MASTER IN TOURISM AND ENVIRONMENTAL

ECONOMICS

END OF MASTER PROJECT

INTRODUCING INSTITUTIONAL VARIABLES IN

THE ENVIRONMENTAL KUZNETS CURVE (EKC):

A LATIN AMERICAN STUDY

By

Italo Raul Abraham Arbulú Villanueva

June 2010

INTRODUCTION

Introduction

� A key policy objective of international efforts:Reduction of global CO2 emissions.

� Over the last years several studies used theEnvironmental Kuznets Curve (EKC) hypothesis toevaluate the impact of several economic variables onenvironmental indicators.

� The main objective of this work is to understand andmeasure the possible impacts of changes in institutionalquality indices and income on the environment using theEKC hypothesis for a sample of 18 Latin Americancountries.

Why Latin America?

Reasons

Important contribution that natural

resources and environmental services

have in the productive structure of these

countries

Several institutional performance

indicators in the region are considered

fairly low compared to developed

countries

What is new about this study?

Few studies � Analysis of

the impact of democracies

(civil liberties and political

rights) on economic behavior.

Attention on the performance

and effectiveness of

democracies (quality)

Unique variable �

Democratic Index

(Freedom House)

6 new institutional

indexes related to

democratic behavior

(World Bank)

Measuring Institutional Quality

Voice and Accountability (VAI)Citizens are able to participate in

elections, as well as freedom of

expression, association and media.

Political Stability and Absence

of Violence (PSI)

Government Effectiveness (GEI)

Regulatory Quality (RQI)

Rule of Law (RLI)

Control of Corruption (CCI)

Likelihood that the government will be

destabilized or overthrown by

unconstitutional or violent means.

Quality of public services, quality of

policy formulation and

implementation.

Ability of the government to

formulate policies that promote

private sector development.

Agents have confidence in the quality

of enforcement and property rights.

Perceptions of the extent to which

public power is exercised to avoid

rent-seeking behavior.

LITERATURE REVIEW

Economic Growth and Pollution

� THE ENVIRONMENTAL KUZNETS CURVE

�Grossman and Krueger (1995)� Relationship between

per capita income and environmental degradation

takes an inverted U shaped form.

Economic Growth and Pollution

� THE ENVIRONMENTAL KUZNETS CURVE

�Why this form?.

Scale EffectAs economic development accelerates

waste generation increases in quantity

and toxicity

Composition Effect

Technology Effect

The service sector may grow relative

to the manufacturing sector � change

the pollution intensity of output.

sectors of the economy may adopt less

polluting technologies � technological

advance or government regulation

Economic Growth and Pollution

� THE ENVIRONMENTAL KUZNETS CURVE

�Grossman and Krueger (1995)

� The strongest link between income and pollution is, in fact,

via an induced policy response.

� Policies are in turn induced by popular demand: As nations

or regions experience greater prosperity, their citizens

demand that more attention should be paid to the

noneconomic aspects of their living conditions.

INSTITUTIONS

MATTER?

Institutions and the Environment

� Payne (1995)

� Theoretical treatise in favor of a positive impact ofdemocracy on the environment.

� In democracies citizens:

� Are better informed about environmental problems (freedom ofpress).

� Can express better their environmental concerns and demands(freedom of speech),.

� Facilitate an organization of environmental interests (freedom ofassociation)

� Increase pressure on policy entrepreneurs operating in acompetitive political system to respond positively to thesedemands (freedom of vote).

Institutions and the Environment

� Fredriksson (1997)

� Analize the effects of political instability and corruption in

environmental policy formation in a three stage model.

� The incumbent government weighs bribes (established as

“political contributions”) and the aggregate social welfare

derived from the outcomes of environmental policies.

� As a conclusion the author establishes that:

� Corruption reduces the stringency of environmental

regulations.

�When the degree of political instability increase the

incentive to offer bribes is reduced.

Institutions and the Environment

� López and Mitra (2000)

� Theoretical model to analyze the impact of corruption on

environmental outcomes.

� The only goal of political parties is to repeat the rewards of

holding office (win the elections)

� Government maximizes a function which depends on its

probability of being re-elected as well as on rents.

� “π” is the probability of being re-elected, “c” represent the lobby

payments

Institutions and the Environment

� López and Mitra (2000)

� The main conclusions of this model are:� An inverted-U-shaped relationship between income and pollution willexist.

� Irrespective of the type of interaction between the firm and thegovernment (cooperative or non-cooperative), for any level of percapita income, pollution levels are always above the socially optimallevel when corruption exists.

� Unless economic growth process brings about a rapid reduction ofcorruption in developing countries, pollution will remain much higher inthese countries than the levels reached in currently developed oneseven when their per capita incomes were comparable.

