IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i16p4068-d395290.html
   My bibliography  Save this article

Energy Price and Energy Efficiency in China: A Linear and Nonlinear Empirical Investigation

Author

Listed:
  • Peng Hou

    (School of Economics and Management, Beijing Forestry University, Beijing 100083, China)

  • Yilin Li

    (School of Economics and Management, Beijing Forestry University, Beijing 100083, China)

  • Yong Tan

    (Department of Accounting, Finance and Economics, Huddersfield Business School, University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK)

  • Yuanjie Hou

    (School of Economics and Management, Beijing Forestry University, Beijing 100083, China)

Abstract

The empirical conclusions regarding the relationship between energy price and energy efficiency are relatively mixed. This paper systematically examines the influence of energy price on energy efficiency in China based on data from 30 provinces between 2003 and 2017, using linear and nonlinear effect analysis. We found that the impact of energy price on energy efficiency in China was positive in general. However, there existed heterogeneous effects of energy price on energy efficiency in various regions, and the effect differed with differences in energy efficiency levels based on the panel quantile regression analysis. Finally, the nonlinear effect analysis based on the panel threshold model indicated that the effect of energy price on energy efficiency increased with the rise of the environmental regulation level and economic growth rate, while it decreased with the ascent of the degree of energy price distortion and economic development level. In particular, when the value of a region’s economic development level and economic growth rate was within a certain range, the impact was not statistically significant. Overall, these findings contribute to a deeper understanding regarding the effect of energy price on energy efficiency in China.

