Impacts of removing fossil fuel subsidies on China ...

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large are impacts of subsidy removal, and how to mitigate negative impacts? ..... subsidy removal, wherein China, Brazil and India remove fossil fuel subsidies.
Impacts of removing fossil fuel subsidies on China: How large and how to mitigate? Boqiang Lin a, b, *, Aijun Li c a

New Huadu Business School, Minjiang University, Fuzhou 350108, China.

b

China Center for Energy Economics Research, Xiamen University, Xiamen 361005, China.

*

Corresponding author.

c

Shandong School of development, The center for Economic Research, Shandong University,

A2311 Shandong University, Jinan 250100, China.

Abstract: G20 committed to removing inefficient fossil fuel subsidies at the Pittsburgh Summit. China is a large energy consumer with large subsidies. Then, how large are impacts of subsidy removal, and how to mitigate negative impacts? This paper simulates the potential impacts of subsidy removal, and compares different policy options to mitigate the adverse effects. The main findings are as follows. Firstly, subsidy removal would affect the competitiveness of different regions, and different regions would be affected disproportionally. Secondly, subsidy removal in China would result in competitiveness issue through trade channel, which would generate positive externalities to China, but negative externalities to other world regions without subsidy removal. Thirdly, subsidy removal in China would result in rebound effects, which would generate positive externalities to regions without subsidy removal, but be harmful to world’s emission reductions. Looking ahead, the government should develop a well-designed planning to overcome resistances to 1

subsidy removal. Keywords: Fossil fuel subsidy removal; Carbon leakage; Computable general equilibrium model; Competitiveness issue 1. Introduction There exists large size of energy subsidies in China. China is a large transitional and developing economy. Since the 1980s, the Chinese government has adopted a series of market-orientated reforms. But to support its domestic economic growth, the Chinese government adopted energy subsidies, wherein China’s domestic sectors would benefit due to relatively low domestic energy prices compared to their international competitions. Even now, energy prices in some energy sectors are still determined or controlled by the government, which would result in energy subsidies. According to [1], China’s subsidy reached 356.73 billion RMB in 2007, accounting for 1.43% in terms of China GDP. In particular, subsidies for coal accounts for 14.9% in terms of total subsidies, subsidies for oil and oil products account for 53.0%, subsidies for natural gas account for 10.7%, and subsidies for electricity account for 21.4%. Up to now, prices in many energy sectors are still influenced or even determined by the government. The Chinese government introduced a market-based pricing system to liberalize coal prices in 2007. As for coal for power generation, the coal prices are largely negotiated by coal companies and power companies. As for crude oil, the Chinese government has adopted measures to gradually liberalize the prices since the 1990s. Prices for oil products are set according to Administration Measures 2

for Petroleum Prices and announced by the National Development and Reform Commission (NDRC). The Measures mean that China’s prices for refined oil products may be adjusted when there is a change of over 4% in a weighted basket of international prices for crude oil lasting for 22 consecutive days, so that domestic prices could track international prices gradually. According to the Measures, the Chinese government established a price-adjustment mechanism, but prices for oil products could be influenced or even occasionally determined by the government. As for gas, the Chinese government adopted a cost-plus pricing mechanism, which implies that end-user prices would be the sum of ex-plant price and transportation tariff. Recently, the Chinese government adopted policies to narrow the price gap between domestically supplied gas and imported gas. As for electricity, the prices vary across provinces and are determined by NDER. [2] Furthermore, most large companies in energy sectors are state-owned enterprises, and hence, the government could influence the energy prices indirectly. Under such circumstances, G20 (including China) made the commitment to remove inefficient fossil fuel subsidies at the Pittsburgh Summit in September 2009. It is necessary for the Chinese government to remove fossil fuel subsidies. Large size of subsidies would become a significant fiscal burden for the Chinese government because of high international energy prices and China’s increasing reliance on energy imports. Meanwhile, fossil fuel subsidies could result in distorting effects on the economy. Fossil fuel subsidies would lead to low energy prices, which would encourage consumers to consume additional fossil fuels. Such additional fossil 3

