Evaluating the Atkinson index of household energy consumption in China

Renewable and Sustainable Energy Reviews 51 (2015) 1080–1087

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Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser

Evaluating the Atkinson index of household energy consumption in China Gang Du a, Chuanwang Sun b,n, Zhongnan Fang c a

Department of Business Management, School of Business, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China Collaborative Innovation Center for Energy Economics and Energy Policy, School of Economics, Xiamen University, Xiamen, Fujian 361005, China c School of Economics, Xiamen University, Xiamen, Fujian 361005, China b

art ic l e i nf o

a b s t r a c t

Article history: Received 12 September 2014 Received in revised form 12 May 2015 Accepted 7 July 2015

Improving equality and efficiency of household energy distribution is the primary concern of China’s policy makers in their effort to reform the energy pricing system. In this paper, we use Atkinson Index as an analytical tool to quantitatively and systematically evaluate the equality and efficiency of household energy distribution. The result shows that the Atkinson index of electricity expenditure is much smaller than that of transportation expenditure, which indicates that transportation expenditure responds better to income differences. Furthermore, a geographical distribution analysis indicates that households in Middle China suffer greater inequality in energy distribution than those in Eastern and Western China. In view of the oncoming energy pricing reform in China, we reevaluate the Atkinson index under the new pricing scenarios for electricity and petroleum products. Compared to the current household energy pricing mechanism, the simulated new policies generate more allocative efficiency of household energy and ensure more equality of energy consumption for low income households. On this account, we suggest that geographical differences and equality in energy distribution be duly addressed in reforming energy policies in China. & 2015 Elsevier Ltd. All rights reserved.

Keywords: Household energy distribution Atkinson index Energy pricing reform

Contents 1. 2. 3.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Literature review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Atkinson index—Measuring household energy distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Atkinson index. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Atkinson parameter—Epsilon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Modified Atkinson index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4. Variables and data collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5. Data presentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Inequality in income and energy distribution by region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Electricity price and transportation expenditure scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Conclusions and suggestions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1080 1082 1083 1083 1083 1083 1084 1084 1084 1084 1085 1086 1087 1087

n Corresponding author at: Collaborative Innovation Center for Energy Economics and Energy Policy, School of Economics, Xiamen University, Xiamen, Fujian 361005, China. Tel.: +86 5922186076; fax: +86 5922186075. E-mail address: [email protected] (C. Sun).

http://dx.doi.org/10.1016/j.rser.2015.07.017 1364-0321/& 2015 Elsevier Ltd. All rights reserved.

G. Du et al. / Renewable and Sustainable Energy Reviews 51 (2015) 1080–1087

1. Introduction There is little doubt that the world has been facing complex and daunting energy challenges since the beginning of the 21st century [1]. Without any change in our current practice, the world energy demand in 2020 would be 50–80% higher than 1990 levels and the world’s energy consumption would increase to 53 billion kW h by 2020 [2]. According to the report by Energy Poverty Action initiative of the World Economic Forum [3], nearly 1.6 billion people still have no access to electricity. This is a stark index of severe energy poverty1 across the world and the energy poverty is undermining the developing achievement in many perspective [4]. Therefore, it is imperative to address equality and efficiency of energy distribution, and to ensure equal energy consumption rights to more people, especially the low income households. As the largest developing country that is undergoing a critical political and economic transition [5]. China has a greater need, and faces a more complex situation than any other countries when it comes to a household energy distribution reform. Obvious factors that complicate China’s reform situation include the high growth rate in economy, the huge amount of energy consumption, the large number of population, the rapid speed in urbanization, and the high degree of income polarization [6]. From 2003 to 2011, electricity consumption in China experienced a rapid growth from 1780 TW h to 4430 TW h with an average annual growth rate of 12.09%, which is much higher than the world average (3.67%). However, the energy savings potential resulted from energy allocative inefficiency is about 9.71%, which is quite significant [7]. In addition, China, whose households make up approximately a quarter of the world’s, is facing a rapid rural–urban transition and transformation. From 2010 to 2025, it is estimated that 300 million Chinese currently living in rural areas (a number almost as large as the entire population of the U.S.) will move into cities [8]. Energies used in urban households are cleaner, more efficient than those in rural place, where the coal and biomass are major energy source [9]. All this implies a great challenge to energy distribution. Meanwhile, China’s unequal income distribution is another problem closely related to energy distribution. The degree of inequality of household income has become more serious since the start of Economics reforms in 1978 [10], and a Gini coefficient of 0.627 in China today is a good index of income polarization. Under such circumstances, a large number of people are adversely affected by energy poverty, which refers to the essential energy consumption by households on low incomes. In contrast, high income households are conspicuous in their energy consumption, which has led to energy overuse and may negatively affect the amount of energy otherwise available to low income families. Since access to energy is fundamental to improving the quality of life and is a key factor for economic development, lower household energy consumption will definitely reduce low income households’ quality of life and inhibit economic growth. Taylor et al. [11] found that household energy demand would increase by the increase of income and it is difficult to meet low income families’ energy demand due to their limited income. Therefore, large population, prodigious energy consumption, and staggering income polarization all make it urgent that the Chinese government take equality and efficiency of energy distribution as essentials for the forthcoming household energy policy reform. Inequality in energy distribution evidently exists among various income groups. In terms of transportation energy expenditure and the ownership of electrical appliances, low income 1

