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Economic and environmental gains of China's fossil energy subsidies reform: A rebound effect case study with EIMO model
Energy Policy 54 (2013) 335–342
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Economic and environmental gains of China’s fossil energy subsidies reform: A rebound effect case study with EIMO model Li Hong a,n, Dong Liang b,c,1, Wang Di d a
School of Economics, Peking University, Haidian District, 5 Yi HeYuan AV., Beijing 100871, PR China National Institute for Environmental Studies (NIES), 16-2 Onogawa, Tsukuba-City, Ibaraki 305-8506, Japan c Graduate School of Environmental Studies, Nagoya University, Furo-cho, Chikusa-ku, Nagoya City 464–8601, Japan d Institute of Population Research, PekingUniversity, Haidian District, 5 Yi HeYuan AV., Beijing 100871, PR China b
H I G H L I G H T S c c c c
Analyze the economic and environmental gains of fossil energy subsidies reform in China. Energy input and monetary output model was applied for analysis. Subsidies reform would help to reduce the rebound effect. The benefits of money saving, energy saving and CO2 mitigation were achieved.
a r t i c l e i n f o
abstract
Article history: Received 16 May 2012 Accepted 20 November 2012 Available online 21 December 2012
Energy consumption and efficiency emerged as the hottest topic in the context of China’s sustainable development. Energy subsidies and ‘‘rebound effect’’ were closely related to this topic while few combinative studies on them with a focus on China. This paper employed a co-thinking approach, focusing on how the energy subsidies reform could mitigate the rebound effect in China, and how to achieve an ‘‘economic and environmental gains’’ that reduced pecuniary spending, improved the distorted energy market and reduced energy consumption simultaneously. Firstly, with price-gap approach we calculated the total energy subsidies scale of China in 2007, which amounted to582.0 billion CNY; then we detected and identified rebound effect of China energy consumption with the features. Furthermore, based on China 2007 monetary input–output table and energy flow analysis, we compiled a hybrid physical energy input and monetary output model (EIMO) to simulate the mitigation effect of subsidies reform. Results showed that removing energy subsidies would decrease ultimate demand of different economy sectors and reduce the accumulatively physical consumption of coal, oil, natural gas and electricity by 17.74, 13.47, 3.64 and 15.82 million tce, respectively. Finally we discussed relevant policy issues on China’s energy subsidies reform in depth. & 2012 Elsevier Ltd. All rights reserved.
Keywords: Energy subsidies Rebound effect EIMO model
1. Introduction With rapid economic growth, China has faced more and more emerging conflicts in terms of energy supply and demand, as well as series of related environmental problems. In 2007, China became the world’s largest CO2 emitter (BP, 2008) and in 2010, it overtook United States becoming the world largest energy consumer, contributing to a share of 20.3% of total worldwide energy consumption (BP, 2011).
n Corresponding author. Tel.: þ86 1367 136 6001, þ 86 10 62755658; fax: þ 86 10 62751460. E-mail addresses: [email protected] (L. Hong), [email protected] (D. Liang). 1 Tel.: þ81 080 4090 2595; fax: þ 81 029 850 2314.
0301-4215/$ - see front matter & 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.enpol.2012.11.045
China is a developing country in industrialization phase with economic development, population growth, and living standardimproving. Undoubtedly its energy demand will soar in the future. Therefore improving energy efficiency is of vital importance for energy conservation and CO2 emissions reduction, and Chinese government has shown growing concern about those issues. Since 2002, several national policies such as the Cleaner Production Promotion law, Circular Economy Promotion law have been launched in which enhancing energy efficiency is one key aspect, and lots of advanced energy conservation technologies have been utilized (Li et al., 2010). Due to those efforts, the energy consumption per unit of GDP of China has decreased by 40% over the past decade. However, although the energy efficiency in China has been enhanced significantly, it is disappointing that the energy
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Energy consumption
Energy consumption/GDP
Energy consumption, 10000 t
300000 250000 200000 150000 100000 50000
Energy consumption/GDP, t/10000RMB
350000
0
Fig. 1. China’s energy consumption and efficiency. Source: (NBS, 2011)
consumption is still increasing aggressively rather than decreasing (Fig. 1). The most important reason is the huge energy demands driven by rapid economic growth, while the ‘‘rebound effect’’ also played an important role (IEA, 1999). The ‘rebound effect’ is the term referring to the behavioral or other systemic response to improved resource utilization efficiency due to new technologies (Greening, 2000; Ouyang et al., 2010; Ruzzenenti and Basosi, 2008; Saunders, 1992; Wang et al., 2012c). Unintended consequences always complemented with technology advances in household level and industries; specifically, part of the energy savings derived from new technologies are offset by increased energy consumption. The mechanism is that energy efficiency enhancement would reduce the prices of energy products or services, thus leading to more demand and consumption. In theory, energy subsidies facilitate the rebound effect as it also lower the end-use price, consequently encourage the consumption and potentially damage the environment (de Moor, 2001; IEA, 1999; Li et al., 2011; Liu and Li, 2011; OECD, 2005; UNEP, 2003, 2008). Based on this point, energy subsidies reform would be an effective way to mitigate the rebound effect, further make the energy efficiency measures more efficient, and ultimately achieve a collaborative benefit in terms of economic benefit and environmental benefit. Since the early study on rebound effect in estimation of energy savings (Khazzoom, 1980), such issues have been widely discussed and debated as rebound effect in different energy consumption sectors (Bentzen, 2004; Khazzoom, 1980; Li and Yonglei, 2012; Ouyang et al., 2010; Wang et al., 2012b), empirical studies in developed and developing regions or countries like UK, Hong Kong, India and China (Barker et al., 2007; Freire Gonza´lez, 2010; Haas and Biermayr, 2000; Mizobuchi, 2008; Roy, 2000; Sorrell et al., 2009; Wang et al., 2012b, 2012c), modeling the rebound effect with partial equilibrium model (Ouyang et al., 2010), general equilibrium model (Grepperud and Rasmussen, 2004)and econometric method (Barker et al., 2007; Bentzen, 2004), and specific technologies or policy (de Haan et al., 2006; Matos and Silva, 2011; Safarzynska, 2012). As for the study about China, most studies focused on direct rebound effect in certain sectors (Li and Yonglei, 2012; Ouyang et al., 2010; Wang et al., 2012b, 2012c). However, although rebound effect and subsidies are intrinsically connected, few studies innovatively have them linked and in quantified method. Energy efficiency measures in cooperation with environmental and energy policy tools are considered to be essential cushion for the rebound effect (Maxwell et al., 2011), therefore research studying the interaction of energy subsidies and rebound effect would provide a beneficial discussion on the topic of energy conservation and climate change.
This paper adopts a co-thinking approach to study the economic and environmental gains of energy subsidies reform and its contribution to reduce the rebound effect, with China as the case study, in application with an improved hybrid physical energy input and monetary output model (EIMO). We mainly contribute to the following aspects: first of all, with the calculation of the national fossil energy subsidies scale in China in 2007, we analyzed its inherent interaction with energy rebound effect in depth; then we proposed an improved energy input–output model based on the 2007 China monetary input–output table; thirdly, with the EIMO model, we quantitatively analyzed the economic and environmental gains of subsidies reform; lastly based on the quantified analysis we discuss the policy issues about China’s energy policy reform. We hope this study would offer an improved understanding of subsidies reform and climate change.