Suggested Citation

  • Peng Hou & Yilin Li & Yong Tan & Yuanjie Hou, 2020. "Energy Price and Energy Efficiency in China: A Linear and Nonlinear Empirical Investigation," Energies, MDPI, vol. 13(16), pages 1-24, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:16:p:4068-:d:395290
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/16/4068/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/16/4068/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wu, Yanrui, 2012. "Energy intensity and its determinants in China's regional economies," Energy Policy, Elsevier, vol. 41(C), pages 703-711.
    2. Fisher-Vanden, Karen & Jefferson, Gary H. & Liu, Hongmei & Tao, Quan, 2004. "What is driving China's decline in energy intensity?," Resource and Energy Economics, Elsevier, vol. 26(1), pages 77-97, March.
    3. Loren Brandt & Trevor Tombe & Xiadong Zhu, 2013. "Factor Market Distortions Across Time, Space, and Sectors in China," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 16(1), pages 39-58, January.
    4. 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.
    5. Doda, Baran, 2014. "Evidence on business cycles and CO2 emissions," Journal of Macroeconomics, Elsevier, vol. 40(C), pages 214-227.
    6. Birol, Fatih & Keppler, Jan Horst, 2000. "Prices, technology development and the rebound effect," Energy Policy, Elsevier, vol. 28(6-7), pages 457-469, June.
    7. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    8. Thompson, Henry, 2006. "The applied theory of energy substitution in production," Energy Economics, Elsevier, vol. 28(4), pages 410-425, July.
    9. Wooldridge, Jeffrey M., 2005. "Instrumental Variables Estimation With Panel Data," Econometric Theory, Cambridge University Press, vol. 21(4), pages 865-869, August.
    10. 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.
    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. Thoma, Mark, 2004. "Electrical energy usage over the business cycle," Energy Economics, Elsevier, vol. 26(3), pages 463-485, May.
    13. Chang-Tai Hsieh & Peter J. Klenow, 2009. "Misallocation and Manufacturing TFP in China and India," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(4), pages 1403-1448.
    14. Antonietti, Roberto & Fontini, Fulvio, 2019. "Does energy price affect energy efficiency? Cross-country panel evidence," Energy Policy, Elsevier, vol. 129(C), pages 896-906.
    15. Herrerias, M.J. & Cuadros, A. & Orts, V., 2013. "Energy intensity and investment ownership across Chinese provinces," Energy Economics, Elsevier, vol. 36(C), pages 286-298.
    16. Behera, Deepak Kumar & Dash, Umakant, 2019. "Prioritization of government expenditure on health in India: A fiscal space perspective," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    17. Huang, Junbing & Du, Dan & Tao, Qizhi, 2017. "An analysis of technological factors and energy intensity in China," Energy Policy, Elsevier, vol. 109(C), pages 1-9.
    18. 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.
    19. Welsch, Heinz & Ochsen, Carsten, 2005. "The determinants of aggregate energy use in West Germany: factor substitution, technological change, and trade," Energy Economics, Elsevier, vol. 27(1), pages 93-111, January.
    20. Mulder, Peter & de Groot, Henri L.F. & Pfeiffer, Birte, 2014. "Dynamics and determinants of energy intensity in the service sector: A cross-country analysis, 1980–2005," Ecological Economics, Elsevier, vol. 100(C), pages 1-15.
    21. Arthur Lewbel, 1997. "Constructing Instruments for Regressions with Measurement Error when no Additional Data are Available, with an Application to Patents and R&D," Econometrica, Econometric Society, vol. 65(5), pages 1201-1214, September.
    22. Farajzadeh, Zakariya & Nematollahi, Mohammad Amin, 2018. "Energy intensity and its components in Iran: Determinants and trends," Energy Economics, Elsevier, vol. 73(C), pages 161-177.
    23. Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
    24. Song, Feng & Zheng, Xinye, 2012. "What drives the change in China's energy intensity: Combining decomposition analysis and econometric analysis at the provincial level," Energy Policy, Elsevier, vol. 51(C), pages 445-453.
    25. Yang, Mian & Yang, Fuxia & Sun, Chuanwang, 2018. "Factor market distortion correction, resource reallocation and potential productivity gains: An empirical study on China's heavy industry sector," Energy Economics, Elsevier, vol. 69(C), pages 270-279.
    26. Pan, Xiongfeng & Ai, Bowei & Li, Changyu & Pan, Xianyou & Yan, Yaobo, 2019. "Dynamic relationship among environmental regulation, technological innovation and energy efficiency based on large scale provincial panel data in China," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 428-435.
    27. Ouyang, Xiaoling & Sun, Chuanwang, 2015. "Energy savings potential in China's industrial sector: From the perspectives of factor price distortion and allocative inefficiency," Energy Economics, Elsevier, vol. 48(C), pages 117-126.
    28. 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.
    29. Ruth A. Judson & Richard Schmalensee & Thomas M. Stoker, 1999. "Economic Development and the Structure of the Demand for Commercial Energy," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 29-57.
    30. Galloway, Emily & Johnson, Erik Paul, 2016. "Teaching an old dog new tricks: Firm learning from environmental regulation," Energy Economics, Elsevier, vol. 59(C), pages 1-10.
    31. Doda, Baran, 2014. "Evidence on business cycles and CO2 emissions," LSE Research Online Documents on Economics 57009, London School of Economics and Political Science, LSE Library.
    32. Zhenghui Li & Hao Dong & Zimei Huang & Pierre Failler, 2019. "Impact of Foreign Direct Investment on Environmental Performance," Sustainability, MDPI, vol. 11(13), pages 1-16, June.
    33. Dai, Xiaoyong & Cheng, Liwei, 2016. "Market distortions and aggregate productivity: Evidence from Chinese energy enterprises," Energy Policy, Elsevier, vol. 95(C), pages 304-313.
    34. Cornillie, Jan & Fankhauser, Samuel, 2004. "The energy intensity of transition countries," Energy Economics, Elsevier, vol. 26(3), pages 283-295, May.
    35. repec:dau:papers:123456789/10972 is not listed on IDEAS
    36. Hamamoto, Mitsutsugu, 2006. "Environmental regulation and the productivity of Japanese manufacturing industries," Resource and Energy Economics, Elsevier, vol. 28(4), pages 299-312, November.
    37. Zhenghui Li & Gaoke Liao & Khaldoon Albitar, 2020. "Does corporate environmental responsibility engagement affect firm value? The mediating role of corporate innovation," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 1045-1055, March.
    38. Xu, Bin & Lin, Boqiang, 2016. "A quantile regression analysis of China's provincial CO2 emissions: Where does the difference lie?," Energy Policy, Elsevier, vol. 98(C), pages 328-342.
    39. Ouyang, Xiaoling & Wei, Xiaoyun & Sun, Chuanwang & Du, Gang, 2018. "Impact of factor price distortions on energy efficiency: Evidence from provincial-level panel data in China," Energy Policy, Elsevier, vol. 118(C), pages 573-583.
    40. Pan, Xiongfeng & Guo, Shucen & Han, Cuicui & Wang, Mengyang & Song, Jinbo & Liao, Xianchun, 2020. "Influence of FDI quality on energy efficiency in China based on seemingly unrelated regression method," Energy, Elsevier, vol. 192(C).
    41. Gamtessa, Samuel & Olani, Adugna Berhanu, 2018. "Energy price, energy efficiency, and capital productivity: Empirical investigations and policy implications," Energy Economics, Elsevier, vol. 72(C), pages 650-666.
    42. Ma, Hengyun & Oxley, Les & Gibson, John, 2009. "Substitution possibilities and determinants of energy intensity for China," Energy Policy, Elsevier, vol. 37(5), pages 1793-1804, May.
    43. Chang, Ting-Huan & Huang, Chien-Ming & Lee, Ming-Chih, 2009. "Threshold effect of the economic growth rate on the renewable energy development from a change in energy price: Evidence from OECD countries," Energy Policy, Elsevier, vol. 37(12), pages 5796-5802, December.
    44. Jun Zhang, 2008. "Estimation of China's provincial capital stock (1952-2004) with applications," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 6(2), pages 177-196.
    45. Zhao, Xiaoli & Ma, Chunbo & Hong, Dongyue, 2010. "Why did China's energy intensity increase during 1998-2006: Decomposition and policy analysis," Energy Policy, Elsevier, vol. 38(3), pages 1379-1388, March.
    46. Tan, Ruipeng & Lin, Boqiang & Liu, Xiying, 2019. "Impacts of eliminating the factor distortions on energy efficiency—A focus on China's secondary industry," Energy, Elsevier, vol. 183(C), pages 693-701.
    47. Behera, Smruti Ranjan & Dash, Devi Prasad, 2017. "The effect of urbanization, energy consumption, and foreign direct investment on the carbon dioxide emission in the SSEA (South and Southeast Asian) region," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 96-106.
    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. Pierre Failler & Yue Liu, 2023. "The Complexity of Energy Price Fluctuations," Energies, MDPI, vol. 16(5), pages 1-3, March.
    2. Chong Peng & Jingjing Zhang & Zhenyu Xu, 2022. "Does Price Distortion Affect Energy Efficiency? Evidence from Dynamic Spatial Analytics of China," Energies, MDPI, vol. 15(24), pages 1-15, December.
    3. Pierre Failler, 2021. "Special Issue on Global Market for Crude Oil," Energies, MDPI, vol. 14(4), pages 1-2, February.
    4. Zhuoxi Yu & Shan Liu & Zhichuan Zhu, 2022. "Has the Digital Economy Reduced Carbon Emissions?: Analysis Based on Panel Data of 278 Cities in China," IJERPH, MDPI, vol. 19(18), pages 1-18, September.

