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Did civilized city policy improve energy efficiency of resource-based cities? Prefecture-level evidence from China

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  • Li, Bo
  • Han, Yukai
  • Wang, Chensheng
  • Sun, Wei

Abstract

Based on panel data of 114 prefecture-level resource-based cities in China from 2004 to 2018, this paper uses SBM model and super-efficiency SBM model to measure the energy efficiency of resource-based cities in China, and systematically analyzes the influence of Civilized City Policy on energy efficiency and the mechanism for that influence using difference-in-differences (DID) model and propensity score matching method. The findings show that the spatial distribution of energy efficiency of resource-based cities is higher in eastern China and lower in western China, and the energy efficiency was continually improved, with fluctuations, between 2004 and 2018. DID analysis and robustness analysis prove that Civilized City Policy is significantly conducive to improving energy efficiency of resource-based cities in China. This positive influence can also be achieved through the mechanism of technological innovation. In addition, there exists regional and type heterogeneity in the influence of Civilized City Policy on energy efficiency of resource-based cities.

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  • Li, Bo & Han, Yukai & Wang, Chensheng & Sun, Wei, 2022. "Did civilized city policy improve energy efficiency of resource-based cities? Prefecture-level evidence from China," Energy Policy, Elsevier, vol. 167(C).
  • Handle: RePEc:eee:enepol:v:167:y:2022:i:c:s0301421522003068
    DOI: 10.1016/j.enpol.2022.113081
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    as
    1. Li, Lan-Bing & Hu, Jin-Li, 2012. "Ecological total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 46(C), pages 216-224.
    2. Jacobson, Louis S & LaLonde, Robert J & Sullivan, Daniel G, 1993. "Earnings Losses of Displaced Workers," American Economic Review, American Economic Association, vol. 83(4), pages 685-709, September.
    3. Ghasemi-Mobtaker, Hassan & Mostashari-Rad, Fatemeh & Saber, Zahra & Chau, Kwok-wing & Nabavi-Pelesaraei, Ashkan, 2020. "Application of photovoltaic system to modify energy use, environmental damages and cumulative exergy demand of two irrigation systems-A case study: Barley production of Iran," Renewable Energy, Elsevier, vol. 160(C), pages 1316-1334.
    4. Louis S. Jacobson & Robert J. LaLonde & Daniel G. Sullivan, 1993. "Long-term earnings losses of high-seniority displaced workers," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 17(Nov), pages 2-20.
    5. Moretti, Enrico, 2011. "Local Labor Markets," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 14, pages 1237-1313, Elsevier.
    6. Sahoo, Nihar R. & Mohapatra, Pratap K.J. & Sahoo, Biresh K. & Mahanty, Biswajit, 2017. "Rationality of energy efficiency improvement targets under the PAT scheme in India – A case of thermal power plants," Energy Economics, Elsevier, vol. 66(C), pages 279-289.
    7. Czarnitzki, Dirk & Hanel, Petr & Rosa, Julio Miguel, 2011. "Evaluating the impact of R&D tax credits on innovation: A microeconometric study on Canadian firms," Research Policy, Elsevier, vol. 40(2), pages 217-229, March.
    8. Eliana La Ferrara & Alberto Chong & Suzanne Duryea, 2012. "Soap Operas and Fertility: Evidence from Brazil," American Economic Journal: Applied Economics, American Economic Association, vol. 4(4), pages 1-31, October.
    9. Zhou, P. & Ang, B.W., 2008. "Linear programming models for measuring economy-wide energy efficiency performance," Energy Policy, Elsevier, vol. 36(8), pages 2901-2906, August.
    10. Thorsten Beck & Ross Levine & Alexey Levkov, 2010. "Big Bad Banks? The Winners and Losers from Bank Deregulation in the United States," Journal of Finance, American Finance Association, vol. 65(5), pages 1637-1667, October.
    11. Zhang, Caiqing & Chen, Panyu, 2022. "Applying the three-stage SBM-DEA model to evaluate energy efficiency and impact factors in RCEP countries," Energy, Elsevier, vol. 241(C).
    12. Du, Weijian & Li, Mengjie & Wang, Faming, 2020. "Role of rent-seeking or technological progress in maintaining the monopoly power of energy enterprises: An empirical analysis based on micro-data from China," Energy, Elsevier, vol. 202(C).
    13. Ma, Chunbo & Stern, David I., 2008. "China's changing energy intensity trend: A decomposition analysis," Energy Economics, Elsevier, vol. 30(3), pages 1037-1053, May.
    14. Zhong, Meirui & Huang, Gangli & He, Ruifang, 2022. "The technological innovation efficiency of China's lithium-ion battery listed enterprises: Evidence from a three-stage DEA model and micro-data," Energy, Elsevier, vol. 246(C).
    15. Hancevic, Pedro Ignacio, 2016. "Environmental regulation and productivity: The case of electricity generation under the CAAA-1990," Energy Economics, Elsevier, vol. 60(C), pages 131-143.