fuel consumptions would be induced by distorting price. Therefore, fossil fuel subsidies would result in wasteful consumption and inefficient resource allocation. [2, 3] Thus, removing fossil fuel subsidies might lead to overall welfare gains. Further, removing fossil fuel subsidy could be helpful in curbing CO2 emission in China. China’s energy mix is coal-dominated, and as a consequence its economy is of high carbon intensity. Currently, China is the largest CO2 emitter in the world. In 2007, its CO2 emission was 6.03 billion tons, accounting for about 21% of the world’s total. (See Table A.1) Under the growing international clamor to reduce carbon emissions, the Chinese government would have to adopt policies to reduce its emissions. To removing fossil fuel subsidies is expected to curb wasteful consumption, and as a consequence, China’s domestic carbon emissions would reduce. Therefore, the Chinese government should remove fossil fuel subsidies. However, there could be some potential resistances to subsidy removal. China is a large transitional economy, and it makes great differences in standards of living across households and regions. Subsidy removal would produce various effects across sectors and households. Some sectors and their stakeholders might be highly adversely affected, and hence there could be some potential resistances. So the government should identify these stakeholders in advance, and build up a well-designed plan to overcome the potential resistances to subsidy removal.

4

Fig. 1. Subsidy rate in different world regions in 2007 (%) Note: We calculate subsidy rate according to calibration method in [4]. [2, 3]

Further, fossil fuel subsidy removal in China might generate potential interactions between China and other economies. Firstly, the subsidy rates of fossil fuel in China are not very high, but China is a large energy consumer, and hence the size of subsidy would be relatively high. (See Fig. 1) Under such circumstances, China’s subsidy removal might generate interactions between China and other economies through energy channel. Secondly, China is a large economy highly open to international trade, and hence its subsidy removal might generate interactions among China and other economies through trade channel. These potential interactions might produce various effects on the world’s economy. Against this background, this paper simulates the potential impacts of fossil fuel subsidy removal in China, and compares different policy options to offset the negative impacts. We seek to provide fresh insights by focusing on the following questions. 5

Firstly, are there significant differences in the effects of removing fossil fuel subsidies across sectors and across world regions, and what may explain these differences? Secondly, how large are the impacts of removing fossil fuel subsidies, and how to mitigate the negative impacts? Thirdly, are there any international externalities generated by fossil fuel subsidy removal through energy and trade channel, and what may explain them? We address these questions through a multi-world-region general equilibrium model. The remainder of this paper is structured as follows. Section 2 provides the literature review. Section 3 describes the model, and data. Section 4 reports model-based economic and environmental implications of fossil fuel subsidy removal. Section 5 compares policies to mitigate the negative impacts. Section 6 provides the concluding remarks.

2. Literature review Some approaches were frequently adopted to estimate the scales of energy subsidies, such as ERA (effective rate of assistance), PSE (producer subsidy equivalent), and the price-gap approach. Every approach has its own virtues and limitations. [1] Many papers estimated the size of energy subsidies, and the corresponding economic and environment implications. For example, [5] discussed the magnitude, causes and consequences of global subsidies in many sectors such as agriculture, energy, and transportation. [6] assessed the global size and distribution of energy subsidies in developed and developing countries and their implications. [7] 6

focused on the relationship between energy subsidies and three dimensions of sustainability, the economy, social welfare and the environment, and argued that energy subsidies would affect sustainable development in wide-ranging and diverse ways. [8] estimated the magnitude of consumption subsidies and production subsidies for fossil fuel in Australia. [9] estimated the size of energy subsidies in the EU 15 in 2001. [10] estimated the size of energy subsidies, and discusses their implications for energy investment and greenhouse gas emissions. [11] estimated subsidies to low-carbon energy including renewable energy, nuclear power and bio-fuels. [12] calculated the optimal ethanol subsidy in US. [13, 14] estimated the size of global energy subsidies. [1] estimated the size of energy subsidies in China. Some studies simulated the implications for removing energy subsidies (especially for fossil fuel subsidies), such as [1, 2, 3, 15-21]. [22] assessed the effects of reducing coal subsidies on greenhouse gas abatement. [23] discussed the effects of removing energy subsidies in developing and transition economics. [19, 24] argued that to remove coal subsidies in OECD countries would not always reduce the overall emissions. Compared to the partial equilibrium models or econometric models, the CGE models could reveal the economic relationships among sectors and countries. And hence, many studies adopted CGE models to simulate the potential impacts of subsidy removal. For example, [1] used a CGE model to assess the potential impacts of subsidy removal in China. [16] adopted OECD ENV-Linkages General Equilibrium model to quantify the potential impacts of subsidy removal. [17] quantified the 7

impacts of subsidy removal by using the general equilibrium model GREEN. [18] used a general equilibrium model to simulate the potential impacts of subsidy removal in Annex I countries. [22] adopted the G-Cubed general equilibrium model to quantify the impacts of lowering subsidies in coal industries.

