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The role of technical progress in China’s northern and southern heating industry

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Abstract

Coal as the main fuel for the heating industry exerts heavy burdens on China’s environment. Based on meta-frontier non-radial distance function, this paper estimates the total-factor unified integrated efficiency of the thermoelectric industry in 29 provinces and analyzes its dynamic changes using Malmquist index. Besides, the composition of the meta-frontier Malmquist unified integrated efficiency is further evaluated to analyze the spatial-temporal features of the thermoelectric industry. The results show that the average total-factor unified integrated efficiency of the thermoelectric industry in the northern and southern China is 0.572 and 0.587, respectively, over 1999–2014. Although the total-factor unified integrated efficiency of the thermoelectric industry tends to improve, technical progress plays different role in the north and the south. Improvement in the thermoelectric industry in the north mainly relies on technical efficiency, while improvement in the south mainly relies on technical progress. Technological catch-up in both the north and south is weak.

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References

  • Agrell, P. J., & Tind, P. B. (2005). DEA and dynamic yardstick competition in Scandinavian electricity distribution[J]. Journal of Productivity Analysis, 23(2), 173–201.

    Article  Google Scholar 

  • Arcos-Vargas, A., Núnez-Hernández, F., & Villa-Caro, G. (2017). A DEA analysis of electricity distribution in Spain: an industrial policy recommendation[J]. Energy Policy, 102, 583–592.

    Article  Google Scholar 

  • Ball, V. E., Färe, R., Grosskopf, S., & Margaritis, D. (2010). Productivity and profitability of US agriculture: evidence from a panel of states. New York: Springer.

    Google Scholar 

  • Barros, C. P., Managi, S., & Matousek, R. (2012). The technical efficiency of the Japanese banks: non-radial directional performance measurement with undesirable output. Omega, 40, 1–8.

    Article  Google Scholar 

  • Battese, G. E., Rao, D. S. P., & O'Donnell, C. J. (2004). A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies. Journal of Productivity Analysis, 21, 91–103.

    Article  Google Scholar 

  • Cherchye, L., & Post, T. (2003). Methodological advances in DEA: a survey and an application for the Dutch electricity sector[J]. Statistica Neerlandica, 57(4), 410–438.

    Article  MathSciNet  Google Scholar 

  • Chambers, R. G., Chung, Y., & Färe, R. (1996). Benefit and distance functions. Journal of Economic Theory, 70, 407–419.

    Article  Google Scholar 

  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429–444.

    Article  MathSciNet  Google Scholar 

  • Chung, Y. H., Färe, R., & Grosskopf, S. (1997). Productivity and undesirable outputs: a directional distance function approach. Microeconomics, 51, 229–240.

    Google Scholar 

  • Färe R., Grosskopf S., Norris M., Zhang, Z. (1994). Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries[J]. American Economic Review, 84(5),1040-1044.

  • Farrell M J. (1957). The Measurement of Productive Efficiency[J]. Journal of the Royal Statistical Society. Series A (General), 120(3), 253-290. 

  • Fukuyama, H., & Matousek, R. (2011). Efficiency of Turkish banking: two-stage network system. Variable returns to scale model. Journal of International Financial Markets Institutions & Money, 21, 75–91.

    Article  Google Scholar 

  • Fukuyama, H., & Weber, W. L. (2009). Estimating indirect allocative inefficiency and productivity change. Journal of the Operational Research Society, 60, 1594–1608.

    Article  Google Scholar 

  • Fukuyama, H., & Weber, W. L. (2010). A slacks-based inefficiency measure for a two-stage system with bad outputs. Omega, 38, 398–409.

    Article  Google Scholar 

  • IPCC, (2006). IPCC Guidelines for National Greenhouse Gas Inventories[R], the Institute for Global Environmental Strategies (IGES) for the IPCC. (https://www.ipcc-nggip.iges.or.jp/public/2006gl/index.html). Accessed 30 Aug 2013.

  • Ghosh, R., & Kathuria, V. (2016). The effect of regulatory governance on efficiency of thermal power generation in India: a stochastic frontier analysis[J]. Energy Policy, 89, 11–24.

    Article  Google Scholar 

  • Geymueller, P. V. (2009). Static versus dynamic DEA in electricity regulation: the case of US transmission system operators[J]. Central European Journal of Operations Research, 17(4), 397–413.

    Article  Google Scholar 

  • Lin, B., & Du, K. (2015). Energy and CO 2 emissions performance in China's regional economies: do market-oriented reforms matter? Energy Policy, 78, 113–124.

    Article  Google Scholar 

  • Oh, D. H., & Lee, J. D. (2010). A metafrontier approach for measuring Malmquist productivity index. Empirical Economics, 38, 47–64.

    Article  Google Scholar 

  • Simab M , Haghifam M R . DEA efficiency for the benchmarking of Iranian electric distribution utilities[C]// Electricity Distribution - Part 1, 2009. CIRED 2009. 20th International Conference and Exhibition on. IET, 2009.

  • Seyoum, E. T., Battese, G. E., & Fleming, E. M. (2004). Technical efficiency and productivity of maize producers in eastern Ethiopia: a study of farmers within and outside the Sasakawa-Global 2000 project. Agricultural Economics of Agricultural Economists, 19, 341–348.

    Google Scholar 

  • Sueyoshi, T., & Goto, M. (2011). DEA approach for unified efficiency measurement: assessment of Japanese fossil fuel power generation. Energy Economics, 33, 292–303.

    Article  Google Scholar 

  • Tulkens, H., & Eeckaut, P. V. (1995). Non-frontier measures of efficiency, progress and regress for time series data. International Journal of Production Economics, 39, 83–97.

    Article  Google Scholar 

  • Wang, K., Wei, Y. M., & Zhang, X. (2013a). Energy and emissions efficiency patterns of Chinese regions: a multi-directional efficiency analysis. Applied Energy, 104, 105–116.

    Article  Google Scholar 

  • Wang, K., Yu, S., & Zhang, W. (2013b). China’s regional energy and environmental efficiency: a DEA window analysis based dynamic evaluation. Mathematical & Computer Modelling, 58, 1117–1127.

    Article  Google Scholar 

  • Wang, Q. W., Zhou, P., & Zhou, D. Q. (2010). Research on dynamic carbon dioxide emissions performance, regional disparity and affecting factors in China. China Industrial Economics, 33, 45–54.

    Google Scholar 

  • Zhang, N., Kong, F., Choi, Y., & Zhou, P. (2014). The effect of size-control policy on unified energy and carbon efficiency for Chinese fossil fuel power plants. Energy Policy, 70, 193–200.

    Article  Google Scholar 

  • Zhouab, P., & Wang, H. (2012). Energy and CO emission performance in electricity generation: a non-radial directional distance function approach. European Journal of Operational Research, 221, 625–635.

    Article  Google Scholar 

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Acknowledgements

This paper is supported by Report Series from Ministry of Education of China (NO.10JBG013).

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Authors and Affiliations

  1. School of Economics and Management, Shanghai Institute of Technology, Shanghai, 200235, People’s Republic of China

    Jing Lin

  2. School of Management, China Institute for Studies in Energy Policy, Collaborative Innovation Center for Energy Economics and Energy Policy, Xiamen University, Xiamen, 361005, Fujian, People’s Republic of China

    Boqiang Lin

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  1. Jing Lin
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Correspondence to Boqiang Lin.

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Lin, J., Lin, B. The role of technical progress in China’s northern and southern heating industry. Energy Efficiency 13, 665–682 (2020). https://doi.org/10.1007/s12053-020-09844-w

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