    16. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    17. Li, Hongbin & Zhou, Li-An, 2005. "Political turnover and economic performance: the incentive role of personnel control in China," Journal of Public Economics, Elsevier, vol. 89(9-10), pages 1743-1762, September.
    18. Wang, Han & Chen, Zhoupeng & Wu, Xingyi & Nie, Xin, 2019. "Can a carbon trading system promote the transformation of a low-carbon economy under the framework of the porter hypothesis? —Empirical analysis based on the PSM-DID method," Energy Policy, Elsevier, vol. 129(C), pages 930-938.
    19. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    20. Paul J. Burke & Md Shahiduzzaman & David I. Stern, 2015. "Carbon dioxide emissions in the short run: The rate and sources of economic growth matter," CAMA Working Papers 2015-12, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    21. Wackernagel, Mathis & Onisto, Larry & Bello, Patricia & Callejas Linares, Alejandro & Susana Lopez Falfan, Ina & Mendez Garcia, Jesus & Isabel Suarez Guerrero, Ana & Guadalupe Suarez Guerrero, Ma., 1999. "National natural capital accounting with the ecological footprint concept," Ecological Economics, Elsevier, vol. 29(3), pages 375-390, June.
    22. Kemfert, Claudia & Truong, Truong, 2007. "Impact assessment of emissions stabilization scenarios with and without induced technological change," Energy Policy, Elsevier, vol. 35(11), pages 5337-5345, November.
    23. Wang, Yun & Sun, Xiaohua & Guo, Xu, 2019. "Environmental regulation and green productivity growth: Empirical evidence on the Porter Hypothesis from OECD industrial sectors," Energy Policy, Elsevier, vol. 132(C), pages 611-619.
    24. Cong, Di & Liang, Lingling & Jing, Shaoxing & Han, Yongming & Geng, Zhiqiang & Chu, Chong, 2021. "Energy supply efficiency evaluation of integrated energy systems using novel SBM-DEA integrating Monte Carlo," Energy, Elsevier, vol. 231(C).
    25. Subal Kumbhakar & Gudbrand Lien & J. Hardaker, 2014. "Technical efficiency in competing panel data models: a study of Norwegian grain farming," Journal of Productivity Analysis, Springer, vol. 41(2), pages 321-337, April.
    26. Martin K. Patel & Jean-Sébastien Broc & Haein Cho & Daniel Cabrera & Armin Eberle & Alessandro Federici & Alisa Freyre & Cédric Jeanneret & Kapil Narula & Vlasios Oikonomou & Selin Yilmaz, 2021. "Why We Continue to Need Energy Efficiency Programmes—A Critical Review Based on Experiences in Switzerland and Elsewhere," Energies, MDPI, vol. 14(6), pages 1-28, March.
    27. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    28. Wu, Haitao & Hao, Yu & Ren, Siyu, 2020. "How do environmental regulation and environmental decentralization affect green total factor energy efficiency: Evidence from China," Energy Economics, Elsevier, vol. 91(C).
    29. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    30. Tombe, Trevor & Winter, Jennifer, 2015. "Environmental policy and misallocation: The productivity effect of intensity standards," Journal of Environmental Economics and Management, Elsevier, vol. 72(C), pages 137-163.
    31. Honma, Satoshi & Hu, Jin-Li, 2014. "A panel data parametric frontier technique for measuring total-factor energy efficiency: An application to Japanese regions," Energy, Elsevier, vol. 78(C), pages 732-739.
    32. Wang, Qunwei & Zhou, Peng & Zhou, Dequn, 2012. "Efficiency measurement with carbon dioxide emissions: The case of China," Applied Energy, Elsevier, vol. 90(1), pages 161-166.
    33. Ang, B.W. & Xu, X.Y. & Su, Bin, 2015. "Multi-country comparisons of energy performance: The index decomposition analysis approach," Energy Economics, Elsevier, vol. 47(C), pages 68-76.
    34. Tang, Liwei & He, Gang, 2021. "How to improve total factor energy efficiency? An empirical analysis of the Yangtze River economic belt of China," Energy, Elsevier, vol. 235(C).
    35. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    36. Trianni, Andrea & Cagno, Enrico & Worrell, Ernst, 2013. "Innovation and adoption of energy efficient technologies: An exploratory analysis of Italian primary metal manufacturing SMEs," Energy Policy, Elsevier, vol. 61(C), pages 430-440.
    37. Patterson, Murray G, 1996. "What is energy efficiency? : Concepts, indicators and methodological issues," Energy Policy, Elsevier, vol. 24(5), pages 377-390, May.
    38. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    39. Bosseboeuf, Didier & Richard, Cecile, 1997. "The need to link energy efficiency indicators to related policies : A practical experience based on 20 years of facts and trends in France (1973-1993)," Energy Policy, Elsevier, vol. 25(7-9), pages 813-823.
    40. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    41. Yoshinori Kobayashi & Hideki Kobayashi & Akinori Hongu & Kiyoshi Sanehira, 2005. "A Practical Method for Quantifying Eco‐efficiency Using Eco‐design Support Tools," Journal of Industrial Ecology, Yale University, vol. 9(4), pages 131-144, October.
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