Energy poverty refers to the situation of large numbers of people in developing countries whose well-being is negatively affected by very low consumption of energy, use of dirty or polluting fuels, and excessive time spent collecting fuel to meet basic needs.

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households have contributed far less to energy consumption and growth rate than their high income counterparts. In 2012, the average transportation and communication expenditure2 of the lowest income group (10%) is US$ 96.76, which is one thirteenth of the highest income group (10%)3, and is significantly lower than the country average (US$ 394.14). From 2003 to 2012, the annual transportation expenditure of the low income group increased from US$ 25.30 to US$ 96.76; however this growth (US$ 71.46) is much lower than that of the high income group (US$ 1001.63)4. As for other major durable consumer goods (automobiles, air conditioners, laundry machines, refrigerators), which determine the level of household energy consumption, the ownership rate of the low income group is significantly smaller than that of the high income group. Since the possession of key appliances determines households’ living quality and reflects their energy consumption behaviors, the gap indicates that much has to be done to satisfy low income households’ basic living requirements, to ensure their equal rights of energy use, and to encourage high income group to use energy more efficiently. As a developing country with a huge population and relatively scarce natural resources, it is urgent for the government to improve efficiency and equality in energy distribution and to clearly identify the vital importance of political and economic transition. This inevitably requires researchers to evaluate the inequality of current energy distribution and come up with more constructive suggestions on energy reform. In China, the market-oriented pricing mechanism is considered as an important tool to regulate energy prices and adjust distribution equilibrium. However, a relatively low and fixed price cannot accurately reflect demand and supply of the energy market and may fail to ensure equality of energy distribution. With their striking difference in incomes, while the well-off households can increase their energy consumption as they wish at a relatively low cost, the low income households have to use larger proportion of their income to consume equal energy. Therefore, a low and fixed energy price for all consumption levels may not be a fair pricing policy; rather it may distort equality of energy distribution. Furthermore, through energy subsidies, the government artificially controls the price of energy below its market price, making it unresponsive to demand and supply. As far as distribution efficiency, equal using rights, and environmental goals are concerned, there are conflicts among energy subsidies, energy demand/ supply, and environmental issues. Although energy subsidies used to play an important role in making energy service affordable for all households [12], particularly the low income group, this policy needs revising to exclude high income households for the simple reason that they are well in a position to pay higher energy bills. Moreover, high income households usually consume much more energy than their low income counterparts and, as a result, enjoy greater subsidies. This is contrary to the original intention of the subsidy policy. Therefore, it is imperative that policy makers introduce a more comprehensive energy reform and implement a better pricing mechanism to ensure equality of energy use. In this paper, we will explain how to evaluate equality in energy distribution, what methods to be applied for policy design and reform, and how to implement new policies of energy pricing. To our knowledge, there are few micro-data-based evaluation studies on current household energy distribution in China, which provides a brand-new view on the existing energy policy. To examine the tradeoff between equality and efficiency, the Atkinson index is used. This index can better take societal benefit into consideration. We will also

2 The transportation and communication expenditure include the cost of public transportation fee, spending on gasoline, gas and diesel for transportation, mailing fee, call charges, etc. 3 Data source: National Bureau of Statistics of the People's Republic of China. 4 Data source: National Bureau of Statistics of the People's Republic of China.

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discuss the distribution effect from a geographic perspective, covering western, middle, and eastern part of China, so that we can better describe the differences and characteristics of energy equality among different regional areas. In view of the rise in energy price resulting from the forthcoming reform, we build two scenarios for long-term electricity expenditure and transportation expenditure, respectively. Under these two scenarios, we will analyze equality and efficiency of household energy distribution to evaluate the degree of equality improvement after the reform of energy policies and to further investigate the effect of energy reform. The remainder of our study is organized as follow: Section 2 reviews the major methods and views on household energy distribution and energy policy reforms in China. Section 3 studies social welfare functions and utilizes the Atkinson index to examine the relationship between income level and consumption capacity by using CRECS5 database. Section 4 presents the results about the inequality of household energy consumption under the current energy pricing mechanism and new scenarios. Section 5 registers our conclusions and suggestions.

