IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v90y2020ics0140988320301766.html
   My bibliography  Save this article

Effects of diversified openness channels on the total-factor energy efficiency in China's manufacturing sub-sectors: Evidence from trade and FDI spillovers

Author

Listed:
  • Wei, Zixiang
  • Han, Botang
  • Pan, Xiuzhen
  • Shahbaz, Muhammad
  • Zafar, Muhammad Wasif

Abstract

Unparalleled, wide-spread, innovative, even intrusive are all words regularly used to describe the tremendous growth that has seen China has a well-established manufacturing system. It happened so quickly that it is often easy to lose sight of the factors that led to this success and, moreover, the costs that may have been paid by the environment. The burgeoning “Made in China 2025” strategy is firmly based on the premise of modernizing manufacturing and becoming a mode for environmentally-friendly practice. But these are goals that cannot reasonably be separated from the need to improve total factor energy efficiency (TFEE) across the manufacturing. Therefore, we investigated the impact of foreign direct investment (FDI) and trade on the TFEE of China's manufacturing at the sub-sector level. Specifically, we assessed capital stocks with a heterogeneous non-fixed depreciation method and used multi stochastic frontier analysis (SFA) models with linear-form inefficient variables to measure credited TFEE in 26 sectors of manufacturing from 2000 to 2016. To deepen our analysis, we also conducted an overall and period-by-period analysis with a modified STRIPAT model and feasible generalized least squares (FGLS) estimation. Our analysis shows an average TFEE of 0.7471 for China's manufacturing, but with several significant differences between the 26 sectors. Trade and FDI spillovers showed an overall increase across the period, with the highest export elasticity at 0.0607%. High-tech industries were generally quite efficient, while the elasticity coefficient of 0.0276% shows that increasing imports is an effective method of improving TFEE for energy-intensive sub-sectors. The regression analysis by periods reveals that the positive effect of imports gradually improved over time but, of the three FDI spillover effects modeled, only backward spillovers had a positive impact.

Suggested Citation

  • Wei, Zixiang & Han, Botang & Pan, Xiuzhen & Shahbaz, Muhammad & Zafar, Muhammad Wasif, 2020. "Effects of diversified openness channels on the total-factor energy efficiency in China's manufacturing sub-sectors: Evidence from trade and FDI spillovers," Energy Economics, Elsevier, vol. 90(C).
  • Handle: RePEc:eee:eneeco:v:90:y:2020:i:c:s0140988320301766
    DOI: 10.1016/j.eneco.2020.104836
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988320301766
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2020.104836?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Shahbaz, Muhammad & Khan, Saleheen & Tahir, Mohammad Iqbal, 2013. "The dynamic links between energy consumption, economic growth, financial development and trade in China: Fresh evidence from multivariate framework analysis," Energy Economics, Elsevier, vol. 40(C), pages 8-21.
    2. Solarin, Sakiru Adebola & Shahbaz, Muhammad & Hammoudeh, Shawkat, 2019. "Sustainable economic development in China: Modelling the role of hydroelectricity consumption in a multivariate framework," Energy, Elsevier, vol. 168(C), pages 516-531.
    3. Jalil, Abdul & Feridun, Mete, 2011. "The impact of growth, energy and financial development on the environment in China: A cointegration analysis," Energy Economics, Elsevier, vol. 33(2), pages 284-291, March.
    4. Salim, Ruhul & Yao, Yao & Chen, George & Zhang, Lin, 2017. "Can foreign direct investment harness energy consumption in China? A time series investigation," Energy Economics, Elsevier, vol. 66(C), pages 43-53.
    5. W.H. Griffith, 2006. "Does Foreign Direct Investment Promote Development?," Journal of Economic Issues, Taylor & Francis Journals, vol. 40(4), pages 1174-1176, December.
    6. Wilfred J. Ethier & James R. Markusen, 2021. "Multinational firms, technology diffusion and trade," World Scientific Book Chapters, in: BROADENING TRADE THEORY Incorporating Market Realities into Traditional Models, chapter 7, pages 131-158, World Scientific Publishing Co. Pte. Ltd..
    7. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    8. Backlund, Sandra & Thollander, Patrik & Palm, Jenny & Ottosson, Mikael, 2012. "Extending the energy efficiency gap," Energy Policy, Elsevier, vol. 51(C), pages 392-396.