2. Analytical framework and methodology Several terminologies, conceptions and methodologies were quoted and applied in this paper. This section would clarify their interconnection under the general analytical framework of this study. In the following part we analyzed the intrinsic connection between rebound effect and subsidies so as to present why the subsidies reform could generate economic growth while reduce the rebound effect. In the context of methodology, price-gap approach is adopted to quantify the scale of China fossil energy subsidy, empirical study approach used to qualitatively analyze the relationship of subsidies reform and rebound effect, and the hybrid energy input–output model applied to quantitatively simulate how subsidies reform would indirectly affect rebound effect. 2.1. Interaction among energy subsidies and rebound effect The so called ‘‘rebound effect’’ is the increasing energy consumption enabled by energy efficiency enhancement. According to a partial equilibrium theory, as energy consumption per unit of economic output decreases, the efficiency improvement would implicitly lead to a reduction in the price of products, in other words people can afford more energy-using outputs if costs per unit have fallen, which is an income effect (Herring and Roy, 2002; Roy, 2000; Sorrell et al., 2009). Basically the key mechanism of rebound effect is that technical advancement enhances the efficiency, and further reduces the price. The effect of energy subsidies is that it could lower the end-use price of energy products or service, so to some extent subsidies would strengthen rebound effect. Fig. 2 showed an internal mechanism of how energy subsidies affect the rebound effect. While rebound effect and subsidies has intersections, it is necessary to find a systematical approach to identify such interaction. Here we make the co-thinking: whether there would be one option that could reduce pollutants and/or save energy and/or make money meanwhile could reduce CO2 emissions and/or other pollutants? Through the analysis in Fig. 2, fossil energy subsidies reform could not only lower the governmental budget and ease the distortion of energy market (monetary issues), but reduce the energy consumption and related carbon emissions as well. The removal of price gap and ensuing energy consumption reduction would contribute to the mitigation of rebound effect, realizing the economic and environmental gains. 2.2. Analytical framework This study mainly focused on a quantified economic and environmental assessment on how energy subsidies reform contributes to the mitigation of rebound effect. The analytical
L. Hong et al. / Energy Policy 54 (2013) 335–342
337
The income effect or indirect effect: lower energy price cause
Fig. 2. Internal connection of energy subsidies and rebound effect.
more spending and subsequent more energy use due to higher disposable income level; The macroeconomic rebound effect: the energy efficiency technologies boost the entire macro economy so that production is upgraded, and as a result more energy is consumed.
In this study, through the hybrid input–output model, it is able to identify the energy consumption from a life cycle perspective, that the consumption in the whole supply chain could be considered. Or rather, we could explore how subsidies reform could contribute to the mitigation of the macroeconomic rebound effect. The analysis targets on the indirect one as we mainly focus on the physical amount of energy savings and emissions reduction of subsidies reform. Before using the energy Input–output framework, it is necessary to quantify the variations in the end user demand when energy efficiency is improved. 2.3. Assessment indicators for economic and environmental gains Based on the analysis in Section 2.1, the economicenvironmental gains mainly generated from the effect that subsidies reform would dismiss the price gap of energy products, thus reducing the end-user demand in relevant sectors, and finally leading to the consumption and related carbon emissions reductions, which could be seen as a mitigation of rebound effect. For evaluation, we proposed two indicators: a. Gains in terms of CO2 emissions reduction per unit of monetary saving (tCO2/CNY), which means how much CO2 emission could be reduced when one unit of money is saved. b. Gains in terms of energy saving per unit of monetary saving (tce/CNY), which means how much energy could be saved when one unit of money is saved. With the two proposed indicators we could identify how subsidies reform could contribute to the mitigation of rebound effect (save energy) and at the same time achieve economic benefit. 2.4. Price-gap approach The Price-gap approach focuses on consumer-side subsidies and quantifies the gap between reference prices and subsidized end-use prices. The methodology is described as follow (IEA, 1999):
Fig. 3. Analytical framework.
framework is shown in Fig. 3. In the first step we identified the key points of economic and environmental gains and propose assessment indicators; then we calculated the subsidies scale in 2007. Subsequently we established a hybrid energy input–output model with which to analyze and simulate. In the case study section, we further analyze the current energy consumption and efficiency situation of China, identify the topic of rebound effect and simulate the scenario of eliminating energy subsidies with the established model. The simulation results would be reevaluated by the assessment indicators to figure out the benefits. In the last section we discuss policy proposals. It is noted that there are three types of rebound effects (Greening, 2000; Wang et al., 2012c; Wei, 2010):
The direct effect: energy becomes cheaper, so an individual uses more direct energy products, such as heat;
Si ¼ PGi C i
ð1Þ
PGi ¼ M i Pi
ð2Þ
where Si is the subsidies scale of energy product I, and PGi the price-gap of energy product i. C i denotes the consumption of energy product i; Mi denotes the reference price of energy product i (refers to the price without subsidies). P i is the enduse prices of energy product i. According to the methodology, subsidies scale is calculable with reference price and end-use price. In most instances the enduse prices are available from statistics; thus in applying the methodology the crux is to figure out the reference prices, which requires the data of market prices of international trade, taxes, transportation costs, and so on. In this paper we concentrate on three primary fossil energy including coal, oil and natural gas, and the secondary energy electricity. For coal, in 2007 China was the net exporter of coal and net importer of oil products. According to the methodology of IEA, the
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related reference coal prices are adjusted as follows (IEA, 1999): M i ¼ FOBi þ Di þVAT
ð3Þ
where, FOBi is free-on-board export price selected as starting point price. Di is internal distribution cost added to reflect variations in different modes of transportation and distances between the ports and the location of consumer market. VAT stands for value added tax. For oil products and natural gas, the reference prices are calculated according to Eq. (4): M i ¼ International_pricei þ Di þ Tax
ð4Þ
Tax includes VAT, customer tax, etc. For electricity, the reference price is long-term marginal price (Lin and Jiang, 2011). The detail description of price-gap approach was showed in our previous research (Li et al., 2011; Liu and Li, 2011).
Table 1 The structure of hybrid energy input monetary output model. Intermediate Final demand monetary output sector Y
Monetary input
Intermediate monetary input Added value Total monetary output Physical energy input
Energy resource
1 y n V X
1 y m
M
Y1 y Yn
Total output X X1 y Xn
Physical input distribution E
demand are shown in Eq. (7):
2.5. Hybrid physical energy input and monetary output model After obtaining the subsidy scale, we build a model to link subsidy and rebound effect as the further key step. Rebound effect relates to the energy prices and its consumption, while energy subsides affects the energy end-use prices, and it is of great importance in the way to connect the price (economic issue) and consumption (physical issue). To resolve it hybrid input output model is a useful tool to estimate the issues combining economic and environmental matters as it explains the inherent relationship between material flows and economic flows (Xu, 2010). Inspired by the previous work of the physical input–output model and material physical input and monetary output model in environmental study fields (Giljum and Hubacek, 2009; Liang et al., 2010; Liang and Zhang, 2011, 2012), in this paper, we propose an improved physical energy input and monetary output model (EIMO) to simulate how subsidies reform could mitigate the rebound effect. The EIMO model is based on China monetary input–output table, and physical energy input was compiled with energy flow analysis. We categorize the 42 sectors into 6 divisions (A to Z) according to the energy consumption features: The primary industry, Industry, Construction industry, Transformation industry, Sale, Living and Catering industry, and the other Service sectors. For each sector, the energy input is in physical units and the output is in monetary units. In this way, the model quantitatively represents the correlations between economic sectors by monetary input output table (MIOTs) and the connections between the ecological system and the economic system by the method of energy or material flow analysis (EFA or MFA). Table 1 shows the structure of EIMO model. The direct monetary consumption matrix A and Leontief inverse matrix (I A) 1 as well as the row balances are illustrated in various studies on I–O analysis (Holub and Schnabl, 1985; Leontief, 1936; Wu and Chen, 1990). The row balances are shown in Eqs. (5) and (6): AX þ Y ¼ X
ð5Þ
X ¼ ðIAÞ1 Y
ð6Þ
The m n matrix E could be seen as the energy intensity among the sectors, or the direct energy consumption matrix. They could be obtained from the energy input data and economic output data of each sector, and based on the energy balance table and energy statistical data, the direct energy flow of each sector is analyzed and the direct energy consumption matrix is obtained. Relationships between total energy consumption and final
D ¼ EX ¼ EðIAÞ1 Y
ð7Þ
where, D denotes the total or cumulative energy consumption. Based on above mathematical relationships, energy consumption can be inherently connected to economic activities. Analysis can be conducted by setting one of the parameters exogenous. The performance of the system, both ecologically and economically, can be simulated from different aspects by changing one of those parameters. Particularly for this study, it could link the price with the real physical material consumption. It is noted that in this study, we allocated the electricity into different sectors due to our research demand (we want to investigate the consumption change of the electricity after the subsidies reform). To allocate the electricity, the issue of power generation and sector selfpower generation are carefully considered. Here we explore it according to the physical energy balance table using energy flow analysis. For primary industry, transportation, construction, and service sector, the allocation amount of electricity is their final consumption transformed into energy unit. For the industry, we deducted the coal, oil and gas consumption of producing electricity because the existence of energy manufacturing process. The original data is avail in the energy balance table of China. For more details about the hybrid input–output table, see the ‘‘Supplementary material’’.
