Energy Poverty in Japan

1. 32nd USAEE/IAEE North American Conference 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

2. Contents • Introduction • Motivation • Energy poverty • Concept and definition • Methodology • Model and microdata • Results • Energy price escalation • Energy price escalation & countermeasure • Conclusion

3. 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

4. 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

5. 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

6. 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

7. 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:

8. 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

9. 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.

10. Methodology: an applied/computable GE model The model is composed with 40 industries and 48 commodities, nine of which are fossil fuels

11. Methodology: an applied/computable GE model X IX Higher income VIII VII V VI IV III II I Lower income The model has 10 household groups characterized by income bracket

12. Methodology: an applied/computable GE model Output 0 0 Transport and retail margin 1 Intermediate goods (Armington goods) Utility 0.5 Labor 0.1 Energy composite goods Capital Armington goods 0.1 0.5 Electricity Fossil fuels (Armington goods)

13. Methodology: an applied/computable GE model Supply side Industry Import Intermediate goods Import goods Labor Capital Goods market Labor market Capital market Export Government Investment Export Households Demand side

14. Methodology: Applied/computable GE model to microdata • 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 Evaluating the impacts of energy price escalation on households by income decile groups Linked 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 Performing a detained analysis of the impact on low-income and vulnerable households like mother-child, single-aged, etc.

15. Results: when energy prices are doubled (Scenario 1) X • This study first analyzes the impact on households when energy prices are doubled IX VIII VII V VI IV Energy prices doubled Scenario 1 III II I • 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))

16. Results: Changes in household income & energy consumption • 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. Changes in household income, energy consumption & energy consumption ratio (compared with BaU, %)

17. Results: the proportion of energy poverty households by income decile group (Scenario1) • 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%

18. Results: the impact by household type (Scenario 1) • 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%

19. Policy scenario (Scenario 2) X According to the results, there are sure signs of energy poverty in lower income groups, as well as vulnerable households IX VIII VII V VI IV III Scenario 2 II I With the policy: Subsidizing the energy costs of low-income households (I & II) Subsidy totaling 500 billion yen (5 billion dollars) 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

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

21. Results: the impact by household type (Scenario 2) • 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%

22. 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)

23. Thank you !