Inequality of Carbon Intensity: Empirical Analysis of China 2000–2014
Abstract
:1. Introduction
2. Literature Review
3. Methodology and Data
3.1. Methodologies
3.2. Data Source
4. Analysis Results and Discussion
4.1. National-Level Carbon Intensity Gini Coefficient
4.2. Sub-National-Level Carbon Intensity Gini Coefficient
4.2.1. Intra-Regional Carbon Intensity Gini Coefficient
4.2.2. Inter-Regional Carbon Intensity Gini Coefficient
4.3. Drivers for Inequality of the Carbon Intensity Gini Coefficient
5. Conclusions and Policy Implications
5.1. Conclusions
- At a national level, the inequality of carbon intensity Gini coefficient is rising throughout China. In particular, the growth rates of carbon intensity coefficient are accelerating since 2007.
- At an inter-regional level, long-term trends of the carbon intensity Gini coefficient in Central China and Western China increased, while they decreased in Eastern China.
- At an intra-regional level, the carbon intensity Gini coefficient increased between Eastern China and Western China, Eastern China and Central China, and Central China and Western China.
- The leading contributing factor for the observed increase of the national-scale carbon intensity Gini coefficient was the trans-variation intensity.
5.2. Policy Implications
Acknowledgments
Author Contributions
Conflicts of Interest
References
- Xinhua China’s Legislature Ratifies Paris Agreement on Climate Change. Available online: http://news.xinhuanet.com/english/2016-09/03/c_135656703.htm (accessed on 25 April 2017).
- Enhanced Actions on Climate Change: China’s Intended Nationally Determined Contributions. Department of Climate Change, National Development and Reform Commission, People’s Republic of China: Beijing, China, 2015. Available online: http://www.ndrc.gov.cn/xwzx/xwfb/201506/t20150630_710204.html (accessed on 25 April 2017).
- Wang, Q.; Li, R.; Jiang, R. Decoupling and Decomposition Analysis of Carbon Emissions from Industry: A Case Study from China. Sustainability 2016, 8, 1059. [Google Scholar] [CrossRef]
- Wang, Q.; Li, R. Journey to burning half of global coal: Trajectory and drivers of China‘s coal use. Renew. Sustain. Energy Rev. 2016, 58, 341–346. [Google Scholar] [CrossRef]
- Feng, T.; Sun, L.; Zhang, Y. The relationship between energy consumption structure, economic structure and energy intensity in China. Energy Policy 2009, 37, 5475–5483. [Google Scholar] [CrossRef]
- Wang, Q.; Chen, X. Energy policies for managing China’s carbon emission. Renew. Sustain. Energy Rev. 2015, 50, 470–479. [Google Scholar] [CrossRef]
- Yuan, J.H.; Kang, J.G.; Zhao, C.H.; Hu, Z.G. Energy consumption and economic growth: Evidence from China at both aggregated and disaggregated levels. Energy Econ. 2008, 30, 3077–3094. [Google Scholar] [CrossRef]
- Wang, Z.; Yang, L. Delinking indicators on regional industry development and carbon emissions: Beijing–Tianjin–Hebei economic band case. Ecol. Indic. 2015, 48, 41–48. [Google Scholar] [CrossRef]
- Fan, Y.; Liu, L.C.; Wu, G.; Tsai, H.T.; Wei, Y.M. Changes in carbon intensity in China: Empirical findings from 1980–2003. Ecol. Econ. 2007, 62, 683–691. [Google Scholar] [CrossRef]
- Lambert, P.J.; Aronson, J.R. Inequality decomposition analysis and the Gini coefficient revisited. Econ. J. 1993, 103, 1221–1227. [Google Scholar] [CrossRef]
- Yitzhaki, S. Relative deprivation and the Gini coefficient. Q. J. Econ. 1979, 93, 321–324. [Google Scholar] [CrossRef]
- Shkolnikov, V.M.; Andreev, E.M.; Begun, A.Z. Gini coefficient as a life table function: Computation from discrete data, decomposition of differences and empirical examples. Demogr. Res. 2003, 8, 305–358. [Google Scholar] [CrossRef]
- Aaberge, R. Axiomatic Characterization of the Gini Coefficient and Lorenz Curve Orderings. J. Econ. Theory 2001, 101, 115–132. [Google Scholar] [CrossRef]
- Dagum, C. A New Approach to the Decomposition of the Gini Income Inequality Ratio. Available online: http://link.springer.com/article/10.1007/BF01205777 (accessed on 25 April 2017).