3. The model 3.1 The production In this paper, we focus on the potential impacts of fossil fuel subsidy removal in China. In the meantime, China’s subsidy removal might generate trade interactions between China and other economies. So we adopt a multi-world-region general equilibrium model, which is a modification and extension of the model in [25], after referring to the models in [25-28]. In our model, there are five world regions, China, Brazil, India, OECD1, and ROW (rest of world). China, Brazil and India are the most important developing economies, and OECD covers the most important developed economies in the world. Then, these world regions could cover most of the important economies in the world. Therefore, it seems sufficient to incorporate the potential trade interactions between China and other economies caused by subsidy removal. Further, we could use OECD to incorporate the rebound effects by assuming that there would be no fossil fuel subsidies in OECD, which might be generated by subsidy removal. According to [2], the majority of consumption subsidies exist in non-OECD

1

OECD has 30 member countries in this paper, wherein they are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Spain, Sweden, Switzerland, Turkey, United Kingdom and United States. 8

countries, and subsidies in OECD countries are mainly in the form of production subsidies. We focus on impacts of removing consumption subsidies, and production subsidies are assumed to be zero and consumption subsidies in OECD at zero at initial benchmark steady state. Then, we could incorporate the potential rebound effects, which might be generated by subsidy removal. ROW does not produce any final goods, and would function as an energy exporter, wherein it could function as avoiding trade imbalances among other world regions. In this paper, there are two non-energy factors of production (capital and labor), and four energy factors of production (coal, oil, gas and other energy). The nesting structure of production is reported in Fig. 2. Due to data availability, we adopt a two-sector classification: industrial and non-industrial goods, wherein industrial goods are energy intensive and non-industrial goods are energy extensive. Labor is assumed immobile across world regions, and mobile across sectors in any world region; energy and capital are assumed mobile across world regions and sectors.

Output

Energy

Non-energy

Capital

Labor

Coal

Oil

Gas

Other energy

Fig. 2. The nesting structure of the production functions

9

The production function takes the form of CES (constant elasticity substitution) function and is given as follows: Y   0 [a1 ( NE )

( 1)

NE   1[b1 ( FK )

 a2 ( E )



(1 1)

E   2 [ cm ( FEm )

1

( 1)

 b2 ( FL)

( 2 1)

2

2

]





]

( 1)

(1 1)

1

1

]

(1) (1 1)

( 2 1)

( 2 ) ( 3 )

m

Where m denotes different kinds of energies. Y represents output. NE and E represent non-energy composite intermediate and energy composite intermediate respectively. FK and FL represent capital and labor respectively. FE represents different kinds of energies. as, bs, cs are share parameters. σs are substitution elasticity. γs are scale parameters. Following [25, 27], our energy supply function is as follows:

ESm  ENm ( PEm )m

(4)

Where ES represents energy supply. EN represents energy supply at initial benchmark steady state before subsidy removal. PE represents energy price. 10

ω represents energy supply elasticity. Producers in different world regions maximize profits under competitive markets, and the following zero profit condition would hold.

 j  Y j PY j  r (1  TK ) K j  wL j   Emj PEm (1  TEm )

( 5 )

m

Where r denotes capital price. w denotes wage. PY denotes goods price. TE denotes subsidy rates of different energies. TK denotes capital tax. 3.2 The household There is one representative household in each world region. The household owns all revenues from goods, taxes and factors of production. We adopt Armington assumption, and thereby goods from different world regions would be treated as heterogeneous. The utility function takes CES function form and is given as follows:  1 

1

U  [(d1 )  ( X1 ) 4

X j  [ (e ji ) i 1

1

j

 1    1

1

 (d 2 )  ( X 2 )

]

 j 1 j j  j 1

( X ji )

]

(6) (7)

Where ds and es are share parameters. Xj denotes the consumption of goods j. Xji denotes the consumption level of goods j produced by world region i. 11

We use the method in [25, 26] to deal with trade imbalance among world regions by introducing an exogenous trade transfer. The income of households from China, Brazil, India and OECD is assumed as follows:

I   PY jY j   NEm  TI j

(8)

m

Where NE denotes net trade payments for energy. TI denotes net trade transfer. The income of ROW is the sum of net trade payment for energy and net trade transfer.