    9. Liu, Kui & Bai, Hongkun & Yin, Shuo & Lin, Boqiang, 2018. "Factor substitution and decomposition of carbon intensity in China's heavy industry," Energy, Elsevier, vol. 145(C), pages 582-591.
    10. Tuan, Chyau & Ng, Linda F. Y., 2004. "Manufacturing agglomeration as incentives to Asian FDI in China after WTO," Journal of Asian Economics, Elsevier, vol. 15(4), pages 673-693, August.
    11. Gale A. Boyd, 2008. "Estimating Plant Level Energy Efficiency with a Stochastic Frontier," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 23-44.
    12. Pedro Martins & Yong Yang, 2009. "The impact of exporting on firm productivity: a meta-analysis of the learning-by-exporting hypothesis," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 145(3), pages 431-445, October.
    13. Porzio, Giacomo Filippo & Fornai, Barbara & Amato, Alessandro & Matarese, Nicola & Vannucci, Marco & Chiappelli, Lisa & Colla, Valentina, 2013. "Reducing the energy consumption and CO2 emissions of energy intensive industries through decision support systems – An example of application to the steel industry," Applied Energy, Elsevier, vol. 112(C), pages 818-833.
    14. Li, Fangyi & Song, Zhouying & Liu, Weidong, 2014. "China's energy consumption under the global economic crisis: Decomposition and sectoral analysis," Energy Policy, Elsevier, vol. 64(C), pages 193-202.
    15. Elliott, Robert J.R. & Sun, Puyang & Chen, Siyang, 2013. "Energy intensity and foreign direct investment: A Chinese city-level study," Energy Economics, Elsevier, vol. 40(C), pages 484-494.
    16. Sharif Hossain, Md., 2011. "Panel estimation for CO2 emissions, energy consumption, economic growth, trade openness and urbanization of newly industrialized countries," Energy Policy, Elsevier, vol. 39(11), pages 6991-6999.
    17. Bu, Maoliang & Li, Shuang & Jiang, Lei, 2019. "Foreign direct investment and energy intensity in China: Firm-level evidence," Energy Economics, Elsevier, vol. 80(C), pages 366-376.
    18. Balsalobre-Lorente, Daniel & Shahbaz, Muhammad & Roubaud, David & Farhani, Sahbi, 2018. "How economic growth, renewable electricity and natural resources contribute to CO2 emissions?," Energy Policy, Elsevier, vol. 113(C), pages 356-367.
    19. 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.
    20. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    21. Aydin, Celil & Esen, Ömer, 2018. "Does the level of energy intensity matter in the effect of energy consumption on the growth of transition economies? Evidence from dynamic panel threshold analysis," Energy Economics, Elsevier, vol. 69(C), pages 185-195.
    22. Chan, David Yih-Liang & Yang, Kuang-Han & Hsu, Chung-Hsuan & Chien, Min-Hsien & Hong, Gui-Bing, 2007. "Current situation of energy conservation in high energy-consuming industries in Taiwan," Energy Policy, Elsevier, vol. 35(1), pages 202-209, January.
    23. Shahbaz, Muhammad & Hye, Qazi Muhammad Adnan & Tiwari, Aviral Kumar & Leitão, Nuno Carlos, 2013. "Economic growth, energy consumption, financial development, international trade and CO2 emissions in Indonesia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 109-121.
    24. 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.
    25. Zheng, Yingmei & Qi, Jianhong & Chen, Xiaoliang, 2011. "The effect of increasing exports on industrial energy intensity in China," Energy Policy, Elsevier, vol. 39(5), pages 2688-2698, May.
    26. Bernard, Andrew B. & Bradford Jensen, J., 1999. "Exceptional exporter performance: cause, effect, or both?," Journal of International Economics, Elsevier, vol. 47(1), pages 1-25, February.
    27. Julie Le Gallo & Sandy Dall'erba, 2008. "Spatial and sectoral productivity convergence between European regions, 1975–2000," Papers in Regional Science, Wiley Blackwell, vol. 87(4), pages 505-525, November.
    28. Wang, Keying & Wu, Meng & Sun, Yongping & Shi, Xunpeng & Sun, Ao & Zhang, Ping, 2019. "Resource abundance, industrial structure, and regional carbon emissions efficiency in China," Resources Policy, Elsevier, vol. 60(C), pages 203-214.