2. Literature review Quantitative study has been found limited on equality of energy distribution; the most typical paper is contributed by Schlör et al. [13], who creatively evaluated the distribution of energy consumption in Germany by using Atkinson Index instead of Gini index for analysis. It is the first time that Atkinson Index was used in the energy sector to measure equality of energy use quantitatively. In China, whose population accounts for more than 20% of the world’s, systematic and quantitative reports on household energy distribution equality are lacking. Most analysis of current energy studies mainly focuses on equality of distribution with regard to household energy subsidies. Because of subsidies, China’s current policy of energy pricing greatly weakens the real effect of equality and efficiency improvement, making it necessary to evaluate the size of subsidies and discuss the negative effects brought about by energy subsidies [14]. Some researchers have tried to work out a better energy pricing mechanism to distribute household energy in a more optimal manner, and to contribute to the improvement of household energy distribution. Hong et al. [15] employed a co-thinking approach to exploring the feasibility of an energy-subsidy reform, and to mitigate the rebound effect6 in China. Lin and Jiang [16] estimated China’s energy subsidies as CNY7 356.73 billion in 2007 and suggested that removing energy subsidies will cause a significant fall in energy demand and emissions. In 2008, China’s fossil-fuel-related subsidies are CNY 1214.24 billion, which is equivalent to 4.04% of GDP. Relative compensation measures should be designed to offset the negative impact of energy subsidies [17]. Besides, gradually removing fossil energy subsidies might become imperative [18]. Some researchers have also discussed the household energy policy reform by designing a better pricing mechanism. Studies suggest that proper energy pricing reform can optimize equality and efficiency of household energy distribution. Gyamfi et al. [19] investigate the challenges in achieving effective voluntary demand reduction and propose the use of a hybrid engineering approach to overcome these challenges. Kasparian [20] finds that French 5 China's Household Energy Consumption Survey (CRECS) is funded by Center of China Energy Economics Research (CCEER), which is the first nationwide survey on household income and energy consuming behaviors after the implementation of new pricing mechanism. 6 The rebound effect is the reduction in expected gains from new technologies that increase the efficiency of resource use, because of behavioral or other systemic response [46]. 7 CNY stands for China yuan renminbi, and 1 CNY ¼ 0.1642 USD roughly.

households with lower income have to suffer relatively higher burden than other groups and describe the unequal phenomena for different income households’ budget. In Netherlands, the large number of new policy measures in the past decade has influenced the response of households to changing price and improved energy distribution [21]. With the increase of energy price, there is a significant reduction in the total primary energy supply and a noticeable increase of renewables, which reconstruct the primary energy supply and improve energy efficiency. Martinsen et al. [22] and Nesbakken [23] find that high income households have higher energy price sensitivity than low income households, which serves as a good evidence that energy price reform can improve and readjust equality of household energy distribution. In China, a number of studies have attempted to evaluate the efficiency improvement of household energy distribution reform by redesigning the pricing mechanism. Zhao et al. [24] used LMDI method to analyze the decomposition of China’s residential energy consumption. They suggest further deregulation in energy prices and regulation of voluntary energy efficiency and conservation policies. Yuan et al. [25] find that higher energy prices will decrease household energy consumption in the long run, which will promote China to deepen and speed up energy reform. Simulation analyses show that reforming refined oil mechanism can reduce around 90.7% of rebound, which will encourage governors to further reform the current refined oil pricing mechanism [26]. Fan et al. [27] find the accelerative marketization has contributed substantially to energy efficiency improvement since 1993 by examining the changes of energy own-price elasticity. Sinton [28] suggests new energy policy should be more market-oriented and maintains that extraordinary efforts have to be made to reduce energy intensity. New government policies and programs need to be introduced and launched to remove energy subsidies and reduce pollutant emissions [29]. Finally, compared with U.S., China has greater capacity to invest more in energy conservation and to improve energy efficiency [30]. On July 1st, 2012, China implemented Rising Block Tariffs8 which is regarded as a breakthrough in China’s residential power tariff reform [31]. This new policy, designed to improve equality and efficiency of household energy policy, has brought about new scenarios of household energy distribution. Therefore, some scholars focus on the impact of new energy policy and estimate its rebound effect. Wang et al. [32] evaluate the public acceptance of Rising Block Tariffs reform based on a survey of four urban cities, and find that the middle income earners are mostly opposed to the reform. The productivity improvements in labor and capital inputs associated with the reforms are approximately 26% and 45%, respectively, which serves as a proof that there is significant efficiency gain from the reform [33]. However, Lin and Liu [26] set up LA-AIDS model to estimate the rebound effect on transportation in China, and argue that efficiency improvement in practice does not always lead to energy saving, as shown by the 107.2% rebound effect. One of the key factors leading to rebound effect is the refined oil pricing mechanism. Besides, the rebound effect of urban residential electricity consumption is approximately 165.22%, further indicating the absence of energy-saving effect in practice. Current researches mainly focus on evaluating the size of energy subsidies [16,31,34]; some papers discuss the pricing mechanism reform [35,36]. Both have provided many evidences of household energy distribution improvement. Although many

8 The new pricing policy was designed to apply a rising block tariff mechanism where the residential tariff would vary according to the electricity consumption. The new policy plans a three-step tariff systems assigned to three consumption thresholds: basic power consumption (BPC), normal power consumption (NPC), and luxury power consumption (LPC) ([45]).