3. Fossil energy subsidies scale Detailed calculation can be referred to our previous work (Li et al., 2011; Liu and Li, 2011). We calculated four categories of energy resources, including coal, oil, natural gas and electricity. Table 2 summarized the price-gap and consumption for different energy products in China in 2007. Based on Eqs. (1) and (2), we calculate the fossil energy subsidies in China and the average subsidy rate for various energy products as a basic for following analysis. In theory, subsidy rate equates to the ratio between price-gap and the reference price. The results are shown as Table 3. According to Table 3, China’s total fossil energy subsidies were 582.0 billion CNY (76.6 billion USD) in 2007 (IEA, 2008) estimated that China’s energy subsidies were about 300 billion CNY (including electricity subsidies) in 2007.Our results are higher than that of IEA due to different views on coal pricing mechanism and the selection of reference prices. It is noted that in effect the subsidies produces a price-gap for the energy products, making the price of energy products and services lower than their real market value. Such lowering-down
L. Hong et al. / Energy Policy 54 (2013) 335–342
Table 2 Price-gap and consumption of energy products of China, 2007. End-use prices
Coal (CNY per ton) Steam coal 480.3 Coal contract 285.0 Oil products(CNY per ton) Gasoline 6464.1 Diesel 5548.2 Fuel oil Aviation kerosene
3526.7 5106.7
Reference prices
Pricegap
500.7 306.0
20.4 21.0
7652.5 7105.9
1188.4 1557.8
4088.1 6893.7
561.4 1787.0
Energy consumption per-GDP Energy consumption per-capita Annual Residential Energy Consumption Per Capita Urban Annual Residential Energy consumption Rural Annual Residential Energy consumption
2500
Consumption 2000
1.33 billion tons 0.76 billion tons 5552.5 104 tons 12466.4 104 tons 1932.2 104 tons 45.3 104 tons
1500
kgce
Energy products
339
1000
500
0
Natural gas(CNY per m3) Industry 2.47 Resident 2.15 Public service 2.09
3.41 3.41 3.41
0.94 1.26 1.32
50.9 billion m3 13.3 billion m3 5.3 billion m3
Electricity ( CNY per kW h) Resident 0.49
1.03
0.54
362.27 billion kW h
Fig. 4. The change of energy consumption and efficiency of China. Source: Calculated by the authors through the data in (NBS, 2010)
6000
Coal consumption per capita,kg Oil consumption per capita,kg Electricity consumption per capita,kWh
5000
4000
Table 3 Calculation for fossil energy subsidies scale of China, 2007.
3000
Energy products
Subsidies scale (billion CNY)
Average subsidies rate
Coal Oil products Gasoline Diesel Fuel oil Aviation kerosene Natural gas Electricity Total (billion CNY)
43.0 271.8 65.9 194.3 10.8 0.8 71.6 195.6 582.0
6.46% 19.52% 15.53% 21.92% 13.73% 25.92% 35.46% 52.43 –
effect has the same effects as technical advancement to some extent, resulting in rebound effect; therefore removing such price-gap would serve as a buffer to the rebound effect, and in the following section using an EIMO model we simulate how much energy consumption would be reduced through removing subsidies.
4. Case study In this section, we conduct an empirical study about China’s energy consumption and efficiency as well as analysis of rebound effect. Next we analyze how energy subsidies reform would affect the energy product or service prices. Based on these two parts and through the established EIMO model, we make a simulation on the mitigating effect mechanism of subsidies reform. 4.1. Empirical study of current energy consumption and efficiency in China First we made an empirical study solely on the statement of energy consumption and efficiency and the results are illustrated in Fig. 4. Although during the first decade of the century the energy efficiency was enhanced dramatically – mostly due to the innovative energy conservation and efficient technologies – however, from the perspective of total energy consumption, it still kept increasing. During the decade, energy consumption per GDP decreased by 39%, while energy consumption per capita, residential energy consumption per capita for urban area and for
2000
1000
0 2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Fig. 5. Different types of energy consumption per capita over time. Source: Calculated by the authors through the data in NBS (2010)
rural area increased by 99%, 100%, 57% and 133%, respectively. Fig. 5 shows explicitly the different energy resources consumption over time. Electricity was the most rapidly increasing energy resource, from 2000 to 2009 its consumption per capita increased more than doubled, from 1067 kW h to 2871 kW h, the consumption of coal and oil rose from1117 kg to 2222 kg and from 178 kg to 288 kg, respectively. Empirical study results indicate there was rebound effect. We only make a qualitative analysis as the focus of this study was not mechanism analysis on the rebound effect in China. China’s rapid energy consumption was mainly driven by the rapid demand growth coming along with economic development; rebound effect, a common phenomenon in developed countries (Barker et al., 2007; Freire Gonza´lez, 2010; Matos and Silva, 2011; Maxwell et al., 2011; Wang et al., 2012b; Wei, 2010), did exist in China. Various studies supported this conclusion and the average rebound effect of China in the past decades ranged from 30 to 50% in general (Li and Yonglei, 2012; LIU and LIU, 2008; Ouyang et al., 2010; Wang et al., 2012a, 2012c). A report in EU published in 2011 also estimated that the rebound effect in China was about 30% (Maxwell et al., 2011). As can been seen, both empirical data and literatures supports the existence of rebound effect in China. In the following part, we make a qualitative analysis on it and further analyze how subsidies reform reduces it. Fig. 6 illustrates rebound effect. Line A shows an ideal condition of energy efficiency measure, that is, the efficiency improvement reduces the total energy consumption; however in reality, it is nearly impossible to happen due to the rapid economic growth and increasing material requirement of mankind. Line B indicates that energy efficiency condition is affected little by rebound effect.
L. Hong et al. / Energy Policy 54 (2013) 335–342
In this more reasonable scenario, the energy consumption generally stays stable while not increasing sharply. Line C shows how rebound effect would affect energy efficiency measures. Despite of a great deal of energy efficiency improvements, the energy consumption would still go up sharply due to the potent rebound effect. The curve is an illustration of what exactly is happening today. Finally, Line D reflects the mitigated rebound effect if proper policy intervention is launched so that energy consumption would be reduced to some extent. As mentioned above, the internal mechanism of energy subsidies would drive the Line C further upward by making a price-gap on the energy price. When applying subsidies reform, the price-gap would be removed and as a result the rebound effect could be reduced. Under this condition, Line C would move closer to Line D. 4.2. Subsidies reform and the price change As subsidies lower the end-use prices, we use the constantelasticity inverse demand function to calculate the impacts of removing the subsidies on energy consumption. q ¼ Pe
ð8Þ
Dq ¼ Q 0 Q 1
ð9Þ
where q is the energy consumption and e is the long-term demand elasticity. Dq stands for the change in consumption after removing the subsidies. Q0 and Q1 are the quantity before and after removing the price-gap, respectively. With price-gap and the consumption quantity, the subsidies scale could be estimated, and with the data of price elasticity, it can be obtained that how the price would change after removing the subsidies. The results are listed in Table 4.