- Dagum, C.; Slottje, D.J. A new method to estimate the level and distribution of household human capital with application. Struct. Chang. Econ. Dyn. 2000, 11, 67–94. [Google Scholar] [CrossRef]
- Sun, T.; Zhang, H.; Wang, Y.; Meng, X.; Wang, C. The application of environmental Gini coefficient (EGC) in allocating wastewater discharge permit: The case study of watershed total mass control in Tianjin, China. Resour. Conserv. Recycl. 2010, 54, 601–608. [Google Scholar] [CrossRef]
- Clarke-Sather, A.; Qu, J.; Wang, Q.; Zeng, J.; Li, Y. Carbon inequality at the sub-national scale: A case study of provincial-level inequality in CO2 emissions in China 1997–2007. Energy Policy 2011, 39, 5420–5428. [Google Scholar] [CrossRef]
- Mussini, M.; Grossi, L. Decomposing changes in CO2 emission inequality over time: The roles of re-ranking and changes in per capita CO2 emission disparities. Energy Econ. 2015, 49, 274–281. [Google Scholar] [CrossRef]
- Chen, J.; Cheng, S.; Song, M.; Wu, Y. A carbon emissions reduction index: Integrating the volume and allocation of regional emissions. Appl. Energy 2016, 184, 1154–1164. [Google Scholar] [CrossRef]
- Asadoorian, M.O. Simulating the spatial distribution of population and emissions to 2100. Environ. Resour. Econ. 2008, 39, 199–221. [Google Scholar] [CrossRef]
- Howarth, R.B.; Kennedy, K. Economic growth, inequality, and well-being. Ecol. Econ. 2016, 121, 231–236. [Google Scholar] [CrossRef]
- Cantore, N.; Padilla, E. Equality and CO2 emissions distribution in climate change integrated assessment modelling. Energy 2010, 35, 298–313. [Google Scholar] [CrossRef]
- Duro, J.A.; Padilla, E. International inequalities in per capita CO2 emissions: A decomposition methodology by Kaya factors. Energy Econ. 2006, 28, 170–187. [Google Scholar] [CrossRef]
- Padilla, E.; Serrano, A. Inequality in CO2 emissions across countries and its relationship with income inequality: A distributive approach. Energy Policy 2006, 34, 1762–1772. [Google Scholar] [CrossRef]
- Wang, Q.; Li, R. Cheaper Oil: a turning point in Paris climate talk? Renew. Sustain. Energy Rev. 2015, 52, 1186–1192. [Google Scholar] [CrossRef]
- Wang, Q.; Chen, X.; Jha, A.N.; Rogers, H. Natural gas from shale formation—The evolution, evidences and challenges of shale gas revolution in United States. Renew. Sustain. Energy Rev. 2014, 30, 1–28. [Google Scholar] [CrossRef]
- Wang, Q. China should aim for a total cap on emissions. Nature 2014, 512, 115. [Google Scholar] [CrossRef] [PubMed]
- Wang, Q.; Chen, X. Rethinking and reshaping the climate policy: Literature review and proposed guidelines. Renew. Sustain. Energy Rev. 2013, 21, 469–477. [Google Scholar] [CrossRef]
- Heil, M.T.; Wodon, Q.T. Future inequality in CO2 emissions and the impact of abatement proposals. Environ. Resour. Econ. 2000, 17, 163–181. [Google Scholar] [CrossRef]
- Fu, X.; Yang, Y.; Dong, W.; Wang, C.; Liu, Y. Spatial structure, inequality and trading community of renewable energy networks: A comparative study of solar and hydro energy product trades. Energy Policy 2017, 106, 22–31. [Google Scholar] [CrossRef]
- Grunewald, N.; Jakob, M.; Mouratiadou, I. Decomposing inequality in CO2 emissions: The role of primary energy carriers and economic sectors. Ecol. Econ. 2014, 100, 183–194. [Google Scholar] [CrossRef]
- Hübler, M. The inequality-emissions nexus in the context of trade and development: A quantile regression approach. Ecol. Econ. 2017, 134, 174–185. [Google Scholar] [CrossRef]
- Jorgenson, A.; Schor, J.; Huang, X. Income Inequality and Carbon Emissions in the United States: A State-level Analysis, 1997–2012. Ecol. Econ. 2017, 134, 40–48. [Google Scholar] [CrossRef]
- Padilla, E.; Duro, J.A. Explanatory factors of CO2 per capita emission inequality in the European Union. Energy Policy 2013, 62, 1320–1328. [Google Scholar] [CrossRef]
- Remuzgo, L.; Sarabia, J.M. International inequality in CO2 emissions: A new factorial decomposition based on Kaya factors. Environ. Sci. Policy 2015, 54, 15–24. [Google Scholar] [CrossRef]
- Wang, Q. China has the capacity to lead in carbon trading. Nature 2013, 493, 273. [Google Scholar] [CrossRef] [PubMed]
- Wang, Q. China’s citizens must act to save their environment. Nature 2013, 497, 159. [Google Scholar] [CrossRef] [PubMed]