G. Du et al. / Renewable and Sustainable Energy Reviews 51 (2015) 1080–1087

scholars have discussed inequality of household energy distribution in different sectors and raised various reform suggestions for the government, few have ever evaluated the degree of current household energy distribution quantitatively and systematically. In our paper, we try to investigate the equality and effectiveness of household energy distribution by using micro household-level data and to provide a new scientific view on energy policy reform through quantitative descriptions and scenario analysis.

3. The Atkinson index—Measuring household energy distribution 3.1. Atkinson index Though various approaches are available to estimate equality of household energy distribution, we use Atkinson index to evaluate equality of household energy distribution in this paper. Theoretically, the Atkinson index is based on social welfare function which provides a way to measure inequality in social distribution [37]. We assume that individual welfare does not affect others’ benefits and the whole benefit of a society is determined by summing up the single benefit for individuals in the society. Based on this assumption, we believe that the distribution of social welfare can be calculated by Atkinson Index. The Atkinson index is used to evaluate the effectiveness and fairness of social distribution, which ranges from 0 to 1 [38]. 0 shows the max equality in distribution, while 1 means it is most unequal in distribution. As for the function of Atkinson index, T i is the income or expenditure in the ith income or expenditure range, f i is the proportion of the population in ith group. T is the mean household income or expenditure, and the Atkinson equation are defined as follows [39,40]: " #1 1 ε Xn T i 1  ε yR ¼ 1  f i ðT i Þ ; if ε a 1 ð1Þ i¼1 T X  n Ti yR ¼ 1  exp f ð T Þlog ; i i e i¼1 T

if ε ¼ 1

ð2Þ

As the equation shows, the Atkinson index evaluates the distributional effect of household income and energy expenditure with the epsilon parameter. This gives us the opportunity to define how sensitively the Atkinson index reacts to income inequalities. Other inequality measures such as Gini coefficient do not have such a parameter which takes social welfare into consideration. Therefore, using Atkinson index and epsilon parameter enables us to enlarge this measure to include social development and avoid ambiguous issues9.

inequality in distribution to infinity if the society only consider distributing all money to low income people. Then we will discuss how to determine the accurate value of epsilon. In the Okun [41] assumption, the transfer in the world is associated with transaction costs, such as administrative costs and work efforts, which will reduce the amount of money the poor can get in the end. Okun [41] made an equation to answer how high transaction costs are before it cannot be justified by society. Suppose z means the value of transfer share, epsilon can be calculated by the equation:   1 ε ¼ log 2 ð3Þ 1z By using this equation, we can easily calculate the accurate value of epsilon when we consider the transfer share first. According to Okun [41], the leakage of transaction would be no more than 60%, which corresponds to 1.3 in epsilon value. Besides, we can analyze the value of epsilon from two aspects, social equality and economic efficiency, which are examined by Rawls10 [42] and Friedman11 [43], respectively. Friedman [43] prefers to choose an epsilon which is below 1, while Rawls [42] would probably choose epsilon parameter above 2. Therefore, the value of epsilon can be determined by dividing equality of Rawls [42] by efficiency of Friedman [43]. Combining the above analyses, we choose the epsilon parameter of 0.1, 0.5, 1, 1.2, 1.5, and 2 by taking both the equality and efficiency effect into consideration. Since there is no statistically objective inequality measure, every measure contains implicit evaluations about a desirable distribution of income. Though the Atkinson index with epsilon parameter provides a connection between the equal rights of energy use and the efficiency criterion of economy, we may need further social investigation before we can determine the real value of epsilon in China. 3.3. Modified Atkinson index In the following part, we will use Atkinson index equation to calculate equality and efficiency in the distribution of income and expenditure. For calculating the household income, electricity expenditure and transportation expenditure, we need to modify Atkinson index into: 2 AIM g ¼ 1 

n X T i;g 4 i1

In the equation of Atkinson index, epsilon represents the weight attached by society to inequality in distribution, and therefore, epsilon measures the degree of inequality aversion among various groups. When epsilon parameter increases, there tends to be less distribution transferred to high income groups and more distribution transferred to low income groups. The epsilon parameter enables Atkinson index to include/assess social welfare function in the social sustainable development. In brief, the epsilon parameter defines the sensitivity of Atkinson index to income inequalities. It ranges from zero if the society ignores 9 Hauser and Barr have claimed that the Gini coefficient is not an unambiguous measure which means different distributions can lead to the same Gini coefficient. However, the Atkinson Index can avoid this disadvantage.

