Abstract
Considering government and market failure of environmental regulation to combat increasing GHG (greenhouse gas) emissions, green innovation can mitigate pollution through production processes and clean production. This paper aims to investigate endogenous green innovation efficiency and its convergence across China’s 30 provinces from 2004 to 2014. Due to factor endowment heterogeneity, it is important to explore the convergence of green innovation efficiency among China’s different regions, which can compare green innovation efficiency spatially and propose scientific policy implications for regions with relatively weaker green innovation efficiency. Green innovation efficiency is evaluated through epsilon-based measure (EBM) global Malmquist-Luenberger (ML) in order to overcome the demerits of radial model and slacks-based measure (SBM). Panel unit root test is implemented to explore the convergence of green innovation efficiency across different provinces of China, which addresses the invalid inference of conventional β convergence. The empirical analysis revealed that green innovation efficiency in the east is the highest among four regions of China. Unit root test of panel data revealed that the northeast had the highest convergence among China’s four regions. It is important to enhance green innovation capacity, and expand knowledge spillover of green innovation technology in order to mitigate GHG emissions.
Similar content being viewed by others
References
Aldieri L, Carlucci F, Cirà A, Ioppolo G, Vinci CP (2019) Is green innovation an opportunity or a threat to employment? An empirical analysis of three main industrialized areas: the USA, Japan and Europe. J Clean Prod 214:758–766
Aloise PG, Macke J (2017) Eco-innovations in developing countries: the case of Manaus free trade zone (Brazil). J Clean Prod 168:30–38
Annala CN, Chen S (2011) Convergence of state and local fiscal policies: an application of panel unit root test. J Econ Econ Educ Res 12(1):27
Arranz N, Arroyabe MF, Molina-García A, Fernandez DAJC (2019) Incentives and inhibiting factors of eco-innovation in the Spanish firms. J Clean Prod 220:167–176
Barassi MR, Cole MA, Elliott RJR (2008) Stochastic divergence or convergence of per capita carbon dioxide emissions: re-examining the evidence. Environ Resour Econ 40(1):121–137
Barro R, Sala-i-Martín X (1992) Convergence. J Polit Econ 100:223–251
Beyaert A, Camacho M (2008) TAR panel unit root tests and real convergence. Rev Dev Econ 12(3):668–681
Bhattacharya M, Inekwe JN, Sadorsky P, Saha A (2018) Convergence of energy productivity across Indian states and territories. Energy Econ 74:427–440
Cai YF, Chang TY, Inglesi-Lotz R (2018) Asymmetric persistence in convergence for carbon dioxide emissions based on quantile unit root test with Fourier function. Energy 161:470–481
Casu B, Ferrari A, Girardone C, Wilsonet JOS (2016) Integration, productivity and technological spillovers: evidence for eurozone banking industries. Eur J Oper Res 255(3):971–983
Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2(6):429–444
Chen JN (2015) http://news.sohu.com/20150307/n409460582.shtml.
Chen XH, Li CQ, Ji HL, Bai SZ, Zhang GR (2013) Spatial conditional β convergence analysis of society-wide energy efficiency based on technological diffusion. Chin Pop Resour Environ 23(8):7–13
Cheng Y, Yin Q (2016) Study on the regional difference of green innovation efficiency in China—an empirical analysis based on the panel data. Proceedings of the 6th International Asia Conference on Industrial Engineering and Management Innovation. Atlantis Press:69–78
Chung YH, Färe R, Grosskopf S (1997) Productivity and undesirable outputs: a directional distance function approach. J Environ Manag 51:229–240
Churchill SA, Inekwe J, Ivanovski K (2018) Conditional convergence in per capita carbon emissions since 1900. Appl Energy 228:916–927
Claudia K (2005) Induced technological change in a multi-regional, multi-sectoral, integrated assessment model (WIAGEM) impact assessment of climate policy strategies. Ecol Econ 54:293–305
Cooper WW, Seiford LM, Tone K (2007) Data envelopment analysis: a comprehensive text with models, applications. Springer, References and DEA-Solver Software
Duan HB, Zhu L, Fan Y (2015) Modelling the evolutionary paths of multiple carbon-free energy technologies with policy incentives. Environ Model Assess 20:55–69
Duan HB, Zhang GP, Wang SY, Fan Y (2019) Integrated benefit-cost analysis of China’s optimal adaptation and targeted mitigation. Ecol Econ 160:76–86
Evans P (1998) Using panel data to evaluate growth theories. Int Econ Rev 39:295–306
Evans P, Karras G (1996) Convergence revisited. J Monet Econ 37:249–265
Färe R, Grosskopf S, Pausurka CAJ (2007) Environmental production functions and environmental directional distance functions. Energy 32:1055–1066
Farrell MJ (1957) The measurement of productive efficiency. J R Stat Soc 120(3):253–281
Feng Y, Wang X, Du W, Wu H, Wang J (2019) Effects of environmental regulation and FDI on urban innovation in China: a spatial Durbin econometric analysis. J Clean Prod 235:210–224
Ghisetti C, Quatraro F (2017) Green technologies and environmental productivity: a cross-sectoral analysis of direct and indirect effects in Italian regions. Ecol Econ 132:1–13
Goulder LH, Schneider SH (1999) Induced technological change and the attractiveness of CO2 abatement policies. Resour Energy Econ 21(3–4):211–253
Grazia C, Nicoletta C, Cédric G, Muge O (2014) Technological pervasiveness and variety of innovators in Green ICT: a patent-based analysis. Res Policy 43:1827–1839
Grossman GM, Helpman E (1993) Innovation and growth in the global economy. The MIT Press.