- Wang, Q.; Li, R.; Liao, H. Toward Decoupling: Growing GDP without Growing Carbon Emissions. Environ. Sci. Technol. 2016, 50, 11435–11436. [Google Scholar] [CrossRef] [PubMed]
- Safi, M.N.; Zobitz, J.M. Quantifying distribution in carbon uptake and environmental measurements with the Gini coefficient. Lett. Biomath. 2016, 3, 1–12. [Google Scholar] [CrossRef]
- Gini, C. Measurement of inequality of incomes. Econ. J. 1921, 31, 124–126. [Google Scholar] [CrossRef]
- Alvaredo, F. A note on the relationship between top income shares and the Gini coefficient. Econ. Lett. 2011, 110, 274–277. [Google Scholar] [CrossRef]
- Mussard, S.; Seyte, F.; Terraza, M. Decomposition of Gini and the generalized entropy inequality measures. Econ. Bull. 2003, 4, 1–6. [Google Scholar]
- Florian, M.K.; Gladders, M.D.; Li, N.; Sharon, K. The Gini Coefficient as a Tool for Image Family Idenitification in Strong Lensing Systems with Multiple Images. Astrophys. J. Lett. 2016, 816, L23. [Google Scholar] [CrossRef]
- Valbuena, R.; Eerikäinen, K.; Packalen, P.; Maltamo, M. Gini coefficient predictions from airborne lidar remote sensing display the effect of management intensity on forest structure. Ecol. Indic. 2016, 60, 574–585. [Google Scholar] [CrossRef]
- Jantzen, R.T. On the Mathematics of Income Inequality: Splitting the Gini Index in Two. Am. Math. Mon. 2012, 119, 824–837. [Google Scholar] [CrossRef]
- Catalano, M.T.; Leise, T.L.; Pfaff, T.J. Measuring resource inequality: The Gini coefficient. Numeracy 2009, 2, 4. [Google Scholar] [CrossRef]
- Groot, L. Carbon Lorenz curves. Resour. Energy Econ. 2010, 32, 45–64. [Google Scholar] [CrossRef]
- Chameni Nembua, C. The multi-decomposition of the Hirschman–Herfindahl index: measuring household inequality in Cameroon, 1996–2001. Appl. Econ. Lett. 2007, 14, 27–34. [Google Scholar] [CrossRef]
- Quintano, C.; Castellano, R.; Regoli, A. The Contribution of Self-Employment to Income Inequality. A Decomposition Analysis of Inequality Measures by Sources and Subgroups for Italy, 1998–2002. In Proceedings of the International Conference in Memory of Two Eminent Social Scientists, Siena, Italy, 23–26 May 2005. [Google Scholar]
- Chameni Nembua, C. A three components subgroup decomposition of the Hirschman-Herfindahl index and household’s income inequalities in Cameroon. Appl. Econ. Lett. 2005, 12, 941–947. [Google Scholar] [CrossRef]
- Notteboom, T.E. Traffic inequality in seaport systems revisited. J. Transp. Geogr. 2006, 14, 95–108. [Google Scholar] [CrossRef]
- Yue, C.; Hu, X.; He, C.; Zhu, J.; Wang, S.; Fang, J. Provincial Carbon Emissions and Carbon Intensity in China from 1995 to 2007 (Carbon Emissions and Social Development, III). Acta Sci. Nat. Univ. Pekin. 2010, 46, 510–516. [Google Scholar]
- Chuai, X.; Lai, L.; Huang, X.; Zhao, R.; Wang, W.; Chen, Z. Temporospatial changes of carbon footprint based on energy consumption in China. J. Geogr. Sci. 2012, 22, 110–124. [Google Scholar] [CrossRef]
- Tsai, S.F. Analysis of Influencing Factors on Regional Carbon Emission Intensity in China-Based on Empirical Research with Provincial Panel Data. J. Sustain. Dev. 2014, 7, 83. [Google Scholar] [CrossRef]
- Cheng, Y.; Zheye, W.; Xinyue, Y.; Wei, Y.D. Spatiotemporal dynamics of carbon intensity from energy consumption in China. J. Geogr. Sci. 2015, 24, 631–650. [Google Scholar] [CrossRef]
- Wang, Q.; Chen, Y. Barriers and opportunities of using the clean development mechanism to advance renewable energy development in China. Renew. Sustain. Energy Rev. 2010, 14, 1989–1998. [Google Scholar] [CrossRef]
- Wang, Q.; Chen, Y. Energy saving and emission reduction revolutionizing China’s environmental protection. Renew. Sustain. Energy Rev. 2010, 14, 535–539. [Google Scholar] [CrossRef]
- Wang, Q. Effective policies for renewable energy--the example of China’s wind power—Lessons for China’s photovoltaic power. Renew. Sustain. Energy Rev. 2010, 14, 702–712. [Google Scholar] [CrossRef]
- Wang, Q. China needing a cautious approach to nuclear power strategy. Energy Policy 2009, 37, 2487–2491. [Google Scholar] [CrossRef]
- Marland, G.; Boden, T.; Andres, R.J. Global, Regional, and National Fossil-Fuel CO2 Emissions. Available online: http://cdiac.ornl.gov/trends/emis/overview.html (accessed on 25 April 2017).