I   PWEm NEm  TI

(9)

m

Where PWE denotes energy price in international markets. NE denotes ROW’s net trade payments for energy. Every household consumes goods in pursuit of utility maximization subject to budget constraint. The utility maximization problem could be expressed as follows: 1

 1 

Max U  [(d1 )  ( X1 )

1

 1    1

 (d 2 )  ( X 2 )

s.t. P1 X1  P2 X 2  I

]

(10)

3.3 Trade Border tax adjustment measures would generate price gaps between imported goods and domestic goods.

PYij (1  Tj )  PYkj EXRik

(11) 12

PEmi (1  TEi )  PWEm EXRi

(12)

ri (1  TKi )  rw EXRi

(13)

Where k denotes different households. Tj denotes export subsidy rate on goods j. rw denotes capital price in international markets. EXR denotes exchange rate adjustments among different currencies. 3.4 Market clearance All markets function well, and clear when supply is equal to demand in all markets. The following conditions would hold:

X

  Yij

kj

k

(14)

i

 FE

mi

i

 FL

ij

  ESkm  NEm

(15)

k

 LDi

(16)

j

 FK   KD ij

i

j

(17)

i

i

Where Xkj denotes the consumption level of household k of goods j. LD represents labor endowments. KD represents capital endowments. 3.5 The data We adopt the method in [4], and calibrate the parameters according to the data in 13

2007. The data are grouped according to the classification of industrial goods and non-industrial goods. GDP data are calculated according to the data from [29, 30]. For simplicity, export subsidy rate is assumed to be zero at the benchmark state. Trade data are calculated according to the data from [30-32]. Labor data and capital data are calculated according to input-output tables from [30, 33]. Energy data and fossil fuel subsidy data are calculated according to the data from [2, 3, 30, 34 and 35]. Key values for substitution elasticity between factors of production are reported in Table A.2. We take the values for substitution elasticity among different goods from [26, 36]. Energy subsidies of different world regions are from [2, 3]. China's electricity consumption subsidy mainly takes the form of cross-subsidy [1], and we do not consider the impacts of electricity subsidy removal in this paper. We assume that all carbon emissions are from fossil fuel consumption, and derive factors of emissions according to [30, 34, 35 and 37]. Due to data availability, we consider two scenarios. The first scenario is global subsidy removal, wherein China, Brazil and India remove fossil fuel subsidies simultaneously. The second scenario is China’s unilateral subsidy removal, wherein China removes its fossil fuel subsidies, and subsidies in other world regions remain unchanged.

4. Economic and environmental implications of subsidy removal 4.1 Competitiveness implications of subsidy removal In this subsection, we consider impacts of subsidy removal on competitiveness. 14

We use price-based indicator to measure bilateral competitiveness. Following [28, 38], we use the relative change in price to measure bilateral competitiveness between world regions. The competitiveness of world region i compared to world region l is defined as follows:

Cil 

Pl1 Pl 0

Pi1 1 Pi 0

(18)

Where C denotes competitiveness. P0 denotes goods price at the benchmark steady state. P1 denotes goods price at the steady state after subsidy removal. A positive value implies that competitiveness of world region i would increase compared to world region l. A negative value indicates that competitiveness of world region i would decline compared to world region l.

Table 1 Implications of subsidy removal (%) World regions Scenarios

Indicators China BC

Scenario 1

Brazil

India

OECD

World

Ind

0.02

-1.49

0.17

Nind

0.46

-1.61

0.62

0.61

0.17

1.28

0.05

Ind

-0.16

-0.08

-1.13

0.00

-0.05

Nind

-0.07

0.11

-0.20

0.03

0.03

Welfare

Output

15

Overall

-0.12

0.05

-0.48

0.03

0.00

-1.55

-0.42

-10.61

1.20

-0.08

Ind

0.18

0.23

0.16

Nind

0.60

0.68

0.62

0.33

0.05

0.01

0.03

Ind

-0.23

0.06

0.09

0.01

-0.02

Nind

-0.27

0.04

0.01

0.02

0.01

Overall

-0.25

0.05

0.03

0.02

0.00

-2.31

0.55

0.46

0.48

-0.04

Emissions BC

Welfare Scenario 2 Output

Emissions

Note 1: BC denotes bilateral competitiveness, wherein bilateral competitiveness in the above table refers to competitiveness compared to China. Scenario 1 refers to global subsidy removal, and scenario 2 refers to China’s unilateral subsidy removal. Overall refers to the sum of industrial goods and non-industrial goods. World refers to the sum of China, Brazil, India and OECD. (Hereafter)

