for net oil exports,
216
exposure to trade, per capita income level, central government debt, other sources of tax
revenue, elections, inflation and the prior year’s tax rate, the impact of additional green
seats in parliament decreases with increasing disproportionality in the electoral system.
At high levels of proportionality (i.e. low levels of disproportionality), the marginal
impact of greens in parliament on tax rates is, as expected, positively associated with
significantly higher tax rates. However, at higher levels of disproportionality, this
positive impact disappears, and actually becomes negative at higher levels of
disproportionality. As indicated in Table 5.6.1.2, the same is true for green/new-left
parties in cabinet (as measured by llc), and is consistent with the theory that in
disproportional systems, green parties are constrained – as are all other parties – in
raising tax rates, especially those that are highly visible among voters.
Because they inflate the share of seats won by particular parties (relative to their share of
votes), disproportional systems tend to favour large governing majorities, or coalitions
made up of a relatively small number of coalitional partners (Steinmo and Tolbert, 1998).
In the context of dominant party government, the lines of accountability between the
government in power and policy outcomes are clearer, and voters know whom to punish
for unpopular policies, like an increase in consumption taxes.189 But just as
disproportionality makes governments more accountable – thereby constraining their
ability to make unpopular policies, the hypotheses in 5.2 suggest they also make
governments and political parties competing for power more responsive. Indeed, in
disproportional systems, small changes in the vote share can have relatively large impacts
in a party’s seat share, given the higher seat-vote elasticity inherent in disproportional
systems (c.f. Rogowski and Kayser, 2002). In contrast, governments and parties in more
proportional systems are relatively insulated from the vagaries of public opinion, since a
small change at the polls will have less of an electoral impact on their proportionally
allocated seats. It follows that while green/left parties might be more constrained to raise
taxes while in government and in the legislature, the government of the day – of
whichever political stripe – will have a greater incentive to respond to public opinion in
189 In contrast, it is more difficult for voters to identify and punish parties responsible for increasing taxes in highly proportional systems favouring coalition governments, where multiple parties can share the blame.
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disproportional systems, relative to those in proportional regimes. Vote-maximizing
parties in disproportional systems are more vulnerable vis a vis changes in public
opinion, and for this reason, policy in such systems should be more responsive to
changing popular sentiment.
This final speculation, the electoral incentive hypothesis (H4), is examined in Table
5.6.1.3. Model 8 examines the impact of increasing the share of the popular vote for
green parties (greenv) under conditions of increasingly disproportional elections
(greenvdis). Model 9 fits an identical model using an alternative measure of the green
vote (llv) under conditions of increasing disproportionality in the electoral system (llvdis).
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Table 5.6.1.3: Diesel tax regression models testing the electoral incentives hypothesis (H4) Model 8 Model 9 PCSE Cluster PCSE Cluster lag_ppp 0.937*** 0.820*** 0.823*** 0.823*** (0.0138) (0.0297) (0.0170) (0.0327) crude_rgdp 3.284 68.93 66.05 66.05 (12.58) (62.21) (116.5) (51.47) openk 0.0126 -0.00829 0.184* 0.184 (0.0183) (0.169) (0.0929) (0.208) log_rgdppc -9.938* 3.772 2.840 2.840 (3.927) (11.30) (9.001) (10.68) debt_gdp 0.00882 0.335* 0.382*** 0.382* (0.0134) (0.132) (0.0481) (0.140) itax_gdp -0.111 -0.726 -0.858 -0.858 (0.109) (0.559) (0.479) (0.624) rural_pop -0.0107 1.722 2.042*** 2.042 (0.0559) (1.403) (0.298) (1.409) electy -0.308 0.314 0.560 0.560 (1.106) (1.184) (1.090) (1.206) inf_cpi_all 0.362 0.374 0.526* 0.526 (0.202) (0.913) (0.263) (0.894) yr_dis_gall -0.198 -0.998 -2.469*** -2.469 (0.187) (0.741) (0.403) (1.370) greenv 0.412* 1.157 (0.201) (0.857) greenvdis 0.0490 0.000757 (0.0273) (0.0607) llv -0.584 -0.584 (0.433) (0.845) llvdis 0.126*** 0.126 (0.0280) (0.0825) _cons 110.7** -62.62 -14.63 -65.24 (40.53) (127.3) (93.14) (122.8) N 382 382 367 367 R2 0.941 0.821 0.950 0.821 Standard errors in parentheses * p < 0.05, ** p < 0.01, *** p < 0.001 The fourth and final hypothesis concerning the conditioning effect of electoral
institutions is tested and summarized in Table 5.6.1.3. Though somewhat weaker, two of
four models provide some empirical support. The model specifications are similar to
those already examined except for two major differences. First, in order to test the
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sensitivity of results to alternative specifications, the dependent variable is measured in
2005 international dollars at purchasing power parities (PPP). Second, the interaction
terms examine the effect on tax levels of increasing the share of votes to green/new-left
parties under electoral systems with increasingly disproportional outcomes. Although
results are somewhat mixed, they do suggest, consistent with our hypothesis,
governments in more disproportional systems are relatively more responsive to a rise in
votes for green and new left/green parties than in less proportional systems. To be sure,
few of the variables are significant across all models. Those that obtain significance –
openness, per capita income, and debt – have been among the best performing variables
so far.
Similarly, the interaction between the share of votes for green/new-left parties and
disproportional systems also achieves significance in one of the models (Model 9). In this
model, estimated with PCSEs, greater disproportionality when green votes are at 0 is
associated with significantly smaller tax rates on diesel, as our theory predicts. Moreover,
as expected, the same model predicts an increase the vote share accruing to green/new-
left parties will result in greater tax rates in disproportional systems. Though the
alternative estimator does not result in as significant results, the interaction between
green votes and disproportional systems (greenvdis) is significant at a level of p<0.1
when PCSEs are used. Thus, using PCSEs, we find empirical support for the argument
that parties competing for power in disproportional systems are more likely to increase
tax rates on motor fuels as the share of green votes rises. This relationship, illustrated in
Figure 5.6.1.5 is worth examining in future work.
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Figure 5.6.1.5: Marginal effect of green/new-left votes in disproportional systems (H4)
Consistent with expectations, Figure 5.6.1.5 illustrates that the marginal increase in the
share of total votes for green/new-left parties is associated with significantly higher tax
rates on diesel in more disproportional systems. In other words, as the seat-vote elasticity
increases, governments are more responsive to an increase in votes for green parties. As
can be seen, this relationship only emerges when the level of disproportionality exceeds a
value of 10. As governments become more vulnerable to small changes in popular
sentiment, they have more of an incentive to adopt elements of the policy program of
increasingly popular parties. This relationship is entirely consistent with our theoretical
argument developed in Chapter 1 and the perspective of vote-maximizing parties under
conditions of increased electoral vulnerability.
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5.6.2: Gasoline The foregoing analysis of diesel tax rates provides additional evidence of the
conditioning role of electoral institutions on the capacity of green/new-left parties to
impose higher rates of taxation on carbon-based fuels, and on the incentives for other
parties to do so. This section adopts the same methodology in order to assess the extent to
which similar patterns can be found in the distribution of tax rates on a different type of
commonly used motor fuel, gasoline. Together with diesel taxes, proceeds from gasoline
taxes constitute an important source of government revenue, making up a over 90 per
cent of revenues derived from “environmentally related” taxes, which contribute
substantial revenues for OECD governments (OECD, 2007).190 At the same time, tax
rates on gasoline are among the most unpopular forms of revenue generation (Hsu et al.
2004), creating a tradeoff for governments interested in raising revenue while also
remaining in power.
As was the case with diesel tax rates, implicit rates of carbon taxation on gasoline fuel are
relatively large across OECD countries, especially when compared to explicitly labeled
carbon taxes or with implicit carbon taxes levied on other fuels. However, substantial
cross-national differences exist. Figure 5.6.2.1 arranges countries from high to low in
terms of average implicit carbon tax rates applied to gasoline. The data cover 22 of the
richest countries – on a per capita GDP basis – in the OECD.191
190 Across the OECD, revenues from environmentally related taxes are in the order of 2 – 3% of GDP. Their contribution to total tax revenues varies widely by country, however. For instance, revenues from environmentally related taxes in Denmark accounted for over 10 per cent of total tax revenues in 2003, while environmental tax revenues accounted for less than 3.5 per cent of total tax revenues in the U.S. for that same year (OECD, 2007). 191 Since fuel grades bought and sold vary across countries, tax rates on the most commonly reported fuel grade are described and analyzed in this dissertation. From a climate perspective, this mixing of fuel grades is not problematic, as all fuel grades are roughly equal in carbon content. The data refer to regular unleaded 91 RON (Research Octane Number) for Australia, Austria, Canada, Denmark, Japan, Korea, Mexico, New Zealand, and the USA; mid-grade unleaded 95 RON for all others.
222
Figure 5.6.2.1: Implicit carbon tax rate on gasoline for private household use
Source: IEA Energy Prices and Taxes (various volumes) The data in Figure 5.6.2.1 summarize the average implicit tax rate on gasoline for private
household use for 22 of the richest OECD countries, in constant (2000) USD per tonne of
CO2 averaged over the years 1978-2006. Tax rates on gasoline are comparatively higher
than tax rates on diesel, and on average, gasoline is the highest taxed fossil fuel in the
OECD, on a per tonne of carbon dioxide basis. At the same time, substantial cross-
national differences exist. For instance, oil-exporting countries Canada and Norway again
lie at opposite ends of the implicit carbon tax spectrum, while substantial differences
exist among geographically proximate countries in Europe. For instance, over the period
1978-2006, the average implicit carbon tax rate applied to gasoline in Spain and
Switzerland is substantially lower than those applied in neighboring countries.
At first glance, visual inspection of the data casts some doubt on the proportional systems
hypothesis (H1), as Great Britain and France stand out as a clear cases with high implicit
223
carbon taxes in the absence of PR. Notwithstanding these deviant cases, which are in part
the result of idiosyncratic factors that do not refute the primary hypotheses,192 a ttest
confirms the pattern of a significant difference (p<0.0005) in the distribution of tax rates
across PR and SMP regimes. As anticipated, implicit carbon tax rates are significantly
higher in countries where PR is the primary system for allocating legislative seats. In fact,
we can expect tax rates on gasoline in majoritarian systems to be, on average, between
$111 to $154 USD per tonne of CO2 lower than those applied in proportional systems, 95
times out of 20. This significant difference is illustrated in Figure 5.6.2.2.
