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Differentiated effects of diversified technological sources on energy-saving technological progress: Empirical evidence from China's industrial sectors

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  • Yang, Zhenbing
  • Shao, Shuai
  • Yang, Lili
  • Liu, Jianghua

Abstract

Although it has been a consensus that the promotion of energy-saving technology plays a vital role in impelling the green transformation of economic development, the existing studies pay little attention to whether diversified technological sources present differentiated effects on energy-saving technological progress. Using the stochastic frontier analysis (SFA) based on the translog production function, this paper estimates and compares the energy-saving technological progress rates of various industrial sub-sectors in China over 2001–2011. Furthermore, using the system generalized method of moments (SGMM), which is able to effectively control the endogeneity problem, we investigate the differentiated effects of six basic technological sources on energy-saving technological progress. The results show that although there are evident differences of energy-saving technological progress rates among different industrial sub-sectors, China's industrial energy-saving technological progress presents an overall improved trend. Among six primary technological sources, only the forward technological spillover effect of foreign direct investment (FDI) and the forced effect of competition have a significant positive impact on energy-saving technological progress, while the influences of backward and horizontal technology spillovers, original innovation, and leaning by exporting are all not significant. Moreover, industrial energy-saving technological progress shows an obvious path dependence property, i.e., the previous high-level energy-saving technological progress has an evident positive impact on the current one. Accordingly, we propose that the Chinese government should encourage domestic industrial enterprises to learn and absorb advanced energy-saving technologies from foreign investment enterprises and by exporting products with more advanced technology content and added value.

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  • Yang, Zhenbing & Shao, Shuai & Yang, Lili & Liu, Jianghua, 2017. "Differentiated effects of diversified technological sources on energy-saving technological progress: Empirical evidence from China's industrial sectors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1379-1388.
  • Handle: RePEc:eee:rensus:v:72:y:2017:i:c:p:1379-1388
    DOI: 10.1016/j.rser.2016.11.072
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    as
    1. Wen, Zongguo & Chen, Min & Meng, Fanxin, 2015. "Evaluation of energy saving potential in China's cement industry using the Asian-Pacific Integrated Model and the technology promotion policy analysis," Energy Policy, Elsevier, vol. 77(C), pages 227-237.
    2. Sofronis K. Clerides & Saul Lach & James R. Tybout, 1998. "Is Learning by Exporting Important? Micro-Dynamic Evidence from Colombia, Mexico, and Morocco," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(3), pages 903-947.
    3. Wang, Zhao-Hua & Zeng, Hua-Lin & Wei, Yi-Ming & Zhang, Yi-Xiang, 2012. "Regional total factor energy efficiency: An empirical analysis of industrial sector in China," Applied Energy, Elsevier, vol. 97(C), pages 115-123.
    4. Shao, Shuai & Huang, Tao & Yang, Lili, 2014. "Using latent variable approach to estimate China׳s economy-wide energy rebound effect over 1954–2010," Energy Policy, Elsevier, vol. 72(C), pages 235-248.
    5. Urpelainen, Johannes, 2011. "Export orientation and domestic electricity generation: Effects on energy efficiency innovation in select sectors," Energy Policy, Elsevier, vol. 39(9), pages 5638-5646, September.
    6. Muhammad Shahbaz & Samia Nasreen & Chong Hui Ling & Rashid Sbia, 2014. "Causality between Trade Openness and Energy Consumption- What Causes What in High, Middle and Low Income Countries," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 53(4), pages 423-459.
    7. M. Murty & Surender Kumar & Kishore Dhavala, 2007. "Measuring environmental efficiency of industry: a case study of thermal power generation in India," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 38(1), pages 31-50, September.
    8. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    9. Philippe Aghion & Christopher Harris & Peter Howitt & John Vickers, 2001. "Competition, Imitation and Growth with Step-by-Step Innovation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 68(3), pages 467-492.
    10. 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.
    11. Li, Yuan & Zhu, Lei, 2014. "Cost of energy saving and CO2 emissions reduction in China’s iron and steel sector," Applied Energy, Elsevier, vol. 130(C), pages 603-616.
    12. Beata Smarzynska Javorcik, 2004. "Does Foreign Direct Investment Increase the Productivity of Domestic Firms? In Search of Spillovers Through Backward Linkages," American Economic Review, American Economic Association, vol. 94(3), pages 605-627, June.
    13. Shao, Shuai & Yang, Lili & Yu, Mingbo & Yu, Mingliang, 2011. "Estimation, characteristics, and determinants of energy-related industrial CO2 emissions in Shanghai (China), 1994-2009," Energy Policy, Elsevier, vol. 39(10), pages 6476-6494, October.
    14. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    15. Özkara, Yücel & Atak, Mehmet, 2015. "Regional total-factor energy efficiency and electricity saving potential of manufacturing industry in Turkey," Energy, Elsevier, vol. 93(P1), pages 495-510.
    16. Bointner, Raphael, 2014. "Innovation in the energy sector: Lessons learnt from R&D expenditures and patents in selected IEA countries," Energy Policy, Elsevier, vol. 73(C), pages 733-747.
    17. Subal Kumbhakar & M. Denny & M. Fuss, 2000. "Estimation and decomposition of productivity change when production is not efficient: a paneldata approach," Econometric Reviews, Taylor & Francis Journals, vol. 19(4), pages 312-320.
    18. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    19. Mary Amiti & Caroline Freund, 2010. "The Anatomy of China's Export Growth," NBER Chapters, in: China's Growing Role in World Trade, pages 35-56, National Bureau of Economic Research, Inc.
    20. Eskeland, Gunnar S. & Harrison, Ann E., 2003. "Moving to greener pastures? Multinationals and the pollution haven hypothesis," Journal of Development Economics, Elsevier, vol. 70(1), pages 1-23, February.
    21. Cappelli, Riccardo & Czarnitzki, Dirk & Kraft, Kornelius, 2014. "Sources of spillovers for imitation and innovation," Research Policy, Elsevier, vol. 43(1), pages 115-120.
    22. Chen, Shiyi & Santos-Paulino, Amelia U., 2013. "Energy consumption restricted productivity re-estimates and industrial sustainability analysis in post-reform China," Energy Policy, Elsevier, vol. 57(C), pages 52-60.
    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. Herrala, Risto & Goel, Rajeev K., 2012. "Global CO2 efficiency: Country-wise estimates using a stochastic cost frontier," Energy Policy, Elsevier, vol. 45(C), pages 762-770.
    25. Honma, Satoshi & Hu, Jin-Li, 2014. "Industry-level total-factor energy efficiency in developed countries: A Japan-centered analysis," Applied Energy, Elsevier, vol. 119(C), pages 67-78.
    26. Zhang, Xing-Ping & Cheng, Xiao-Mei & Yuan, Jia-Hai & Gao, Xiao-Jun, 2011. "Total-factor energy efficiency in developing countries," Energy Policy, Elsevier, vol. 39(2), pages 644-650, February.
    27. Wang, Q.W. & Zhou, P. & Shen, N. & Wang, S.S., 2013. "Measuring carbon dioxide emission performance in Chinese provinces: A parametric approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 324-330.
    28. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    29. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    30. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
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