1. Introduction
Electric energy plays an important role in contemporary economic, social and human development [
1,
2]. As a basic energy industry of the national economy, the electric power industry can provide an important material basis for people’s lives and socio-economic development. Electric universal service (EUS), as a kind of social responsibility taken by state-owned power grid enterprises, is meant to meet the basic electricity demand for backward and vulnerable groups, and holds the characteristic of commonweal [
3,
4]. Therefore, it is more important than other commonweal services provided by utility companies. As an important public function of government, EUS aims to enable all citizens to receive basic electric service with a reasonable and acceptable price and without consideration of regional restriction. The implementation of EUS is an important way for Chinese government to undertake the public service function and fulfill social responsibility [
5]. In recent years, the Chinese government has promulgated several policies and implemented strategic measures related to EUS, such as ‘China’s Energy Policy (2012)’ promulgated by the State Council of China, the ‘Twelfth Five-Year Plan of Energy Development’ made by the State Council of China, and the ‘Three-year action plan for comprehensively solving electric usage problems for rural residents (2013–2015)’ issued by the National Energy Administration. Owing to those related policies and measures, those living in the remote and backward regions, especially rural residents, can access electric energy. Nowadays, most rural residents use electric energy in daily life, such as lighting, cooking, and watching TV, which brings convenience to rural residents’ lives and improves their living quality.
Well-being, as a kind of subjective spiritual feeling, represents a kind of satisfactory state of a person regarding his/her life [
6]. In philosophy, well-being refers to how well a person’s life goes for the person who lives it. In economics, well-being is used for one or more quantitative measures intended to access the life quality of a person or a group [
7]. Well-being is an individual sensuous response to current living conditions or economic and social activities, which is an important means to measure the individual’s happiness level [
8,
9]. Individual well-being is a complex conceptual system related to many disciplines such as philosophy, psychology, sociology, and economics. Well-being usually reflects individual cognitive thinking and psychological sentiments and is influenced by many factors, such as individual characteristic, economic condition and social status [
10]. Studies on individual well-being are a current area of research emphasis and difficulty in the field of welfare economics [
11,
12]. As a government-oriented public service, the EUS is provided by electric power enterprises in China, which can give rural residents living in remote or backward areas access to electric energy [
3]. The electricity consumption (such as lighting, cooking and watching TV) of rural residents owing to EUS implementation will facilitate their daily life, which can improve their well-being and promote their sustainable development. The well-being of rural residents due to electricity consumption is influenced by many factors, such as educational background, health condition and individual income. However, different factors may have different impacts on individual well-being. Therefore, it is quite important to identify the key and significant factors, and then the well-being of rural residents can be improved by perfecting those significant factors, which can have targeted policy implications for relevant policy makers and make the EUS policy play its prescribed role as well as possible, which can promote sustainable implementation of related EUS policy.
The well-being of rural residents due to electricity consumption is the subjective feelings and psychological evaluation of rural residents on electric usage, which can be measured via a plurality of ordered ratings, such as ‘Very satisfied’, ‘Generally satisfied’, and ‘Dissatisfied’. Therefore, the well-being evaluation of rural residents is discrete, ordered and multivariable. The Ordered Probit model is an econometric method suitable for the discrete, ordered and multi-grade issues [
13]. In statistics, Ordered Probit is a generalization of popular Probit analysis to the case of more than two outcomes of an ordinal dependent variable, which has been widely applied in many fields, such as internationalization choices [
14], the monetary policy stance measure of the People’s bank of China [
15], determinants of life satisfaction in Albania [
16], US bond default forecasting [
17], the factors affecting credit rating [
18], and so on. However, the Ordered Probit model has unfortunately rarely been employed in the field of electric power, and this method may be quite suitable for some electricity-related issues, such as the well-being of individuals due to electricity consumption. In this paper, the well-being of rural residents due to electricity consumption is studied by attempting to employ the Ordered Probit model. Considering the population’s sociological factors, economic factors and electricity consumption behavioral factors, the significant factors influencing the well-being of rural residents due to electricity consumption are identified by employing the Ordered Probit technique with practical data obtained from on-the-spot visits and questionnaire surveys. Finally, several policy recommendations are proposed for further improving the well-being of rural residents, which can also contribute to the effective and sustainable implementation of EUS policy in China.
Section 2 reviews the existing research related to the electricity consumption of rural residents; the Ordered Probit model, variable (factor) selection, and data sources are described in
Section 3; the empirical analysis is performed in
Section 4; and
Section 5 lists the main findings and policy implications.
2. Literature Review
Considering the economic efficiency and regional discrepancy, rural electrification mainly depends on the EUS policy implemented by the Chinese government. Currently, the domestic research and foreign research on rural electrification are quite different. For domestic research, because the EUS policy is very important for rural residents who live in remote and backward regions accessing electric energy, current studies mainly focus on how to effectively formulate and implement EUS policy.