We first consider the impacts of global subsidy removal, which is reported in scenario 1 in Table 1. For industrial and non-industrial goods, competitiveness of Brazil and OECD are positive, implying that they would get competitiveness gains compared to China. Competitiveness of India is negative, indicating that it would suffer competitiveness losses compared to China. These results are not surprising, since fossil fuel subsidy rates in China and India are relatively high. To investigate impacts of China’s unilateral subsidy removal, we consider 16

scenario 2 in table 1. For industrial and non-industrial goods, competitiveness of Brazil, India and OECD are positive,

implying they would

experience

competitiveness gains compared to China. The simulation results show that different world regions would be affected differently by fossil fuel subsidy removal. Firstly, the world regions to remove fossil fuel subsidies would experience competitiveness loss, since domestic sectors would face relatively high energy costs. Further, world regions with different size of subsidy rates would be affected disproportionately by subsidy removal. Secondly, world regions without fossil fuel subsidy removal would gain benefits from rebound effects, wherein they would experience fall in energy prices in international markets. As a result, their domestic sectors might obtain competitiveness gains in international competition. These above results imply that subsidy removal would result in competitiveness issue, which would cause competitiveness losses in world region to remove subsidy, especially for world regions with high subsidy rate. Then, we compare scenario 1 and 2 in table 1. In scenario 1, there would be international cooperation and all world regions would remove fossil fuel subsidies at the same time. In scenario 2, China moves ahead and removes its subsidies while other countries do not. The simulation results show that competitiveness issue would exist in scenario 1 and 2. In the meantime, China’s competitiveness losses in scenario 1 would be smaller than those in scenario 2.

17

4.2 Welfare implications of subsidy removal Welfare is defined as the ratio of Hicksian equivalent valuation in terms of GDP. W

EV GDP

EV 

(U1  U 0 ) I U0

(19)

Where W denotes welfare level. EV denotes Hicksian equivalent valuation. U denotes utility level. I denotes income level.

Then, we consider the welfare implications, which are reported in scenario 1 and 2 in table 1. The simulation results show that China, Brazil, India and OECD would experience welfare gains. These results are not surprising, since subsidy removal could reduce the pre-existing distorting effects on the economy, and consequently, result in welfare gains for world regions to remove subsidies. It is interesting to note that OECD would experience overall welfare gains in scenario 1, and Brazil, India and OECD would experience overall welfare gains in scenario 2. These world regions do not remove fossil fuel subsidies, but they could gain benefits from subsidy removal in other world regions. The reasons are mainly twofold. Firstly, to remove fossil fuel subsidies would result in competitiveness issue, wherein world regions with subsidy removal would suffer competitiveness losses while other world regions would experience competitiveness gains. Secondly, world 18

regions without subsidy removal would benefit from rebound effects. Subsidy removal in China would curb its domestic energy consumption, and hence would result in drop in international energy prices. Therefore, other world regions would get benefits from fall in energy price, wherein such effects are termed as rebound effects. We compare the simulation results in scenario1 and 2 in table 1. The welfare levels of China, Brazil, India and OECD in scenario 1 would be greater than those in scenario 2 respectively. Therefore, international cooperation to remove subsidy would lead to higher benefits (in terms of welfare) for all countries. 4.3 Output implications of subsidy removal Now, we explore the output implications of global subsidy removal, which is reported in scenario 1 in Table 1. For industrial goods, China, Brazil and India would experience significant output declines, while OECD would face slight output improvements. For non-industrial goods and overall outputs, China, and India would experience significant output declines, while Brazil and OECD would face output improvements. Therefore, removing of fossil fuel subsidies would affect different sectors in different world regions differently, and result in relocation of outputs across world regions. Then, we consider the world’s output. The world would experience output declines for industrial goods, and output improvements for non-industrial goods. Therefore, subsidy removal would result in a shift of production from industrial goods to non-industrial goods, and as a result, induce structure change of the economy. In the meantime, the world would experience overall output improvements. These results 19

