Factors influencing renewable electricity consumption in China

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Abstract

Renewable energy is an important factor in achieving a low-carbon economic development path in China. This paper investigates the factors influencing renewable electricity consumption in China. Specifically, the factors that influence the share of renewable electricity in total electricity consumption in China is investigated using data from 1980 to 2011 and employing the Johansen cointegration technique and vector error correction model. The result of the analysis shows that there is a long run relationship between renewable electricity consumption and GDP per capita, trade openness, foreign direct investment, financial development and share of fossil fuel in energy consumption. Economic development and financial development promotes renewable electricity consumption while foreign direct investment, trade openness and the lobby of conventional energy sources undermine the share of renewables in total electricity consumption in China. While the effects of shocks to the other variables appear to die out over time, the “lobby effect” is persistent and explosive. The results also show that there is a uni-directional short run causality from financial development to renewable electricity consumption and from renewable electricity consumption to trade openness. The Chinese government should pursue policies that not only increase the amount of renewable electricity, but also increase the share of renewables in total electricity consumption.

Introduction

China’s impressive economic performance in the past decades has resulted in increased energy consumption and carbon intensity. Over the past few years, China’s economy has grown at an average of over 7%, exceeding that of the United States and the European Union combined. However, this impressive economic performance has led to increase in energy consumption and carbon (CO2) emission. According to the United States Energy Information Administration (EIA), China’s primary energy consumption increased from 17.29 Quad BTU in 1980 to 103.72 Quad BTU in 2011. Similarly, her electricity net consumption increased from 261.49 billion kilowatthours in 1980 to 4207.70 billion kilowatthours in 2011 (Fig. 1), an increase of over 1500%. With the increase in total primary energy and coal-dominated electricity consumption, carbon emission also increased significantly as shown in Fig. 1. Carbon emission associated with electricity production and consumption in China is high because coal is the dominant fuel for electricity production in the country. As at 2012, China’s energy consumption-related CO2 emission stands at 8547.74 million metric tons compared to 1448.46 million metric tons in 1980, which makes it the largest CO2 emitter in the world. The current emission in China is almost that of Africa (1152.22), Europe (4305.17), Middle East (1951.80) and Central and South America (1339.47) combined. The current trend of high resource intensity, energy consumption and emission is not sustainable. If current trend continues, China’s emission level will undermine global effort to stem climate change and global warming.

The high level of energy intensity and CO2 emission in China has attracted local and international attention, and has called for significant changes to the country’s energy strategy and policy. In response to this, measures are being put in place to address the situation. One of the key measures aimed at addresing energy-related CO2 emission in China is increasing the share of renewable energy in the total energy mix. The share of renewable-generated electricity in total electricity consumption in China is small and has decreased over time, as shown in Fig. 2. China has the highest amount of renewable electricity net consumption in 2011 (800.96 billion Kwh) compared to the United States (527.48 Kw h), Germany (126.18 Kwh), India (160.36 Kw h) and Finland (23.39 Kw h). Yet, the share of renewable-generated electricity in total electricity net consumption in China (19.03%) is low compared to Germany (23.46%), India (21.15%) and Finland (28.86%).

However, the enactment of the Renewable Energy Law of 2005 was aimed at reversing the trend and promoting renewable energy in the country. The 11th Five-Year Plan (2006–2010) targets 20% reduction in per capita GDP energy consumption and 10% reduction in two major air pollutants, while the renewable energy plan of the National Development and Reform Committee (NDRC) for the same period sets a 10% of renewable in total enrgy consumption by 2010 [48]. The 12th Five-Year Plan (2011–2015) sets more ambitious goals of achieveing a share of 11.4% of non-fossil fuel (renewables and nuclear) in total energy consumption. Also, during the National People’s Congress (NPC) and Chinese People׳s Political Consultative Conference (CPPPC) 2014 Annual Session, the government states its commitment towards reducing environmental pollution and energy-related CO2 emissions by promoting the development, deployment and use of renewable energy. This is a significant step towards reducing energy-related CO2 emission in China and globally, given the position of China as the largest carbon emitter in the world. Reducing energy consumption and CO2 emission in China will, to a large extent, facilitate the achievement of global target for CO2 emissions and climate change mitigation. Against this background, this paper examines the influencing factors of renewable energy consumption in China.