!1  ε1

Tg

31 1ε 1   f i;g T i;g 5 ;

for ε ¼ 0:1; 0:5; 1:2; 1:5; 2 ð4Þ

" AIM g ¼ 1  exp

n X i1

3.2. Atkinson parameter—Epsilon

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log e

T i;g Tg

!

#

  f i;g T i;g ;

for ε ¼ 1

ð5Þ

T i;g represents the household income of specific groups g (geographical area) in the ith income range, n is the sum of the income class. f i;g is the proportion of the population in the social groups with income in the ith income range.T g is the mean value of income in all groups. For the calculation of electricity expenditure and transportation expenditure, we can use Ei;g and K i;g instead of T i;g to calculate the Atkinson index of electricity expenditure distribution and transportation expenditure distribution. 10 John Rawls asserted that “The natural distribution is neither just nor unjust; nor is it unjust that persons are born into society at some particular positions. These are simply facts. What is just or unjust is the way that institutions can adjust the epsilon parameter”. 11 Friedman responded that, “Life is not fair. It is tempting to believe that government can rectify what nature has spawned”.

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Table 1 The description of sample by regions. Region

Sample size

Ratio (%)

Western China Middle China Eastern China All

362 338 377 1077

33.6 31.4 35.0 100

Table 2 Distribution of household annual income among different regional groups. Region

Less than US US$ 10,000 $ 10,000 (%) to 15,000 (%)

US$ 15,000 to 20,000 (%)

More than US$ 20,000 (%)

Western China Middle China Eastern China All

47.79 32.54 28.12 36.12

10.77 15.68 27.06 18.01

8.84 15.98 22.55 15.88

32.60 35.80 22.28 29.99

The value of Atkinson index increases when there is a higher epsilon parameter in each group. However, differences between different research topic (household income, electricity expenditure and transportation expenditure) still exist. We will carry out our analysis about the distribution of income and expenditure among the Chinese households on the basis of China’s Household Energy Consumption Survey (CRECS).

better local economy. On the contrary, western provinces have a higher proportion of low income households, accounting for almost half (47.79%) of all families in the same area. The striking income difference in different geographical groups results in a dramatic gap of household energy consumption. 3.5. Data presentation Our survey data are in accord with the national statistics, which justifies the representativeness of our data resource. For some key standard variables of family size, living space per capita and household energy consumption expenditure per capita, their results are quite similar. The survey data of urban family size is 3.00, which is close to the national statistics (2.89). The living space per capita in urban cities is 40.18 m2, which is a little larger than the national statistics (32.7 m2). Household energy consumption expenditure per capita of survey data also coincides with that of the national statistics. Table 3 outlines the key variables surveyed and investigated in this paper, with electricity expenditure and transportation expenditure based on monthly data. Household income refers to the disposable household annual income. The average monthly residential electricity bill is US$ 18.38, with a standard deviation of 11.80 in the sample. The average expenditure of transportation energy is US$ 66.97.

4. Results 4.1. Inequality in income and energy distribution by region

3.4. Variables and data collection China’s Household Energy Consumption Survey (CRECS) is funded by the Center of China Energy Economics Research (CCEER), which is a nationwide survey on household incomes and energy consuming behaviors after the implementation of the new electricity pricing mechanism. This survey focuses on collecting micro household-level energy data of the whole country and its different social groups, which enables us to estimate the consequence of household energy distribution changes and discuss the improvement of energy equality and efficiency. We therefore select some typical data for our analysis. The behavior and habit of household energy use vary with population size and region. In order to clarify the variance of residential energy consumption geographically in China, we sample 1077 households randomly in the mainland China, including 362 in Western China, 338 in Middle China and 377 in Eastern China. In order to evaluate the influence of China’s residential energy policy, these variables are intended to collect data of household income and cost of living, especially electricity and transportation energy expenditures. The description of samples by regions is shown in Table 1. The CRECS data provides details about income and expenditure of specific families. Therefore, these data enable us to examine income levels and consumer behaviors in different regional groups. Table 2 shows how China’s households are distributed by income and region. We divide household income into four different levels to describe the household financial situation. With respect to the distribution of the households across the four income levels, the table shows that households whose income is below US$ 10,000 or between US$ 10,000 to 15,000 constitute the largest group, whereas the average household income in the eastern part is relatively larger than that in the middle part and the western part, respectively. Within Eastern China, there is a larger proportion of high income families, accounting for 22.55% of all households in Eastern China, higher than that in the middle (15.98%) and western areas (8.84%), which is in accord with their