4.3. Simulation of mitigation effect from subsidies reform In this section we apply the EIMO model to simulate how the elimination of the energy subsidies would further reduce the consumption from the life cycle perspective. Fig. 7 shows the physical energy consumption for different sectors. Through the calculation of total consumption matrix, we obtain an accumulative consumption matrix for physical energy consumption in different sectors (Table 5). The process of simulation is: removing energy subsidies would coherently increase the price, and according to the equilibrium theory end-use demand would be reduced, thus further decreasing the physical input of energy in specific sectors. In detail, removing coal subsidies would basically reduce the end-user demand of industry, removing oil subsidies would mainly lower demand of transportation, reducing natural gas and electricity subsidies would virtually decrease demand of households living related sectors—sale, accommodation and catering industry and the other service industry. The change of final demand is shown in Table 6. The simulation results of EIMO model are shown in Fig. 8, indicating that by removing energy subsidies, the coal, oil, natural gas and electricity would be reduced by 17.74, 13.47, 3.64 and 15.82 million tce, respectively.
40000 35000 30000
10000 tce
340
25000 20000 15000 10000 5000 0 A
B
C
D
E
F
Coal
1669.89
35860.17
403.82
489.62
620.21
6365.87
Oil
1917.31
11163.82
1640.75
10918.25
1005.22
3746.76
NG
0.00
5323.72
27.82
138.67
227.54
1988.04
1203.14
27737.42
379.76
653.72
1142.75
6552.18
Electricity
Fig. 7. Physical energy consumption in different sectors. Note: A to F present the primary industry, Industry, Construction industry, Transformation industry, Sale, Living and Catering industry, and the other Service sectors.
Table 5 Total consumption matrix for physical energy consumption.
Fig. 6. Illustration of rebound effect. Source: Revised from Ouyang et al. (2010).
Coal Oil Natural gas Electricity
A
B
C
D
E
F
0.1047 0.0839 0.0104 0.0811
0.2310 0.1078 0.0353 0.1826
0.1646 0.1276 0.0253 0.1330
0.1063 0.3250 0.0189 0.0930
0.0939 0.0861 0.0189 0.0925
0.1401 0.0883 0.0325 0.1283
Table 4 Price change of different energy resources after removing the subsidies.
Energy sources Coal
Subsidy rate (%) 6.46
Oil
19.52
Natural gas Electricity
23.56 52.43
Price elasticity 0.35 0.27(Transportation) 0.19(Industry) 0.31 0.16
Source Li and Yonglei (2012) (Lin and Jiang, 2011) (Lin and Jiang, 2011; Liu and Li, 2011) (Qi et al., 2009; Liu and Li, 2011)
Price change after removing the subsidies (%) þ6.37 þ 18.26 þ 18.98 þ20.42 þ 46.55
L. Hong et al. / Energy Policy 54 (2013) 335–342
Table 6 The change of final demand of each sector. Sectors
Change of final demand
A B C D E F
0 1.45% 1.45% 6.47% 11.21% 11.21%
0
10000 tce
-200 -400 -600 -800 -1000 -1200 Coal Oil NG Electricity
A
B
C
D
E
F
0.00 0.00 0.00 0.00
-313.47 -146.36 -47.88 -247.87
-144.92 -112.30 -22.25 -117.12
-81.34 -248.65 -14.49 -71.13
-215.04 -197.27 -43.21 -211.91
-1019.83 -642.24 -236.32 -933.52
Fig. 8. Simulation result of EIMO model.
Table 7 Carbon emissions coefficients of different energy types.
341
the scale of fossil energy subsidies of China in 2007, the total of which is 582.0 billion CNY (76.6 billion USD) in 2007 and a high subsidies rate was identified; then with statistical and survey data, we prove the existence of rebound effect in China’s energy consumption from 2000 to 2009: the rebound effect of electricity consumption is the most evident, consistent with the importance of electricity in modern societal lives. Additionally, based on the 2007 national monetary input–output table of China and physical energy flow analysis, we develop a hybrid physical energy input and monetary output table (EIMO) to simulate the mitigation effect of subsidies reform. The EIMO model innovatively reveals the relationship between economic activities and physical energy flows. Simulation results shows that removing energy subsidies would conduce to price increases of coal, oil, natural gas and electricity by 6.37%, 18.62%, 20.42% and 46.55%, respectively; moreover the physical total consumption of coal, oil, natural gas and electricity would be reduced by 17.74, 13.47, 3.64 and 15.82 million tce, respectively. The economic and environmental gains of reducing budget as well as lowering energy consumption and the related CO2 emissions are achieved. This paper focuses on the physical energy input reduction through a life cycle perspective; however, energy policy reform and mitigation of rebound effect are much more than just what the data display. While international studies have already identified that energy and environmental tax-related policies are effective support to energy efficiency technologies in the reduction of the overall energy consumption and the accompanied CO2 emissions, therefore we propose several policy designs and future studies based on our analytical results.
Energy subsidies have been highly controversial for a long Energy types
Carbon emissions coefficients
Source
Coal Oil Natural gas Electricity
0.76 tC/tce 0.57 tC/tce 4.48E-05 tC/tce 0.00 tC/tce
Liang Liang Liang Liang
and and and and
Zhang Zhang Zhang Zhang
(2011) (2011) (2011) (2011)
4.4. Analysis for economic and environmental gains Based on the proposed indicators and EIMO model’s simulation results, we calculate the two assessment indicators. The CO2 emissions reduction could be derived via the emissions coefficients (Table 7) of different energy types. The results shows that fossil energy subsidies reform could result in a money saving of 582.00 billion RMB, an energy saving of 50.67 million tce plus the total CO2 emissions reduction of 77.60 million tons. Based on the proposed assessment indicators:
In terms of CO2 emissions reduction per unit of monetary
saving, the gains is 1.33 tCO2/10000 CNY; In terms of energy saving per unit of monetary saving, the gains is 0.87tce/10000 CNY.
5. Conclusion and discussion There have been a history of fierce debate about energy subsidies and rebound effect of energy consumption, especially under the background of the rapid economic growth of China and the global threat of climate change. They attract worldwide attention and energy policies on those issues are important as a result. Aiming to contribute to this topic, this paper makes a comprehensive analysis on how energy subsidies reform could mitigate rebound effect. Applying price-gap approach, we calculate
time in that they distort the energy price and indirectly harm the environment, hence it become a worldwide trend to decrease or eliminate it. However, reform should not only target on its environmental effects, but also the comprehensive social-economic matters such as how it would affect the macro economy, households living, and the interconnection among each industries. Rebound effect is not only driven by the economic growth, but the industrial structure as well. Thus the mitigation measures should incorporate and bind technological, fiscal, and structure adjustment issues together. Our previous study indicates that subsidies reform also exerts optimization effect on energy consumption structure and industrial structure. However for further study, more detail research is needed in the future. The reform of removing subsidies should be executed in cooperation with appropriate redistribution mechanism on economic benefits coming from increased energy efficiency, and other policies such as environmental taxation. In this study, we narrow our concentration on the economic and environmental gains of subsidies reform and mainly explore how it indirectly contributes to the mitigation of rebound effect. In the future, we would conduct more detailed study on the following issues: what is the internal mechanism of China’s rebound effect, and what is the econometric relationship between energy subsidies and the rebound effect.
Acknowledgement This study is financially supported by the Ministry of Education of the People’s Republic of China, Philosophy Social Planning project, ‘‘Renewable energy industry’s financing risk management and policy support system building— based on life cycle theory’’, 2012(12YJAZH056); The Energy Foundation (USA) projects, ‘‘Energy subsidies reform and the sustainable development of
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China’s economy’’,2011(G-1111-15134); Post-doctoral Scientific Fund projects, ‘‘Sustainable development and social equity: based on energy subsidies theory and the practice of policy’’, 2009(20090460202). We also thank the editors and reviewers for their comments.