Hall BH, Helmers C (2013) Innovation and diffusion of clean/green technology: can patent commons help? J Environ Econ Manag 66(1):33–51
Han L, Han BT, Shi XP, Su B, Lv X, Lei X (2018) Energy efficiency convergence across countries in the context of China’s Belt and Road initiative. Appl Energy 213:112–122
Herrerias MJ (2013) The environmental convergence hypothesis: carbon dioxide emissions according to the source of energy. Energy Policy 61(10):1140–1150
Hu X (2016) Research on China’s provincial environmental total factor productivity calculation, convergence and influencing factors. Jiangxi University of Finance and Economics
Karakaya,E., Hidalgo,A., Nuur,C..Diffusion of eco-innovations: a review, Renewable and Sustainable Energy Reviews,2014,33: 392-399.
Kim T, Maskus KE, Oh KY (2009) The effects of patents on productivity growth in Korean manufacturing. Pac Econ Rev 13(4):137–154
Lambertini L, Poyago-Theotoky J, Tampieri A (2017) Cournot competition and ‘green’ innovation: an inverted-u relationship. Energy Econ 68:116–123
Levin A, Lin CF, Chu CSJ(2002) Unit Root Tests in Panel Data: Asymptotic and Finite-Sample Properties. Journal of econometrics, 108, 1-24.
Li XS, Zhu JP (2013) Innovation efficiency and convergence research on China’s provincial industrial enterprises. J Appl Stat Manag 32(6):1090–1099
Lin PC, Huang HC (2012) Convergence in income inequality? Evidence from panel unit root tests with structural breaks. Empir Econ 43:153–174
Liu MG (2017) Research on spatial distribution and convergence of green innovation efficiency in regional innovation system. J Ind Technol Econ 282(4):10–18
Liu ZM, Ma SC, Ma WT (2017) The research on innovation efficiency of pharmaceutical manufacturing and its convergence based on dynamic network SBM model. J Ind Technol Econ 284(6):63–69
Long XL, Chen YQ, Du JG, Oh KY, Han IS (2017a) Environmental innovation and its impact on economic and environmental performance: evidence from Korean-owned firms in China. Energy Policy 107:131–137
Long XL, Chen YQ, Du JG, Oh KY, Han IS, Yan JH (2017b) The effect of environmental innovation behavior on economic and environmental performance of 182 Chinese firms. J Clean Prod 166:1274–1282
Long XL, Sun M, Cheng FX, Zhang JJ (2017c) Convergence analysis of eco-efficiency of China’s cement manufacturers through unit root test of panel data. Energy 134:709–717
Long XL, Chen B, Byounggu P (2018a) Effect of 2008’s Beijing Olympic Games on environmental efficiency of 268 China’s cities. J Clean Prod 172:1423–1432
Long XL, Wu C, Zhang JJ, Zhang J (2018b) Environmental efficiency for 192 thermal power plants in the Yangtze River Delta considering heterogeneity: a metafrontier directional slacks-based measure approach. Renew Sust Energ Rev 82:3962–3971
Luo YS, Long XL, Wu C,Zhang JJ(2017)Decoupling CO2 emissions from economic growth in agricultural sector across 30 Chinese provinces from 1997 to 2014. Journal of Cleaner Production, 159: 220-228.
