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Does internet development improve green total factor energy efficiency? Evidence from China

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  • Wu, Haitao
  • Hao, Yu
  • Ren, Siyu
  • Yang, Xiaodong
  • Xie, Guo

Abstract

Information and communication technology supported by the internet has become an important driving force that promotes the intelligent development of environmental governance in China. Using Chinese provincial panel data for the period 2006–2017, this study investigates whether the internet has improved China's green total factor energy efficiency (GTFEE) using a dynamic spatial Durbin model, mediation effect model and dynamic threshold panel model. The empirical results indicate that the GTFEE has a significant positive spatial correlation. Internet development can not only directly improve local GTFEE but also improve GTFEE in neighboring regions. After accounting for potential endogeneity, this conclusion is still valid. Meanwhile, internet development can indirectly improve regional GTFEE by reducing the degree of resource mismatch while enhancing GTFEE by improving regional innovation capabilities and promoting industrial structure upgrades. In addition, the regression results of the dynamic threshold model show that there is a nonlinear relationship between the influence of the internet development and GTFEE. Specifically, due to an increase in the degree of labor resource mismatch and capital resource mismatch, the impact of the internet on GTFEE has gradually decreased, and this effect has gradually increased with the improvement of regional innovation capabilities and the industrial structure.

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  • Wu, Haitao & Hao, Yu & Ren, Siyu & Yang, Xiaodong & Xie, Guo, 2021. "Does internet development improve green total factor energy efficiency? Evidence from China," Energy Policy, Elsevier, vol. 153(C).
  • Handle: RePEc:eee:enepol:v:153:y:2021:i:c:s0301421521001166
    DOI: 10.1016/j.enpol.2021.112247
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    as
    1. Liu, Guangtian & Wang, Bing & Zhang, Ning, 2016. "A coin has two sides: Which one is driving China’s green TFP growth?," Economic Systems, Elsevier, vol. 40(3), pages 481-498.
    2. 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.
    3. Chang, Tzu-Pu & Hu, Jin-Li, 2010. "Total-factor energy productivity growth, technical progress, and efficiency change: An empirical study of China," Applied Energy, Elsevier, vol. 87(10), pages 3262-3270, October.
    4. Yoruk, BarIs K. & Zaim, Osman, 2005. "Productivity growth in OECD countries: A comparison with Malmquist indices," Journal of Comparative Economics, Elsevier, vol. 33(2), pages 401-420, June.
    5. Eliasson, Ludvik & Turnovsky, Stephen J., 2004. "Renewable resources in an endogenously growing economy: balanced growth and transitional dynamics," Journal of Environmental Economics and Management, Elsevier, vol. 48(3), pages 1018-1049, November.
    6. Yin, Jianhua & Zheng, Mingzheng & Chen, Jian, 2015. "The effects of environmental regulation and technical progress on CO2 Kuznets curve: An evidence from China," Energy Policy, Elsevier, vol. 77(C), pages 97-108.
    7. Melvyn Weeks & James Yudong Yao, 2003. "Provincial Conditional Income Convergence in China, 1953-1997: A Panel Data Approach," Econometric Reviews, Taylor & Francis Journals, vol. 22(1), pages 59-77, February.
    8. Hausman, Jerry A & Taylor, William E, 1981. "Panel Data and Unobservable Individual Effects," Econometrica, Econometric Society, vol. 49(6), pages 1377-1398, November.
    9. 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.
    10. Wang, Shuhong & Zhao, Danqing & Chen, Hanxue, 2020. "Government corruption, resource misallocation, and ecological efficiency," Energy Economics, Elsevier, vol. 85(C).
    11. Choi, Yongrok & Zhang, Ning & Zhou, P., 2012. "Efficiency and abatement costs of energy-related CO2 emissions in China: A slacks-based efficiency measure," Applied Energy, Elsevier, vol. 98(C), pages 198-208.
    12. Ligthart, Jenny E. & van der Ploeg, Frederick, 1994. "Pollution, the cost of public funds and endogenous growth," Economics Letters, Elsevier, vol. 46(4), pages 339-349, December.
    13. Lin, Boqiang & Zhu, Junpeng, 2019. "Impact of energy saving and emission reduction policy on urban sustainable development: Empirical evidence from China," Applied Energy, Elsevier, vol. 239(C), pages 12-22.
    14. Ronald Bernstein & Reinhard Madlener, 2010. "Impact of disaggregated ICT capital on electricity intensity in European manufacturing," Applied Economics Letters, Taylor & Francis Journals, vol. 17(17), pages 1691-1695.
    15. Dang, Jianwei & Motohashi, Kazuyuki, 2015. "Patent statistics: A good indicator for innovation in China? Patent subsidy program impacts on patent quality," China Economic Review, Elsevier, vol. 35(C), pages 137-155.
    16. Rolf Färe & Shawna Grosskopf & Carl A Pasurka, Jr., 2001. "Accounting for Air Pollution Emissions in Measures of State Manufacturing Productivity Growth," Journal of Regional Science, Wiley Blackwell, vol. 41(3), pages 381-409, August.
    17. Sadorsky, Perry, 2012. "Information communication technology and electricity consumption in emerging economies," Energy Policy, Elsevier, vol. 48(C), pages 130-136.