Figure 5.6.2.2: Implicit carbon tax rate on gasoline by electoral regime (H1)
Figure 5.6.2.2 displays the distribution of implicit carbon tax rates on gasoline across the
two primary categories of electoral regime used in rich democratic OECD countries. As
can be seen, tax rates on gasoline used in transportation tend to be higher in PR relative to
192 These factors are discussed in section 5.7.
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majoritarian systems. For instance, the median tax rate under PR is nearly three times as
high as the median tax rate under majoritarian systems. Similarly, the difference in mean
tax rate between the two systems is a non-trivial $133 USD per tonne of CO2. These
differences are consistent with the hypothesized effect of electoral regimes (H1). In order
to better test hypotheses H2 to H4, and to control for the plausible effects of other
variables, the data are more closely examined in a series of regression models, just as was
done earlier in the case of diesel fuels. Table 5.6.2.1 begins by summarizing results of
models testing the ideological space hypothesis (H2). Like the earlier panel regressions,
models estimated with PCSEs tend to have substantially higher adjusted R-squares.
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Table 5.6.2.1: Gasoline tax regression models testing the ideological space hypothesis (H2) Model 1 Model 2 Model 3 PCSE Cluster PCSE Cluster PCSE Cluster lag_tax 0.986*** 0.801*** 0.991*** 0.804*** 1.009*** 0.806*** (0.0391) (0.0264) (0.0367) (0.0269) (0.0368) (0.0301) crude_rgdp 5.344 28.13* 4.505 26.45 -3.092 26.60 (10.26) (12.91) (9.661) (12.86) (8.944) (14.53) openk 0.000651 0.138 0.00809 0.0731 0.0662 0.239 (0.0371) (0.266) (0.0377) (0.271) (0.0571) (0.334) log_rgdppc 3.511 43.18* 2.201 43.86* 6.012 36.52 (12.83) (16.04) (13.61) (16.48) (12.95) (18.30) debt_gdp -0.0371 0.0847 -0.0507 0.0775 -0.0807* 0.127 (0.0427) (0.0641) (0.0355) (0.0624) (0.0353) (0.0898) electy 2.643 2.734 2.757 2.613 1.915 1.084 (3.086) (3.841) (3.094) (3.795) (3.043) (3.826) inf_cpi_all -0.154 1.145 -0.178 1.004 -0.0537 0.978 (0.953) (0.917) (0.939) (0.906) (0.909) (0.917) pr 5.667 -15.51 4.041 -21.68* 0.608 -32.17*** (5.154) (7.952) (4.200) (7.783) (5.165) (4.308) greenv 0.715 -0.0935 (0.868) (0.817) greenvpr -0.362 -2.264 (0.882) (2.567) greens -0.134 -1.448 (1.136) (2.522) greenspr 0.466 0.432 (1.344) (3.469) llc -4.643 -9.671*** (2.408) (1.632) llcpr 4.334* 8.867*** (2.147) (1.786) _cons -28.11 -392.0* -14.05 -394.0* -54.42 -324.5 (130.9) (151.3) (139.2) (154.7) (132.7) (170.5) N 348 348 348 348 333 333 R2 0.934 0.699 0.934 0.697 0.937 0.718 Standard errors in parentheses * p < 0.05, ** p < 0.01, *** p < 0.001
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Models 1 to 3 in Table 5.6.2.1 test the hypothesis that PR systems create ideological
space for green and green/new-left parties to impose higher rates of implicit carbon
taxation on gasoline, while controlling and testing other factors. The basic results suggest
that while green legislative seats and votes do little to affect gasoline tax rates in
proportional systems, green cabinet government does play a role. At the same time, the
general findings are less conclusive than those for the previous fossil fuels – coal, heavy
fuel oil and diesel. For instance, of all the independent variables examined in model 1,
few of the variables of theoretical interest are significant. Even variables that consistently
performed well – like the inverse relationship between carbon tax rates and trade
exposure – fail to conform to expectations in the gasoline tax regressions presented in
Table 5.6.2.1. The only exceptions are crude oil production and per capita income, which
are moderately significant when the cluster robust estimator is used. However, there is no
evidence to support the claim that increasing the vote for green parties under proportional
systems will lead to an increase in tax rates on gasoline, regardless of which estimator is
used.
The same is true for the second model (2). As expected, per capita income is significantly
associated with higher tax rates on gasoline, but this is only the case using the cluster
robust estimates of standard errors. The only other variable to attain significance (besides
the temporal lag) is PR. Here, PR is significantly associated with lower tax rates on
gasoline when the share of green seats is 0. This is consistent with the theory that the
effect of PR regimes on implicit rates of carbon taxation is conditioned by the presence of
green/left parties. When PR is included by itself (without the interaction in a model not
shown), its effect is positive and significant, as expected. However, the non-significance
of greenspr is not consistent with theoretical expectations. As is the case with green party
votes, increasing the share of green party seats in the legislature appears to have no effect
on gasoline tax rates under PR systems.
In all, model 3 is most consistent with expectations. Using both estimators, the coefficient
on the share of green/new-left party cabinet posts is associated with significantly higher
taxes under PR systems, consistent with the ideological space hypothesis. This might be
227
expected, given the fact that green/new left cabinet portfolios is the best measure used
here that captures green party participation in government.193 Holding constant crude oil
production, exposure to trade, per capita income levels, debt, election year, and
controlling for the inflation rate and autocorrelation, the interaction between green/new-
left parties in cabinet and systems of proportional representation is associated with
significantly higher tax rates on gasoline, as expected. This is true using both estimates
for standard errors in the presence of heteroskedasticity and contemporaneously
correlated errors across panels. The marginal effect of green party members in cabinet in
plurality and proportional systems is visually depicted in Figure 5.6.2.3.
Figure 5.6.2.3: The marginal effect of green/new left party cabinet portfolios by electoral regime (H2)
Figure 5.6.2.3 depicts the marginal effect of increasing green and new left party
representation in government, under plurality and proportional electoral systems. As can 193 To be sure, the llc is a measure of greens and other “new left” parties in government as coded by Swank, who does not have a separate measure for green party only.
228
be seen, moving from simple plurality (PR=0) to a proportional electoral system (PR=1)
results in a significant increase in the marginal impact of green/left cabinet posts on
gasoline taxes (about $8 USD per tonne of carbon dioxide), when holding other variables
in Model 3 at their mean. This result is consistent with expectations and lends support to
the ideological space hypothesis, which suggests that green parties are more able to
increase environmental taxes when in power under proportional electoral systems.
Turning now to the disproportional constraints hypothesis (H3), Models 4 to 6 test the
idea that the ability of green parties in the legislature/government to increase implicit
carbon tax rates on gasoline will be reduced under more disproportional electoral systems
(H3). The empirical results of each model are summarized in Table 5.6.2.2.
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Table 5.6.2.2: Gasoline tax regression models testing the disproportional constraints hypothesis (H3) Model 4 Model 5 Model 6 PCSE Cluster PCSE Cluster PCSE Cluster lag_rtax 0.667*** 0.667*** 0.664*** 0.664*** 0.661*** 0.661*** (0.0920) (0.0352) (0.0902) (0.0326) (0.0854) (0.0348) net_oil_xp 0.0512 0.0512 0.0535 0.0535 0.119 0.119 (0.208) (0.290) (0.232) (0.294) (0.201) (0.296) openk -0.676 -0.676* -0.623 -0.623 -0.526 -0.526 (0.424) (0.278) (0.372) (0.348) (0.350) (0.339) log_rgdppc 42.01* 42.01 42.66* 42.66 35.05 35.05 (20.49) (20.78) (21.39) (22.10) (20.48) (22.31) debt_gdp 0.239 0.239 0.236 0.236 0.328* 0.328 (0.174) (0.217) (0.155) (0.216) (0.150) (0.231) itax_gdp -4.095*** -4.095* -4.171*** -4.171* -3.447*** -3.447 (1.168) (1.873) (1.091) (1.861) (0.918) (1.867) electy 3.205 3.205 3.133 3.133 2.825 2.825 (3.268) (4.821) (3.167) (4.806) (3.241) (4.710) inf_cpi_all -0.971 -0.971 -1.002 -1.002 -0.925 -0.925 (1.542) (1.595) (1.458) (1.554) (1.391) (1.561) yr_dis_gall 0.193 0.193 0.159 0.159 -0.277 -0.277 (0.602) (0.697) (0.499) (0.719) (0.459) (0.780) green_dum -4.700 -4.700 (12.75) (6.905) greendis -0.610 -0.610 (1.242) (0.590) greens 0.481 0.481 (1.390) (2.432) greensdis -0.946* -0.946 (0.466) (0.529) llc 0.0507 0.0507 (0.642) (0.586) llcdis -0.382* -0.382** (0.161) (0.102) _cons -297.6 -248.6 -304.2 -254.4 -237.8 -193.1 (202.1) (200.9) (211.0) (209.0) (199.8) (210.9) N 327 327 327 327 327 327 R2 0.941 0.624 0.942 0.630 0.943 0.635 Standard errors in parentheses * p < 0.05, ** p < 0.01, *** p < 0.001
230
The basic results in Table 5.6.2.2 provide additional evidence of the conditioning effect
of PR electoral regimes for the relationship between green parties and implicit carbon
taxes. Models 4 to 6 present regression results using tax rates on gasoline in constant
2000 USD per tonne of carbon dioxide. I substitute net crude oil exports for crude oil
production to see if results change, and add an additional independent variable – the
personal and corporate taxes on income and capital gains as a percentage of GDP – to test
for the plausible impact of the tax mix on implicit carbon tax rates for gasoline. Even
after these alternative model specifications are introduced, evidence of a significant
mediating effect of electoral institutions on implicit carbon tax rates is fairly robust.
Substituting net crude oil exports for crude oil production makes little difference to the
expected direction and significance of the effect of oil producers on gasoline tax rates,
which remain positive and insignificant. The coefficient on trade openness is, as
expected, negative, but is only significant in model 4 using the cluster robust estimator.
Per capita income is consistently positive and significant in two of the three models using
PCSEs, suggesting that richer countries levy higher taxes on gasoline. Although central
government debt fails to reach significance across all models, coefficients are positive as
expected (more debt translates into greater need for revenue and thus higher taxes).
Consistent with expectations, the income tax variable is associated with significantly
lower gasoline tax rates. This finding is consistent with the expectation that the overall
tax mix is an important explanatory factor in accounting for differences in consumption
taxes on fossil fuels, as well as the idea that high income tax countries will face greater
resistance to additional consumption taxes. This also helps explain why, in the absence of
PR (but in the presence of greens), France is a high motor fuel tax country, as it has the
lowest tax rates on personal and corporate taxes on income and capital gains of all
countries in the sample. The variables indicating an election year and the inflation rate
are not significant.