Mensah CN, Long XL, Dauda L, Boamah KB, Salman M, Appiah-Twum F, Tachie A K(2019)Technological innovation and green growth in the Organization for Economic Cooperation and Development economies, Journal of Cleaner Production,
Ma HL, Ding YQ, Wang L (2017) Measurement and convergence analysis of green water utilization efficiency. J Nat Res 32(3):406–417. https://doi.org/10.1016/j.jclepro.2019.118204
Pan XF, Liu FC (2010) Research on industrial enterprise’s innovation efficiency in China based on regional comparison. Manag Rev 22(2):59–64
Pang RZ, Li P (2011) Transformation performance of China’s industrial growth pattern. J Quant Tech Econ 9:34–46
Pastor JT, Lovell CAK (2005) A global Malmquist productivity index. Econ Lett 88(2):266–271
Popp D (2002) Induced innovation and energy prices. Am Econ Rev 92(1):160–180
Ren Y, Niu CK, Niu T, Yao XL (2014) The theoretical model and empirical analysis of green innovation efficiency. Management World 7:176–177
Reyer G (2007) Measuring the value of induced technological change. Energy Policy 35:5287–5297
Robalino-López A, García-Ramos JE, Golpe AA, Mena-Nieto A (2016) CO2 emissions convergence among 10 South American countries. A study of Kaya components(1980-2010). Carbon Management 7(1-2):1–12
Romer P (1986) Increasing returns and long-run growth. J Polit Econ 99:1002–1037
Shephard RW (1970) Theory of cost and production functions. Princeton University Press
Song ML, Tao J, Wang SH (2015) FDI, technology spillovers and green innovation in China: analysis based on Data Envelopment Analysis. Ann Oper Res 228(1):47–64
Stahlke T (2019) The impact of the Clean Development Mechanism on developing countries’ commitment to mitigate climate change and its implications for the future. Mitig Adapt Strateg Glob Chang. https://doi.org/10.1007/s11027-019-09863-8
Sun C, Ma T, Xu M (2018) Exploring the prospects of cooperation in the manufacturing industries between India and China: a perspective of embodied energy in India-China trade. Energy Policy 113:643–650
Tian G, Shi J, Sun L, Long X, Guo B (2017) Dynamic changes in the energy-carbon performance of Chinese transportation sector: a meta-frontier non-radial directional distance function approach. Nat Hazards 1:1–23
Tone K (2001) A Slacks-based measure of efficiency in data envelopment analysis. J Oper Res 130(3):498–509
Tone K, Tsutsui M (2010) An epsilon-based measure of efficiency in DEA – a third pole of technical efficiency. Eur J Oper Res 207(3):1554–1563
Tu ZG (2008) The coordination of industrial growth with environment and resource. Econ Res 2:93–105
Wang W, Fan D (2012) Influential factors and convergence of total factor energy efficiency in China based on the Malmqulist-Luenberger index. Resources Science 34(10):1816–1824
Wang Y, Wang J (2019) Does industrial agglomeration facilitate environmental performance: new evidence from urban China? J Environ Manag 248:109244
Wang ZP, Tao CQ, Shen PY (2014) Regional green technical efficiency with its influencing factors analysis based on ecological footprint. Chin Pop Resour Environ 1:35–40
Wang QW, Hang Y, Sun LC, Zengyao Zhao ZY (2016a) Two-stage innovation efficiency of new energy enterprises in China: a non-radial DEA approach. Technol Forecast Soc Chang 112:254–261
Wang QW, Su B, Zhou P, Chiu CR (2016b) Measuring total-factor CO2 emission performance and technology gaps using a non-radial directional distance function: a modified approach. Energy Econ 56:475–482
Wang QW, Hang Y, Hu JL, Chiu CR (2018) An alternative metafrontier framework for measuring the heterogeneity of technology. Nav Res Logist 65(5):427–445
Wang, K., Zhang, J., Geng, Y., Xiao, L., Xu, Z., Rao, Y., Zhou, X.. Differential spatial-temporal responses of carbon dioxide emissions to economic development: empirical evidence based on spatial analysis .Mitigation and Adaptation Strategies for Global Change,2019, https://doi.org/10.1007/s11027-019-09876-3.
Westerlund J, Basher SA (2008) Testing for convergence in carbon dioxide emissions using a century of panel data. Environ Resour Econ 40(1):109–120
Wu, J.L. http://news.sciencenet.cn/htmlnews/2012/8/267652.shtm. 2012
Xia D, Chen B, Zheng Z (2015) Relationships among circumstance pressure, green technology selection and firm performance. J Clean Prod 106:487–496
Xu JX, Lin LM, Huang SW, Zheng YF (2015) Analysis of the regional technical innovation efficiency and its convergence. J Fuj Agric Fores Univ 18(2):31–35
Yang L, Hu XZ (2010) Analysis on regional difference and convergence of the efficiency of China’s green economy based on DEA. Economist 2:46–54
Yang F, Yang M (2015) Analysis on China’s eco-innovations: regulation context, intertemporal change and regional differences. Eur J Oper Res 247(3):1003–1012
Yavuz NC, Yilanci V (2013) Convergence in per capita carbon dioxide emissions among G7countries: a TAR panel unit root approach. Environ Resour Econ 54(2):283–291
Zhang N, Wang B, Liu Z (2016) Carbon emissions dynamics, efficiency gains, and technological innovation in China’s industrial sectors. Energy 99:10–19
Zhang Y, Shen L, Shuai C, Bian J, Zhu M, Tan Y, Ye G (2019) How is the environmental efficiency in the process of dramatic economic development in the Chinese cities? Ecol Indic 98:349–362
Acknowledgements
This work received financial support from the National Natural Science Foundation of China (Nos. 71911540483, 71603105, 71673230, 71803068, and 71303199), Natural Science Foundation of Jiangsu, China (No. SBK2016042936), and China Postdoctoral Science Foundation (No.2017M610051, 2018T110054).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Long, X., Sun, C., Wu, C. et al. Green innovation efficiency across China’s 30 provinces: estimate, comparison, and convergence. Mitig Adapt Strateg Glob Change 25, 1243–1260 (2020). https://doi.org/10.1007/s11027-019-09903-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11027-019-09903-3