Appendix A. Supporting information Supplementary data associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.enpol.2012.11.045.
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Contents lists available at SciVerse ScienceDirect
Energy Policy journal homepage: www.elsevier.com/locate/enpol
Economic and environmental gains of China’s fossil energy subsidies reform: A rebound effect case study with EIMO model Li Hong a,n, Dong Liang b,c,1, Wang Di d a
School of Economics, Peking University, Haidian District, 5 Yi HeYuan AV., Beijing 100871, PR China National Institute for Environmental Studies (NIES), 16-2 Onogawa, Tsukuba-City, Ibaraki 305-8506, Japan c Graduate School of Environmental Studies, Nagoya University, Furo-cho, Chikusa-ku, Nagoya City 464–8601, Japan d Institute of Population Research, PekingUniversity, Haidian District, 5 Yi HeYuan AV., Beijing 100871, PR China b
H I G H L I G H T S c c c c
Analyze the economic and environmental gains of fossil energy subsidies reform in China. Energy input and monetary output model was applied for analysis. Subsidies reform would help to reduce the rebound effect. The benefits of money saving, energy saving and CO2 mitigation were achieved.
a r t i c l e i n f o
abstract
Article history: Received 16 May 2012 Accepted 20 November 2012 Available online 21 December 2012
Energy consumption and efficiency emerged as the hottest topic in the context of China’s sustainable development. Energy subsidies and ‘‘rebound effect’’ were closely related to this topic while few combinative studies on them with a focus on China. This paper employed a co-thinking approach, focusing on how the energy subsidies reform could mitigate the rebound effect in China, and how to achieve an ‘‘economic and environmental gains’’ that reduced pecuniary spending, improved the distorted energy market and reduced energy consumption simultaneously. Firstly, with price-gap approach we calculated the total energy subsidies scale of China in 2007, which amounted to582.0 billion CNY; then we detected and identified rebound effect of China energy consumption with the features. Furthermore, based on China 2007 monetary input–output table and energy flow analysis, we compiled a hybrid physical energy input and monetary output model (EIMO) to simulate the mitigation effect of subsidies reform. Results showed that removing energy subsidies would decrease ultimate demand of different economy sectors and reduce the accumulatively physical consumption of coal, oil, natural gas and electricity by 17.74, 13.47, 3.64 and 15.82 million tce, respectively. Finally we discussed relevant policy issues on China’s energy subsidies reform in depth. & 2012 Elsevier Ltd. All rights reserved.
Keywords: Energy subsidies Rebound effect EIMO model
1. Introduction With rapid economic growth, China has faced more and more emerging conflicts in terms of energy supply and demand, as well as series of related environmental problems. In 2007, China became the world’s largest CO2 emitter (BP, 2008) and in 2010, it overtook United States becoming the world largest energy consumer, contributing to a share of 20.3% of total worldwide energy consumption (BP, 2011).
n Corresponding author. Tel.: þ86 1367 136 6001, þ 86 10 62755658; fax: þ 86 10 62751460. E-mail addresses: [email protected] (L. Hong), [email protected] (D. Liang). 1 Tel.: þ81 080 4090 2595; fax: þ 81 029 850 2314.
0301-4215/$ - see front matter & 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.enpol.2012.11.045
China is a developing country in industrialization phase with economic development, population growth, and living standardimproving. Undoubtedly its energy demand will soar in the future. Therefore improving energy efficiency is of vital importance for energy conservation and CO2 emissions reduction, and Chinese government has shown growing concern about those issues. Since 2002, several national policies such as the Cleaner Production Promotion law, Circular Economy Promotion law have been launched in which enhancing energy efficiency is one key aspect, and lots of advanced energy conservation technologies have been utilized (Li et al., 2010). Due to those efforts, the energy consumption per unit of GDP of China has decreased by 40% over the past decade. However, although the energy efficiency in China has been enhanced significantly, it is disappointing that the energy
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Energy consumption
Energy consumption/GDP
Energy consumption, 10000 t
300000 250000 200000 150000 100000 50000
Energy consumption/GDP, t/10000RMB
350000
0
Fig. 1. China’s energy consumption and efficiency. Source: (NBS, 2011)
consumption is still increasing aggressively rather than decreasing (Fig. 1). The most important reason is the huge energy demands driven by rapid economic growth, while the ‘‘rebound effect’’ also played an important role (IEA, 1999). The ‘rebound effect’ is the term referring to the behavioral or other systemic response to improved resource utilization efficiency due to new technologies (Greening, 2000; Ouyang et al., 2010; Ruzzenenti and Basosi, 2008; Saunders, 1992; Wang et al., 2012c). Unintended consequences always complemented with technology advances in household level and industries; specifically, part of the energy savings derived from new technologies are offset by increased energy consumption. The mechanism is that energy efficiency enhancement would reduce the prices of energy products or services, thus leading to more demand and consumption. In theory, energy subsidies facilitate the rebound effect as it also lower the end-use price, consequently encourage the consumption and potentially damage the environment (de Moor, 2001; IEA, 1999; Li et al., 2011; Liu and Li, 2011; OECD, 2005; UNEP, 2003, 2008). Based on this point, energy subsidies reform would be an effective way to mitigate the rebound effect, further make the energy efficiency measures more efficient, and ultimately achieve a collaborative benefit in terms of economic benefit and environmental benefit. Since the early study on rebound effect in estimation of energy savings (Khazzoom, 1980), such issues have been widely discussed and debated as rebound effect in different energy consumption sectors (Bentzen, 2004; Khazzoom, 1980; Li and Yonglei, 2012; Ouyang et al., 2010; Wang et al., 2012b), empirical studies in developed and developing regions or countries like UK, Hong Kong, India and China (Barker et al., 2007; Freire Gonza´lez, 2010; Haas and Biermayr, 2000; Mizobuchi, 2008; Roy, 2000; Sorrell et al., 2009; Wang et al., 2012b, 2012c), modeling the rebound effect with partial equilibrium model (Ouyang et al., 2010), general equilibrium model (Grepperud and Rasmussen, 2004)and econometric method (Barker et al., 2007; Bentzen, 2004), and specific technologies or policy (de Haan et al., 2006; Matos and Silva, 2011; Safarzynska, 2012). As for the study about China, most studies focused on direct rebound effect in certain sectors (Li and Yonglei, 2012; Ouyang et al., 2010; Wang et al., 2012b, 2012c). However, although rebound effect and subsidies are intrinsically connected, few studies innovatively have them linked and in quantified method. Energy efficiency measures in cooperation with environmental and energy policy tools are considered to be essential cushion for the rebound effect (Maxwell et al., 2011), therefore research studying the interaction of energy subsidies and rebound effect would provide a beneficial discussion on the topic of energy conservation and climate change.
This paper adopts a co-thinking approach to study the economic and environmental gains of energy subsidies reform and its contribution to reduce the rebound effect, with China as the case study, in application with an improved hybrid physical energy input and monetary output model (EIMO). We mainly contribute to the following aspects: first of all, with the calculation of the national fossil energy subsidies scale in China in 2007, we analyzed its inherent interaction with energy rebound effect in depth; then we proposed an improved energy input–output model based on the 2007 China monetary input–output table; thirdly, with the EIMO model, we quantitatively analyzed the economic and environmental gains of subsidies reform; lastly based on the quantified analysis we discuss the policy issues about China’s energy policy reform. We hope this study would offer an improved understanding of subsidies reform and climate change.