Returning to the disproportional constraints hypothesis (H3), two of the three models
produce results that are consistent with theoretical expectations. The interaction between
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at least one member of the green party in the legislature, and disproportionality in the
electoral system, is negative but insignificant (model 1). However, when a more precise
measure of green representation is used (i.e. share of legislative seats held by green
parties), the results are significant at a level of p<0.05 (using PCSE) and p<0.01 (using
cluster robust standard errors) in model 5. Moreover, model 6 finds that increasing
green/new left cabinet government has a reductive effect on gasoline tax rates in
disproportional regimes, just as the theory predicts. This last result is illustrated in Figure
5.6.2. 4.
Figure 5.6.2.4: The marginal effect of green/left cabinet in disproportional systems (H3)
As shown in Figure 5.6.2.4, the marginal impact of the share of cabinet portfolios held by
green/new-left parties on implicit carbon tax rates for gasoline decreases as
disproportionality in the electoral system increases. Controlling for net exports of crude
oil, exposure to trade, per capita income, central government debt, other sources of tax
232
revenue, elections, inflation and the prior year’s tax rate, the impact of additional cabinet
portfolios held by green/new-left parties decreases with increasing disproportionality in
the electoral system. Consistent with theoretical expectations, the marginal impact of
green/new-left government on tax rates is higher at low levels of disproportionality.
However, as disproportionality increases, the ability of green/new-left government to
impose higher tax rates on gasoline appears to diminish, as parties become more
vulnerable to voters in disproportional electoral systems, just as H3 suggests.
The key causal mechanism that is responsible for the disproportional constraints is the
seat-vote elasticity, which is greater in disproportional systems. As the label implies,
disproportional systems are those that allocate a disproportionate amount of seats to a
given level of the popular vote. In such situations, typically the product of majoritarian
systems, small changes in the vote share can have relatively large impacts in terms of
seats, resulting in high seat-vote elasticity. Under such conditions, I hypothesize that the
electoral fortunes of parties are more vulnerable, and therefore more likely to respond to
changes in popular sentiment. This electoral incentives hypothesis (H4) is examined in
Table 5.6.2.3. The dependent variable (gasoline tax) in both models is measured at
purchasing power parities (PPPs) as opposed to USD, as a check for robustness.
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Table 5.6.2.3: Gasoline tax regression models testing the electoral incentives hypothesis (H4) Model 7 Model 8 PCSE Cluster PCSE Cluster lag_ppp 0.949*** 0.715*** 0.707*** 0.707*** (0.0160) (0.0337) (0.0593) (0.0338) crude_rgdp 14.42 57.79*** 59.76 59.76*** (9.676) (9.582) (39.03) (9.530) openk 0.0331 0.0615 0.0594 0.0594 (0.0317) (0.107) (0.138) (0.155) log_rgdppc -17.07* -6.326 -4.556 -4.556 (7.239) (9.536) (9.189) (10.36) debt_gdp 0.00201 0.381*** 0.384*** 0.384** (0.0269) (0.0990) (0.0928) (0.105) itax_gdp -0.269 -0.547 -0.693 -0.693 (0.184) (0.860) (0.611) (0.895) rural_pop -0.0869 0.750 0.673 0.673 (0.0748) (0.727) (0.824) (0.770) electy 0.344 0.655 -0.105 -0.105 (1.888) (2.381) (1.621) (2.319) inf_cpi_all -2.055*** -1.332** -1.262 -1.262* (0.570) (0.450) (0.690) (0.467) yr_dis_gall -0.378* -0.637** -0.927** -0.927* (0.185) (0.188) (0.334) (0.395) greenv 0.509 -0.477 (0.366) (0.710) greenvdis 0.0708* 0.0927 (0.0339) (0.0468) llv -1.402 -1.402** (0.879) (0.459) llvdis 0.0819** 0.0819* (0.0316) (0.0373) _cons 195.3* 102.6 95.78 95.82 (77.24) (104.1) (98.67) (108.4) N 336 336 321 321 R2 0.975 0.774 0.983 0.777 Standard errors in parentheses * p < 0.05, ** p < 0.01, *** p < 0.001 The basic results presented in Table 5.6.2.3 provide evidence to support the electoral
incentives hypothesis. In fact, 3 of 4 coefficients on the interactive vote variables are
significant at conventional levels. For instance, model 7 examines the impact of
234
increasing the share of popular vote obtained by green parties (greenv) on tax rates, under
conditions of increasingly disproportionate (or highly elastic) electoral systems. As can
be seen crude oil production, per capita income, debt and inflation are variously
significant depending on which estimator is used. The only variable to be consistently
significant across both estimates is yr_dis_gall, which is the 5 year moving average of the
level of disproportionality produced by a country’s electoral system. Consistent with
theoretical expectations, more disproportional election results are associated with
significantly lower tax rates on gasoline fuel. For the theoretical reasons discussed earlier,
it is more difficult for governments in disproportional systems to raise taxes on gasoline,
because such charges are visible and can therefore jeopardize a government’s chances of
re-election, especially where the seat-vote elasticity is particularly high, as it is in highly
disproportional systems. In addition, as indicated by the greenvdis, increasing the share
of total votes to green parties is positively associated with higher implicit carbon tax rates
on fossil fuels, like gasoline. This variable is significant at a level of p<0.05 using PCSEs
and at a level of p<0.1 using cluster robust estimates of standard errors, as presented in
model 7.
As a further test, I substitute green vote with votes for green and other new left parties, as
coded by Swank (2007). The results provide additional empirical support. Crude oil
production is again significant, but only in one model. Debt emerges as associated with
significantly higher tax rates on gasoline, as expected since gasoline taxes can provide a
non-trivial amount of government revenue for governments in debt. Consistent with our
theory, the variable measuring disproportionality – when green votes is at 0 – produces
smaller tax rates on gasoline. As the environment becomes increasingly salient, to the
point where an increasing proportion of the population votes green, implicit carbon tax
rates tend to rise in disproportional systems, as governments seek to maximize votes to
assure re-election.194 This dynamic is illustrated in Figure 5.6.5.6.2.4.
194 Alternatively, one might speculate that the rising support for greens creates the conditions for governments to raise gasoline taxes for revenue purposes.
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Figure 5.6.2.4: Marginal effect of green votes in disproportional systems (H4)
As can be seen in Figure 5.6.2.4, the marginal increase in the share of total votes for
green parties is associated with significantly higher tax rates on gasoline in more
disproportional systems, just as our theory predicts. At low levels of disproportionality,
there is less incentive for small changes in votes for greens to have a direct influence on
tax policy. As disproportionality in the electoral increases, however, and as governments
become more vulnerable to a small change in the popular vote, there are more incentives
to respond to popular sentiment. This relationship is consistent with a view of political
parties as vote-maximizers, and with the argument that electoral systems shape not just
the access to power of greens, but also the strategies of other parties engaged in electoral
competition.
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Robustness checks As should be clear, the foregoing analysis of implicit carbon taxes on motor fuels
includes a series of built-in robustness checks integrated into the various models
examined. Different models were estimated using different operationalizations of the
dependent variable (USD and PPP), different estimators (PCSE and Clustered robust
standard errors), and different model specifications included/excluded different
independent variables. In addition, a series of pre and post estimation checks were run
discussed in section 5.6, which determined the appropriateness of using fixed effects,
temporal lags, and estimators robust to serial and contemporaneous correlation. This
section briefly extends robustness and diagnostic checks by commenting on two further
issues in TSCS data, multicolinearity and unit roots.
Multicolinearity tests, specifically a correlation matrix of all variables included in the
models (excluding the interactive terms) reveal no problems of collinearity. The two most
correlated independent variables are PR (pr) and disproportioanlity (yr_dis_gall), which
are expected to be correlated and are never used in the same regression models. The two
second most highly correlated independent variables are PR (pr) and income tax
(itax_gdp). These latter variables are theoretically distinct, but it is interesting to note that
PR systems tend to be correlated with lower levels of income tax (and as shown here,
higher consumption taxes). The correlation matrix is provided in the data appendix.
Finally, I follow the advice of Beck (2006) in checking for unit roots. While variables
containing unit roots can invalidate results (Kennedy, 2003: 325), the tendency for
“random walks” in TSCS data is not very common (Beck and Katz, 2009). However,
Beck (2006) warns that estimation of models with a lagged dependent variable and or
with serially correlated errors (as is the case here) can lead to such misleading results as
spurious regressions. To guard against this possibility, I check to see if residuals appear
stationary after estimating the dynamic models discussed in 5.6. Regressing the residuals
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on their lags, all coefficients approximate a value of 1. According to this test, the
residuals appear stationary and no further tests are performed.195
5.7: Summary and discussion
The results presented in sections 5.5 (implicit carbon taxes on industry) and 5.6 (implicit
carbon taxes on households) provide considerable evidence in support of the hypotheses
examined in this dissertation. In general, the results clearly demonstrate systematic
differences in carbon energy tax rates across majoritarian and proportional systems. I
also find that the partisan makeup of government matters for policy, particularly in
proportional systems.196 These results hold across the 4 commonly used fossil fuels
examined here, covering both the industrial and household sectors. Specifically, with
reference to political parties favouring higher energy taxes, and to electoral competition
between parties, the theoretical argument developed in Chapter 1, and analyzed in
Chapter 5, helps to better understand why these institutional differences matter, and to
specify the conditions under which proportional systems are most likely to result in
higher rates of implicit taxes on carbon-based energy sources. Methodologically, the
difference between models estimated with PCSEs and cluster-robust standard errors is
substantial in terms of the adjusted R-squares.
H1: The PR hypothesis
In general, the most robust finding is that the type of electoral system employed by
countries has an influence on rates of carbon-energy taxation. This hypothesis is
consistently supported by statistically significant differences in mean tax rates across
majoritarian and proportional systems. Across all fuels examined here, PR systems
generally tax fossil fuels at a higher rate, consistent with theoretical expectations. I argue
that PR systems better insulate governments from the vagaries of public opinion,
195 Attempts at implementing a Levin-Lin-Chu test were unsuccessful due to the requirement of a strongly balanced panel. 196 To be sure, whether the ideological preferences of government matters is an important debate in political science. The evidence presented here suggests that the ideological makeup of government matters most under proportional systems.
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allowing them to increase taxes on energy without necessarily being “punished” by
voters. They also produce incentives for parties to target broader social welfare goals
(like a better environment), given the larger constituency districts. In contrast,
governments in majoritarian systems are more vulnerable to small changes in public
opinion, and for this reason are less likely to implement tax increases. They are also more
likely to target policy benefits for key districts, foregoing policy with broader social
welfare goals (Persson and Tabellini, 2008). However, the PR variable by itself leaves
much to be explained.197 Indeed, there are some exceptional cases unaccounted for by
PR, and there are clear differences in tax rates even among countries with PR as well. In
order to better understand these differences, I consider the interaction between the
electoral system and the ideological orientation of different parties.
H2: The ideological space hypothesis
Evidence in support of the disproportional constraints hypothesis is strong across all
fossil fuels. This hypothesis specifies that, by increasing the importance of smaller
parties, PR systems should lead to higher taxes. Thus, the political agency is in the form
of green and left parties, which previous studies clearly show prefer higher taxes on
energy for environmental and other reasons. For industrial use of coal and heavy fuel oil,
tax rates are clearly influenced by left-wing cabinet government, and this influence is
particularly pronounced in countries using PR systems to translate vote shares into seat
shares, as our theory suggests. Interestingly, traditional left-wing governments are less
able to predict tax rates on household use of motor fuels used for transportation. Instead,
green/new-left parties are associated with significantly higher tax rates for household
fuels, under PR. This might be expected given the former’s emphasis on protecting
labour rights while the latter’s emphasis tends to be for environmental protection and
broader equity goals (Kitschelt, 1988; 1994). For instance, in the case of diesel fuel,
green party strength – whether measured by the presence/absence of greens in the
legislature, the share of seats to green parties, or the share of cabinet posts held by
green/new-left parties – are strongly associated with significantly higher tax rates across
all models analyzed. In contrast, left wing cabinet government appears to have no
197 This is why I consider the evidence in support of H1 to be “moderate,” as indicated in Table 5.7.1.
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influence on household tax rates for diesel fuel (though they are associated with higher
tax rates on industry use of diesel fuel, not reported here). Perhaps owing to more
complicated politics, the results are somewhat less consistent in the case of gasoline. The
share of green votes and the share of green seats appear unrelated to rates of gasoline
taxation under PR (Table 5.6.2.1.). However, when green/new-left parties are in power in
PR systems, we find significantly larger taxes on gasoline, as expected. To be sure, green
members in cabinet are precisely where we might expect greens to have the greatest
influence on policy, so the fact that greens in the legislature fail to translate into higher
taxes on gasoline makes intuitive sense.
H3: The disproportional constraints hypothesis
The idea that disproportional systems constrain the ability of parties to increase green
taxes is also strongly supported across all fossil fuels. The causal logic specifies that
disproportional systems increase the lines of accountability between governments and the
electorate. Since disproportional systems tend to produce majority government, voters
know whom to “punish” when taxes are increased. Moreover, governments are more
vulnerable to small changes in the vote share, since disproportionality implies that even a
small change in votes can have a large impact on the composition of the legislature. For
both these reasons, governments are more accountable and vulnerable, and will thus be
constrained in their ability to increase taxes (usually unpopular policy). It follows that the
ability of green/left parties to implement higher taxes will be constrained under
disproportional systems, and evidence of this effect can be found across the board. For
instance, this argument holds for the ability of left-wing parties to increase taxes on coal
and heavy fuel oil, even when robustness checks are performed. Similarly, nearly all
models show an inverse relationship between greens/new-left party strength under
increasing disproportionality, and the opposite (i.e. higher taxes with increasing
green/new-left strength under proportional systems) is by definition also true.
H4: The electoral incentives hypothesis
The final hypothesis regarding the institutional incentives created by electoral systems
also receives some empirical support, and should be investigated in further work. This
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hypothesis specifies that, while green parties will be constrained in disproportional
systems, voting for green parties in such systems will induce other parties to adopt green
policies, in order to maximize vote gains and minimize vote losses, thus leading to higher
rates of green taxation. This hypothesis is tested in the diesel and gasoline tax
regressions, both of which provide empirical support. For instance, I find that voting for
greens and green/new-left parties is associated with significantly higher tax rates on
gasoline under highly disproportional systems. Though weaker, these findings also hold
for diesel when the PCSE estimator is used (Table 5.6.1.3).
To conclude, the general performance of each hypothesis is summarized in Table 5.7.1.
Table 5.7.1: Performance of primary research hypotheses across fuels H1 H2 H3 H4 coal
moderate
very strong
very strong
not tested
heavy fuel oil
moderate
strong
strong
not tested
diesel
moderate
very strong
very strong
moderate
gasoline
moderate
moderate
strong
strong
Empirically, the variables used to test hypotheses H2 to H4 are consistently the best
performing variables used in the fossil fuel tax regressions. Other variables that perform
well include government debt levels, suggesting that fossil fuel tax rates are also
influenced by government revenue needs. This is particularly true in the case of tax rates
on gasoline. Consistent with the existing literature, exposure to international trade is only
sometimes associated with lower tax rates, and the interests of fossil fuel producers varies
by fuel type, with coal producers apparently having the most influence over tax rates
affecting their product.
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Outliers While the goal of this research is to identify patterns in the way countries tax fossil fuels,
and to explain these differences with a parsimonious account of the interaction between
parties and the electoral systems, two outlying cases deserve brief mention as cases for
further exploration. These cases include France and Great Britain, which apply relatively
large tax rates to motor fuels, despite their use of majoritarian electoral systems. To be
sure, further research into the electoral incentives in both countries could assist in
accounting for these deviant cases within the logic outlined in this dissertation. In
addition, the outlier status of both is likely best explained with reference to a confluence
of idiosyncratic factors. I briefly offer some initial thoughts here.
The French case appears to be a clear example of the importance of a country’s overall
tax-mix. For instance, when considering France’s historical tax policy mix, it is clear this
country has consistently maintained relatively low rates on personal and corporate
income (Peters, 1980). In fact, averaged over the period between 1978-2006, France
imposes the lowest personal and corporate taxes on income and capital gains (category
1000 in OECD Revenue Statistics) across the entire 22 countries examined in section 5.6.
As such, the deviant nature of the French case might be understood as a historically
rooted tradeoff between relatively low income taxes and higher consumption taxes. A
more detailed account of how and why such choices were historically made in France,
while not directly in opposition to the theoretical argument made here, is beyond the
scope of the present study.
In the case of the U.K., the reason for higher tax rates on gasoline and diesel fuel is
relatively more recent. Indeed in 1979, diesel tax rates in Great Britain were among the
lowest in the world. However in 1993 a fuel escalator duty was imposed, increasing fuel
taxes at 3% annually above inflation. This was done partly in response to growing public
concern over poor air quality pollution and traffic congestion in London, and as a means
of generating government revenue. To be sure, the London protests and the factors
leading to the fuel escalator are not well covered in the existing literature and merit
further analysis, which is beyond the scope of this project. That said, in more recent
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times, and consistent with the disproportional constraints and electoral incentives
hypotheses, the escalator was abandoned in 1999 in response to country-wide protest. As
might be expected from the theory developed here, rising opposition to the fuel escalator,
under highly disproportional conditions, produced incentives for Tony Blair’s Labour
Government to abandon the escalator in 1999, and sacrifice this source of revenue, or else
suffer at the polls.
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Chapter 6: Conclusion
6. Carbon-energy policy at a cross-roads: prospects for the future Ten years into the twenty-first century, countries face the unenviable task of finding ways
to reduce dependence on carbon-based energy, in order to become more secure and
environmentally sustainable. From a security perspective, price volatility and a
concentration of reserves in geopolitically unstable regions of the world constitute
significant economic and security vulnerabilities for fossil-energy dependent states.
Moreover, even where fossil energy is cheap and abundant (e.g. coal), a continuation of
its use threatens to destabilize the Earth’s climate, further producing economic and
security risks for the advanced developed democracies that make up the OECD.198 In
response to these challenges, taxing the consumption of carbon-based fuels is now widely
advocated by economists and other experts as a key instrument for internalizing the costs
of energy security and climate change.
At the same time, the introduction of this dissertation opened with the idea that, for a
variety of well-known reasons, increasing tax rates on carbon-based energy is politically
very difficult. At present, fossil fuels constitute the single largest energy source used
across the globe. Crucially, these patterns in energy consumption have been encouraged
by a favourable mix of tax and subsidy policy aimed at helping countries to modernize,
industrialize, and accelerate the process of economic development. Given the public good
nature of a stable climate, and incentives to free-ride on the GHG mitigation of others,
why would any country unilaterally impose higher domestic rates of carbon-energy
taxation? In addition to this question, it was found that even in instances where an
explicit “carbon tax” is successfully implemented, numerous design characteristics (e.g. 198 If countries do not dramatically change course, the best estimates of a “business as usual” scenario project that global GHG emissions will double by 2030, leading to a CO2 equivalent concentration of over 500 ppm, and a temperature increase of greater than 2 degrees Celsius, representing a potential cost in the range of 5 to 20 per cent of global GDP (Jowit and Wintour, 2008).
244
non-uniform rates and sectoral exemptions) lead to more heavily polluting fuels and
sectors being taxed at lower rates, suggesting that taxing fossil fuels may actually be
more difficult than is commonly understood. In the presence of such constraints,
explaining large cross-national differences in implicit rates of carbon energy taxation is
the fundamental question this dissertation set out to answer. Specifically, what
characteristcs are shared by countries where rates of carbon-energy taxes are relatively
higher? Exploiting large cross-national differences in the way countries tax the same
fuels, I attempt to identify the political conditions that help explain when and why energy
tax reform is politically possible.
6.1. Key findings
Conventional thinking around carbon-energy taxation suggests two variables are key –
the ability to overcome resistance from domestic energy producers and the need for bold
political will. There is some evidence to support both perspectives. Case study research
has found empirical evidence of successful business opposition to carbon energy taxation,
resulting in numerous sectoral exemptions (Anger et al. 2006; Kasa, 2000; 2005).
Moreover, some authors argue that tripartite policy networks (corporatism) and the
consensual decision-making they foster is what allows such reforms to materialize
politically (Midttun and Hagen, 1997). But while these arguments are helpful in
explaining the ultimate design of carbon taxes and the sectoral exemptions they offer,
they are of limited use in explaining why carbon tax proposals appear on the political
agenda in the first place.
On this score, notions of political will and leadership help to identify the source of
political agency. To be sure, some form of political will is necessary for any type of
policy change. For instance, Harrison (2009) identifies the environmental transformation
of Gordon Campbell as constituting an important factor explaining the emergence of the
BC carbon tax. In another work, Simpson et al. (2007: 157) go as far as saying a lack of
political will among the Federal Liberal Party is a reason for Canada’s poor performance
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in mitigating GHGs. But political will alone does not seem to explain the large cross-
national differences in rates of carbon energy taxation described in this dissertation.
Moreover, one can find several instances of political will being decisively denied by
opposing forces, as evidenced in the 2008 Federal election in Canada. Despite
personifying political will and having the courage to propose a broad-based carbon tax
reform, Liberal leader Stéphane Dion saw his proposal fail, miserably, costing his party
to lose 16 seats in one of the most dismal campaigns in Liberal party history (Harrison
2010; MacKenzie, 2009). Nor were such charismatic leaders as Bill Clinton and Al Gore
able to overcome opposition to their much more modest BTU tax in 1993 (Erlandson,
1994; Royden, 2002). As these leaders learned, political will takes one only so far.
In contrast to this received wisdom, the analysis developed in this dissertation points to
one currently under-appreciated causal pathway that appears to account for much of the
variation in energy tax rates across the advanced capitalist democracies in the OECD.
Indeed, empirical analysis of rates of carbon energy taxation on four fossil fuels (coal,
heavy fuel oil, diesel and gasoline) in roughly 20 OECD countries demonstrates that
energy taxes vary systematically across countries employing majoritarian and
proportional (PR) electoral formulae, and suggests that tax increases might be easier
under different conditions depending on which system is used. At the same time, tax rates
differ even among countries employing the same type of electoral system. I argue that the
electoral system helps to explain differences in rates of carbon energy taxation, and that
this variable interacts with party votes, seats and the ideological composition of
government.
The analysis developed in this dissertation finds substantial evidence supporting the
claim that systems of proportional representation, in addition to partisanship preferences,
work together to explain differential rates in carbon energy taxation. By opening up the
ideological space for “green” and “green/new-left” political parties to win legislative
seats and participate in government, I argue that PR systems create the institutional
context within which higher rates of carbon-energy taxation become politically possible.
By specifying a key causal mechanism within different types of electoral systems – the
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seat-vote elasticity – I argue further that, voters in disproportional systems actually have
more leverage over politicians, and that an increase in environmental voting can have an
impact on rates of carbon energy taxation, even in the absence of PR. This is due to the
fact that disproportional systems clarify the lines of accountability between voters and
government, whereas in proportional systems, which typically produce coalition
government, parties share the blame. In sum, while the accession to power of green
political parties in PR systems is more likely to lead to higher rates of carbon energy
taxation, voting for green parties in highly disproportional systems will provide the
incentive for other parties to adopt “green” policies, leading to the same outcome (i.e.
higher taxation of carbon based energy). In this way, the effect of green votes and green
seats will have the opposite effect on taxes according the type of electoral system in
use.199
To be sure, the precise nature of which fuels are taxed, and by which parties, varies under
PR regimes. Given the analysis developed in Chapter 5, it appears as though social
democratic parties are more effective at implementing higher rates of carbon-energy
taxation on industry use of fossil fuels, like coal and heavy fuel oil (and industry use of
diesel) under proportional electoral systems. In contrast, green and green/new-left parties
are more effective at implementing environmental taxes on household consumption of
commonly used fossil fuels used for private transportation, diesel and gasoline (again,
under proportional electoral systems). The ideological orientation of the party in power
appears less important under majoritarian systems, where electoral incentives generated
by shifting voter preferences under disproportionality, not ideology, explain when and
why governments increase (or fail to increase) rates of energy taxation. I thus find
evidence for both sides of the debate in political science, on whether the partisanship
makeup of government matters, and offer an important specification indicating the
conditions (i.e. proportional systems) under which the ideological makeup of parties are
most likely to matter. Future research in this area would benefit from more refined
199 For instance, under increasingly disproportional electoral systems, green parties in the legislature and green parties in government are increasingly constrained in their ability to raise taxes on carbon-based energy. Under these same systems, however, increasing the vote share for green parties produces an incentive to adopt greener policy, like an increase in carbon energy taxation.
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measures of the political preferences of various parties in their country-specific context,
as well as cross-nationally comparable data on the policy preferences of the voting
public.
In addition to the role of parties under PR, and votes in disproportional systems, I find
some evidence of other determinants of carbon energy taxation. In particular, exposure to
trade is often found to be associated with lower rates of carbon energy taxation,
consistent with the view that governments need to protect energy intensive, trade exposed
sectors in their economy. While posing an important barrier, this finding points to the
political importance of developing internationally harmonized rates of carbon-energy
taxation. In the absence of such an arrangement, the pricing of carbon-based fuels for
environmental and other objectives will lead to the application of border tax adjustments
and concerns over “environmental protectionism,” as is already evident in current
discussions at the WTO. These climate trade wars can best be prevented through the
careful reform and “ratcheting up” of domestic taxes on carbon-based fuels. Preliminary
evidence of countries adopting taxes in line with their largest trading partners is evident
in the data examined in this dissertation (e.g. a NAFTA block, a European block), and
requires further research. Moreover, when examining tax rates for industry, greater
attention should be paid to the many rebates, exemptions and loopholes granted to
industry.200
Finally, the analysis developed in Chapter 5 also finds evidence of governments raising
taxes in order to meet revenue needs. For instance, while greater coal production (and a
larger coal lobby) tends to be associated with lower taxes on coal (though not
significantly lower), greater oil production has the opposite effect, where countries
producing larger quantities also tax oil products at relatively higher rates. While
suggesting that coal lobbies are more effective at keeping tax rates on their products low
(perhaps due to the relatively more labour intensive and unionized coal producing sector),
this also suggests that countries tax energy sources that are relatively inelastic (like crude
200 As much as possible, the analysis developed in this dissertation accounts for rebates and exemptions to industry, based on information provided in the detailed country notes published in the IEA’s Energy Prices and Taxes. It is possible that some tax loopholes are excluded from this publication.
248
oil and oil products). Consistent with this, empirical models of gasoline taxes are more
complex, and central government debt consistently emerges as an important predictor.
All of this suggests that tax rates on fossil fuels are an important source of government
revenue, and that tax rates can at times be expected to follow from the financial needs of
the state.
6.2. Contributions
As one of the first studies of the political determinants of implicit rates of carbon energy
taxation across a large number of countries, fuels and sectors, this dissertation makes a
number of unique contributions to the literature on the comparative politics of energy
taxation, and builds our understanding of why energy tax rates differ so widely.
Importantly, the very fact that different countries tax the same fuels at widely different
rates suggests there is scope for reform of carbon-energy taxation. To the extent that
these differences exist even among the similarly situated, advanced industrial economies
that make up the OECD, there appears to be considerable room for harmonizing rates of
carbon energy taxes upward, without necessarily harming a country’s international
competitiveness. Though more research is required in this area – in order to cluster the
tax rates of countries that trade together – there is no a priori reason to reject coordinated
harmonization among the OECD countries out of hand. Similarly, the fact that rates of
carbon-energy taxation vary over time, in some countries more than others, suggests tax
rates in some areas may not be keeping up with inflation, further providing room for tax
policy maneuver. Whether and how the advanced industrial OECD can lead in this area is
a research area that warrants further study.
Turning to the empirical focus of the present study, this dissertation is the first to test the
role of electoral systems across more than just one fossil fuel, and over a longer time
period. As such, it improves on existing studies in at least two important ways. First, this
study provides a novel explanation of cross-national differences in carbon-energy
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taxation. Previous studies have relied on corporatism as a key independent variable.
While the qualitative literature on explicit carbon taxes finds some support for the claim
that corporatist decision-making networks help shape the ultimate design of carbon taxes
(Midttun and Hagen, 1997), quantitative studies testing this variable find only limited
support (Morozova, 2005).
In contrast, the present study finds that PR electoral systems help explain why increased
carbon energy taxes appear in the first place. Moreover, the plausibility probe in Chapter
4 suggests that, at least in the case of British Columbia, the distribution of resources and
votes across districts, and the associated electoral incentives, help to explain the ultimate
design of the BC carbon tax. Testing for both the effects of corporatism and the electoral
system in tax rates affecting fossil fuels used by industry also suggests that the electoral
system explanation performs better in empirical tests. The electoral system argument
advanced here thus adds value to existing studies, and may potentially explain both the
ultimate design of carbon taxes, and why they emerge in the first place. Second, the
present study improves on existing analyses of the electoral system (e.g. Fredriksson and
Millimet, 2004) by applying this variable to a larger number of different types of fossil
fuels, and by specifying the causal mechanism at work. Thus, the present study develops
a more comprehensive and coherent analysis of the role of electoral systems for carbon-
energy taxation, and develops an argument explaining when and why they should matter.
In addition, the present research has developed an alternative measure of “carbon taxes,”
that is deeper and applicable across a wider number of countries. This measure allows for
a more comprehensive account of the effective rate of carbon energy taxation across
countries, allowing an analysis across fuels, sectors and countries, for which data are
available. This measure can be used in future work on the comparative politics of carbon
energy taxation.
While open questions remain, this dissertation points to one particularly robust pattern,
and a coherent argument explaining cross-national differences in rates of carbon energy
taxation. To be sure, the results of empirical tests point to probabilistic generalizations
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only. Future work might consider more closely instances of broad-based tax policy
change in the absence of PR electoral systems, or the case of gasoline taxation, the
politics of which appear comparatively more complex. Where instances of broad-based
tax reform occurs, the theoretical argument developed here suggests one should pay
particular attention to the electoral incentives and constraints produced by
(disproportional) electoral systems and the distribution of votes across the political
system.
6.3. The way forward
Returning to the discussion of carbon taxes and cap-and-trade raised in Chapter 2, it
appears as though the debate is far from settled. To be sure, the received wisdom is that
carbon taxes simply won’t work. Especially in a North American context, it is sometimes
said that the “t” word is simply too toxic, and that carbon taxes are too difficult to
implement politically. In these lights, the BC carbon tax stands out as an important
anomaly deserving of closer study. Indeed, Gordon Campbell not only successfully
implemented a comprehensive, broad-based carbon tax in the absence of PR, but also
survived an election in which his policy was fiercely debated. The analysis developed
here suggests electoral incentives in a highly disproportional electoral system help to
explain this successful green shift.
Moreover, notwithstanding the apparent popularity of emissions trading over carbon
taxes (Chapter 2), recent events suggest that participants in the climate policy debate may
have underestimated the political difficulty inherent in designing and implementing a
system of cap-and-trade. As the example of policy debate in Canada and the U.S.
demonstrate, emissions trading policy is not necessarily easier than carbon taxes to
implement. For instance, Congressional consideration of cap-and-trade legislation in the
U.S. reached a high water mark in June 2009, when the House narrowly passed a 1,482
page bill (much longer than any carbon tax proposal) known as the American Clean
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Energy and Security Act.201 Subsequently, the Senate, which over-represents the less
populated, GHG-intensive states, has consistently blocked all climate legislation.
Meanwhile, the Western Climate Initiative (WCI) once heralded as an opportunity to
move forward with cap-and-trade in the absence of a federal role, has seen one of its
members (Arizona) back out, citing concerns over the economic recession. Moreover, the
current status of the WCI was recently in peril, as Proposition 23, which was recently
voted on in November, threatened to repeal California’s monumental Global Warming
Solutions Act of 2006, upon which the future of the WCI depends. Backed by out-of-state
oil interests in the California Jobs Initiative, Proposition 23, if passed, would have
prevented California from participating in the WCI, which could effectively kill the
regional cap-and-trade effort. While Proposition 23 failed to materialize, there is no
reason to believe the interests behind this effort will not continue their efforts to block
regional cap-and-trade, as well as other carbon policy.
Finally, though two distinct Canadian governments have attempted since 2003 to
implement a system of cap-and-trade for large final emitters in Canada, these efforts have
consistently failed. Despite proposing ostensibly the same policy in his party’s
misleadingly labeled, “Turning the Corner,” Stephen Harper has recently made explicit
his policy of harmonizing Canadian climate policy with whatever happens in the U.S.,
which given the legislative gridlock in the Washington, effectively constitutes an excuse
for doing nothing. Less cynically, the difficulty in reconciling regional differences across
provinces, which are empowered with the sole constitutional responsibility for the
management and ownership of their natural resources, is often cited as the key reason for
the lack of a federal role, prompting former leader of the Liberal Party of Canada,
Stéphane Dion to quip, “that’s why I proposed a carbon tax – I would not have to consult
the provinces!” (Dion, 2010).
In sum, the future of cap-and-trade is by no means clear, and it appears as though we are
now perceiving the very real limits on the ability of executive federalism and the
201 The bill passed by a margin of 219 to 212.
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separation of political power systems to implement cap-and-trade in North America.
Indeed, there is a great deal of political uncertainty at the national level with respect to a
federal or continental regime, and in fact, the debate has moved away from cap-and-trade
and is now more focused on regulation, on both sides of the 49th parallel. There is also
uncertainty at sub-federal levels, as evidenced recently by Arizona’s dropping out of the
WCI. Meanwhile, carbon taxes have re-emerged in policy debates elsewhere, and there is
no reason to question the ontological status of the tax policy instrument. For instance,
recent calls to consider a carbon tax have appeared in recent policy discussions in
Australia, where cap-and-trade was once thought to be the obvious policy choice
(Andrew et al. 2010).
Looking forward, it is highly unlikely that carbon taxes will ever be taken off the political
negotiation table. Cap-and-trade systems have proven to be politically complex and
difficult to design, requiring all manner of compromises to be made, and failure to reach
such accommodation might prove to be their political Achilles heel. In contrast, energy
taxes are infinitely simpler, requiring comparably less elaborate legislative design and
bureaucracy, and are inherently revenue raising, an important consideration in the current
fiscal context affecting many governments across the OECD. Moreover, governments are
very familiar with the tax instrument, and as this dissertation demonstrates, carbon taxes
have been in place in every country from the day fossil fuels were used. There is thus no
reason to believe that governments will stop taxing fossil fuels. The question thus
becomes how to reform rates of carbon energy taxation so that they are more compatible
with other economic, social and environmental objectives. As suggested by the findings
of this dissertation, the extent to which such reforms will take place will crucially depend
on the interaction between party preferences, electoral incentives, and the type of
electoral system used.
253
Appendix 1: Variable definitions 1. FOSSIL FUEL INTERESTS coal_rgdp A measure of coal production (EIA) divided by real gross domestic product (Heston et al. 2009) to measure size of coal producers relative to size of economy. Units: toe/000 constant 2005 PPP$ in rgdp Note: real gross domestic product rgdp is rgdppc*population, with population data drawn from the WDI and rgdppc being real per-capita income in year 2005 measured at purchasing power parity, based on Penn World Tables version 6.3 (Heston et al. 2009). Source: Own calculations using data from EIA (2009) and Heston et al. (2009) net_coal_xp Is a measure of net coal trade balance (XP-IM) as a percentage of all coal consumed [Coal XP-IM in QBtu] / [Coal consumption in QBtu] Source: Own calculation using EIA energy data crude_rgdp A measure of crude oil production (IEA) divided by real gross domestic product (Heston et al. 2009) to measure size of oil producers relative to size of economy. Units: toe/000 constant 2005 PPP$ in rgdp Source: Own calculations using data from IEA (various volumes) and Heston et al. (2009). See note above.
net_crude_xp A measure of net crude oil exports (XP – IM) as a % total crude oil consumed [Crude oil XP-IM in ktoe] / [Crude oil Production + IM – XP in ktoe] *100 Source: own calculation using data from IEA World Energy Balances.
2. TRADE EXPOSURE openk Is a measure of total trade as a percentage of GDP in constant $ Source: Penn World Tables 6.3Notes: See Heston et al. for original variable definition. Exports plus imports divided by RGDPL (real gdp per capita Laspayeres). This is the constant price equivalent of the OPENC variable and is the total trade as a GDP. 3. ELECTORAL SYSTEM pr Measures the primary electoral rule for assigning seats to the lower chamber. Is a modified version of the variablecountry’s score a “1” if the majority of seatsrepresentation and “0” if plurality. Source: adapted from Keefer (2007) dis_gall Gallagher’s (1991) proposed system, by which scholars refer to “the difference between parties’ shares of the votes and their shares of the seats” (Gallagher and Mitchell, 2005: 602). The measure, now commonly used in the literleast squares index and is calculated as follows:
dis_gall =
where vi is the share of votes for party i, number of parties. The measure can be conceptualizedsystems, a small change in the share of the votes can produce a relatively large change in the share of seats allocated to individual parties (hence, they are considered to lead to “disproportional” electoral results). In contrast, the seatproportional systems is relatively inelastic
total trade as a percentage of GDP in constant $
Tables 6.3 (Heston et al. 2009). Notes: See Heston et al. for original variable definition.
Exports plus imports divided by RGDPL (real gdp per capita Laspayeres). This is the constant price equivalent of the OPENC variable and is the total trade as a percentage of
Measures the primary electoral rule for assigning seats to the lower chamber.
a modified version of the variable housesys from the DPI, that is recoded scountry’s score a “1” if the majority of seats are allocated based on proportional representation and “0” if plurality.
eefer (2007)
measure of disproportionality produced by an electoral system, by which scholars refer to “the difference between parties’ shares of the votes and their shares of the seats” (Gallagher and Mitchell, 2005: 602).
now commonly used in the literature on electoral systems, is known as the least squares index and is calculated as follows:
is the share of votes for party i, si is the share of seats for party I and m is the
The measure can be conceptualized as the seats-vote elasticity. In more disproportional systems, a small change in the share of the votes can produce a relatively large change in the share of seats allocated to individual parties (hence, they are considered to lead to
lectoral results). In contrast, the seat-vote relationship in more proportional systems is relatively inelastic – a small change in the share of votes will
254
Exports plus imports divided by RGDPL (real gdp per capita Laspayeres). This is the percentage of
Measures the primary electoral rule for assigning seats to the lower chamber.
that is recoded so that are allocated based on proportional
measure of disproportionality produced by an electoral system, by which scholars refer to “the difference between parties’ shares of the votes
ature on electoral systems, is known as the
is the share of seats for party I and m is the
vote elasticity. In more disproportional systems, a small change in the share of the votes can produce a relatively large change in the share of seats allocated to individual parties (hence, they are considered to lead to
vote relationship in more a small change in the share of votes will
255
produce a comparatively small change in the allocation of seats to parties (hence they are considered more “proportional”). Source: Armingeon et al. (2009) yr_dis_gall Is the 5 year moving average of dis_gall. The period 2002 to 2006 is only a 4 year average. For New Zealand the immediate average pre-reform is calculated from 1993 to 1995; then 1996 to 2000; and finally from 2001 to 2006. This is done to better capture the large difference in dis_gall between the two different electoral systems used. Source: Own calculations 4. PARTISANSHIP gov_left = cabinet composition: left wing parties in % total cabinet posts greenv = share of votes for all parties classified as green.202 = green1 + green2 + green3 greens = share of seats in the parliament for all parties classified as green. = sgreen1 + sgreen2 + sgreen3 green_party = dummy variable indicating presence (1) or absence (0) of green party in legislature (derived from greens). Source for above partisanship variables: Armingeon et al. 2009. See their appendix for categorization details. llc = percentage of cabinet portfolios in national government held by green/left libertarian (“new left”) parties (as defined by Kitschelt, 1994) and listed in Swank’s Appendix A1. llv = percentage of votes (lower chamber) for green/left-libertarian parties Note: these parties are mostly Greens. Source for left-libertarian variables: Swank (2007). 202 In some countries, there can be more than one party classified as “green.” Example: votes for the Green Party of Switzerland and the Green Alliance are added together for greenv.