Universal service, first proposed in the field of industry, is mainly to solve the contradiction between the social service function and profit target of the network industry. In 2002, the concept of ‘universal service’ was proposed in the files related to electric power system reform promulgated by the China State Council, which marked that the electric universal service had been officially proposed in China [
19]. In China, related studies focus on the connotation, social welfare measurement and implementation mechanism of EUS. Wang J. and Gao W. examined the electricity demand of rural residents, accessing approach and relative regulatory policies in the background of electric power system reform [
20]. Liao J. and Wu C. analyzed the electricity supply subjects for rural residents living in remote and backward regions under the modes of vertical integration and transmission-distribution-sale integration, and corresponding subsidy mechanisms were designed [
21]. Cai J. reviewed the EUS and electricity supply for rural residents in China, and explored several key issues including government duty and legislation, policy classification and standards as well as the quality and price of EUS [
22]. In terms of social welfare measurement, Li C. et al. evaluated the comprehensive effectiveness of power supply in rural areas including the three subjects of society, enterprise and residents by applying an eigenvalue method and coordination degree hybrid model [
23]. Zhao H. et al. quantitatively examined the efficiency of power supply in rural areas and the coordination between power supply and regional economic development by using DEA and coordinated development theory, and then comprehensively measured the social value of EUS [
24]. From the perspective of sustainability, Zhao H. et al. constructed the social welfare measure function for electricity consumption of rural residents by employing expected utility theory and prospect theory, and performed the empirical analysis by taking Yunnan province as example [
3]. In terms of implementation mechanism of EUS, Zhao H. et al. firstly analyzed the factors affecting electricity demand of rural residents, and then built an income compensation model for EUS based on a Keynesian consumption function [
25]. Chi N. et al. analyzed the funding mechanism of EUS, examined the cost of switching from the original cross-subsidy mechanism to a funding mechanism, and constructed a decision model for the best time to switch [
26].
For foreign research, the recent researchers mainly focus on how to effectively provide electric energy for rural residents, such as using a distributed power supply and micro-grid. Hoque N. and Kumar S. analyzed the composition, layout and effectiveness of home solar systems for proving electric energy for residents living in remote areas in Bangladesh [
27]. Williams A. and Simpson R. explored the technical requirements, successful experiences and influencing factors of electricity provision for British residents in remote areas using small hydropower [
28]. Saheb-Koussa D. et al. investigated the technological economy of a wind-photovoltaic-diesel hybrid power system by which the rural residents can access electricity in Algeria, and the optimal composition of a wind-solar-oil hybrid power system was also studied [
29]. Lay J. et al. studied the feasibility of distributed solar home systems and conventional lighting fuel power generation system for providing electricity to rural residents in Kenya [
30]. Gómez M.F. et al. analyzed the important challenges faced by rural electrification initiative Luz Para Todos-LPT (Light for All) in the Brazilian Amazon, and proposed several measurements to promote the LPT, such as developing distributed power generation techniques and optimizing subsidies [
31]. Shaahid S.M. and El-Amin I. assessed the techno-economic feasibility of hybrid PV-diesel-battery power systems for rural electrification in Saudi Arabia using NREL’s HOMER software [
32]. Bhattacharyya S.C. comprehensively reviewed the energy access situation of rural areas in India and analyzed the main problems, and finally discussed whether the rural electrification can resolve the energy access issue in India [
33]. Urmee T. et al. performed a literature review on renewable-based rural electrification to analyze the causes of slow progress in providing electricity to rural residents in developing countries in Asia and the Pacific, and proposed suggestions for rural electrification implementation in these countries [
34].
Overall, the current foreign studies mainly focus on the economic and technological feasibility of adopting distributed power generation techniques to provide electricity for rural residents, which can also be summarized as the implementation path of rural electrification. However, in China, the marketization reform of the electric power system is in progress. Power grid extension and distributed power generation are two main paths for rural electrification in China. Close attention is paid by Chinese scholars to the implementation subjects and compensation mechanisms of those two paths. It can be said that the current study remains to be enriched and improved. The existing literature studying the rural electrification in China are mainly from the angles of government (the subject of liability) and electric power enterprises (the subject of implementation). However, there is little related research from the perspective of rural residents (the recipients), not to mention the well-being of rural residents due to electricity consumption. Therefore, the significant factors influencing the well-being of rural residents due to electricity consumption are studied in this paper, which can fill the current research gap. The study in this paper is of great practical value and can provide references for improving the well-being of rural residents and playing the prescribed role of EUS policy as well as possible.
3. Model, Variables and Data Source
3.1. Ordered Probit Model
As a kind of multi-grade discrete choice model, the Ordered Probit model can build a relationship between a non-continuous sequenced dependent variable and explanatory variables, and has been widely used for many practical issues. Different from the Probit model, in the Ordered Probit model, the dependent variable is multi-grade, ordered and discrete, while the explanatory variables are a set of many factors influencing the dependent variables, which can be discrete or continuous. The basic principle of the Ordered Probit model is expounded as follows.
