Energy Poverty in Japan

How does the energy price escalation affect low income and vulnerable households?

Shinichiro OKUSHIMA * and Azusa OKAGAWA #

* University of Tsukuba #National Institute for Environmental Studies

32nd USAEE/IAEE North American Conference

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Contents

I. Introduction Motivation

II. Energy poverty Concept and definition

III. Methodology Model and microdata

IV. Results Energy price escalation Energy price escalation & countermeasure

V. Conclusion

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Introduction: motivation

Increasing concern about energy/fuel poverty in Japan

Energy costs are soaring More dependent on fossil fuel imports after the Fukushima accident Introduction of a feed-in tariff scheme A new tax on fossil fuels (a carbon tax) in October 2012 Raising the consumption tax twice by 2015 A weak yen, etc.

Share of low-income households is increasing Reflecting Japan’s aging and sluggish economy since the 1990s Deteriorating job quality Vulnerable households (e.g., lone-parent-with-dependent children,

elderly, and single-person households) are also increasing

Energy poverty could be an important political issue in Japan

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Introduction: motivation

This study examines the energy poverty issues in Japan by the applied / computable general equilibrium model the microdata on the Japanese household

This study analyzes the impact on households when energy prices are doubled the effectiveness of an alleviation policy (a kind of social tariffs)

This study empirically shows the severe impacts especially on low-income or vulnerable households An alleviation policy will be effective when the energy price escalation

goes forward in the future

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Energy poverty: concept and definition

To date, much less attention has been given to the energy poverty problem in developed countries compared with developing countries The lack of access to modern types of energy (e.g., electricity) is the

focal point in the context of energy poverty in developing countries (e.g., IEA, 2010)

Only a few studies for developed countries except the UK In the UK, since Boardman’s (1991) seminal work, several studies

have been made• Various reports are published by the UK government such as the Hills fuel

poverty review (2011, 2012)• The recent literature on the UK; e.g., Chawla and Pollitt (2013), Moore (2012),

and Waddams Price et al. (2012)

However, no research has been found that examined the energy poverty problem in Japan in detail

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Energy poverty: concept and definition

Energy poverty can be defined conceptually as the condition of lacking the resources necessary

to meet their basic energy needs

A similar definition by Bouzarovski et al. (2012) the condition wherein a household is unable to access

energy services at the home up to a socially and materially necessitated level

In developed countries like Japan, broader issues that prevent people from satisfying their basic energy needs should be the focus of the energy poverty problem

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Energy poverty: concept and definition

Energy poverty can be measured practically by the two steps like the general income poverty measurement (Sen, 1979) “Identification”- who are the poor? “Aggregation” - how are the poverty characteristics of different people

to be combined into an aggregate measure?

For simplicity, this study defines energy poverty households as those that spend more than 10% of their income on energy expenses (electricity, gas, and heating oil) “Identification” (poverty line) – energy budget share, 10% “Aggregation” - identifying the extent of poverty in the society

simply with the proportion of the “poor” to the total population

Energy poverty:

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Energy poverty: concept and definition

The definition is similar to the UK government’s one However, the energy expenses in this study are actual ones based on

our microdata, rather than the calculated ones like the UK.

Identification (setting the poverty line) and aggregation are controversial but necessary tasks Energy budget shares have often been used for the poverty lines

(Pachauri et al., 2004). However, this simple “10% ratio” measure has various problems,

e.g., it pays no attention to the “depth” of poverty- the “10% ratio” measure evaluates the marginally poor as the same as

the miserably poor- Future research is needed for the definition

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Methodology: an applied/computable GE model

Many studies point out that economic impacts cannot be evaluated correctly without using general equilibrium models (e.g., Hazilla and Kopp, 1990)

Hence, this study develops an applied/computable general equilibrium model with multihouseholds characterized by their income levels on the Japanese economy The model is composed of 10 households, 40 industries, a government

and 48 commodities (9 fossil fuels)

The model’s parameters are calibrated to the 2005 base year social accounting matrix (SAM) the data sources: the most recent 2005 Input–Output Tables,

the 2005 Family Income and Expenditure Survey, etc.