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5. CONTROLS rgdp_pc = real gross domestic product per capita in constant (2005) USD Source: Penn World Tables v.6.3 (Heston et al., 2009) rgdp_pc_sq = square of rgdp_pc rural_pop = rural population (% of total population) Source: WDI pop_den = population density (people per square km) Source: WDI itax_rev = tax revenue from taxes on income, profit and capital gains as % total tax rev Source: OECD Revenue Statistics
itax_gdp = tax rev from taxes on income, profits and capital gains % gdp Source: see itax_rev Notes: category 1000, which includes taxes on individuals and corporations debt_gdp = total central government debt as % gdp Source: OECD Note: missing 1978-79 inf_cpi_all = general inflation rate – basket of all goods and services Source: OECD electy Election year; dummy variable coded 1 for years in which elections occurred, otherwise, 0. For US, both Congressional and Presidential election years are coded; for Fifth Republic in France, both Presidential and National Assembly elections are coded. For all other countries, national elections to the lower chamber of the national legislature are coded 1. Source: Swank (2009) and Armingeon et al. (2009)
257
Correlation matrix: IVs in coal tax regressions | coal_tax openk net_co~p coal_p~d corpor~m left_cab pr dis_gall pr_leftc left_dis -------------+------------------------------------------------------------------------------------------ coal_tax | 1.0000 openk | 0.1411 1.0000 net_coal_xp | -0.2578 -0.3666 1.0000 coal_prod | -0.2486 -0.3256 0.9177 1.0000 corporatism | 0.6610 0.5311 -0.4293 -0.3884 1.0000 left_cab | 0.6438 0.2519 -0.0073 -0.0077 0.5857 1.0000 pr | 0.3985 0.6075 -0.6211 -0.4910 0.7287 0.3490 1.0000 dis_gall | -0.3609 -0.4275 0.4584 0.3240 -0.6920 -0.1376 -0.8392 1.0000 pr_leftc | 0.7588 0.4975 -0.4830 -0.4128 0.8525 0.6328 0.8450 -0.7339 1.0000 left_dis | -0.1174 -0.2505 0.3824 0.2953 -0.3234 0.4174 -0.5158 0.7558 -0.3899 1.0000
Correlation matrix: IVs in heavy fuel oil tax regressions | hfo_tax openk net_cr~p crude_~d corpor~m left_cab pr dis_gall pr_leftc left_dis -------------+------------------------------------------------------------------------------------------ hfo_tax | 1.0000 openk | 0.0610 1.0000 net_crude_xp | 0.0326 -0.1527 1.0000 crude_prod | 0.2865 0.0285 0.7363 1.0000 corporatism | 0.4117 0.5447 -0.0179 0.3000 1.0000 left_cab | 0.6218 0.0427 0.0002 0.1813 0.3279 1.0000 pr | 0.3482 0.5405 -0.4079 0.0086 0.5721 0.3507 1.0000 dis_gall | -0.2201 -0.4346 0.3573 0.0246 -0.6796 -0.0619 -0.7857 1.0000 pr_leftc | 0.6799 0.2707 -0.2209 0.1773 0.5311 0.7020 0.8036 -0.5885 1.0000 left_dis | 0.0334 -0.3313 0.1895 0.0484 -0.4155 0.5181 -0.3937 0.7388 -0.1380 1.0000
Correlation matrix: IVs in diesel and gasoline tax regressions | crude_~p net_oi~p openk pr yr_dis~l gov_left llc llv greenv greens green_~m electy log_rg~c rural_~p pop_den itax_gdp debt_gdp -------------+--------------------------------------------------------------------------------------------------------------------------------------------------------- crude_rgdp | 1.0000 net_oil_xp | 0.6856 1.0000 openk | 0.0393 -0.1047 1.0000 pr | 0.0456 -0.3336 0.4761 1.0000 yr_dis_gall | -0.0021 0.2516 -0.2775 -0.6624 1.0000 gov_left | 0.1008 0.0251 0.0640 0.1982 -0.0546 1.0000 llc | -0.0732 -0.1428 0.1965 0.0948 -0.0411 0.1956 1.0000 llv | 0.2040 0.0759 0.4516 0.3211 -0.2555 0.0442 0.2626 1.0000 greenv | -0.2236 -0.3669 0.5061 0.2332 -0.1483 0.0567 0.4162 0.5690 1.0000 greens | -0.2016 -0.3519 0.5142 0.3285 -0.3606 0.1274 0.4207 0.5261 0.8920 1.0000 green_dum | -0.2395 -0.4270 0.5094 0.3086 -0.2841 0.0990 0.2901 0.4634 0.8310 0.8428 1.0000 electy | -0.0292 -0.0018 -0.0728 -0.0531 -0.0222 -0.0611 -0.0431 -0.0235 -0.0048 -0.0060 -0.0222 1.0000 log_rgdppc | 0.3658 0.3592 0.2627 -0.2030 -0.0056 -0.0377 0.1184 0.2632 0.2725 0.2665 0.2642 -0.0223 1.0000 rural_pop | -0.0873 -0.3667 -0.2389 0.2029 -0.0910 -0.1778 -0.0291 -0.3397 -0.2437 -0.1819 -0.1119 -0.0009 -0.3934 1.0000 pop_den | -0.2627 -0.4166 0.2771 0.1557 -0.2152 -0.1138 0.0737 0.1165 0.2699 0.2988 0.2998 -0.0199 0.0416 -0.0203 1.0000 itax_gdp | 0.1637 0.4636 0.2227 -0.0062 -0.2116 0.0477 0.0284 0.4563 0.0123 0.0291 0.0058 -0.0150 0.2404 -0.5803 -0.1951 1.0000 debt_gdp | -0.2527 -0.3500 0.2934 0.1243 -0.0642 -0.0106 0.0518 -0.0067 0.0498 0.0669 0.0896 -0.0158 -0.2053 0.0820 0.3165 0.0171 1.0000
258
Appendix 2: Operationalizing the dependent variable
The original data used to generate the dependent variables in this dissertation were
obtained from various volumes of the IEA’s quarterly publication, Energy Prices and
Taxes. A sample table from which the data are drawn appears below.
Table A.1: Tax rates on Unleaded Gasoline in Canada
Regular Unleaded (92 RON) Gasoline
(per litre) X-Tax Price Excise Tax GST Total Tax Total Price 2003 0.437 0.252 0.048 0.300 0.737 2004 0.508 0.254 0.053 0.307 0.815 2005 0.612 0.254 0.060 0.314 0.926 2006 0.661 0.260 0.064 0.324 0.985 Source: IEA (2008) Table A.2: Tax rates on Natural Gas in Switzerland
Natural Gas for Households (per 107 kilocalories GCV)
X-Tax Price Excise Tax GST Total Tax Total Price 2003 699.4 3.8 53.4 57.2 756.6 2004 704.2 3.8 53.8 57.6 761.8 2005 773.0 3.7 59.0 62.7 835.7 2006 887.1 4.3 67.7 72.0 959.1 Source: IEA 2008 These data are yearly averages based on statistics collected from national sources,
expressed in terms of national currency, in this case, Canadian dollars and Swiss Francs.
The fact that these data are expressed in units of national currency makes direct cross-
national comparison difficult. Moreover, the tax data are expressed in base units (e.g.
litres, tonnes, cubic metres), which are not directly comparable. For instance, in 2006, the
Canadian tax on gasoline ($0.324 Canadian dollars per litre) and the Swiss tax on natural
gas ($72 Swiss Francs per 107 kilocalorie) are not directly comparable, even though we
might want to compare them as taxes on carbon-based fuels.
259
The type of data summarized in Tables A.1 and A.2 present different options for
transforming energy tax data into meaningful and comparable data. Each option carries
with it unique advantages and disadvantages. Ultimately, the goal is to estimate the
“implicit tax on carbon,” and this goal is the standard against which each option is
assessed.
Percentage of Revenue. Much of the tax policy literature operationalizes tax data in
terms of revenues. For instance, scholars concerned with explaining cross-national
differences in tax burdens (Steinmo and Tolbert, 1998), or in the “tax revenue structure”
(Kato, 2003), have operationlized taxation in terms of revenues derived from a particular
tax, expressed as a proportion of total tax revenue, or gross domestic product (GDP). In
the area of the environment, the OECD, Eurostat and IEA have established data
collection protocols for the collection of environmental tax data, providing a measure of
the magnitude of environmental taxes as a proportion of total tax revenues and GDP
(Eurostat, 2001; OECD 2010).203 Using this kind of data, scholars have described the
structure of environmental taxation, expressed as a percentage of GDP (Barde and
Braathen, 2007), and explained variation in environmental tax revenues expressed in
terms of both total tax revenue (Ciocirlan and Yandle, 2003), and environmental tax
revenue per capita (Ward and Cao, 2010). Even the more descriptive work on carbon
taxes has also operationalized carbon tax policy using revenue data, giving some sense of
the relative magnitude of carbon taxes in the total tax system (Baranzini et al. 2000: 399
Table 2; Ekins and Barker, 2001: 341 Table 3.1).
To be sure, revenues derived from “environmentally-related” taxes can be interpreted as
indicators of the development of environmental protection over time and across countries
(Bruvoll, 2009: 3), the “environmental tax burden” (Ward and Cao, 2010), or for some,
even as an indicator of environmental concern (Ekins and Barker, 2001: 341). However,
tax revenues should not be taken as an indicator of the effectiveness of tax policy
(Barde and Braathen, 2007: 58). Moreover, as pointed out by Eismeier (1983) and others
203 This discussion sets aside Bruvoll’s (2009) concern that many of the taxes considered by the OECD, IEA and Eurostat to be “environmentally-related” are not environmental at all.
260
(Stults and Winters, 2004), tax revenues are not a reliable indicator of tax policy, or for
our purposes, of the effect of policy on the relative price of fossil fuels. Revenues from
taxes on carbon-based fuels will be strongly associated (correlated) with levels of
consumption, or that which the tax may actually be intended to deter. This is problematic
because the carbon tax component of total tax revenues will rise and fall with levels of
consumption, irrespective of what happens to policy. As such, the revenue approach does
not really provide a reliable measure of tax policy affecting the relative price of fossil
fuels, or crucially for the present study, a measure of the implicit tax on carbon.
Second, such an approach faces problems of internal validity as well. To be sure,
measuring a carbon tax in terms of its contribution to total tax revenue might be a good
indicator of the magnitude of taxes on carbon, relative to taxes on other goods, for a
particular country in a given year. However, expressing carbon tax levels in terms of
their contribution to total tax revenues seems to be a better measure of the dependence of
a particular state’s public purse on taxing carbon, rather than an indicator of
environmental protection. Indeed, as much of the recent political economy research on
environmental taxation now suggests (Svendson et al. 2000; Ciocirlan and Yandle, 2003),
including the present study, the purpose of environmental taxation, like all taxes, is
fundamentally to raise revenue.204
For these reasons, using tax revenues does not seem to be the best option for measuring
the effect of policy on the price of fossil fuels. If the purpose is to measure the implicit
carbon tax, it seems preferable to focus on actual tax rates.
Tax Rate in USD. One option is to convert tax data like that summarized in Tables A.1
and A.2, expressed in national currency per base unit, into the equivalent U.S. dollar
(USD) or Purchasing Power Parity (PPP). While the USD conversion essentially
converts price data into the equivalent USD using market exchange rates, PPPs convert
national currency into a common international currency, based on the relative
204 Svendsen et al. (2001: 497) take this argument further, suggesting that “many green taxes […] are merely fiscal taxes which have been labeled green taxes in order to legitimate them to the public.”
261
“purchasing power” of different currencies vis a vis a common basket of goods. The
transformation from national currency to USD is relatively straightforward, involving a
simple calculation using exchange rate information from sources like the IMF, and more
easily accessible through OECD and World Bank databases. Similarly, data on PPPs are
readily available from the Penn World Tables (Heston et al., 2009).
In cross-national research, monetary data are commonly converted to a common
currency, like USD (Ciocirlan and Yandle, 2003) or PPP (Rogowski and Kayser, 2002)
in order to provide a common metric that facilitates international comparison. Due to
wide fluctuations in international currency markets and in highly variable factor prices,
however, international price comparisons in USD and PPPs should be undertaken with
caution. Variables converted to USD may be highly sensitive to fluctuations in exchange
rates, which are determined by market forces and monetary policy (IEA, 2008: 48).
Similar caution is warranted when using PPPs. While PPPs assume that prices for
internationally traded goods should be the same anywhere in the world once they are
expressed in a common currency (i.e. the Law of One Price), the reality is that not all
inputs going into the production of goods and services are traded internationally. As a
result, estimates of PPP may be sensitive to a host of domestic factors that vary from
country to country, producing an imperfect conversion ratio (Taylor and Taylor, 2004).
Notwithstanding these issues, USD and PPPs are the best “international” currencies
available for macro-comparative research. In the absence of an alternative, and consistent
with the comparative economics and political science literature, the present research uses
standardized data in USD and PPP. Moreover, as recommended by a recent OECD
(2010) study, using multiple base currencies can act as a check against bias created by
market exchange rates. Following this advice, I estimate separate regressions using
variables converted to both USD and PPPs as a check for robustness across models.205
205 In addition, exchange rate and PPP conversion ratios can be included in empirical models to control for any independent influence they might have.