2. Analytical framework and methodology Several terminologies, conceptions and methodologies were quoted and applied in this paper. This section would clarify their interconnection under the general analytical framework of this study. In the following part we analyzed the intrinsic connection between rebound effect and subsidies so as to present why the subsidies reform could generate economic growth while reduce the rebound effect. In the context of methodology, price-gap approach is adopted to quantify the scale of China fossil energy subsidy, empirical study approach used to qualitatively analyze the relationship of subsidies reform and rebound effect, and the hybrid energy input–output model applied to quantitatively simulate how subsidies reform would indirectly affect rebound effect. 2.1. Interaction among energy subsidies and rebound effect The so called ‘‘rebound effect’’ is the increasing energy consumption enabled by energy efficiency enhancement. According to a partial equilibrium theory, as energy consumption per unit of economic output decreases, the efficiency improvement would implicitly lead to a reduction in the price of products, in other words people can afford more energy-using outputs if costs per unit have fallen, which is an income effect (Herring and Roy, 2002; Roy, 2000; Sorrell et al., 2009). Basically the key mechanism of rebound effect is that technical advancement enhances the efficiency, and further reduces the price. The effect of energy subsidies is that it could lower the end-use price of energy products or service, so to some extent subsidies would strengthen rebound effect. Fig. 2 showed an internal mechanism of how energy subsidies affect the rebound effect. While rebound effect and subsidies has intersections, it is necessary to find a systematical approach to identify such interaction. Here we make the co-thinking: whether there would be one option that could reduce pollutants and/or save energy and/or make money meanwhile could reduce CO2 emissions and/or other pollutants? Through the analysis in Fig. 2, fossil energy subsidies reform could not only lower the governmental budget and ease the distortion of energy market (monetary issues), but reduce the energy consumption and related carbon emissions as well. The removal of price gap and ensuing energy consumption reduction would contribute to the mitigation of rebound effect, realizing the economic and environmental gains. 2.2. Analytical framework This study mainly focused on a quantified economic and environmental assessment on how energy subsidies reform contributes to the mitigation of rebound effect. The analytical
L. Hong et al. / Energy Policy 54 (2013) 335–342
337
The income effect or indirect effect: lower energy price cause
Fig. 2. Internal connection of energy subsidies and rebound effect.
more spending and subsequent more energy use due to higher disposable income level; The macroeconomic rebound effect: the energy efficiency technologies boost the entire macro economy so that production is upgraded, and as a result more energy is consumed.
In this study, through the hybrid input–output model, it is able to identify the energy consumption from a life cycle perspective, that the consumption in the whole supply chain could be considered. Or rather, we could explore how subsidies reform could contribute to the mitigation of the macroeconomic rebound effect. The analysis targets on the indirect one as we mainly focus on the physical amount of energy savings and emissions reduction of subsidies reform. Before using the energy Input–output framework, it is necessary to quantify the variations in the end user demand when energy efficiency is improved. 2.3. Assessment indicators for economic and environmental gains Based on the analysis in Section 2.1, the economicenvironmental gains mainly generated from the effect that subsidies reform would dismiss the price gap of energy products, thus reducing the end-user demand in relevant sectors, and finally leading to the consumption and related carbon emissions reductions, which could be seen as a mitigation of rebound effect. For evaluation, we proposed two indicators: a. Gains in terms of CO2 emissions reduction per unit of monetary saving (tCO2/CNY), which means how much CO2 emission could be reduced when one unit of money is saved. b. Gains in terms of energy saving per unit of monetary saving (tce/CNY), which means how much energy could be saved when one unit of money is saved. With the two proposed indicators we could identify how subsidies reform could contribute to the mitigation of rebound effect (save energy) and at the same time achieve economic benefit. 2.4. Price-gap approach The Price-gap approach focuses on consumer-side subsidies and quantifies the gap between reference prices and subsidized end-use prices. The methodology is described as follow (IEA, 1999):
Fig. 3. Analytical framework.
framework is shown in Fig. 3. In the first step we identified the key points of economic and environmental gains and propose assessment indicators; then we calculated the subsidies scale in 2007. Subsequently we established a hybrid energy input–output model with which to analyze and simulate. In the case study section, we further analyze the current energy consumption and efficiency situation of China, identify the topic of rebound effect and simulate the scenario of eliminating energy subsidies with the established model. The simulation results would be reevaluated by the assessment indicators to figure out the benefits. In the last section we discuss policy proposals. It is noted that there are three types of rebound effects (Greening, 2000; Wang et al., 2012c; Wei, 2010):
The direct effect: energy becomes cheaper, so an individual uses more direct energy products, such as heat;
Si ¼ PGi C i
ð1Þ
PGi ¼ M i Pi
ð2Þ
where Si is the subsidies scale of energy product I, and PGi the price-gap of energy product i. C i denotes the consumption of energy product i; Mi denotes the reference price of energy product i (refers to the price without subsidies). P i is the enduse prices of energy product i. According to the methodology, subsidies scale is calculable with reference price and end-use price. In most instances the enduse prices are available from statistics; thus in applying the methodology the crux is to figure out the reference prices, which requires the data of market prices of international trade, taxes, transportation costs, and so on. In this paper we concentrate on three primary fossil energy including coal, oil and natural gas, and the secondary energy electricity. For coal, in 2007 China was the net exporter of coal and net importer of oil products. According to the methodology of IEA, the
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related reference coal prices are adjusted as follows (IEA, 1999): M i ¼ FOBi þ Di þVAT
ð3Þ
where, FOBi is free-on-board export price selected as starting point price. Di is internal distribution cost added to reflect variations in different modes of transportation and distances between the ports and the location of consumer market. VAT stands for value added tax. For oil products and natural gas, the reference prices are calculated according to Eq. (4): M i ¼ International_pricei þ Di þ Tax
ð4Þ
Tax includes VAT, customer tax, etc. For electricity, the reference price is long-term marginal price (Lin and Jiang, 2011). The detail description of price-gap approach was showed in our previous research (Li et al., 2011; Liu and Li, 2011).
Table 1 The structure of hybrid energy input monetary output model. Intermediate Final demand monetary output sector Y
Monetary input
Intermediate monetary input Added value Total monetary output Physical energy input
Energy resource
1 y n V X
1 y m
M
Y1 y Yn
Total output X X1 y Xn
Physical input distribution E
demand are shown in Eq. (7):
2.5. Hybrid physical energy input and monetary output model After obtaining the subsidy scale, we build a model to link subsidy and rebound effect as the further key step. Rebound effect relates to the energy prices and its consumption, while energy subsides affects the energy end-use prices, and it is of great importance in the way to connect the price (economic issue) and consumption (physical issue). To resolve it hybrid input output model is a useful tool to estimate the issues combining economic and environmental matters as it explains the inherent relationship between material flows and economic flows (Xu, 2010). Inspired by the previous work of the physical input–output model and material physical input and monetary output model in environmental study fields (Giljum and Hubacek, 2009; Liang et al., 2010; Liang and Zhang, 2011, 2012), in this paper, we propose an improved physical energy input and monetary output model (EIMO) to simulate how subsidies reform could mitigate the rebound effect. The EIMO model is based on China monetary input–output table, and physical energy input was compiled with energy flow analysis. We categorize the 42 sectors into 6 divisions (A to Z) according to the energy consumption features: The primary industry, Industry, Construction industry, Transformation industry, Sale, Living and Catering industry, and the other Service sectors. For each sector, the energy input is in physical units and the output is in monetary units. In this way, the model quantitatively represents the correlations between economic sectors by monetary input output table (MIOTs) and the connections between the ecological system and the economic system by the method of energy or material flow analysis (EFA or MFA). Table 1 shows the structure of EIMO model. The direct monetary consumption matrix A and Leontief inverse matrix (I A) 1 as well as the row balances are illustrated in various studies on I–O analysis (Holub and Schnabl, 1985; Leontief, 1936; Wu and Chen, 1990). The row balances are shown in Eqs. (5) and (6): AX þ Y ¼ X
ð5Þ
X ¼ ðIAÞ1 Y
ð6Þ
The m n matrix E could be seen as the energy intensity among the sectors, or the direct energy consumption matrix. They could be obtained from the energy input data and economic output data of each sector, and based on the energy balance table and energy statistical data, the direct energy flow of each sector is analyzed and the direct energy consumption matrix is obtained. Relationships between total energy consumption and final
D ¼ EX ¼ EðIAÞ1 Y
ð7Þ
where, D denotes the total or cumulative energy consumption. Based on above mathematical relationships, energy consumption can be inherently connected to economic activities. Analysis can be conducted by setting one of the parameters exogenous. The performance of the system, both ecologically and economically, can be simulated from different aspects by changing one of those parameters. Particularly for this study, it could link the price with the real physical material consumption. It is noted that in this study, we allocated the electricity into different sectors due to our research demand (we want to investigate the consumption change of the electricity after the subsidies reform). To allocate the electricity, the issue of power generation and sector selfpower generation are carefully considered. Here we explore it according to the physical energy balance table using energy flow analysis. For primary industry, transportation, construction, and service sector, the allocation amount of electricity is their final consumption transformed into energy unit. For the industry, we deducted the coal, oil and gas consumption of producing electricity because the existence of energy manufacturing process. The original data is avail in the energy balance table of China. For more details about the hybrid input–output table, see the ‘‘Supplementary material’’.