METHODOLOGY

Econometric Technique: Pool Model

� A general formulation of the pool model can be

expressed as:

• : Dependent variable.

• : Notation to represent a given country.

• : Notation to represent a given explanatory variable.

• : Notation to represent a given period of time.

• : Constant term.

• : Vector of coefficients.

• : Matrix of explanatory variables.

• : Random error term.

Econometric Technique: Models

BASIC MODELregressing per capita CO2 emission on

GDP per capita and GDP per capita

squared .

EXTENDED MODEL Nº 1

EXTENDED MODEL Nº 2

Basic Environmental Kuznets Curve

formulation plus a series of additional

economic variables .

Extended Model Nº 1 plus the set of

institutional variables.

Extended Models aim to capture the main characteristics of the economy and,

therefore, the heterogeneity of the countries analyzed

DATA SOURCES

Variables

CODE VARIABLE UNIT SCALE SOURCE

VAI Voice and Accountability Index IndexRanging from about -2.5 to 2.5, with higher values

corresponding to better governance outcomes.World Bank

PSIPolitical Stability & Absence of Violence/Terrorism

IndexIndex

Ranging from about -2.5 to 2.5, with higher values

corresponding to better governance outcomes.World Bank

GEI Government Effectiveness Index IndexRanging from about -2.5 to 2.5, with higher values

corresponding to better governance outcomes.World Bank

RQI Regulatory Quality Index IndexRanging from about -2.5 to 2.5, with higher values

corresponding to better governance outcomes.World Bank

RLI Rule of Law Index IndexRanging from about -2.5 to 2.5, with higher values

corresponding to better governance outcomes.World Bank

CCI Control of Corruption Index IndexRanging from about -2.5 to 2.5, with higher values

corresponding to better governance outcomes.World Bank

POP Total Population Hab. 1000 hab. FAO

GDP Gross domestic product, current prices U.S. dollars (Billions) Billion of US$ IMF

GDPPC Gross domestic product per capita, current prices U.S. dollars IMF

GDPPCPPPGross domestic product based on purchasing-power-

parity (PPP) per capita GDPCurrent international dollar IMF

UNEMP Average annual unemployment rate Percentage CEPAL

RURP Rural Population Hab. 1000 hab. FAO

RURPR Rural Population % of total population FAO

EXDBT External Debt US$ Millions of US$ CEPAL

INF Inflation PercentageData for inflation are averages for the year, not end-of-

period data.IMF

CO2 CO2 Emissions per capita metric tons per capita World Bank

The Sample

� Sample:18 countries from Latin AmericaPaís / Área COD FAO COD WB COD FMI

Argentina 9 ARG 213

Bolivia 19 BOL 218

Brasil 21 BRA 223

Colombia 44 COL 233

Costa Rica 48 CRI 238

Chile 40 CHL 228

Ecuador 58 ECU 248

El Salvador 60 SLV 253

Guatemala 89 GTM 258

Honduras 95 HND 268

México 138 MEX 273

Nicaragua 157 NIC 278

Panamá 166 PAN 283

Paraguay 169 PRY 288

Perú 170 PER 293

República Dominicana 56 DOM 243

Uruguay 234 URY 298

Venezuela (República Bolivariana de) 236 VEN 299

Time Period

� The analysis used the 1998-2005 since there were

no previous estimation of institutional variables.