are not surprising since subsidy removal would reduce the pre-existing distorting effects of energy subsidies on the economy, and hence result in overall output gains. To explore impacts of China’s unilateral subsidy removal, we consider output implications in scenario 2 in table 1. For industrial goods, non-industrial goods and overall outputs, China would suffer output declines, while India, Brazil and OECD would experience output improvements. These results imply that China’s unilateral subsidy removal would result in negative impacts on China’s output and positive impacts on other world regions without subsidy removal compared to global subsidy removal. In the meantime, the world would experience output declines for industrial goods, and output improvements for non-industrial goods. And hence, subsidy removal in China would affect the structure of the world’s economy, too. Meanwhile, the world would achieve overall output improvements, since subsidy removal would reduce the pre-existing distorting impacts of energy subsidies on the economy. Finally, we compare the simulation results in scenario 1 and 2 in Table 1. It would make significant differences in China’s output implications in scenario 1 and 2. China would experience much more output losses in scenario 2 than it would in scenario 1. 4.4 Emissions implications of subsidy removal In this subsection, we consider the emissions implications of subsidy removal. Relative changes in emissions are calculated as follows:

20

CE 

 m

m1

FEm1    m 0 FEm 0 m



m0

(20)

FEm 0

m

Where CE denotes relative changes in emissions. ε denotes factors of emissions. Firstly, we evaluate the emissions implications of subsidy removal. We first consider the implications of global subsidy removal, which is reported scenario 1 in Table 1. China, Brazil and India would experience emissions declines, while OECD would experience emissions increases. These results imply that carbon leakage would exist. We then consider the emissions implications of China’s unilateral subsidy removal, which is illustrated in scenario 2 in Table 1. China would experience emissions decreases, while Brazil, India, and OECD would experience emissions increases, implying that carbon leakage would exist, too. Thus, carbon leakage would exist in these two scenarios. Meanwhile, in scenario 1 and 2, the world would experience emissions declines, indicating that subsidy removal would contribute to world’s emissions reduction. Now, we turn to factors affecting the size of world’s emissions reduction. Fig. 3 illustrates the relationship between world’s emission reduction and values of key elasticity. We perform sensitivity analyses of values of energy substitution elasticity, coal supply elasticity, and oil supply elasticity, which are described in Fig. 3-1, 3-2 and 3-3 respectively. We first consider Fig. 3-1. There would be downward trend of world’s emissions 21

changes in scenario 1 and upward trend in scenario 2, as energy substitution elasticity increases. These results are not surprising, since subsidy removal would lead to a relative switch from oil and gas to coal and other energy in scenario 1, while it would lead to a relative switch from oil to coal and other energy in scenario 2. The value of energy substitution elasticity would play an important role in determining the size of the inter-fuel substitution effects, and consequently affecting the size of world’s emissions changes. It is interesting to note that the size of world’s emission changes would be not necessarily be greater than that in scenario 2, since China is a large energy

consumer

with

large

energy

subsidies

and

there

are

different

energy-substitution switches between these two scenarios. We then turn to Fig. 3-2 and 3-3. Fig. 3-2 shows that there would be an upward trend of world’s emissions changes, as coal supply elasticity increases. However, there would be a downward trend of world’s emissions changes, as oil supply elasticity increases. These results are not surprising, since different energy supply elasticity would indicate different direction and size of inter-fuel substitution.

world’s emissions changes (%)

0 scenario 1

-0.02 -0.04

scenario 2

-0.06 -0.08 -0.1

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Energy substitution elasticity

Fig. 3-1 Energy substitution elasticity and world’s emissions change 22

1

world’s emissions changes (%)

-0.02 scenario 2

-0.04 -0.06 scenario 1

-0.08 -0.1 -0.12 0

1

2

3

4

5

6

7

8

9

10

9

10

Coal supply elasticity

Fig. 3-2 Coal supply elasticity and world’s emissions change

world’s emissions changes (%)

-0.03 scenario 2

-0.04 -0.05 -0.06 -0.07

scenario 1

-0.08 -0.09 0

1

2

3

4

5

6

7

8

Oil supply elasticity

Fig. 3-3 Oil supply elasticity and world’s emissions change Fig. 3. Elasticity values and world’s emissions change

Finally, we turn to another important indicator leakage rate. Leakage rate is measured as the ratio of the emissions increases in world regions without subsidy removal over the emissions decreases in world regions with subsidy removal. Leakage rate would be 65.88% in scenario 1 and above 50.13% in scenario 2. We then consider factors affecting the size of leakage rate. Fig. 4 illustrates the 23

relationship between value for key elasticity and leakage rate. Fig. 4-1, 4-2 and 4-3 show the relationship between energy substitution elasticity, coal supply elasticity and oil supply elasticity respectively. Fig. 4-1 shows that with the increase of energy substitution elasticity, there would be a downward trend in scenario 1, while an upward trend in scenario 2. Fig. 4-2 shows that with the increase of coal supply elasticity, there would be an upward trend of leakage rate, wherein more energy consumption would be switched to coal. Fig. 4-3 shows that with the increase of oil supply elasticity, there would be a downward trend of leakage rate.