The analysis shows that Atkinson index of household income changes with region. Inequality of the distribution of household income for the western part rises from 0.012 to 0.182 if the epsilon changes from 0.1 to 2 (Table 4). In the case of electricity expenditure distribution, we see that inequality rises from 0.0007 to 0.012 by increasing epsilon for the western households. However, for transportation energy expenditure, there exists a bigger increase, from 0.011 to 0.159. For the cities in the middle part of China, there exists a significant inequity in distribution of income and energy expenditure (Table 5). The Atkinson index of household income ranges from 0.013 to 0.217, which suggests that the distribution of household income in the middle part of China is less equal than that in the western part. The greater spread of the Atkinson index in the middle indicates high degree of income polarization. By the Atkinson index, electricity expenditure is more equally distributed than the household income distribution with the chosen epsilon parameter, and this result is also in correspondence with the result from Western China. The household transportation energy expenditure among the residents in Middle China reveals a bigger gap in inequality according to the Atkinson index. What’s more, for the eastern part of China, the biggest increase from 0.0225 to 0.340 is shown in Table 6. The gap of Atkinson index between the west and the east indicates the different degree of income distribution equality. Since the east part has a better economic condition, eastern provinces are more likely to suffer income inequality. Special attention is needed when new energy distribution policies are made, for energy consumption has a strong relationship with household life quality. The split of the Atkinson index of electricity expenditure and transportation energy expenditure ranges from 0.0027 to 0.0531 and 0.0126 to 0.2177, respectively. By the distribution of household income and electricity expenditure, there is a positive correlation between the two indexes, which shows that income levels affect households’ electricity consumption in all areas. With the increase of household income, there will be a corresponding increase in electricity expenditure, for families have a strong motivation

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Table 3 Statistical description of key variables. Variables

Unit

Observations

Mean

Standard deviation

95% Conf. interval

Electricity expenditure Transportation energy expenditure Household annual income

US$ US$ 105 US$

1077 1077 1077

18.38 66.97 1.50

11.80 85.85 1.77

[17.68, 19.09] [61.86, 72.08] [1.39, 1.60]

Table 4 Atkinson index of households in western China.

Table 6 Atkinson index of households in eastern China.

Epsilon Household income

Electricity expenditure

Transportation energy expenditure

Epsilon Household income

Electricity expenditure

Transportation energy expenditure

0.1 0.5 1 1.2 1.5 2

0.0007 0.0033 0.0065 0.0077 0.0094 0.0122

0.0107 0.0506 0.0938 0.1090 0.1297 0.1591

0.1 0.5 1 1.2 1.5 2

0.0028 0.0137 0.0272 0.0325 0.0404 0.0532

0.0126 0.0620 0.1203 0.1420 0.1726 0.2177

0.0121 0.0572 0.1061 0.1235 0.1473 0.1816

0.0225 0.1083 0.2024 0.2356 0.2794 0.3400

Table 5 Atkinson index of households in Middle China. Epsilon Household income

Electricity expenditure

Transportation energy expenditure

0.1 0.5 1 1.2 1.5 2

0.0042 0.0209 0.0413 0.0492 0.0608 0.0793

0.0176 0.0845 0.1577 0.1831 0.2172 0.2637

0.0130 0.0633 0.1214 0.1428 0.1730 0.2177

to improve their life quality by consuming more electricity. However, we need to take some measures to prevent people from overusing electricity, so as to ensure equal rights of energy use for the low income household. Rising Block Tariff or a ladder pricing mechanism may work well to serve this purpose. Discriminatory pricing policies based on income levels may be a good measure to discourage high income households from overusing energy, hence ultimately improving energy equality and efficiency. The Atkinson index of household electricity distribution among different parts of China is significantly smaller than the Atkinson index of income distribution. We find that after dividing all households into different income groups, electricity expenditure differences between income groups are much smaller than income differences. This result implies two conclusions: first, electricity is regarded as a necessity for households’ daily life, and the consumption of a certain amount of energy is a fundamental determinant of the quality of life [44]. The distributions of electricity would not vary dramatically among different income groups. Second, this result indicates that the expenditure gap is too small to reflect the household income difference. When the epsilon parameter is 2, there is still no significant difference in Atkinson index. A small change in Atkinson index number can be regarded as a strong signal of unequal electricity distribution. With substantial energy subsidies, the high income groups consume more electricity and enjoy more energy subsidies, which is intended to help the low income groups. Therefore, a new electricity pricing mechanism is needed and the high income group should pay more considering their better financial condition and greater electricity consumption. In the case of transportation energy expenditure, the data obtained show that transportation expenditure is more unequally distributed than electricity expenditure in general. This result can be analyzed in two ways: first, the Atkinson index of transportation