Tax Component. In light of the potential
PPP, and alternative approach to standardizing IEA tax data is to take the proportion of
tax in the total price paid by consumers for a particular fuel. For instance, using the data
in Tables A.1 and A.2, it is po
for a particular fuel, using the following formula:
Tax Component =
Where: totaltax(t), is the total tax levied on a fuel at time t;
totalprice(t), is the total price of a fuel at tim
The above formula gives the percentage of
of a particular fossil fuel. Although the option of including or excluding VAT is
available (since the data as summarized in Tables A.1 and A.2 differentiate b
excise and VAT), I think it is
have the same effect on total price, and therefore, consumption.
The advantage of this measure is that it allows for cross
reliance on exchange rates, thus avoiding the potential sensitivity of the measure
fluctuations in international monetary
cost. Relative to energy prices,
time, and often remain constant
market fluctuations in energy prices, and inflation, will have an independent effect on the
“tax component” measure, irrespective of what happens to the tax ra
206 On the other hand, one might be solely interested in excise taxes, and it would therefore bedisaggregate as much as possible (Thanks to Steven Bernstein for raising this point). For instance, the reasons for governments levying VAT may bwant to analyze them seperately. Though this might be true, I would argue that if the purpose is to estimate and explain the implicit carbon price, VAT should be accounted for, since it too will affeccarbon. 207 For instance, if the formula above is applied to the data in the Table 4.1, it appears as though the tax component falls from 38% to 34% between the years 2004 and 2005. However, during this time, the
In light of the potential problems associated with data in USD and
PPP, and alternative approach to standardizing IEA tax data is to take the proportion of
tax in the total price paid by consumers for a particular fuel. For instance, using the data
in Tables A.1 and A.2, it is possible to calculate the tax component in the final price paid
for a particular fuel, using the following formula:
*100
is the total tax levied on a fuel at time t;
is the total price of a fuel at time t
The above formula gives the percentage of total tax (i.e. VAT + excise) in the
. Although the option of including or excluding VAT is
as summarized in Tables A.1 and A.2 differentiate b
excise and VAT), I think it is preferable to use total tax (including VAT), since VAT will
have the same effect on total price, and therefore, consumption.206
The advantage of this measure is that it allows for cross-national comparison without
thus avoiding the potential sensitivity of the measure
fluctuations in international monetary markets. This advantage, however, comes at a
cost. Relative to energy prices, tax rates on energy products change very slowly o
time, and often remain constant from one year to the next. In this context, such factors as
market fluctuations in energy prices, and inflation, will have an independent effect on the
“tax component” measure, irrespective of what happens to the tax rate or tax policy.
On the other hand, one might be solely interested in excise taxes, and it would therefore begregate as much as possible (Thanks to Steven Bernstein for raising this point). For instance, the
VAT may be different than reasons for excise taxes, therefore one may Though this might be true, I would argue that if the purpose is to estimate
and explain the implicit carbon price, VAT should be accounted for, since it too will affect the price of
For instance, if the formula above is applied to the data in the Table 4.1, it appears as though the tax component falls from 38% to 34% between the years 2004 and 2005. However, during this time, the
262
problems associated with data in USD and
PPP, and alternative approach to standardizing IEA tax data is to take the proportion of
tax in the total price paid by consumers for a particular fuel. For instance, using the data
in the final price paid
the total price
. Although the option of including or excluding VAT is
as summarized in Tables A.1 and A.2 differentiate between
preferable to use total tax (including VAT), since VAT will
national comparison without
thus avoiding the potential sensitivity of the measure vis a vis
. This advantage, however, comes at a
tax rates on energy products change very slowly over
. In this context, such factors as
market fluctuations in energy prices, and inflation, will have an independent effect on the
te or tax policy.207 In
On the other hand, one might be solely interested in excise taxes, and it would therefore be better to gregate as much as possible (Thanks to Steven Bernstein for raising this point). For instance, the
, therefore one may Though this might be true, I would argue that if the purpose is to estimate
t the price of
For instance, if the formula above is applied to the data in the Table 4.1, it appears as though the tax component falls from 38% to 34% between the years 2004 and 2005. However, during this time, the
263
fact, excise taxes and VAT have declined in real terms over time, since it is difficult for
governments to change tax rates on energy consumption each year to keep pace with
inflation. Using this measure might increase within panel variance in the estimate of the
size of energy taxes (relative to total price), when no changes to policy occur. On
balance, it would seem as though the noise created by using exchange rates and PPPs is
less severe than this possibility. Indeed, the “tax component” seems a better measure of
the potential erosion of real tax revenues (as opposed to the implicit carbon tax), since it
is not automatically adjusted for inflation/deflation.208 While an analysis of how closely
governments adjust energy tax rates for inflation is an interesting question, it is only
tangentially related to the present concern with taxing carbon. Future work may wish to
pursue this question.
Tax Policy Change (i.e. change in the nominal tax rate). To the extent that the present
analysis is interested in tax policy, and not the erosion of the tax rate, the focus can
legitimately be with the nominal tax rate, which is not adjusted for inflation. Here the
analysis is simplified in that policy changes are changes in the nominal rate, so the focus
of the study should be on years in which there is a change to the nominal rate. Using a
simple formula to calculate year to year percentage change, units of measurement are
washed out, eliminating the problem of cross-national comparison using national
currency data. However, the primary purpose of this study is to provide an estimate of
the implicit price on carbon, not changes in tax policy over time. The tax policy change
variable will be analyzed in future work, once broad trends in the data are identified, and
the original research questions of this dissertation are answered.
average excise tax remained unchanged at $0.254 Canadian dollars per litre. The reason for the fall in the tax component has to do with the fact that the tax rate did not keep up with inflation. 208 The question answered by the “tax component” measure is essentially the following: given changes in energy markets, is the tax becoming more/less important as a determinant of price? To be sure, this question has important implications for policy. For instance, the ratio between tax and price can generate opposing forces. If the price goes up, there is pressure for tax relief, but there is also an incentive for government to maintain the “real” tax rate. The potential erosion in “real” tax rates is a good reason why governments are ill-advised to set taxes at fixed rates, since adjusting tax rates might be politically difficult if visible to the tax payer. As a result, automatic adjustment mechanisms might be preferred, from a political standpoint. My thanks to Donald Dewees for raising this issue.
264
Tax per tonne of CO2 (implicit carbon tax). A final option that is used in this dissertation
is to develop an estimate of the implicit carbon tax for each type of fuel. This approach
involves first standardizing tax rates in constant (2000) U.S. dollars (or PPPs), using
market exchange rates, then deflating by country-specific consumer prices. Next,
standardized tax rates (e.g. constant USD/base unit) are divided by corresponding
emission factors for each type of fuel, in order to transform the tax rate into from a tax
per unit to a tax per tonne of CO2.
To calculate the tax rate on a tonne of carbon dioxide, original tax rate (expressed in
terms of constant USD/unit of fuel) are divided by the corresponding emission factor for
that particular fuel. This gives the tax rate per unit of carbon. Depending on whether the
emission factor is given for Kg or metric tonne, an additional multiplication procedure is
required to ensure the tax rate is per tonne of CO2, as opposed to Kg.
For instance, to calculate the implicit carbon tax for motor fuels, tax rates (in USD) are
divided by the CO2 emissions from gasoline (2.32 Kg of CO2/litre) and diesel (2.66 Kg of
CO2/litre), which gives an estimate of the implicit carbon tax per kilogram of CO2.209
This figure is then multiplied by 1000, to express the tax in terms of per metric tonne of
CO2. The result is a standardized measure of the tax, in USD, per metric tonne of CO2
emitted into the atmosphere. Such a conversion allows for comparison across different
fuels with different carbon contents and different units of measurement (e.g. tones of coal
vs. litres of diesel fuel).
Example: If tax on a litre of gasoline is taxed at a rate of USD $0.28/litre (or the tax rate
in Canada in 2007), then the corresponding tax rate on a tonne of carbon dioxide is:
[0.28/2.32]*1000
= USD $120.69
209 These figures are generated from the EPA (2005: 1-2), which provide estimates of CO2 emissions from gasoline and diesel motor fuels using the method recommended by the IPCC. The original figures, expressed in gallons, are converted to litres by the following formula: 1 gallon = 3.8 metric litres.
265
Thus, a tax of $0.28 USD per litre is equivalent to a carbon tax of $120.69 per tonne of
carbon dioxide. These transformed measures give a sense of the tax rate on a given fuel
(in this case, gasoline), in constant (2000) USD, per tonne of CO2 emitted, and are
directly comparable across countries, fuels and sectors.
266
Appendix 3: Emission factors Emission Factor Units Coal210 2.77 tCO2/tonne Heavy fuel oil211 2.955 tCO2/kilolitre Light fuel oil 2.642 tCO2/kilolitre Diesel 0.00269 tCO2/litre Gasoline 0.00232 tCO2/litre Natural gas 2.34 tCO2/10
7kilocalories (GCV) Source: IPCC (1996) and IEA (2008a)
IPCC Emission Factors Emission Factor (tCO2) Unit Coal British Columbia 2.766 tonne Denmark 2.717 tonne Finland 2.364 tonne Netherlands 2.766 tonne Norway 2.605 tonne Sweden 2.490 tonne HFO 3.078 tonne HFO 2.955 kl LFO 2.642 kl Diesel 0.00269 l Gasoline 0.00232 l Natural gas 2.1 107 kcal Natural gas 0.001954 m3 Notes: calculated using default emission factors in revised 1996 IPCC Guidelines; adjusted for cross-national variation in chemical makeup and quality of fuels using country-specific calorific values from the IEA. EIA Emission Factors Emission Factor (tCO2) Unit Coal 2.471 tonne HFO 3.26 tonne HFO 3.126 kl LFO 2.69 kl Diesel 0.00269 l Gasoline 0.00235 l Natural gas 2.08 107 kcal Natural gas 0.001936 m3 Notes: using standard EIA emission factors assuming coal is bituminous (most commonly used type in OECD, exceptions are the predominant use of anthracite in the Netherlands and Norway, which means estimates of their tax rates are over-estimated to a small extent when these emission factors are used)
210 For coal, an emission factor for bituminous is used. Bituminous coal is the most commonly consumed type of coal in the OECD. 211 If converted to tCO2/tonne, the emission factor for HFO is 3.078. It is higher than the emission factor for coal due to the fact that HFO is a denser form of energy. Conversely, on an energy unit basis, which is the more common way to measure carbon content, coal is the dirtiest fuel, containing more carbon per TJ. On a per energy unit basis, coal is “dirtier” because more tonnes of coal must be burned in order to get the same amount of energy as from burning a tonne of HFO.
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