Transcript ENERGY POVERTY IN JAPAN - The United States Association

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
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
1
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
2
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
3
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
4
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
5
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:
6
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
7
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.
8
Methodology: an applied/computable GE model
Industry (40)
1 AGR Agriculture
2 MIN Mining
3 COG Coal, oil and gas
1
2
3
4
5
4 FDP Food
6
5 TEX Textiles
7
6 WPP Paper and pulp
8
7 CHE Chemicals
9
8 O_P Oil products
10
11
12
13
14
15
16
17
18
9 C_P Coal products
19
10 PLR Plastics
20
11 CLY Cement
21
12 STL Iron and steel
22
13 MTL Non-ferrous metal
23
14 MTP Metal products
24
15 MCH Machinery
25
16 ELM Electrical machinery 26
17 TRM Transport equipment 27
18 OMF Other manufacturing 28
19 CNS Construction
29
Commodity （48）
AGR Agriculture
MIN Mining
COL Coal
OIL Crude oil
GAS Gas
FDP Food
TEX Textiles
WPP Paper and pulp
CHE Chemicals
GSL Gasoline
JET Jet fuel
KRS Heating oil
LGH Light gas oil
FOA Bunker A
FOC Bunker B&C
NPH Naphtha
LPG Liquid petroleum gas
OOP Other oil products
C_P Coal products
PLR Plastics
CLY Cement
STL Iron and steel
MTL Non-ferrous metal
MTP Metal products
MCH Machinery
ELM Electrical machinery
TRM Transport equipment
OMF Other manufacturing
CNS Construction
Industry (40) cont
20 NUC Nuclear electricity supply
21 THM Thermal electricity supply
22 HYD Hydro electricity supply
Privately owned power
23 OWP
generation
24 GHS Gas supply
25 WTR Water supply
Commodity （48） cont
30 ELY Electricity
31 OWP
32 GHS
33 WTR
26 WST Waste management service 34 WST
27
28
29
30
31
32
33
34
35
36
37
38
39
40
CMM
FIN
EST
TRT
TRR
TRO
TRW
TRA
TRX
ICT
SVG
SVB
SVP
OTH
Trade
Finance and insurance
Real estate
Transport via railways
Transport by road
Private transport
Water transport
Air transport
Other transport
Telecommunications
Public service
Business service
Private service
Other
35
36
37
38
39
40
41
42
43
44
45
46
47
48
CMM
FIN
EST
TRT
TRR
TRO
TRW
TRA
TRX
ICT
SVG
SVB
SVP
OTH
Privately owned power
generation
Gas supply
Water supply
Waste
management
service
Trade
Finance and insurance
Real estate
Transport via railways
Transport by road
Private transport
Water transport
Air transport
Other transport
Telecommunications
Public service
Business service
Private service
Other
The model is composed with 40 industries
and 48 commodities, nine of which are fossil
fuels
9
Methodology: an applied/computable GE model
HHLD group
I
II
III
IV
V
VI
VII
VIII
IX
X
Yearly income
(10 thousand yen)
- 192
192 - 272
272 - 336
336 - 399
399 - 473
473 - 556
556 - 655
655 - 792
792 - 1003
1003 -
Higher income
X
IX
VIII
VII
V
VI
IV
III
II
I
Lower income
The model has 10 household groups characterized by income bracket
10
Methodology: an applied/computable GE model
Output
0
0
Intermediate goods Transport and retail
margin
(Armington goods)
1
Utility
Labor
Capital
0.5
0.1
Energy composite goods
Armington goods
0.1
0.5
Electricity
Fossil fuels
(Armington goods)
11
Methodology: an applied/computable GE model
Supply side
Industry
Labor
Labor
market
Capital
Import
Intermediate
goods
Capital
market
Import goods
Goods
market
Export
Households
Government
Investment
Export
Demand side
12
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.
13
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
Scenario 1
Energy prices
doubled
VI
IV
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))
14
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, %)
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
15
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%
I
II
III
IV
V
VI
VII
VIII
IX
X
2% to 10%
Base case
Energy prices doubled
0%
10%
20%
30%
40%
50%
16
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.
Mother–child
11% to 23%
Single-aged
12% to 22%
Aged
Single-person
Base case
Other
Energy prices doubled
0%
10%
20%
30%
40%
50%
17
Policy scenario (Scenario 2)
According to the results, there are sure signs
of energy poverty in lower income groups,
as well as vulnerable households
X
IX
VIII
VII
V
VI
IV
III
Scenario 2
With the policy:
Subsidizing the energy costs of
low-income households (I & II)
II
I
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
18
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.
I
II
III
IV
V
VI
VII
VIII
IX
X
42% to 27%
10% to 4%
Base case
Energy prices doubled
Energy prices doubled
with policy
0%
10%
20%
30%
40%
50%
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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.
Mother–child
23% to 14%
Single-aged
22% to 14%
Base case
Aged
Energy prices doubled
Single-person
Energy prices doubled
with policy
Other
0%
10%
20%
30%
40%
50%
20
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 !
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