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Energy Efficiency Transitions in China: How Persistent are the Movements to/from the Frontier?

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  • Lin Zhang and Philip Kofi Adom

Abstract

This study examines the energy efficiency transitions in China using provincial data covering the period 2003-2015. Sustainable progress in energy efficiency achievement is beneficial to energy security and the achievement of the Paris Agreement. This article combines the stochastic frontier method with the panel Markov-switching regression to model energy efficiency transitions. The estimated energy efficiency scores show significant regional and provincial heterogeneity. Also, while human capital development, urbanization, and foreign direct investment promote energy efficiency, price and income per capita reduce it. The transition probabilities indicate that the high energy-efficient state is less sustainable, and the movement towards the frontier seems less persistent than movement from the frontier. Thus, it appears that China is not making sustainable progress in energy efficiency. The unsustainable nature of the high energy-efficient state suggests that in China, there are weak energy efficiency efforts and energy efficiency policies lack robustness.

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  • Lin Zhang and Philip Kofi Adom, 2018. "Energy Efficiency Transitions in China: How Persistent are the Movements to/from the Frontier?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
  • Handle: RePEc:aen:journl:ej39-6-zhang
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    1. Zhang, Lin, 2017. "Correcting the uneven burden sharing of emission reduction across provinces in China," Energy Economics, Elsevier, vol. 64(C), pages 335-345.
    2. Roberto Colombi & Subal Kumbhakar & Gianmaria Martini & Giorgio Vittadini, 2014. "Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency," Journal of Productivity Analysis, Springer, vol. 42(2), pages 123-136, October.
    3. Kangjuan Lv & Anyu Yu & Yiwen Bian, 2017. "Regional energy efficiency and its determinants in China during 2001–2010: a slacks-based measure and spatial econometric analysis," Journal of Productivity Analysis, Springer, vol. 47(1), pages 65-81, February.
    4. Efthymios G. Tsionas & Subal C. Kumbhakar, 2014. "FIRM HETEROGENEITY, PERSISTENT AND TRANSIENT TECHNICAL INEFFICIENCY: A GENERALIZED TRUE RANDOM‐EFFECTS model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 110-132, January.
    5. Massimo Filippini & William Greene, 2016. "Persistent and transient productive inefficiency: a maximum simulated likelihood approach," Journal of Productivity Analysis, Springer, vol. 45(2), pages 187-196, April.
    6. Meng, Fanyi & Su, Bin & Thomson, Elspeth & Zhou, Dequn & Zhou, P., 2016. "Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey," Applied Energy, Elsevier, vol. 183(C), pages 1-21.
    7. Massimo Filippini & Lester C. Hunt, 2011. "Energy Demand and Energy Efficiency in the OECD Countries: A Stochastic Demand Frontier Approach," The Energy Journal, , vol. 32(2), pages 59-80, April.
    8. Su, Bin & Ang, B.W., 2017. "Multiplicative structural decomposition analysis of aggregate embodied energy and emission intensities," Energy Economics, Elsevier, vol. 65(C), pages 137-147.
    9. Du, Huibin & Matisoff, Daniel C. & Wang, Yangyang & Liu, Xi, 2016. "Understanding drivers of energy efficiency changes in China," Applied Energy, Elsevier, vol. 184(C), pages 1196-1206.
    10. Belotti, Federico & Ilardi, Giuseppe, 2018. "Consistent inference in fixed-effects stochastic frontier models," Journal of Econometrics, Elsevier, vol. 202(2), pages 161-177.
    11. 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.
    12. He, Yong & Liao, Nuo & Zhou, Ya, 2018. "Analysis on provincial industrial energy efficiency and its influencing factors in China based on DEA-RS-FANN," Energy, Elsevier, vol. 142(C), pages 79-89.
    13. Zeng, Lin & Xu, Ming & Liang, Sai & Zeng, Siyu & Zhang, Tianzhu, 2014. "Revisiting drivers of energy intensity in China during 1997–2007: A structural decomposition analysis," Energy Policy, Elsevier, vol. 67(C), pages 640-647.
    14. Xiaobo Shen & Boqiang Lin, 2017. "Total Factor Energy Efficiency of China’s Industrial Sector: A Stochastic Frontier Analysis," Sustainability, MDPI, vol. 9(4), pages 1-17, April.
    15. Manuel Llorca & Jose Banos & Somoza Jose & Pelayo Arbues, 2017. "A Stochastic Frontier Analysis Approach for Estimating Energy Demand and Efficiency in the Transport Sector of Latin America and the Caribbean," The Energy Journal, , vol. 38(5), pages 153-174, September.
    16. Wang, Qiang & Li, Rongrong, 2016. "Drivers for energy consumption: A comparative analysis of China and India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 954-962.
    17. Dayong Zhang & David C. Broadstock, 2016. "Club Convergence in the Energy Intensity of China," The Energy Journal, , vol. 37(3), pages 137-158, July.
    18. Fei, Rilong & Lin, Boqiang, 2016. "Energy efficiency and production technology heterogeneity in China's agricultural sector: A meta-frontier approach," Technological Forecasting and Social Change, Elsevier, vol. 109(C), pages 25-34.
    19. Chen, Yi-Yi & Schmidt, Peter & Wang, Hung-Jen, 2014. "Consistent estimation of the fixed effects stochastic frontier model," Journal of Econometrics, Elsevier, vol. 181(2), pages 65-76.
    20. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    21. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
    22. Wang, H. & Ang, B.W. & Wang, Q.W. & Zhou, P., 2017. "Measuring energy performance with sectoral heterogeneity: A non-parametric frontier approach," Energy Economics, Elsevier, vol. 62(C), pages 70-78.
    23. Lin, Boqiang & Wang, Xiaolei, 2014. "Exploring energy efficiency in China׳s iron and steel industry: A stochastic frontier approach," Energy Policy, Elsevier, vol. 72(C), pages 87-96.
    24. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    25. Adom, Philip Kofi, 2016. "The transition between energy efficient and energy inefficient states in Cameroon," Energy Economics, Elsevier, vol. 54(C), pages 248-262.
    26. Zhang, Jiangshan & Lin Lawell, C.-Y. Cynthia, 2017. "The macroeconomic rebound effect in China," Energy Economics, Elsevier, vol. 67(C), pages 202-212.
    27. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    28. Jie Wu & Beibei Xiong & Qingxian An & Jiasen Sun & Huaqing Wu, 2017. "Total-factor energy efficiency evaluation of Chinese industry by using two-stage DEA model with shared inputs," Annals of Operations Research, Springer, vol. 255(1), pages 257-276, August.
    29. Lin, Boqiang & Du, Kerui, 2014. "Measuring energy efficiency under heterogeneous technologies using a latent class stochastic frontier approach: An application to Chinese energy economy," Energy, Elsevier, vol. 76(C), pages 884-890.
    30. Deliang Pang & Hongwei Su, 2017. "Determinants of energy intensity in Chinese provinces," Energy & Environment, , vol. 28(4), pages 451-467, June.
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