3. Fossil energy subsidies scale Detailed calculation can be referred to our previous work (Li et al., 2011; Liu and Li, 2011). We calculated four categories of energy resources, including coal, oil, natural gas and electricity. Table 2 summarized the price-gap and consumption for different energy products in China in 2007. Based on Eqs. (1) and (2), we calculate the fossil energy subsidies in China and the average subsidy rate for various energy products as a basic for following analysis. In theory, subsidy rate equates to the ratio between price-gap and the reference price. The results are shown as Table 3. According to Table 3, China’s total fossil energy subsidies were 582.0 billion CNY (76.6 billion USD) in 2007 (IEA, 2008) estimated that China’s energy subsidies were about 300 billion CNY (including electricity subsidies) in 2007.Our results are higher than that of IEA due to different views on coal pricing mechanism and the selection of reference prices. It is noted that in effect the subsidies produces a price-gap for the energy products, making the price of energy products and services lower than their real market value. Such lowering-down
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Table 2 Price-gap and consumption of energy products of China, 2007. End-use prices
Coal (CNY per ton) Steam coal 480.3 Coal contract 285.0 Oil products(CNY per ton) Gasoline 6464.1 Diesel 5548.2 Fuel oil Aviation kerosene
3526.7 5106.7
Reference prices
Pricegap
500.7 306.0
20.4 21.0
7652.5 7105.9
1188.4 1557.8
4088.1 6893.7
561.4 1787.0
Energy consumption per-GDP Energy consumption per-capita Annual Residential Energy Consumption Per Capita Urban Annual Residential Energy consumption Rural Annual Residential Energy consumption
2500
Consumption 2000
1.33 billion tons 0.76 billion tons 5552.5 104 tons 12466.4 104 tons 1932.2 104 tons 45.3 104 tons
1500
kgce
Energy products
339
1000
500
0
Natural gas(CNY per m3) Industry 2.47 Resident 2.15 Public service 2.09
3.41 3.41 3.41
0.94 1.26 1.32
50.9 billion m3 13.3 billion m3 5.3 billion m3
Electricity ( CNY per kW h) Resident 0.49
1.03
0.54
362.27 billion kW h
Fig. 4. The change of energy consumption and efficiency of China. Source: Calculated by the authors through the data in (NBS, 2010)
6000
Coal consumption per capita,kg Oil consumption per capita,kg Electricity consumption per capita,kWh
5000
4000
Table 3 Calculation for fossil energy subsidies scale of China, 2007.
3000
Energy products
Subsidies scale (billion CNY)
Average subsidies rate
Coal Oil products Gasoline Diesel Fuel oil Aviation kerosene Natural gas Electricity Total (billion CNY)
43.0 271.8 65.9 194.3 10.8 0.8 71.6 195.6 582.0
6.46% 19.52% 15.53% 21.92% 13.73% 25.92% 35.46% 52.43 –
effect has the same effects as technical advancement to some extent, resulting in rebound effect; therefore removing such price-gap would serve as a buffer to the rebound effect, and in the following section using an EIMO model we simulate how much energy consumption would be reduced through removing subsidies.
4. Case study In this section, we conduct an empirical study about China’s energy consumption and efficiency as well as analysis of rebound effect. Next we analyze how energy subsidies reform would affect the energy product or service prices. Based on these two parts and through the established EIMO model, we make a simulation on the mitigating effect mechanism of subsidies reform. 4.1. Empirical study of current energy consumption and efficiency in China First we made an empirical study solely on the statement of energy consumption and efficiency and the results are illustrated in Fig. 4. Although during the first decade of the century the energy efficiency was enhanced dramatically – mostly due to the innovative energy conservation and efficient technologies – however, from the perspective of total energy consumption, it still kept increasing. During the decade, energy consumption per GDP decreased by 39%, while energy consumption per capita, residential energy consumption per capita for urban area and for
2000
1000
0 2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Fig. 5. Different types of energy consumption per capita over time. Source: Calculated by the authors through the data in NBS (2010)
rural area increased by 99%, 100%, 57% and 133%, respectively. Fig. 5 shows explicitly the different energy resources consumption over time. Electricity was the most rapidly increasing energy resource, from 2000 to 2009 its consumption per capita increased more than doubled, from 1067 kW h to 2871 kW h, the consumption of coal and oil rose from1117 kg to 2222 kg and from 178 kg to 288 kg, respectively. Empirical study results indicate there was rebound effect. We only make a qualitative analysis as the focus of this study was not mechanism analysis on the rebound effect in China. China’s rapid energy consumption was mainly driven by the rapid demand growth coming along with economic development; rebound effect, a common phenomenon in developed countries (Barker et al., 2007; Freire Gonza´lez, 2010; Matos and Silva, 2011; Maxwell et al., 2011; Wang et al., 2012b; Wei, 2010), did exist in China. Various studies supported this conclusion and the average rebound effect of China in the past decades ranged from 30 to 50% in general (Li and Yonglei, 2012; LIU and LIU, 2008; Ouyang et al., 2010; Wang et al., 2012a, 2012c). A report in EU published in 2011 also estimated that the rebound effect in China was about 30% (Maxwell et al., 2011). As can been seen, both empirical data and literatures supports the existence of rebound effect in China. In the following part, we make a qualitative analysis on it and further analyze how subsidies reform reduces it. Fig. 6 illustrates rebound effect. Line A shows an ideal condition of energy efficiency measure, that is, the efficiency improvement reduces the total energy consumption; however in reality, it is nearly impossible to happen due to the rapid economic growth and increasing material requirement of mankind. Line B indicates that energy efficiency condition is affected little by rebound effect.
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In this more reasonable scenario, the energy consumption generally stays stable while not increasing sharply. Line C shows how rebound effect would affect energy efficiency measures. Despite of a great deal of energy efficiency improvements, the energy consumption would still go up sharply due to the potent rebound effect. The curve is an illustration of what exactly is happening today. Finally, Line D reflects the mitigated rebound effect if proper policy intervention is launched so that energy consumption would be reduced to some extent. As mentioned above, the internal mechanism of energy subsidies would drive the Line C further upward by making a price-gap on the energy price. When applying subsidies reform, the price-gap would be removed and as a result the rebound effect could be reduced. Under this condition, Line C would move closer to Line D. 4.2. Subsidies reform and the price change As subsidies lower the end-use prices, we use the constantelasticity inverse demand function to calculate the impacts of removing the subsidies on energy consumption. q ¼ Pe
ð8Þ
Dq ¼ Q 0 Q 1
ð9Þ
where q is the energy consumption and e is the long-term demand elasticity. Dq stands for the change in consumption after removing the subsidies. Q0 and Q1 are the quantity before and after removing the price-gap, respectively. With price-gap and the consumption quantity, the subsidies scale could be estimated, and with the data of price elasticity, it can be obtained that how the price would change after removing the subsidies. The results are listed in Table 4.