- CEADS China Emission Accounts and Datasets. Available online: http://www.ceads.net/ (accessed on 25 April 2017).
- Mi, Z.; Zhang, Y.; Guan, D.; Shan, Y.; Liu, Z.; Cong, R.; Yuan, X.C.; Wei, Y.M. Consumption-based emission accounting for Chinese cities. Appl. Energy 2016, 184, 1073–1081. [Google Scholar] [CrossRef]
- Mi, Z.; Wei, Y.M.; Wang, B.; Meng, J.; Liu, Z.; Shan, Y.; Liu, J.; Guan, D. Socioeconomic impact assessment of China's CO 2 emissions peak prior to 2030. J. Clean. Prod. 2017, 142, 2227–2236. [Google Scholar] [CrossRef]
- Sun, J.; Kong, W. Research on comprehensive evaluation index of China’s economic efficiency–Comparative analysis based on panel data of eastern, central and western regions. J. Beijing Technol. Bus. Univ. (Soc. Sci.) 2017, 32, 110–120. [Google Scholar]
- Cai, X.; Mo, J.; Feng, Z.J. The regional difference of the effect of export and FDI on employment in China—Based on panel data of eastern, middle and western district. Econ. Geogr. 2009, 29, 215–219. [Google Scholar]
- Yang, R.; Li, Y. The Empirical Analysis of Regional Differences in Financial Support to the Development of Chinese Tourism Industry—On the Basis of the Panel Data of the Eastern, Central and Western. Econ. Manag. 2013, 27, 86–91. [Google Scholar]
- Zhou, C.X.; Mao, C.X.; Yang, Z. An Empirical Study on the Wealth Effect of Residents’ Wealth—Based on the Difference among Eastern, Central and Western Regions. Econ. Surv. 2014, 31, 14–18. [Google Scholar]
- Wang, Q.; Li, R. Research status of shale gas: A review. Renew. Sustain. Energy Rev. 2017, 74, 715–720. [Google Scholar] [CrossRef]
- Wang, Q.; Jiang, X.T.; Li, R. Comparative decoupling analysis of energy-related carbon emission from electric output of electricity sector in Shandong Province, China. Energy 2017, 127, 78–88. [Google Scholar] [CrossRef]
- Wang, Q.; Li, R. Drivers for energy consumption: A comparative analysis of China and India. Renew. Sustain. Energy Rev. 2016, 62, 954–962. [Google Scholar] [CrossRef]
- Wang, Q.; Li, R. Natural gas from shale formation: A research profile. Renew. Sustain. Energy Rev. 2016, 57, 1–6. [Google Scholar] [CrossRef]
- Yang, Q.; Liu, H.J. Regional Differences and Convergence of Carbon Intensity Distribution in China: Based on an Empirical Study of Provincial Data 1995-2009. Contemp. Financ. Econ. 2012, 2, 87–98. [Google Scholar]
- Lu, G. Study on Disparity and Converagence of Carbon Intensity in the Western Region. Ph.D. Thesis, Lanzhou University, Lanzhou, China, 8 June 2015. [Google Scholar]
- Liao, S.H.; Xiao, Y.F. Pollution Industry Transfer and Carbon Transfer Space Characteristic in Midland of China. Econ. Geogr. 2017, 37, 132–140. [Google Scholar]
© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Li, R.; Jiang, X.-T. Inequality of Carbon Intensity: Empirical Analysis of China 2000–2014. Sustainability 2017, 9, 711. https://doi.org/10.3390/su9050711
Li R, Jiang X-T. Inequality of Carbon Intensity: Empirical Analysis of China 2000–2014. Sustainability. 2017; 9(5):711. https://doi.org/10.3390/su9050711
Chicago/Turabian StyleLi, Rongrong, and Xue-Ting Jiang. 2017. "Inequality of Carbon Intensity: Empirical Analysis of China 2000–2014" Sustainability 9, no. 5: 711. https://doi.org/10.3390/su9050711