VAI PSI RQI RLI CCI GEI

Country COD FAO COD WB COD FMIAverage 1996 -2008

Average 1996 -2008

Average 1996 -2008

Average 1996 -2008

Average 1996 -2008

Average 1996 -2008

Argentina 9 ARG 213 0.2776 -0.0901 -0.2671 -0.3394 -0.2838 -0.0503

Bolivia 19 BOL 218 0.0339 -0.4762 -0.2124 -0.4921 -0.5158 -0.3861

Brasil 21 BRA 223 0.4942 -0.1142 0.1318 -0.2519 -0.0342 -0.0529

Colombia 44 COL 233 -0.2208 -1.3403 0.0979 -0.5670 -0.2783 -0.0870

Costa Rica 48 CRI 238 0.7127 0.6007 0.4377 0.4338 0.4581 0.2885

Chile 40 CHL 228 0.8169 0.5256 1.0951 0.9356 1.0410 0.9208

Ecuador 58 ECU 248 -0.2070 -0.6390 -0.4825 -0.6086 -0.6639 -0.6358

El Salvador 60 SLV 253 0.0561 -0.0589 0.1372 -0.4173 -0.2409 -0.2120

Guatemala 89 GTM 258 -0.2167 -0.6020 -0.0951 -0.7533 -0.5445 -0.3932

Honduras 95 HND 268 -0.1204 -0.3244 -0.2616 -0.6307 -0.5803 -0.4373

México 138 MEX 273 0.1515 -0.2611 0.3228 -0.3517 -0.2437 0.1147

Nicaragua 157 NIC 278 -0.0571 -0.2327 -0.2284 -0.5655 -0.4779 -0.5751

Panamá 166 PAN 283 0.4763 0.1029 0.3781 -0.1191 -0.2844 0.0282

Paraguay 169 PRY 288 -0.4213 -0.5144 -0.3913 -0.7314 -0.8666 -0.6229

Perú 170 PER 293 -0.0555 -0.6914 0.2050 -0.5006 -0.1757 -0.2807

República Dominicana 56 DOM 243 0.1038 -0.0179 -0.1271 -0.4427 -0.4151 -0.3058

Uruguay 234 URY 298 0.8589 0.5144 0.3368 0.3817 0.6547 0.3172

Venezuela (República Bolivariana de) 236 VEN 299 -0.4544 -0.7863 -0.6861 -0.8794 -0.7591 -0.6080

REGION AVERAGE 0.1238 -0.2447 0.0217 -0.3278 -0.2339 -0.1654

EMPIRICAL FINDINGS

Econometric Results

Dependent Variable: CO2 Emissions

Linear estimation after one-step weighting matrix

White cross-section standard errors & covariance (d.f. corrected)

INDEPENDENT VARIABLE

Coefficient t-Statistic Coefficient t-Statistic Coefficient t-Statistic

Constant 0.036332 0.759852 0.053741 0.836159 -0.571314 -4.08082***

GDPPC 0.000839 17.44645*** 0.000908 18.64481*** 0.0007 10.93161***

GDPPC^2 -4.57E-08 -7.154299*** -7.37E-08 -9.084384*** -3.49E-08 -3.012249***

RURP -2.89E-05 -4.003441*** -5.35E-05 -7.85784***

EXDBT 1.12E-05 9.053483*** 1.04E-05 9.940891***

INF 6.30E-06 1.031276 0.007472 6.27357***

UNEMP -0.249857 -0.900385 0.244624 0.321209

CCI -0.501422 -3.302914***

CCI 2 0.745271 9.907683***

PSI -0.104618 -1.779556***

VAI -0.238984 -15.97884***

GEI 0.607658 2.679024***

RQI -0.105945 -1.185813

RLI -0.273657 -2.378383***

WEIGHTED STATISTICS

R-squared

Adjusted R-squared

F-statistic

UNWEIGHTED STATISTICS

R-squared

* Significance at 10%

** Significance at 5%

*** Significance at 1%

BASIC MODEL EXTENDED MODEL Nº 2EXTENDED MODEL Nº 1

0.664879

464.2624***

0.666314

0.413158 0.6513

0.768356

0.739676

26.79089***

0.748843

0.745378

216.1635***

0.459292

EKC

Econometric Results

� CCI: Quadratic relationship between the pollution and the level ofcorruption as López and Mitra proposed.

� PSI: Negatives Relationship with CO2 � Did not confirm the ideaproposed by Fredriksson.

� VAI: Negatives Relationship with CO2 � confirm the ideas of Payne.

� GEI: Positive Relationship with CO2 � More efficiency in theallocation of resources would lead to an increase in factorsproductivity� Increase production (increase emissions).

� RLI: Negatives Relationship with CO2 � confirm the ideas of Deaconand Mueller (enforcement capacity of governments will lead tobetter environmental quality).

Graphical Analysis

� The estimation of the

Environmental Kuznets

Curve with only

economic variables

(Extended Model Nº 1)

gave biased estimators

� This would explain the

big difference in the

value of the turning

point.

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

72

7

1,5

80

2,4

33

3,2

85

4,1

38

4,9

91

5,8

44

6,6

97

7,5

50

8,4

03

9,2

56

10

,10

9

10

,96

2

CO

2E

mis

sio

n

GDPPC

Environmental Kuznets Curve

Basic Model

Extended Model Nº 1

Extended Model Nº 2

Basic ModelExtended

Model Nº 1Extended

Model Nº 2Turning Point

(US$) 9,256 6,058 10,109

Contrast with other studies

Source Author Region Period Dependant Variable

Additional Explanatory Variables

Turning Point

Almeida and

Sabadini

Moomaw and Unhruh

(1997)16 countries 1950-1992 CO2 Emissions none $12,813

Almeida and

Sabadini

Agras and Chapman

(1999)34 countries 1971-1989 CO2 Emissions

Trade variables and

temporally lagged

dependent variable

$13,630

Almeida and

Sabadini

Dijkgraaf and

Vollebergh

(2001)

OECD countries 1960-1997 CO2 Emissions none $15,704 and $13,959

Almeida and

Sabadini

Almeida and

Sabadini167 countries 2000-2004 CO2 emissions

Cubic GDP per

capita, KPt Kyoto

Protocol dummy,

Sum of imports and

exports (over total

GDP by country),

energy consumption

and population

US$ 10,193.68 and

US$ 13,484.85

Bhattarai and

Hammig

Bhattarai and

Hammig

(2001)