    18. Zhang, Shaohui & Worrell, Ernst & Crijns-Graus, Wina, 2015. "Evaluating co-benefits of energy efficiency and air pollution abatement in China’s cement industry," Applied Energy, Elsevier, vol. 147(C), pages 192-213.
    19. Xie, Bai-Chen & Shang, Li-Feng & Yang, Si-Bo & Yi, Bo-Wen, 2014. "Dynamic environmental efficiency evaluation of electric power industries: Evidence from OECD (Organization for Economic Cooperation and Development) and BRIC (Brazil, Russia, India and China) countrie," Energy, Elsevier, vol. 74(C), pages 147-157.
    20. Zhou, P. & Ang, B.W., 2008. "Decomposition of aggregate CO2 emissions: A production-theoretical approach," Energy Economics, Elsevier, vol. 30(3), pages 1054-1067, May.
    21. Watanabe, Michio & Tanaka, Katsuya, 2007. "Efficiency analysis of Chinese industry: A directional distance function approach," Energy Policy, Elsevier, vol. 35(12), pages 6323-6331, December.
    22. Elena Ketteni & Theofanis Mamuneas & Panos Pashardes, 2013. "ICT and Energy Use: Patterns of Substitutability and Complementarity in Production," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 7(1), pages 63-86, June.
    23. Bastida, Leire & Cohen, Jed J. & Kollmann, Andrea & Moya, Ana & Reichl, Johannes, 2019. "Exploring the role of ICT on household behavioural energy efficiency to mitigate global warming," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 455-462.
    24. Andrey I. Vlasov & Vadim A. Shakhnov & Sergey S. Filin & Sergey S. Filin & Aleksey I. Krivoshein & Aleksey I. Krivoshein, 2019. "Sustainable energy systems in the digital economy: concept of smart machines," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 6(4), pages 1975-1986, June.
    25. Honma, Satoshi & Hu, Jin-Li, 2008. "Total-factor energy efficiency of regions in Japan," Energy Policy, Elsevier, vol. 36(2), pages 821-833, February.
    26. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, February.
    27. Wilson, Bruce & Trieu, Luan Ho & Bowen, Bruce, 1994. "Energy efficiency trends in Australia," Energy Policy, Elsevier, vol. 22(4), pages 287-295, April.
    28. Michael T. French & Ioana Popovici, 2011. "That instrument is lousy! In search of agreement when using instrumental variables estimation in substance use research," Health Economics, John Wiley & Sons, Ltd., vol. 20(2), pages 127-146, February.
    29. Botang Han & Dong Wang & Weina Ding & Lei Han, 2016. "Effect of information and communication technology on energy consumption in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(1), pages 297-315, November.
    30. 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.
    31. Peter Kuhn & Mikal Skuterud, 2004. "Internet Job Search and Unemployment Durations," American Economic Review, American Economic Association, vol. 94(1), pages 218-232, March.
    32. 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).
    33. Kais Saidi & Hassen Toumi & Saida Zaidi, 2017. "Impact of Information Communication Technology and Economic Growth on the Electricity Consumption: Empirical Evidence from 67 Countries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 8(3), pages 789-803, September.
    34. 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.
    35. Choi, Changkyu & Hoon Yi, Myung, 2009. "The effect of the Internet on economic growth: Evidence from cross-country panel data," Economics Letters, Elsevier, vol. 105(1), pages 39-41, October.
    36. Chen, Yueh H. & Lin, Winston T., 2009. "Analyzing the relationships between information technology, inputs substitution and national characteristics based on CES stochastic frontier production models," International Journal of Production Economics, Elsevier, vol. 120(2), pages 552-569, August.
    37. Zhang, Zibin & Ye, Jianliang, 2015. "Decomposition of environmental total factor productivity growth using hyperbolic distance functions: A panel data analysis for China," Energy Economics, Elsevier, vol. 47(C), pages 87-97.
    38. Patterson, Murray G, 1996. "What is energy efficiency? : Concepts, indicators and methodological issues," Energy Policy, Elsevier, vol. 24(5), pages 377-390, May.
    39. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    40. Lange, Steffen & Pohl, Johanna & Santarius, Tilman, 2020. "Digitalization and energy consumption. Does ICT reduce energy demand?," Ecological Economics, Elsevier, vol. 176(C).
    41. Betsey Stevenson, 2009. "The Internet and Job Search," NBER Chapters, in: Studies of Labor Market Intermediation, pages 67-86, National Bureau of Economic Research, Inc.
    42. Moyer, Jonathan D. & Hughes, Barry B., 2012. "ICTs: Do they contribute to increased carbon emissions?," Technological Forecasting and Social Change, Elsevier, vol. 79(5), pages 919-931.
    43. Wang, Zhaohua & Feng, Chao, 2015. "A performance evaluation of the energy, environmental, and economic efficiency and productivity in China: An application of global data envelopment analysis," Applied Energy, Elsevier, vol. 147(C), pages 617-626.
    44. Li, Jianglong & Lin, Boqiang, 2017. "Ecological total-factor energy efficiency of China's heavy and light industries: Which performs better?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 83-94.
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