Referring to some well-being quantification-related literatures, in this paper, we suppose that the dependent variable
y, the well-being of rural residents due to electricity consumption, can be represented by five grades, namely “very dissatisfied (VD)”, “not satisfied (NS)”, “generally satisfied (GS)”, “relatively satisfied (RS)” and “very satisfied (VS)”. The explanatory variables
x are composed of a set of factors influencing rural residents’ well-being. When using the multi-grade discrete variable
y as a dependent variable to perform regression analysis with explanatory variables, there may be inconformity and heteroscedasticity. Therefore, it needs to convert discrete dependent variable
y to continuous dependent variable
y*. Suppose there is a continuous dependent variable
y* that cannot be directly observed, but it can be expressed as a continuous function of explanatory variable
x as follows:
where
y* is the converted dependent variable (also called as decision preference),
x = [
x1,
x2, …,
xn] are a set of
n explanatory variables,
β = [
β1,
β2, …,
βn] are the parameters to be estimated in regression model which indicate the contribution degree of
n explanatory variables to dependent variable
y*, and
ε is random disturbance which represents other neglected factors that affect
y*. Meanwhile, ε obeys the standard normal distribution, namely
.
Equation (1) is also called the latent regression equation of the Ordered Probit model. In practice, y* cannot be directly measured, and needs to be obtained by y indirectly.
Let
be the unknown cutting points (also called threshold parameters). Because
y is represented by five grades in this paper, there are four cutting points, namely
α1,
α2,
α3 and
α4. The relationship between
y and
y* is shown as below:
Thus, the probability of
y for each grade value can be computed via Equation (3) as follows:
where
represents the density function of standard normal distribution.
Although y* is unobservable, the range that y* belongs to can be determined. Therefore, we can correlate y* with the probability of y* belonging to the range according to a certain known distribution, and then the estimated value of parameter β can be obtained using the maximum likelihood estimation method based on the sample probabilities of different ranges that y* belongs to.
After the latent regression equation is built, the marginal contribution of each explanatory variable can be calculated, which can explore the influence direction (positive or negative) and influence degree of each explanatory variable
x = [
x1,
x2, …,
xn] on dependent variable
y. The marginal contribution of an explanatory variable refers to the fact that under the condition of other explanatory variables taking average values, the change in the probability of the dependent variable takes certain value that arises when the explanatory variable value changes by one unit, which can be measured by
3.2. Variables Selection
The selection of explanatory variables, namely the factors possibly influencing the well-being of rural residents due to electricity consumption, is very important. In this paper, the initial possible influencing factors were selected based on consulting a large number of literatures. Then, those selected factors were further screened by way of on-the-spot visits and expert consultation. Finally, the final influencing factors were determined, which include demographical and sociological factors, economic factors and electric usage behavior factors.
- (1)
Demographical and sociological factors: These factors aim to reflect the personal features and heterogeneous characteristics of rural residents, which include age, gender, educational level, household population, and health condition.
- (2)
Economic factors: This kind of factors mainly characterize the economic conditions and situations of rural residents, which include each person income of a family per month, income satisfaction, and income source.
- (3)
Electric usage behavior factors: This kind of factors represent the electric consumption features and patterns of rural residents in a certain economic and social environment, which include average power interruption times, monthly electric charge, and service time of household appliances.
The detailed connotations and valuing characteristics of factors are listed in
Table 1.
The well-being of rural residents due to electricity consumption is the dependent variable in this paper. According to the design principle of Likert’s 5-level scale, the well-being of rural resident is divided into five grades, namely “very dissatisfied (VD)”, “not satisfied (NS)”, “generally satisfied (GS)”, “relatively satisfied (RS)” and “very satisfied (VS)”. The connotations and value characteristics of this dependent variable are also listed in
Table 1.
3.3. Data Source
The data used in this paper were obtained through on-the-spot visits and questionnaire surveys at Yunnan province in China. As one of the key provinces where the EUS is implemented, Yunnan province is located on the southwest border of China, and is a mountainous frontier region with a minority population and significant poverty. In 2005, the project ‘Providing electric energy for rural residents living in remote and backward regions’ was launched. In the past ten years, popularizing power-supply projects with a total investment of 3.458 billion RMB yuan have been built, which give nearly 0.32 million of rural residents access to electric energy and increase the electrified rate to more than 99.2%.
Face-to-face interview and questionnaire distribution are two main ways to obtain the data on related factors (variables) used in this paper. For face-to-face interviews, we communicated with rural residents through the asking and answering method, which can make rural residents conscientiously express their thoughts. Finally, 702 valid questionnaires were obtained. For questionnaire surveys, 1020 questionnaires were distributed, and the survey location was the power supply station in the township. When the rural residents paid the electricity bills at the power supply station, they will be asked to fill out questionnaires. Finally, 845 valid questionnaires were obtained by this way, and the valid return rate is 82.84%. Finally, a total of 1547 valid questionnaires were obtained which are used in this paper, and the valid return rate is 89.84%.