Latin America

(20 countries)1972-1991 Deforestation rate

Political institution

index (WRI), black

market foreing

exchange rate,

external debt,

population, rural

population, change in

cerial yield index

$ 6,600

Brajer, Mead and Xiao

(2008)China (128 cities) 1990–2004 SO2 Emission Time trend $ 7,793

Brajer, Mead and Xiao

(2008)China (128 cities) 1990–2004 SO2 Emission

Time trend, dummy

for coast zone and

dummy for cities in

the north

$ 6,766

Brajer, Mead and Xiao

(2008)China (128 cities) 1990–2004 SO2 Emission

Time trend, GDP

cubic$ 4,765

Brajer, Mead and Xiao

(2008)China (128 cities) 1990–2004 SO2 Emission

Time trend, GDP

cubic, dummy for

coast zone and

dummy for cities in

the north

$ 4,429

Lee, Chiu

and SunLee, Chiu and Sun

(2010)97 countries 1980-2001 Water Polution

GDP cubic, trade and

population and

lagged dependant

variable

$ 13,956

Selden and Song

(1993)30 countries

1973-1975, 1979-

1981, 1982-1984SO2 Emission

Population density

and period effects

dummies

$ 10,292

(1985 US Dollars)

Selden and Song

(1993)31 countries

1973-1975, 1979-

1981, 1982-1985SO2 Emission

period effects

dummies

$ 10, 681

(1985 US Dollars)

Selden and Song

(1993)32 countries

1973-1975, 1979-

1981, 1982-1986CO2 Emission

Population density

and period effects

dummies

$ 15,741

(1985 US Dollars)

Selden and Song

(1993)33 countries

1973-1975, 1979-

1981, 1982-1987CO2 Emission

period effects

dummies

$ 19,092

(1985 US Dollars)

Brajer, Mead

and Xiao

Selden and

Song

The results obtained

by other authors do

not vary considerably

from the results of the

three models.

We can consider that

these turning points

belong to a

reasonable range

The Importance of Institutions

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

-2.5

-2.2

-1.9

-1.6

-1.3

-1.0

-0.7

-0.4

-0.1

0.2

0.5

0.8

1.1

1.4

1.7

2.0

2.3

CO

2 E

mis

sio

n

INDEX

Estimated CO2 Emissions

(Related Institutional Variable)

CCI

PSI

VAI

RQI

RLI

GEI

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

-2.5 -2.2 -1.9 -1.6 -1.3 -1.0 -0.7 -0.4 -0.1 0.2 0.5 0.8 1.1 1.4 1.7 2.0 2.3

CO

2 E

mis

sio

n

CCI

Estimated CO2 Emissions

(Related to Corruption)

Even though five of these

variables obtained a coefficient

value statistically different from

zero, not all of these variables

have the same impact over

environmental quality.

CCI showed a quadratic form

this means that an improvement

of 0.1 units on this variable

would lead to higher

improvement on environmental

quality for the most corrupt

countries.

CONCLUSIONS

Conclusions

� As worldwide environmental quality degenerates over time, manycountries are beginning to be concerned about the determinants ofenvironmental degradation.

� Empirical results for Latin American countries support the EKChypothesis (inverted U-shaped relationship) for per capita CO2emissions and per capita GDP for the three models.

� Extended Model Nº 2 was considered the most appropriate toexplain the EKC theory since it corrected the bias generated by theomission of relevant explanatory variables.

� The empirical findings also attempted to test the theoreticalexplanation made by Payne, López and Mitra, Fredriksson andDeacon and Mueller regarding to environmental impacts ofinstitutional improvements.

Main Contributions of the Study

� ECONOMIC RESEARCH � There is a significant

relationship with institutional variables (that measure

government performance) which should be taken into

account in future researches.

� PUBLIC POLICY � These results should be considered

in public policy assessment as additional benefits

from institutional improvement.

� Decision variable when resources from international

cooperation are allocated into developing countries.

In sum…

� The main conclusion of this paper is that economic

growth does not guarantee the cure for the world’s

environmental problems.

� Proper institutional performance on environmental

policies have a fundamental role in the reduction of

greenhouse gases emission in the world.

In sum…

The solution is still in our hands…GET INVOLVED!

THANK YOU FOR YOUR ATTENTION

MASTER IN TOURISM AND ENVIRONMENTAL

ECONOMICS

END OF MASTER PROJECT

INTRODUCING INSTITUTIONAL VARIABLES IN

THE ENVIRONMENTAL KUZNETS CURVE (EKC):

A LATIN AMERICAN STUDY

By

Italo Raul Abraham Arbulú Villanueva

June 2010