A number of studies have been conducted on renewable energy development, with substantial studies focusing on China. However, this present study differs by examining the share of renewables in total energy consumption instead of the amount of renewable energy. The main contribution of this paper to the literature is threefold. First, although there have been enormous studies on renewable energy in the field of energy and environmental economics, majority of these studies focus on developed and industrialised countries such as United States, EU and generally, OECD countries [18], [31]. In contrast, this paper models and analyses the determinants of renewable electricity consumption in an emerging country. Second, most of the empirical studies analysing the drivers of and barriers to renewable energy employ panel data techniques, and do not adequately investigate country specific factors [1], [27], [30]. Following SSDN and IDDRI [39], deep decarbonisation of energy system requires both globally coordinated decarbonisation strategy and individual country-level decarbonisation pathways. Also, according to Vachon and Menz [42], individual country characteristics such as culture, wealth and renewable energy endowment are important drivers of renewable energy. The individual country characteristics and pathways are necessary given the significant differences in income level, resource endowment, energy consumption level and structure, technology advancement, amount of CO2 emission, energy market structure, mitigation and adaptation capabilities, and development policy goals across countries. Thus, this study takes these factors into consideration, and focuses the analysis on an individual country – China – whose decarbonisation pathway is crucial for meeting global climate change goals. Third, most of the previous studies on renewable energy use the amount of renewable energy produced or consumed as dependent variables. However, based on Aguirre and Ibikunle [1] and SSDN and IDDRI [39], it is the share of renewable energy in total energy consumption and not the amount of renewable energy consumed that is important for climate change mitigation. Therefore, this study deviates from previous studies and uses the share of renewable energy-generated electricity in total electricity consumption as the dependent variable. Therefore, the objective of this paper is to empirically investigate the drivers of and barriers to renewable electricity consumption in China.

Section snippets

Literature review

There has been substantial research attention on renewable energy in recent years. Renewable energy is recognised as a viable option to enhance energy access and at the same time mitigate climate change [22]. Research on the determinants of renewable energy can be classified into panel and time series analysis, developed and developing countries, investigation of individual variables, and various types of renewable energy.

Marques et al. [18] analyse the drivers of renewable energy in the

Methods

To capture the dynamic relationship between the renewable electricity and its influcencing factors in China, the Vector Error Correction Method (VECM) and cointegration technique are employed. The VECM framework determines the direction of causality between the variables while providing estimates on both the long run and the short run. The co-integration analysis which is a property of long run equilibrium provides information about the long run relationship among the variables while the

Unit root test

Before analysing the impact of the determinants of renewable energy in China using Eq. (2) above, the properties of the time series data used in this study is tested for unit root. The Augmented Dickey Fuller (ADF) unit root test is used to examine the stationarity of the series and the result is presented in Table 1. From the table, it is observed that the variables are non-stationary at levels, but their first difference forms are stationary. Thus, the variables fulfils the condition for

Conclusions and policy implications

This study examines the long term determinants of renewable electricity in China using data from 1980 to 2011. A number of studies have been conducted on renewable energy adoption but most of these studies adopt panel data analysis, and focus on the amount of renewable energy. This study differs by focusing on time series analysis of China and examine the determinants of the share of renewables in total electricity consumption. The Johansen cointegration technique and vector error correction

Acknowledgements

This paper is supported by Xiamen University-Newcastle University Joint Strategic Partnership Fund, the Grant for Collaborative Innovation Center for Energy Economics and Energy Policy (No. 1260-Z0210011), Xiamen University Flourish Plan Special Funding (No. 1260-Y07200), and the China Sustainable Energy Program (G-1506-23315).

The authors also acknowledge the initial comments by Dr. John T. Dalton of the Department of Economics, Wake Forest University, Winston-Salem, North Carolina, United

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