Methodology: an applied/computable GE model

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  Industry (40)   Commodity （ 48 ）1 AGR Agriculture 1 AGR Agriculture2 MIN Mining 2 MIN Mining3 COG Coal, oil and gas 3 COL Coal      4 OIL Crude oil      5 GAS Gas4 FDP Food 6 FDP Food5 TEX Textiles 7 TEX Textiles6 WPP Paper and pulp 8 WPP Paper and pulp7 CHE Chemicals 9 CHE Chemicals8 O_P Oil products 10 GSL Gasoline      11 JET Jet fuel      12 KRS Heating oil      13 LGH Light gas oil      14 FOA Bunker A      15 FOC Bunker B&C      16 NPH Naphtha      17 LPG Liquid petroleum gas      18 OOP Other oil products9 C_P Coal products 19 C_P Coal products

10 PLR Plastics 20 PLR Plastics11 CLY Cement 21 CLY Cement12 STL Iron and steel 22 STL Iron and steel13 MTL Non-ferrous metal 23 MTL Non-ferrous metal14 MTP Metal products 24 MTP Metal products15 MCH Machinery 25 MCH Machinery16 ELM Electrical machinery 26 ELM Electrical machinery17 TRM Transport equipment 27 TRM Transport equipment18 OMF Other manufacturing 28 OMF Other manufacturing19 CNS Construction 29 CNS Construction

  Industry (40) cont   Commodity （ 48 ） cont20 NUC Nuclear electricity supply 30 ELY Electricity21 THM Thermal electricity supply      22 HYD Hydro electricity supply      

23 OWPPrivately owned power generation

31 OWPPrivately owned power generation

24 GHS Gas supply 32 GHS Gas supply25 WTR Water supply 33 WTR Water supply

26 WST Waste management service 34 WSTWaste management service

27 CMM Trade 35 CMM Trade28 FIN Finance and insurance 36 FIN Finance and insurance29 EST Real estate 37 EST Real estate30 TRT Transport via railways 38 TRT Transport via railways31 TRR Transport by road 39 TRR Transport by road32 TRO Private transport 40 TRO Private transport33 TRW Water transport 41 TRW Water transport34 TRA Air transport 42 TRA Air transport35 TRX Other transport 43 TRX Other transport36 ICT Telecommunications 44 ICT Telecommunications37 SVG Public service 45 SVG Public service38 SVB Business service 46 SVB Business service39 SVP Private service 47 SVP Private service40 OTH Other 48 OTH Other

The model is composed with 40 industries and 48 commodities, nine of which are fossil fuels

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Methodology: an applied/computable GE model

HHLD groupYearly income

(10 thousand yen)I 　　 - 192II 192 - 272III 272 - 336IV 336 - 399V 399 - 473VI 473 - 556VII 556 - 655VIII 655 - 792IX 　 792 - 1003X 1003 - 　　

The model has 10 household groups characterized by income bracket

III

IIIIV

VVI

VIIVIII

IXX

Higher income

Lower income

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Methodology: an applied/computable GE model

Intermediate goods(Armington goods)

1

0

0.1

0

Capital

Labor

Transport and retail margin

Output

ElectricityFossil fuels

(Armington goods)

0.5

0.1

Energy composite goodsArmington goods

Utility0.5

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Methodology: an applied/computable GE model

Industry

Households Government Investment Export

Import

Goods market

Labor market

Capital market

Intermediate goodsLabor Import goods

Supply side

Demand side

Capital

Export

Methodology: Applied/computable GE model to microdata

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This study links the simulation results given by the AGE model to the detailed information on individual households provided by the microdata

Applied/computable GE model

Microdata (provided by the National Statistics Center for our research purpose)

A sample of about 50,000 households, covering the whole of Japan The dataset is created from the anonymized data based on the 2004 National Survey of Family Income and Expenditure

Evaluating the impacts of energy price escalation on households by income decile groups

Linked

Performing a detained analysis of the impact on low-income and vulnerable households like mother-child, single-aged, etc.

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Results: when energy prices are doubled (Scenario 1)

In the scenario, electricity prices for households are doubled compared with those in the base case (BaU)

Electricity price escalation is caused by the change of power supply composition from nuclear to thermal (oil and LNG), as well as rises in the import prices of fossil fuels

Together with the electricity price hike, all kinds of energy are appreciated in the simulation

The scenario and assumptions are in line with the scenarios in the governmental reports (e.g., Energy and Environmental Council (2012a, 2012b))

III

III

VVI

VIIIIX

X

IV

VII

Scenario 1 Energy prices doubled

This study first analyzes the impact on households when energy prices are doubled

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Results: Changes in household income & energy consumption

Changes in household income, energy consumption & energy consumption ratio (compared with BaU, %)

I II III IV V VI VII VIII IX X

1. Changes in household income

-9.7 -10.7 -11.6 -11.8 -12.1 -12.5 -13.4 -13.9 -14.5 -17.7

2. Changes in energy consumption (in real terms)

-26.2 -27.3 -28.2 -28.5 -28.8 -29.5 -30.1 -30.8 -31.4 -34.4

3. Changes in the energy consumption ratio

1.36 1.36 1.34 1.34 1.34 1.34 1.32 1.32 1.31 1.27

The table indicates the changes in household income, energy consumption, and energy consumption ratios (energy budget shares) by income group

The changes in the energy consumption ratios (energy expenses / income) are larger for the lower income groups.

The results clearly indicate that the impacts of the energy price escalation are regressive.

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Results: the proportion of energy poverty households by income decile group (Scenario1)

0% 10% 20% 30% 40% 50%

III

IIIIVV

VIVIIVIIIIXX

Base case

Energy prices doubled

This study combines the simulation results with the detailed information on individual households by the microdata.

The result shows the severe impact on low-income households, especially the lowest income decile group when energy prices are escalated.

23% to 42%

2% to 10%

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Results: the impact by household type (Scenario 1)

0% 10% 20% 30% 40% 50%

Mother–child

Single-aged

Aged

Single-person

Other

Base case

Energy prices doubled

From the result, mother–child households and single-aged households can be categorized as vulnerable to the energy price escalation.

About one-tenth of mother–child and single-aged households are in energy poverty even in the BaU. The poverty rates are almost doubled by the energy price escalation.

11% to 23%

12% to 22%

Policy scenario (Scenario 2)

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According to the results, there are sure signs of energy poverty in lower income groups, as well as vulnerable households

With the policy:Subsidizing the energy costs of low-income households (I & II)

This policy can be interpreted as a kind of social tariffs, i.e., it involves discounted energy prices for low-income households Social tariffs were introduced in the UK from 2008 to 2011

III

IIIIV

VVI

VIIVIII

IXX

Subsidy totaling 500 billion yen

(5 billion dollars)

Scenario 2

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Results: the proportion of energy poverty households by income decile group (Scenario 2)

0% 10% 20% 30% 40% 50%

III

IIIIVV

VIVIIVIIIIXX

Base case

Energy prices doubled

Energy prices doubledwith policy

The policy offsets the negative impacts of energy price escalation.

The result indicates the effectiveness of the policy to counteract the negative influence of energy price escalation.

42% to 27%

10% to 4%

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Results: the impact by household type (Scenario 2)

0% 10% 20% 30% 40% 50%

Mother–child

Single-aged

Aged

Single-person

Other

Base case

Energy prices doubled

Energy prices doubledwith policy

The policy can also neutralize the negative impact of energy prices doubling on the vulnerable households.

This study empirically shows the effectiveness of the alleviation policy as well as the amount of the budget needed to cancel out the impact.

23% to 14%

22% to 14%

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Conclusion

This study investigates the impact of energy price escalation on the Japanese households the effectiveness of countermeasure (social tariffs)

This study empirically shows energy price escalation greatly harms Japanese households

• especially, low-income and vulnerable households the effectiveness of countermeasure the budget required to offset the negative impacts

Future research: definition of energy poverty a number of problems related to the 10% ratio measure

(e.g., Hills, 2012) plural standards may be needed to reflect regional differences in

the country (e.g., climates or prices)

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Thank you !