    29. Xie, Chunping & Bai, Mengqi & Wang, Xiaolei, 2018. "Accessing provincial energy efficiencies in China’s transport sector," Energy Policy, Elsevier, vol. 123(C), pages 525-532.
    30. Hang, Leiming & Tu, Meizeng, 2007. "The impacts of energy prices on energy intensity: Evidence from China," Energy Policy, Elsevier, vol. 35(5), pages 2978-2988, May.
    31. Lin, Boqiang & Sun, Chuanwang, 2010. "Evaluating carbon dioxide emissions in international trade of China," Energy Policy, Elsevier, vol. 38(1), pages 613-621, January.
    32. 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.
    33. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-286, July.
    34. 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.
    35. 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.
    36. Lin, Boqiang & Yang, Lisha, 2013. "The potential estimation and factor analysis of China′s energy conservation on thermal power industry," Energy Policy, Elsevier, vol. 62(C), pages 354-362.
    37. Yu, Huayi, 2012. "The influential factors of China's regional energy intensity and its spatial linkages: 1988–2007," Energy Policy, Elsevier, vol. 45(C), pages 583-593.
    38. Mary Amiti & Stephen J. Redding & David E. Weinstein, 2019. "The impact of the 2018 trade war on US prices and welfare," CentrePiece - The magazine for economic performance 553, Centre for Economic Performance, LSE.
    39. 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.
    40. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    41. 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.
    42. Pao, Hsiao-Tien & Tsai, Chung-Ming, 2010. "CO2 emissions, energy consumption and economic growth in BRIC countries," Energy Policy, Elsevier, vol. 38(12), pages 7850-7860, December.
    43. Stern, David I., 2012. "Modeling international trends in energy efficiency," Energy Economics, Elsevier, vol. 34(6), pages 2200-2208.
    44. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    45. Zheng, Wei & Walsh, Patrick Paul, 2019. "Economic growth, urbanization and energy consumption — A provincial level analysis of China," Energy Economics, Elsevier, vol. 80(C), pages 153-162.
    46. Haoran Zhao & Sen Guo & Huiru Zhao, 2018. "Characterizing the Influences of Economic Development, Energy Consumption, Urbanization, Industrialization, and Vehicles Amount on PM 2.5 Concentrations of China," Sustainability, MDPI, vol. 10(7), pages 1-19, July.
    47. 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.
    48. Federico Belotti & Silvio Daidone & Giuseppe Ilardi & Vincenzo Atella, 2013. "Stochastic frontier analysis using Stata," Stata Journal, StataCorp LP, vol. 13(4), pages 718-758, December.
    49. Wang, Zhaohua & Feng, Chao & Zhang, Bin, 2014. "An empirical analysis of China's energy efficiency from both static and dynamic perspectives," Energy, Elsevier, vol. 74(C), pages 322-330.
    50. Zhao, Haoran & Guo, Sen & Zhao, Huiru, 2019. "Provincial energy efficiency of China quantified by three-stage data envelopment analysis," Energy, Elsevier, vol. 166(C), pages 96-107.
    51. Wang, Shaojian & Fang, Chuanglin & Guan, Xingliang & Pang, Bo & Ma, Haitao, 2014. "Urbanisation, energy consumption, and carbon dioxide emissions in China: A panel data analysis of China’s provinces," Applied Energy, Elsevier, vol. 136(C), pages 738-749.
    52. Cappelli, Riccardo & Czarnitzki, Dirk & Kraft, Kornelius, 2014. "Sources of spillovers for imitation and innovation," Research Policy, Elsevier, vol. 43(1), pages 115-120.
    53. 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.
    54. Liu, Hongtao & Xi, Youmin & Guo, Ju'e & Li, Xia, 2010. "Energy embodied in the international trade of China: An energy input-output analysis," Energy Policy, Elsevier, vol. 38(8), pages 3957-3964, August.
    55. Wilson, Bruce & Trieu, Luan Ho & Bowen, Bruce, 1994. "Energy efficiency trends in Australia," Energy Policy, Elsevier, vol. 22(4), pages 287-295, April.
    56. Enevoldsen, Martin K. & Ryelund, Anders V. & Andersen, Mikael Skou, 2007. "Decoupling of industrial energy consumption and CO2-emissions in energy-intensive industries in Scandinavia," Energy Economics, Elsevier, vol. 29(4), pages 665-692, July.