Leakage rate (%)

71

51

Global subsidy removal

70

50.5

69

50

68

49.5

67

49

66

48.5

65 0.2

0.4

0.6

0.8

1

48 0.2

China’s unilateral subsidy removal

0.4

0.6

Energy substitution elasticity

Fig. 4-1 Energy substitution elasticity and leakage rate

24

0.8

1

66.5

50.3 Global subsidy removal

Leakage rate (%)

66

China’s unilateral subsidy removal

50.2

65.5 50.1 65 50

64.5

49.9

64 63.5 0

2

4

6

49.8 10 0

8

2

4

6

8

10

Coal supply elasticity

Fig. 4-2 Coal supply elasticity and leakage rate

67

51.5 China’s unilateral subsidy removal

Leakage rate (%)

Global subsidy removal 66.5

51

66

50.5

65.5

50

65 0

2

4

6

8

49.5 10 0

2

4

6

8

10

Oil supply elasticity

Fig. 4-3 Oil supply elasticity and leakage rate Fig. 4. Elasticity values and leakage rate Note: x axis and y axis denote elasticity values and leakage rate (%) respectively. 5. Comparing policies to mitigate negative impacts on output 5.1 Comparing policy options to mitigate the negative impacts on output In this subsection, we compare policy options to mitigate the adverse output effects of subsidy removal in scenario 2, wherein China unilaterally removes its fossil fuel subsidies. We consider two policy instruments: export subsidy and capital tax. 25

To investigate the output implications of these policy options, we consider the simulation results in Table 2. Firstly, we consider the output implications of export subsidy. According to the simulation results, with the increase of export subsidy rate on industrial goods, China would experience significant output increases in industrial goods, and slight output increases in non-industrial goods. Meantime, with the increase of export subsidy rate on non-industrial goods, China would experience significant output improvements for non-industrial goods, and suffer output declines for industrial goods. Further, when industrial and non-industrial goods both subsidized, with the increase of export subsidy rates, there would be significant output improvements for both industrial goods and non-industrial goods. Therefore, export subsidy could mitigate the negative output impacts induced by subsidy removal.

Table 2 Policy options to mitigate negative impacts on China’s output Policy options

Tax rate increased by or subsidy rate

Output changes (%) Ind

Nind

reduced by (%)

Welfare changes (%)

Export

Industrial

0.1

-0.11

-0.26

0.38

subsidy

goods

0.5

0.40

-0.24

0.55

subsidized

1.0

1.04

-0.21

0.76

Non-industrial

0.1

-0.25

-0.24

0.34

goods

0.5

-0.32

-0.10

0.35

26

subsidized

1.0

-0.40

0.06

0.36

All goods

0.1

-0.12

-0.23

0.38

subsidized

0.5

0.32

-0.08

0.56

1.0

0.87

0.12

0.78

0.1

-0.16

-0.21

0.40

0.5

0.16

0.04

0.69

1.0

0.55

0.35

1.04

Capital tax

Secondly, we consider the simulation results of capital tax reduction. The simulation results show that with the increase of capital tax reduction, there would be large output increases for both industrial goods and non-industrial goods. Therefore, capital tax reduction could offset the negative output impacts induced by subsidy removal, too. To explore the welfare implications of different policy instruments, we consider the simulation results in Table 2. According to the simulation results, export subsidy would result in welfare gains. These results are not suspiring, since export subsidy would result in competitiveness advantages and hence, contribute to output gains. In the meantime, capital tax reduction would also induce welfare gains, since it would reduce the pre-existing distorting effects of capital tax on the economy. 5.2 Comparing policies to keep outputs unchanged relative to pre-removal level In this subsection, we compare the implications of different policy options to keep output levels unchanged compared to pre-removal level, which are reported in 27

Table 3.

Export subsidy on industrial goods could keep output unchanged for

industrial goods, and result in welfare gains and slight output improvements for non-industrial goods. Export subsidy on non-industrial goods could keep output unchanged for non-industrial goods, and result in overall welfare gains, but induce output declines for industrial goods. Policy mix 1 could keep output unchanged for industrial and non-industrial goods, with differentiated export subsidy rate on industrial and non-industrial goods respectively. In the meantime, policy mix 1 could result in overall welfare gains. Policy mix 2 and 3 could keep output unchanged and result in overall welfare gains, wherein export subsidies and capital tax reduction are used simultaneously. The simulation results show that China’s welfare gains in policy mix 2 would be larger than those in policy mix 3. These results are not surprising since capital tax reduction would function in reducing pre-existing distorting effects while export subsidies would add new additional distorting effects on the economy. Table 3 Policy options to keep output level at pre-removal level Unchanged

Policy options

goods

Output changes (%) Ind

Nind -0.26

Ind

Export subsidy

/

Nind

Export subsidy

-0.37

Ind and Nind

Policy mix 1 Policy mix 2 Policy mix 3 28

/

/

/

/

/

/

/

Welfare level (%)

0.41 0.35 0.47 0.53 0.50

Note: / indicates that output level would remain unchanged compared to pre-removal level. Export subsidy rate is 0.19% for industrial goods to keep industrial goods unchanged, and 0.82% for non-industrial goods. Policy mix 1 denotes that industrial goods are subsidized at 0.29%, and non-industrial goods at 0.76%. Policy mix 2 denotes that capital tax rate is 24.80% and export subsidy rate 0.12% for industrial goods and 0.42% for non-industrial goods. Policy mix 3 denotes that capital tax rate is 24.90%, and export subsidy rate is 0.20% for industrial goods and 0.59% for non-industrial goods.

6. Concluding remarks China has committed itself to removing inefficient fossil fuel subsidies, which would produce various effects across sectors and households. To remove subsidy successfully, the Chinese government should identify the negative impacts and adopt policy instruments to offset the negative impacts. Under such circumstances, this paper assesses the potential impacts of subsidy removal, and compares different policy options to mitigate the negative effects on output. The simulation results show that subsidy removal in China would generate international externalities, which would affect different economies differently. Firstly, subsidy removal in China would produce global effects through trade channel. China’s subsidy removal would result in competitiveness issue, which would generate negative externalities to China, and positive externalities to other world regions without subsidy removal. So subsidy removal in China would cause harm to China’s 29

output. To mitigate these negative output impacts, ppolicies to reduce the pre-existing distorting effects would be preferred, and policies to add additional distorting effects on the economy should be avoided. Secondly, subsidy removal in China would generate global effects through energy channel. Subsidy removal would result in rebound effects, which would generate positive externalities to other world regions without subsidy removal. However, rebound effects would result in relocation of energy consumption and carbon emissions from China to other world regions without subsidy removal. Therefore, carbon leakage would exist, which would cause harms to world’s emissions reduction. China is a large energy consumer with high openness to international trade. Looking ahead, before performing subsidy or tax reforms, the Chinese government should consider the potential interactions among China and other economies. Our paper has some limitations that could be overcome by further research. Firstly, sectors could be disaggregated, which could produce more helpful policy suggestions to policy-makers. Secondly, carbon policies of different world regions could be added, since these policies might affect carbon leakage. Finally, differentiated values for energy substitution among fuels should be considered, since they would affect the size of inter-fuel substitution effects and carbon leakage.

30

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34

Table A.1 Key economic and energy indicators for China

GDP

Unit

2007

billion USD

3206

Share of industrial goods

%

49

Share of non-industrial goods

%

51

Total primary energy demand

Mtoe

1970

Coal

%

65.6

Oil

%

27.7

Gas

%

17.0

CO2 emissions

billion tonnes

6.0

Share of coal

%

82.9

Share of oil

%

14.9

Share of gas

%

2.1

Trade values

billion USD

2173.7

Exports

billion USD

1217.8

Imports

billion USD

956.0

Trade surplus

billion USD

261.8

Sources: [29, 30, 34, and 35].

35

Table A.2 Key elasticity in production function Production substitution elasticity σ

0.88

σ1

1.16

σ2

0.80

Energy supply elasticity ω1

5.0

ω2

1.5

ω3

1.5

ω4

1.5

Source: [39, 40]

36