Fig. 1. Atkinson index of electricity expenditure distribution under new scenarios.

expenditure is significantly higher than electricity expenditure. For cities in Middle China, when epsilon equals 2, the Atkinson index will rise to 0.264, which is a strong signal of inequality. Since there is a strong relationship between car ownership and transportation expenditure, energy consumption in transportation is independent of the household’s income relatively. Moreover, the use of private cars in China is not as popular as in developed countries, inequality in private car ownership will be even more outstanding in different regions and cities. Second, the range of the Atkinson index for transportation expenditure becomes wider from Middle China to the other parts, because the development of public constructions and city transportation can significantly affect the transportation expenditure. For instance, as public transportation is much more convenient in the east than in other areas, residents in eastern cities tend to use public transportation more frequently, which helps reduce the degree of transportation expenditure inequality. On the other hand, the long distance between cities and the poor road condition in the west discourage residents there from using private cars, which will result in low transportation expenditure in the west and shorten the differences within income groups. 4.2. Electricity price and transportation expenditure scenarios After analyzing the distribution of household incomes, electricity expenditure and transportation expenditure, we add two new price scenarios when ladder prices are implemented in the new energy policy. These two new scenarios outline the new distribution condition if policy makers enlarge the price gap between

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income groups, which shows equality and efficiency to some extent. The new scenario on transportation expenditure doesn’t find significant changes in its distribution equality and efficiency. Therefore, policy makers should redesign the transportation pricing system, making it more capable of achieving the goal of energy distribution optimization. Combining the results from the two new scenarios above, we can conclude that widening the price gap according to household incomes will increase the Atkinson index, and then promote equality and efficiency. Now that high income people have to pay more on their excessive energy consumption, they will become more sensitive to price changes and thus be encouraged to be energy-saving in the future. Fig. 2. Atkinson index of transportation expenditure distribution under new scenarios.

income groups. Drawing on the study of Sun and Lin [45], which uses a translog demand model to capture the non-linear relationship about residential electricity price elasticity of demand in China, we build a scenario of residential electricity price reform. The new scenario of electricity expenditure assumes that future policies will increase electricity prices by 30% for households who spend less than 1% of their income on electricity consumption and decrease electricity price by 30% for families who pay more than 2.5% of their income on electricity consumption. After revising the price ladder, 22.5% residents have to pay 30% more on their electricity consumption and 19.5% residents will be paying less on the electricity. In the new scenario of transportation expenditure, we base our estimate of price elasticity of transportation demand on the study of Lin and Liu [26], which uses Linear Approximation of the Almost Ideal Demand System Model (LAAIDS model). On the basis of LA-AIDS model, we increase the oil price by 30% to decrease subsidies, but keep public transportation fees unchanged to encourage the use of public transportation. From the results of the new scenarios (Figs. 1 and 2), we find that the Atkinson indexes of energy consumption and transportation expenditure increase when the pricing gap become widened. With regard to electricity expenditure in the western areas, there seems to be a change from nearly equal distribution to relatively less equal distribution (from 0.006 to 0.0234 at an epsilon of 1). However, we cannot evaluate the efficiency and equality by merely applying the Atkinson index. Though Atkinson index increases in the new scenario, the high income group has to pay more on their electricity consumption, which will then lead to a flow of more subsidiaries to the low income group. On the other hand, low income households need to pay relatively less than before, which will facilitate the redistribution of energy consumption. In the east, this change in distribution equality is more obvious, with the new Atkinson index ranging from 0.0055 at an epsilon of 0.1 to 0.101 at an epsilon value of 2, which is much wider and more dramatic than in a normal scenario. Therefore, we can conclude that if the government decides to reform the policy for household energy consumption by increasing the pricing gap within income groups, electricity in the east will be better optimized than in other areas. As a result, the whole country, especially those in the west, will benefit from the change in pricing. This conclusion can be used to support policies for energy price reform in the future, and help the government to design a better pricing ladder and to distinguish the policy in different regions. From the new scenario on transportation expenditure (Fig. 2), we can conclude that there won’t be dramatic changes in the Atkinson index in any area. The similarity between the former Atkinson index of transportation expenditure and that of household income distribution indicates that disparity in transportation expenditure distribution has already existed among different