    57. Marco Alfo & Giovanni Trovato & Robert J. Waldmann, 2008. "Testing for country heterogeneity in growth models using a finite mixture approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(4), pages 487-514.
    58. Ren, Shenggang & Yuan, Baolong & Ma, Xie & Chen, Xiaohong, 2014. "International trade, FDI (foreign direct investment) and embodied CO2 emissions: A case study of Chinas industrial sectors," China Economic Review, Elsevier, vol. 28(C), pages 123-134.
    59. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    60. Shi, Guang-Ming & Bi, Jun & Wang, Jin-Nan, 2010. "Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs," Energy Policy, Elsevier, vol. 38(10), pages 6172-6179, October.
    61. Reinhard, Stijn & Knox Lovell, C. A. & Thijssen, Geert J., 2000. "Environmental efficiency with multiple environmentally detrimental variables; estimated with SFA and DEA," European Journal of Operational Research, Elsevier, vol. 121(2), pages 287-303, March.
    62. Du, Kerui & Lin, Boqiang, 2017. "International comparison of total-factor energy productivity growth: A parametric Malmquist index approach," Energy, Elsevier, vol. 118(C), pages 481-488.
    63. Yang, Shenglang & Shi, Xunpeng, 2018. "Intangible capital and sectoral energy intensity: Evidence from 40 economies between 1995 and 2007," Energy Policy, Elsevier, vol. 122(C), pages 118-128.
    64. Liu, Wei & Li, Hong, 2011. "Improving energy consumption structure: A comprehensive assessment of fossil energy subsidies reform in China," Energy Policy, Elsevier, vol. 39(7), pages 4134-4143, July.
    65. Muhammad Shahbaz & Saleheen Khan & Amjad Ali & Mita Bhattacharya, 2017. "The Impact Of Globalization On Co2 Emissions In China," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 62(04), pages 929-957, September.
    66. Feng, Taiwen & Sun, Linyan & Zhang, Ying, 2009. "The relationship between energy consumption structure, economic structure and energy intensity in China," Energy Policy, Elsevier, vol. 37(12), pages 5475-5483, December.
    67. Xiaoli, Zhao & Rui, Yang & Qian, Ma, 2014. "China's total factor energy efficiency of provincial industrial sectors," Energy, Elsevier, vol. 65(C), pages 52-61.
    68. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Jusoh, Ahmad & Khoshnoudi, Masoumeh, 2017. "A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1298-1322.
    69. Min-Ren Yan & Kuo-Ming Chien, 2013. "Evaluating the Economic Performance of High-Technology Industry and Energy Efficiency: A Case Study of Science Parks in Taiwan," Energies, MDPI, vol. 6(2), pages 1-15, February.
    70. 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.
    71. Pao, Hsiao-Tien & Tsai, Chung-Ming, 2011. "Multivariate Granger causality between CO2 emissions, energy consumption, FDI (foreign direct investment) and GDP (gross domestic product): Evidence from a panel of BRIC (Brazil, Russian Federation, I," Energy, Elsevier, vol. 36(1), pages 685-693.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yang Liu & Ruochan Xiong & Shigong Lv & Da Gao, 2022. "The Impact of Digital Finance on Green Total Factor Energy Efficiency: Evidence at China’s City Level," Energies, MDPI, vol. 15(15), pages 1-17, July.
    2. Ya Wu & Yin Liu & Minglong Zhang, 2023. "How Does Digital Finance Affect Energy Efficiency?—Characteristics, Mechanisms, and Spatial Effects," Sustainability, MDPI, vol. 15(9), pages 1-24, April.
    3. Yang, Zhenbing & Shi, Qingquan & Lv, Xiangqiu & Shi, Qi, 2022. "Heterogeneous low-carbon targets and energy structure optimization: Does stricter carbon regulation really matter?," Structural Change and Economic Dynamics, Elsevier, vol. 60(C), pages 329-343.
    4. Shihong Zeng & Ya Zhou, 2021. "Foreign Direct Investment’s Impact on China’s Economic Growth, Technological Innovation and Pollution," IJERPH, MDPI, vol. 18(6), pages 1-24, March.
    5. Kassouri, Yacouba, 2022. "Fiscal decentralization and public budgets for energy RD&D: A race to the bottom?," Energy Policy, Elsevier, vol. 161(C).
    6. Abudureheman, Maliyamu & Jiang, Qingzhe & Dong, Xiucheng & Dong, Cong, 2022. "Spatial effects of dynamic comprehensive energy efficiency on CO2 reduction in China," Energy Policy, Elsevier, vol. 166(C).
    7. Liangjun Yi & Wei Zhang & Yuanxin Liu & Weilin Zhang, 2021. "An Analysis of the Impact of Market Segmentation on Energy Efficiency: A Spatial Econometric Model Applied in China," Sustainability, MDPI, vol. 13(14), pages 1-23, July.
    8. 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).
    9. Zheng, Wei, 2021. "Effects of China’s market-oriented economic reform, FDI inflows on electricity intensity," Energy, Elsevier, vol. 220(C).
    10. Tan, Ruipeng & Xu, Mengmeng & Qiao, Gang & Wu, Huaqing, 2023. "FDI, financial market development and nonlinearities of energy and environmental efficiency in China: Evidence from both parametric and nonparametric models," Energy Economics, Elsevier, vol. 119(C).
    11. Jianxu Liu & Heng Wang & Sanzidur Rahman & Songsak Sriboonchitta, 2021. "Energy Efficiency, Energy Conservation and Determinants in the Agricultural Sector in Emerging Economies," Agriculture, MDPI, vol. 11(8), pages 1-18, August.
    12. Li, Hongbing & Zheng, Qingbiao & Zhang, Bingbing & Sun, Chuanwang, 2021. "Trade policy uncertainty and improvement in energy efficiency: Empirical evidence from prefecture-level cities in China," Energy Economics, Elsevier, vol. 104(C).
    13. Quito, Byron & del Río-Rama, María de la Cruz & Álvarez- García, José & Bekun, Festus Victor, 2023. "Spatiotemporal influencing factors of energy efficiency in 43 european countries: A spatial econometric analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    14. Zhou, Anhua & Li, Jun, 2021. "Investigate the impact of market reforms on the improvement of manufacturing energy efficiency under China’s provincial-level data," Energy, Elsevier, vol. 228(C).
    15. Tao Ma & Xiaoxi Cao, 2022. "FDI, technological progress, and green total factor energy productivity: evidence from 281 prefecture cities in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(9), pages 11058-11088, September.
    16. Yan Wu & Cong Hu & Xunpeng Shi, 2021. "Heterogeneous Effects of the Belt and Road Initiative on Energy Efficiency in Participating Countries," Energies, MDPI, vol. 14(18), pages 1-21, September.
    17. Maliyamu Abudureheman & Qingzhe Jiang & Jiong Gong & Abulaiti Yiming, 2023. "Estimating and Decomposing the TFP Growth of Service-Oriented Manufacturing in China: A Translogarithmic Stochastic Frontier Approach," Sustainability, MDPI, vol. 15(7), pages 1-20, March.
    18. Gao, Kang & Yuan, Yijun, 2022. "Spatiotemporal pattern assessment of China’s industrial green productivity and its spatial drivers: Evidence from city-level data over 2000–2017," Applied Energy, Elsevier, vol. 307(C).
    19. Lin, Boqiang & Sai, Rockson, 2022. "Has mining agglomeration affected energy productivity in Africa?," Energy, Elsevier, vol. 244(PA).
    20. Huang, Hongyun & Mbanyele, William & Fan, Shuangshuang & Zhao, Xin, 2022. "Digital financial inclusion and energy-environment performance: What can learn from China," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 342-366.
    21. Xing, Menglin & Liu, Xiaojun & Luo, Fuzhou, 2023. "How does the development of urban agglomeration affect the electricity efficiency of resource-based cities?—An empirical research based on the fsQCA method," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    22. Yang, Zhenbing & Shao, Shuai & Xu, Lili & Yang, Lili, 2022. "Can regional development plans promote economic growth? City-level evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    23. Peng, Hua-Rong & Tan, Xiujie & Managi, Shunsuke & Taghizadeh-Hesary, Farhad, 2022. "Club convergence in energy efficiency of Belt and Road Initiative countries: The role of China’s outward foreign direct investment," Energy Policy, Elsevier, vol. 168(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Du, Minzhe & Wang, Bing & Zhang, Ning, 2018. "National research funding and energy efficiency: Evidence from the National Science Foundation of China," Energy Policy, Elsevier, vol. 120(C), pages 335-346.
    2. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2020. "Effects of urbanization on energy efficiency in China: New evidence from short run and long run efficiency models," Energy Policy, Elsevier, vol. 147(C).
    3. Akihiro Otsuka, 2020. "How do population agglomeration and interregional networks improve energy efficiency?," Asia-Pacific Journal of Regional Science, Springer, vol. 4(1), pages 1-25, February.
    4. Sun, Huaping & Edziah, Bless Kofi & Kporsu, Anthony Kwaku & Sarkodie, Samuel Asumadu & Taghizadeh-Hesary, Farhad, 2021. "Energy efficiency: The role of technological innovation and knowledge spillover," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    5. Lei Jiang & Henk Folmer & Minhe Ji & Jianjun Tang, 2017. "Energy efficiency in the Chinese provinces: a fixed effects stochastic frontier spatial Durbin error panel analysis," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 58(2), pages 301-319, March.
    6. Yan, Huijie, 2015. "Provincial energy intensity in China: The role of urbanization," Energy Policy, Elsevier, vol. 86(C), pages 635-650.
    7. Amjadi, Golnaz & Lundgren, Tommy, 2022. "Is industrial energy inefficiency transient or persistent? Evidence from Swedish manufacturing," Applied Energy, Elsevier, vol. 309(C).
    8. Ouyang, Xiaoling & Chen, Jiaqi & Du, Kerui, 2021. "Energy efficiency performance of the industrial sector: From the perspective of technological gap in different regions in China," Energy, Elsevier, vol. 214(C).
    9. Yu, Dejian & He, Xiaorong, 2020. "A bibliometric study for DEA applied to energy efficiency: Trends and future challenges," Applied Energy, Elsevier, vol. 268(C).
    10. 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.
    11. Daniel Balsalobre‐Lorente & Oana M. Driha & George Halkos & Shekhar Mishra, 2022. "Influence of growth and urbanization on CO2 emissions: The moderating effect of foreign direct investment on energy use in BRICS," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(1), pages 227-240, February.
    12. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Yan, Ming-Zhe & Wang, Jian-Lin & Xie, Bai-Chen, 2019. "Which provincial administrative regions in China should reduce their coal consumption? An environmental energy input requirement function based analysis," Energy Policy, Elsevier, vol. 127(C), pages 51-63.
    13. Liu, Fengqin & Sim, Jae-yeon & Sun, Huaping & Edziah, Bless Kofi & Adom, Philip Kofi & Song, Shunfeng, 2023. "Assessing the role of economic globalization on energy efficiency: Evidence from a global perspective," China Economic Review, Elsevier, vol. 77(C).
    14. Sun, Huaping & Edziah, Bless Kofi & Sun, Chuanwang & Kporsu, Anthony Kwaku, 2019. "Institutional quality, green innovation and energy efficiency," Energy Policy, Elsevier, vol. 135(C).
    15. Victor Moutinho & Mara Madaleno, 2021. "Assessing Eco-Efficiency in Asian and African Countries Using Stochastic Frontier Analysis," Energies, MDPI, vol. 14(4), pages 1-17, February.
    16. Ren, Shenggang & Yuan, Baolong & Ma, Xie & Chen, Xiaohong, 2014. "The impact of international trade on China׳s industrial carbon emissions since its entry into WTO," Energy Policy, Elsevier, vol. 69(C), pages 624-634.
    17. Akihiro Otsuka, 2018. "Regional Determinants of Energy Efficiency: Residential Energy Demand in Japan," Energies, MDPI, vol. 11(6), pages 1-14, June.
    18. Tiba, Sofien & Omri, Anis, 2017. "Literature survey on the relationships between energy, environment and economic growth," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1129-1146.
    19. Giovanni Marin & Alessandro Palma, 2015. "Technology invention and diffusion in residential energy consumption. A stochastic frontier approach," IEFE Working Papers 81, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    20. Sun, Huaping & Edziah, Bless Kofi & Sun, Chuanwang & Kporsu, Anthony Kwaku, 2022. "Institutional quality and its spatial spillover effects on energy efficiency," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:90:y:2020:i:c:s0140988320301766. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.