    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. Yue Liu & Siming Liu & Xueying Xu & Pierre Failler, 2020. "Does Energy Price Induce China’s Green Energy Innovation?," Energies, MDPI, vol. 13(15), pages 1-18, August.
    2. Qiao, Sen & Zhao, Dong Hao & Guo, Zi Xin & Tao, Zhang, 2022. "Factor price distortions, environmental regulation and innovation efficiency: An empirical study on China's power enterprises," Energy Policy, Elsevier, vol. 164(C).
    3. Wu, Anbing & Chen, Junying & Zhang, Yanyan, 2023. "Natural resources and energy resources prices an answer to energy insecurity? The role of mineral, forest, coal resources and financial development," Resources Policy, Elsevier, vol. 87(PA).
    4. Adom, Philip Kofi, 2015. "Business cycle and economic-wide energy intensity: The implications for energy conservation policy in Algeria," Energy, Elsevier, vol. 88(C), pages 334-350.
    5. Zhang, Dayong & Cao, Hong & Wei, Yi-Ming, 2016. "Identifying the determinants of energy intensity in China: A Bayesian averaging approach," Applied Energy, Elsevier, vol. 168(C), pages 672-682.
    6. 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).
    7. Huang, Junbing & Du, Dan & Tao, Qizhi, 2017. "An analysis of technological factors and energy intensity in China," Energy Policy, Elsevier, vol. 109(C), pages 1-9.
    8. Wu, Shu & Ding, Song, 2021. "Efficiency improvement, structural change, and energy intensity reduction: Evidence from Chinese agricultural sector," Energy Economics, Elsevier, vol. 99(C).
    9. Hong, Junjie & Shi, Fangyuan & Zheng, Yuhan, 2023. "Does network infrastructure construction reduce energy intensity? Based on the “Broadband China” strategy," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    10. Tan, Ruipeng & Lin, Boqiang & Liu, Xiying, 2019. "Impacts of eliminating the factor distortions on energy efficiency—A focus on China's secondary industry," Energy, Elsevier, vol. 183(C), pages 693-701.
    11. Hongyun Han & Shu Wu, 2018. "Structural Change and Its Impact on the Energy Intensity of Agricultural Sector in China," Sustainability, MDPI, vol. 10(12), pages 1-23, December.
    12. Ajayi, V. & Reiner, D., 2018. "European Industrial Energy Intensity: The Role of Innovation 1995-2009," Cambridge Working Papers in Economics 1835, Faculty of Economics, University of Cambridge.
    13. Zha, Jianping & Tan, Ting & Fan, Rong & Xu, Han & Ma, Siqi, 2020. "How to reduce energy intensity to achieve sustainable development of China's transport sector? A cross-regional comparison analysis," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    14. Ru Sha & Tao Ge & Jinye Li, 2022. "How Energy Price Distortions Affect China’s Economic Growth and Carbon Emissions," Sustainability, MDPI, vol. 14(12), pages 1-27, June.
    15. Jiang, Lei & Folmer, Henk & Ji, Minhe, 2014. "The drivers of energy intensity in China: A spatial panel data approach," China Economic Review, Elsevier, vol. 31(C), pages 351-360.
    16. Huang, Junbing & Hao, Yu & Lei, Hongyan, 2018. "Indigenous versus foreign innovation and energy intensity in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1721-1729.
    17. Chao Bi & Minna Jia & Jingjing Zeng, 2019. "Nonlinear Effect of Public Infrastructure on Energy Intensity in China: A Panel Smooth Transition Regression Approach," Sustainability, MDPI, vol. 11(3), pages 1-21, January.
    18. Dayong Zhang and David C. Broadstock, 2016. "Club Convergence in the Energy Intensity of China," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    19. Huang, Junbing & Chen, Xiang, 2020. "Domestic R&D activities, technology absorption ability, and energy intensity in China," Energy Policy, Elsevier, vol. 138(C).
    20. Yang, Guangfei & Li, Wenli & Wang, Jianliang & Zhang, Dongqing, 2016. "A comparative study on the influential factors of China's provincial energy intensity," Energy Policy, Elsevier, vol. 88(C), pages 74-85.

    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:gam:jeners:v:13:y:2020:i:16:p:4068-:d:395290. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.