5. Conclusions and suggestions Our analysis has shown that Atkinson index provides a good way to evaluate equality and efficiency of energy distribution in different regions among various income groups. By using epsilon parameter, we demonstrate the distribution results under different degrees of inequality-aversion. Therefore, the Atkinson index provides a scientific way to assess the current energy pricing policy. For energy policy reform, our research provides strong evidence that policy makers need to take into account equality and efficiency of household energy distribution, and, at the same time, to ensure equal rights to the use of household energy. By evaluating household energy distribution quantitatively and building two new scenarios, we can better describe the improvement of equality after reforms and provide policy suggestions. The results reveal that electricity distribution does not fully reflect income differences, but transportation expenditure distribution shows similarity with income distribution. It suggests that high income groups do not have to increase their expenditure significantly for their excessive consumption under the current electricity policy. This runs counter to the intention of the subsidy system and absurdly encourages waste of energy. However, transportation expenditure shows a positive correlation to the household income. From the two new scenarios, we can see that a widening price gap will redistribute electricity expenditure more significantly than transportation expenditure. This result reveals that there is greater need to not only reform the current electricity pricing mechanism, but also motivate high income households to actively save energy. In addition, the Atkinson index results vary with region, which shows the diversity of geographical areas. Since different areas or different cities have their unique situations, the government should launch discriminatory policies instead of implementing unified policies and regulations throughout the country. For example, eastern residents rely more on public transportation, which affects transportation expenditure among different income groups. On the other hand, Middle China residents tend to use more private transportation means, which points to the necessity of oil price reform. In addition, our results can provide support for future energy reform from many important aspects. 1. Policy makers should take social welfare, energy equality, and efficiency into consideration. The government should redesign its energy pricing mechanism and give more concern to its distribution effects. 2. As household electricity consumption is less equally distributed than transportation energy distribution, policy makers need to pay more attention to electricity pricing and use subsidies to adjust the equality of distribution. 3. Different regions in China have their unique situation, which suggests that future energy policies need to be adjusted to

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better respond to different geographical factors. For Middle China, where household energy is less equally distributed, more targeted policies and regulations should be made to meet the basic requirements of household energy consumption, especially among low income households. 4. Energy policies should not only focus on the price increase for the average household but also take into account the negative impact of price changes on low income households. Therefore, more differential price mechanisms should be implemented for different income levels. Our initial results leave space for future research. The samples only describe electricity and transportation expenditure in different regions in China. Actually, more variables, such as household factors, natural gas consumption, and energy saving appliances, are all possible areas to be explored. In addition, since Rising Block Tariff (RBT) has been implemented for only one year, more substantive data and information will appear in the years to come, which will serve as good materials for further research. With the predicted reform on natural gas and renewable energy, we can conduct a more comprehensive analysis in the future. These analytical results are good references for researchers and policy makers in the reform of China’s energy policy. Acknowledgement The paper is supported by National Natural Science Foundation of China (Grant nos. 71303199 and 71472065), Ministry of Education Foundation of China (Grant nos. 13YJC790123 and 11JBGP006), Fundamental Research Funds for the Central Universities (Grant no. 2014221001), Soft Science Plan Funded Project of Fujian Province (Grant no. 2014R0088), Natural Science Foundation of Fujian Province (Grant no. 2014J01269), Research Projects of the Social Science and Humanity on Young Fund of the Ministry of Education (Grant no. 14YJC630026), Program of Research on the Generalized Virtual Economy (Grant no. GX2014-1020[M]), Principal Foundation of Xiamen University (Grant nos. 20720151026 and 20720151039) and Shanghai Pujiang Program (Grant no. 14PJC027). References [1] Karlsson-Vinkhuyzen SI. From Rio to Rio via Johannesburg: integrating institutions across governance levels in sustainable development deliberations. Nat Resour Forum 2012;36:3–15. [2] Omer AM. Energy, environment and sustainable development. Renewable Sustainable Energy Rev 2008;12:2265–300. [3] Frei C, Angelloz-nicoud D. Energy Poverty Action (EPA) Further Information. 2007. [4] Nussbaumer P, Bazilian M, Modi V. Measuring energy poverty: focusing on what matters. Renewable Sustainable Energy Rev 2012;16:231–43. [5] Sun C, Zhu X. Evaluating the public perceptions of nuclear power in China: evidence from a contingent valuation survey. Energy Policy 2014;69:397–405. [6] Ma H, Oxley L, Gibson J. China’s energy situation in the new millennium. Renewable Sustainable Energy Rev 2009;13:1781–99. [7] Ouyang X, Sun C. Energy savings potential in China’s industrial sector: from the perspectives of factor price distortion and allocative inefficiency. Energy Economics 2015;48:117–26. [8] Sun C, Ouyang X, Cai H, Luo Z, Li A. Household pathway selection of energy consumption during urbanization process in China. Energy Convers Manage 2014;84:295–304. [9] Cai J, Jiang Z. Changing of energy consumption patterns from rural households to urban households in China: an example from Shaanxi Province, China. Renewable Sustainable Energy Rev 2008;12:1667–80. [10] Tao Yang D. Urban-biased politics and rising income inequality in China. Am Econ Rev 1998:89. [11] Taylor RP, Liu F, Meyer AS. China: opportunities to improve energy efficiency in buildings. Asia Altern Energy Progr World Bank; 2001.

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