The distribution dynamics of Carbon Dioxide Emission intensity across Chinese provinces: A weighted Approach

📝 Abstract

This paper examines the distribution dynamics of carbon dioxide (CO2) emission intensity across 30 Chinese provinces using a weighted distribution dynamics approach. The results show that CO2 emission intensity tends to diverge during the sample period of 1995-2014. However, convergence clubs are found in the ergodic distributions of the full sample and two sub-sample periods. Divergence, polarization and stratification are the dominant characteristics in the distribution dynamics. Weightings with economic and population sizes have important impacts on current distributions and hence long run steady distributions. Neglecting economic size may under-estimate the deterioration in the long run steady state. The result also shows that conditioning on space and income cannot eliminate the multimodality in the long run distribution. However, capital intensity has important impact on the formation of convergence clubs. Our findings have contributions in the understanding of the spatial dynamic behaviours of CO2 emissions across Chinese provinces, and have important policy implications for CO2 emissions reduction in China.

💡 Analysis

This paper examines the distribution dynamics of carbon dioxide (CO2) emission intensity across 30 Chinese provinces using a weighted distribution dynamics approach. The results show that CO2 emission intensity tends to diverge during the sample period of 1995-2014. However, convergence clubs are found in the ergodic distributions of the full sample and two sub-sample periods. Divergence, polarization and stratification are the dominant characteristics in the distribution dynamics. Weightings with economic and population sizes have important impacts on current distributions and hence long run steady distributions. Neglecting economic size may under-estimate the deterioration in the long run steady state. The result also shows that conditioning on space and income cannot eliminate the multimodality in the long run distribution. However, capital intensity has important impact on the formation of convergence clubs. Our findings have contributions in the understanding of the spatial dynamic behaviours of CO2 emissions across Chinese provinces, and have important policy implications for CO2 emissions reduction in China.

📄 Content

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The distribution dynamics of Carbon Dioxide Emission intensity across Chinese provinces: A weighted Approach Jian-Xin Wu1,2 and Ling-Yun He1,3,*

1School of Economics, Jinan University, China 2Business School, University of Western Australia, Australia 3School of Economics and Management, Nanjing University of Information Science and Technology, China *Corresponding Author, Email: lyhe@amss.ac.cn.

Abstract: This paper examines the distribution dynamics of carbon dioxide (CO2) emission intensity across 30 Chinese provinces using a weighted distribution dynamics approach. The results show that CO2 emission intensity tends to diverge during the sample period of 1995-2014. However, convergence clubs are found in the ergodic distributions of the full sample and two sub-sample periods. Divergence, polarization and stratification are the dominant characteristics in the distribution dynamics. Weightings with economic and population sizes have important impacts on current distributions and hence long run steady distributions. Neglecting economic size may under-estimate the deterioration in the long run steady state. The result also shows that conditioning on space and income cannot eliminate the multimodality in the long run distribution. However, capital intensity has important impact on the formation of convergence clubs. Our findings have contributions in the understanding of the spatial dynamic behaviours of CO2 emissions across Chinese provinces, and have important policy implications for CO2 emissions reduction in China.
Keywords: Carbon dioxide emissions; weighted kernel estimation; distribution dynamics; conditional distribution; Chinese provinces

Acknowledgements: This paper is supported by the National Social Science Foundation (15ZDA054), Humanities and Social Sciences of Ministry of Education Planning Fund (16YJA790050), and the Natural Science Foundation of China (Nos. 71573258 and 71273261).

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1. Introduction Under threat of global warming, CO2 emission abatement has become one of the most important environmental concerns during the past decades. As one of the major energy consumers and CO2 emitters, China has surpassed the United States to be the world largest CO2 emitter since 2007. The huge amount and rapid growth of CO2 emissions in China have attracted considerable attentions from both policy-makers and researchers. Moreover, after decades of rapid economic growth, the income growth is accompanied by serious environmental deterioration. Therefore, the Chinese government is facing the problem of environmental protection and international pressure to reduce CO2 emissions, and have taken actions to reduce CO2 emissions in recent development plans. For example, in the 2009 Copenhagen conference, the Chinese government pledged a CO2 emission intensity (the ratio of CO2 emissions over GDP) reduction of 40%-45% from 2005 to 2020. In 2014, the Government further promised to reach its carbon emissions peak before 2030.
   China is a country with a vast territory and 34 heterogeneous provinces of significant diversity. These provinces differ greatly in factor endowment, industry structure, income level and CO2 emissions. More importantly, the national CO2 emission reduction target is disaggregate on the provincial level. Therefore, understanding the distribution dynamics of CO2 emissions across provinces is important in future CO2 emissions prediction and environmental policy making. Therefore, some studies focus on the convergence behaviour of CO2 emissions across provinces in China (Huang and Meng, 2013; Wang and Zhang, 2014; Wang et al., 2014; Hao et al., 2015; Zhao et al., 2015). However, due to different sample periods and econometric approaches, current empirical results remain inherently controversial in existing literature. For example, Wang et al., (2014) find evidence of divergence in CO2 emissions, while many others found evidence of convergence (Huang and Meng, 2013; Wang and Zhang, 2014; Hao et al., 2015; Zhao et al., 2015). Traditionally, there are three types of convergences, namely, sigma, beta, and stochastic convergences. As indicated by Barro and Sala-i-Martin (1992), these traditional approaches are based on models for average or representative economies, which help us understand the evolution of CO2 emissions in general, but provide little information for the spatial distribution dynamics of CO2 emissions across provinces. In addition, these approaches provide no information on the entire shape of the distribution and intradistribution mobility, namely the relative position changes in terms of CO2 emissions. Finally, Chinese provinces differ greatly in economic and population sizes. For example, the economic and population sizes of Guangdong, a southern province in China, are 43 times, and 16 times than those of Ninxia Province, one of Chinese northwest provinces, respectively. The welfare effect of one p

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