Search Advanced

Green Finance

2019, Volume 1, Issue 2: 174-187. doi: 10.3934/GF.2019.2.174
Previous Article Next Article
Research article

An analysis of financial support, technological progress and energy efficiency：evidence from China

  • 1.
    College of Finance and Statistics, Hunan University, Changsha, China
  • 2.
    Economics and Finance Subject Group, Portsmouth Business School, University of Portsmouth, UK
  • Received: 15 April 2019 Accepted: 22 April 2019 Published: 30 April 2019

  • JEL Codes: C33, O53, Q43, Q56

  • In order to explore the nonlinear relationship between financial support, technological progress and energy efficiency, a panel smooth transition regression (PSTR) is developed to analyze the impact of financial support and technological progress on the energy efficiency. Based on panel data of 30 provinces in China from 2003 to 2016, the total-factor energy efficiency of 30 province-level divisions in China are evaluated using Data Envelopment analysis (DEA). The results show that financial support and technological progress are generally conducive to increasing energy efficiency. However, the increment effect of financial support and technological progress on energy efficiency transitions smoothly between high and low regimes with the changes of the transition variables, such as local government expenditure; foreign direct investment, energy structure and industrial structure. Therefore, the results emphasize the need for enhancing financial support and technological progress in increasing energy efficiency.

    Citation: Gaoke Liao, Benjamin M. Drakeford. An analysis of financial support, technological progress and energy efficiency：evidence from China[J]. Green Finance, 2019, 1(2): 174-187. doi: 10.3934/GF.2019.2.174

    Related Papers:

  • In order to explore the nonlinear relationship between financial support, technological progress and energy efficiency, a panel smooth transition regression (PSTR) is developed to analyze the impact of financial support and technological progress on the energy efficiency. Based on panel data of 30 provinces in China from 2003 to 2016, the total-factor energy efficiency of 30 province-level divisions in China are evaluated using Data Envelopment analysis (DEA). The results show that financial support and technological progress are generally conducive to increasing energy efficiency. However, the increment effect of financial support and technological progress on energy efficiency transitions smoothly between high and low regimes with the changes of the transition variables, such as local government expenditure; foreign direct investment, energy structure and industrial structure. Therefore, the results emphasize the need for enhancing financial support and technological progress in increasing energy efficiency.