4.3. Simulation of mitigation effect from subsidies reform In this section we apply the EIMO model to simulate how the elimination of the energy subsidies would further reduce the consumption from the life cycle perspective. Fig. 7 shows the physical energy consumption for different sectors. Through the calculation of total consumption matrix, we obtain an accumulative consumption matrix for physical energy consumption in different sectors (Table 5). The process of simulation is: removing energy subsidies would coherently increase the price, and according to the equilibrium theory end-use demand would be reduced, thus further decreasing the physical input of energy in specific sectors. In detail, removing coal subsidies would basically reduce the end-user demand of industry, removing oil subsidies would mainly lower demand of transportation, reducing natural gas and electricity subsidies would virtually decrease demand of households living related sectors—sale, accommodation and catering industry and the other service industry. The change of final demand is shown in Table 6. The simulation results of EIMO model are shown in Fig. 8, indicating that by removing energy subsidies, the coal, oil, natural gas and electricity would be reduced by 17.74, 13.47, 3.64 and 15.82 million tce, respectively.
40000 35000 30000
10000 tce
340
25000 20000 15000 10000 5000 0 A
B
C
D
E
F
Coal
1669.89
35860.17
403.82
489.62
620.21
6365.87
Oil
1917.31
11163.82
1640.75
10918.25
1005.22
3746.76
NG
0.00
5323.72
27.82
138.67
227.54
1988.04
1203.14
27737.42
379.76
653.72
1142.75
6552.18
Electricity
Fig. 7. Physical energy consumption in different sectors. Note: A to F present the primary industry, Industry, Construction industry, Transformation industry, Sale, Living and Catering industry, and the other Service sectors.
Table 5 Total consumption matrix for physical energy consumption.
Fig. 6. Illustration of rebound effect. Source: Revised from Ouyang et al. (2010).
Coal Oil Natural gas Electricity
A
B
C
D
E
F
0.1047 0.0839 0.0104 0.0811
0.2310 0.1078 0.0353 0.1826
0.1646 0.1276 0.0253 0.1330
0.1063 0.3250 0.0189 0.0930
0.0939 0.0861 0.0189 0.0925
0.1401 0.0883 0.0325 0.1283
Table 4 Price change of different energy resources after removing the subsidies.
Energy sources Coal
Subsidy rate (%) 6.46
Oil
19.52
Natural gas Electricity
23.56 52.43
Price elasticity 0.35 0.27(Transportation) 0.19(Industry) 0.31 0.16
Source Li and Yonglei (2012) (Lin and Jiang, 2011) (Lin and Jiang, 2011; Liu and Li, 2011) (Qi et al., 2009; Liu and Li, 2011)
Price change after removing the subsidies (%) þ6.37 þ 18.26 þ 18.98 þ20.42 þ 46.55
L. Hong et al. / Energy Policy 54 (2013) 335–342
Table 6 The change of final demand of each sector. Sectors
Change of final demand
A B C D E F
0 1.45% 1.45% 6.47% 11.21% 11.21%
0
10000 tce
-200 -400 -600 -800 -1000 -1200 Coal Oil NG Electricity
A
B
C
D
E
F
0.00 0.00 0.00 0.00
-313.47 -146.36 -47.88 -247.87
-144.92 -112.30 -22.25 -117.12
-81.34 -248.65 -14.49 -71.13
-215.04 -197.27 -43.21 -211.91
-1019.83 -642.24 -236.32 -933.52
Fig. 8. Simulation result of EIMO model.
Table 7 Carbon emissions coefficients of different energy types.
341
the scale of fossil energy subsidies of China in 2007, the total of which is 582.0 billion CNY (76.6 billion USD) in 2007 and a high subsidies rate was identified; then with statistical and survey data, we prove the existence of rebound effect in China’s energy consumption from 2000 to 2009: the rebound effect of electricity consumption is the most evident, consistent with the importance of electricity in modern societal lives. Additionally, based on the 2007 national monetary input–output table of China and physical energy flow analysis, we develop a hybrid physical energy input and monetary output table (EIMO) to simulate the mitigation effect of subsidies reform. The EIMO model innovatively reveals the relationship between economic activities and physical energy flows. Simulation results shows that removing energy subsidies would conduce to price increases of coal, oil, natural gas and electricity by 6.37%, 18.62%, 20.42% and 46.55%, respectively; moreover the physical total consumption of coal, oil, natural gas and electricity would be reduced by 17.74, 13.47, 3.64 and 15.82 million tce, respectively. The economic and environmental gains of reducing budget as well as lowering energy consumption and the related CO2 emissions are achieved. This paper focuses on the physical energy input reduction through a life cycle perspective; however, energy policy reform and mitigation of rebound effect are much more than just what the data display. While international studies have already identified that energy and environmental tax-related policies are effective support to energy efficiency technologies in the reduction of the overall energy consumption and the accompanied CO2 emissions, therefore we propose several policy designs and future studies based on our analytical results.
Energy subsidies have been highly controversial for a long Energy types
Carbon emissions coefficients
Source
Coal Oil Natural gas Electricity
0.76 tC/tce 0.57 tC/tce 4.48E-05 tC/tce 0.00 tC/tce
Liang Liang Liang Liang
and and and and
Zhang Zhang Zhang Zhang
(2011) (2011) (2011) (2011)
4.4. Analysis for economic and environmental gains Based on the proposed indicators and EIMO model’s simulation results, we calculate the two assessment indicators. The CO2 emissions reduction could be derived via the emissions coefficients (Table 7) of different energy types. The results shows that fossil energy subsidies reform could result in a money saving of 582.00 billion RMB, an energy saving of 50.67 million tce plus the total CO2 emissions reduction of 77.60 million tons. Based on the proposed assessment indicators:
In terms of CO2 emissions reduction per unit of monetary
saving, the gains is 1.33 tCO2/10000 CNY; In terms of energy saving per unit of monetary saving, the gains is 0.87tce/10000 CNY.
5. Conclusion and discussion There have been a history of fierce debate about energy subsidies and rebound effect of energy consumption, especially under the background of the rapid economic growth of China and the global threat of climate change. They attract worldwide attention and energy policies on those issues are important as a result. Aiming to contribute to this topic, this paper makes a comprehensive analysis on how energy subsidies reform could mitigate rebound effect. Applying price-gap approach, we calculate
time in that they distort the energy price and indirectly harm the environment, hence it become a worldwide trend to decrease or eliminate it. However, reform should not only target on its environmental effects, but also the comprehensive social-economic matters such as how it would affect the macro economy, households living, and the interconnection among each industries. Rebound effect is not only driven by the economic growth, but the industrial structure as well. Thus the mitigation measures should incorporate and bind technological, fiscal, and structure adjustment issues together. Our previous study indicates that subsidies reform also exerts optimization effect on energy consumption structure and industrial structure. However for further study, more detail research is needed in the future. The reform of removing subsidies should be executed in cooperation with appropriate redistribution mechanism on economic benefits coming from increased energy efficiency, and other policies such as environmental taxation. In this study, we narrow our concentration on the economic and environmental gains of subsidies reform and mainly explore how it indirectly contributes to the mitigation of rebound effect. In the future, we would conduct more detailed study on the following issues: what is the internal mechanism of China’s rebound effect, and what is the econometric relationship between energy subsidies and the rebound effect.
Acknowledgement This study is financially supported by the Ministry of Education of the People’s Republic of China, Philosophy Social Planning project, ‘‘Renewable energy industry’s financing risk management and policy support system building— based on life cycle theory’’, 2012(12YJAZH056); The Energy Foundation (USA) projects, ‘‘Energy subsidies reform and the sustainable development of
342
L. Hong et al. / Energy Policy 54 (2013) 335–342
China’s economy’’,2011(G-1111-15134); Post-doctoral Scientific Fund projects, ‘‘Sustainable development and social equity: based on energy subsidies theory and the practice of policy’’, 2009(20090460202). We also thank the editors and reviewers for their comments.
Appendix A. Supporting information Supplementary data associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.enpol.2012.11.045.
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