    加载中


    [1] Aguilera-Caracuel J, Ortiz-de-Mandojana N (2013) Green innovation and financial performance: An institutional approach. Organ Environ 26: 365–385. doi: 10.1177/1086026613507931
    [2] Al-Refaie A, Hammad M, Li MH (2016) DEA window analysis and Malmquist index to assess energy efficiency and productivity in Jordanian industrial sector. Energy Effic 9: 1299–1313. doi: 10.1007/s12053-016-9424-0
    [3] Amore MD, Schneider C, Zaldokas A (2013) Credit Supply and Corporate Innovation. J Financ Econ 109: 835–855. doi: 10.1016/j.jfineco.2013.04.006
    [4] Benfratello L, Schiantarelli F, Sembenelli A (2008) Banks and Innovation: Microeconometric Evidence on Italian Firms. J Financ Econ 90: 197–217. doi: 10.1016/j.jfineco.2008.01.001
    [5] Brown JR, Martinsson G, Petersen BC (2013) Law, Stock Markets, and Innovation. J Financ 68: 1517–1549. doi: 10.1111/jofi.12040
    [6] Chen L, Jia G (2017) Environmental efficiency analysis of China's regional industry: a data envelopment analysis (DEA) based approach. J Clean Prod 142: 846–853. doi: 10.1016/j.jclepro.2016.01.045
    [7] Costantini V, Crespi F, Marin G, et al. (2017) Eco-innovation, sustainable supply chains and environmental performance in European industries. J Clean prod 55: 141–154. doi: 10.1016/j.jclepro.2016.09.038
    [8] Filippini M, Zhang L (2016) Estimation of the energy efficiency in Chinese provinces. Energy Effic 9: 1315–1328. doi: 10.1007/s12053-016-9425-z
    [9] Gerarden TD, Newell RG, Stavins RN (2017) Assessing the energy-efficiency gap. J Econ Lit 55: 1486–1525. doi: 10.1257/jel.20161360
    [10] Hou J, Teo TS, Zhou F, et al. (2018) Does industrial green transformation successfully facilitate a decrease in carbon intensity in China? An environmental regulation perspective. J Clean Prod 184: 1060–1071. doi: 10.1016/j.jclepro.2018.02.311
    [11] Hsu PH, Tian X, Xu Y (2014) Financial Development and Innovation: Cross-Country Evidence. J Financ Econ 112: 116–135. doi: 10.1016/j.jfineco.2013.12.002
    [12] Jabbour CJC, Jugend D, de Sousa Jabbour ABL, et al. (2015) Green product development and performance of Brazilian firms: measuring the role of human and technical aspects. J Clean Prod 87: 442–451. doi: 10.1016/j.jclepro.2014.09.036
    [13] Jaffe AB, Newell RG, Stavins RN (2002) Environmental policy and technological change. Environ Resour Econ 22: 41–70. doi: 10.1023/A:1015519401088
    [14] Kenney M (2011) How Venture Capital Became a Component of the US National System of Innovation. Ind Corp Change 20: 1677–1723. doi: 10.1093/icc/dtr061
    [15] Kim J, Park K (2016) Financial development and deployment of renewable energy technologies. Energy Econ 59: 238–250. doi: 10.1016/j.eneco.2016.08.012
    [16] King RG, Levine R (1993) Finance and growth: Schumpeter might be right. Q J Econ 108: 717–737. doi: 10.2307/2118406
    [17] Li Z, Wang Z, Huang Z (2017) Modeling Business Cycle with Financial Shocks Basing on Kaldor-Kalecki Model. Quant Financ Econ 1: 44–66. doi: 10.3934/QFE.2017.1.44
    [18] Manne A, Richels R (2004) The impact of learning-by-doing on the timing and costs of CO2 abatement. Energy Econ 26: 603–619. doi: 10.1016/j.eneco.2004.04.033
    [19] Shahbaz M, Bhattacharya M, Mahalik MK (2018) Financial development, industrialization, the role of institutions and government: a comparative analysis between India and China. Appl Econ 50: 1952–1977. doi: 10.1080/00036846.2017.1383595
    [20] Wang K, Wei YM (2014) China's regional industrial energy efficiency and carbon emissions abatement costs. Appl Energy 130: 617–631. doi: 10.1016/j.apenergy.2014.03.010
    [21] Wang K, Wei YM, Zhang X (2013) Energy and emissions efficiency patterns of Chinese regions: a multi-directional efficiency analysis. Appl Energy 104: 105–116. doi: 10.1016/j.apenergy.2012.11.039
    [22] Wei J, Guo X, Marinova D, et al. (2014) Industrial SO2 pollution and agricultural losses in China: evidence from heavy air polluters. J Clean Prod 64: 404–413. doi: 10.1016/j.jclepro.2013.10.027
    [23] Zhang YJ, Da YB (2015) The decomposition of energy-related carbon emission and its decoupling with economic growth in China. Renew Sust Energy Rev 41: 1255–1266. doi: 10.1016/j.rser.2014.09.021
    [24] Zhang YJ, Peng YL, Ma CQ, et al. (2017) Can environmental innovation facilitate carbon emissions reduction? Evidence from China. Energy Policy 100: 18–28. doi: 10.1016/j.enpol.2016.10.005
  • Reader Comments
  • © 2019 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Green Finance
5.5 9.6

Metrics

Article views(5130) PDF downloads(1588) Cited by(22)

Preview PDF
Download XML
Export Citation
Article outline

Figures and Tables

Tables(6)

Other Articles By Authors

Related pages

Tools

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog