Determinants of renewable energy technological innovation in China under CO2 emissions constraint.

Renewable energy is not only an efficient way to ensure energy independence and security but also supports the transition to a low carbon economy and society. The progress of renewable energy technological innovation is an important factor that influences the development of renewable energy. An in-depth analysis of the driving factors that influence this progress is crucial to China's energy transition. Based on Chinese provincial data over 2000-2015 and panel data models, this paper regards the CO2 emissions as climate change and explores the response of renewable energy technological innovation to intensive CO2 emissions. We also analyze the effect of the driving factors such as energy price and R&D investment on this innovation process. The main conclusions drawn are: (1) There are significant differences in technological innovation levels across China's provinces. (2) We observe that the intensive CO2 emissions have promoted renewable energy technological innovation level, meaning that innovation process responds actively to climate changes. (3) R&D investment from government and enterprise both are conducive for promoting the innovation level. (4) Energy price has an insignificant effect on innovation in renewable energy technologies and we attribute this to the unreasonable energy price mechanism. This paper provides clear evidence for understanding the role of innovation on climate change.

[1]  A. A. Bhatti,et al.  Energy security and renewable energy policy analysis of Pakistan , 2017 .

[2]  Lili Yang,et al.  Differentiated effects of diversified technological sources on energy-saving technological progress: Empirical evidence from China's industrial sectors , 2017 .

[3]  Feifei Yu,et al.  The impact of government subsidies and enterprises’ R&D investment: A panel data study from renewable energy in China , 2016 .

[4]  Hsin-Ning Su,et al.  Does innovation respond to climate change? Empirical evidence from patents and greenhouse gas emissions , 2017 .

[5]  M. Arellano,et al.  Another look at the instrumental variable estimation of error-components models , 1995 .

[6]  Boqiang Lin,et al.  Does electricity price matter for innovation in renewable energy technologies in China? , 2019, Energy Economics.

[7]  C. Granger,et al.  Co-integration and error correction: representation, estimation and testing , 1987 .

[8]  Ying Fan,et al.  The relationship between regional natural gas markets and crude oil markets from a multi-scale nonlinear Granger causality perspective , 2017 .

[9]  Boqiang Lin,et al.  Renewable energy consumption – Economic growth nexus for China , 2014 .

[10]  Judith Gurney BP Statistical Review of World Energy , 1985 .

[11]  B. W. Ang,et al.  Energy security: Definitions, dimensions and indexes , 2015 .

[12]  Boqiang Lin,et al.  Assessing the development of China's new energy industry , 2018 .

[13]  Roula Inglesi-Lotz,et al.  Renewable energy and growth: Evidence from heterogeneous panel of G7 countries using Granger causality , 2015 .

[14]  Valeria Costantini,et al.  Environmental Regulation and the Export Dynamics of Energy Technologies , 2007 .

[15]  Gong Chen,et al.  Coal use embodied in globalized world economy: From source to sink through supply chain , 2018 .

[16]  Seema Narayan,et al.  An investigation of renewable and non-renewable energy consumption and economic growth nexus using industrial and residential energy consumption , 2017 .

[17]  Bo Shen,et al.  Can environmental innovation facilitate carbon emissions reduction? Evidence from China , 2017 .

[18]  Youngho Chang,et al.  Energy security in China: A quantitative analysis and policy implications , 2014 .

[19]  David Popp,et al.  Induced Innovation and Energy Prices , 2001 .

[20]  Ke Li,et al.  Choice of technological change for China's low-carbon development: Evidence from three urban agglomerations. , 2018, Journal of environmental management.

[21]  José Ramón San Cristóbal,et al.  A multi criteria data envelopment analysis model to evaluate the efficiency of the Renewable Energy technologies , 2011 .

[22]  Boqiang Lin,et al.  Factors influencing renewable electricity consumption in China , 2016 .

[23]  Lanouar Charfeddine,et al.  Impact of renewable and non-renewable energy consumption on economic growth: New evidence from the MENA Net Oil Exporting Countries (NOECs) , 2016 .

[24]  Yi-Ming Wei,et al.  China's Farewell to Coal: A Forecast of Coal Consumption through 2020 , 2015 .

[25]  Lili Yang,et al.  Using latent variable approach to estimate China's economy-wide energy rebound effect over 1954-2010 , 2014 .

[26]  M. Pesaran,et al.  Testing for unit roots in heterogeneous panels , 2003 .

[27]  Xilong Yao,et al.  Can urbanization process and carbon emission abatement be harmonious? New evidence from China , 2018, Environmental Impact Assessment Review.

[28]  Energy Prices, Technological Knowledge, and Innovation in Green Energy Technologies: a Dynamic Panel Analysis of European Patent Data , 2016 .

[29]  Barry D. Solomon,et al.  The coming sustainable energy transition: History, strategies, and outlook , 2011 .

[30]  Mirjana Radovanović,et al.  Energy security measurement – A sustainable approach , 2017 .

[31]  Ke Li,et al.  How to promote energy efficiency through technological progress in China , 2018 .

[32]  Kwangwoo Park,et al.  Financial Development and Deployment of Renewable Energy Technologies , 2016 .

[33]  Kerui Du,et al.  Convergence or divergence? Understanding the global development trend of low-carbon technologies , 2017 .

[34]  Andrew T. Levin,et al.  Unit root tests in panel data: asymptotic and finite-sample properties , 2002 .

[35]  R. Blundell,et al.  Initial Conditions and Moment Restrictions in Dynamic Panel Data Models , 1998 .

[36]  Bin Su,et al.  Does energy-price regulation benefit China's economy and environment? Evidence from energy-price distortions , 2017 .

[37]  Elena Verdolini,et al.  At Home and Abroad: An Empirical Analysis of Innovation and Diffusion in Energy-Efficient Technologies , 2011 .

[38]  Boqiang Lin,et al.  Do we really understand the development of China's new energy industry? , 2018, Energy Economics.

[39]  Boqiang Lin,et al.  The role of renewable energy technological innovation on climate change: Empirical evidence from China. , 2019, The Science of the total environment.

[40]  Shouzhen Zeng,et al.  Review of and comparative assessment of energy security in Baltic States , 2017 .

[41]  Joëlle Noailly,et al.  Knowledge Spillovers from Renewable energy Technologies, Lessons from patent citations , 2017 .

[42]  Ke Li,et al.  The path of technological progress for China's low-carbon development: Evidence from three urban agglomerations , 2018 .

[43]  Qiao-Mei Liang,et al.  Changes to pollutants and carbon emission multipliers in China 2007-2012: An input-output structural decomposition analysis. , 2017, Journal of environmental management.

[44]  P. Pedroni Current Version : July 25 , 1999 CRITICAL VALUES FOR COINTEGRATION TESTS IN HETEROGENEOUS PANELS WITH MULTIPLE REGRESSORS * , 1999 .

[45]  Yi-Ming Wei,et al.  Role of renewable energy in China’s energy security and climate change mitigation: An index decomposition analysis , 2018, Renewable and Sustainable Energy Reviews.

[46]  L. Hunt,et al.  Prices versus policy: An analysis of the drivers of the primary fossil fuel mix , 2017 .

[47]  M. Arellano,et al.  Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations , 1991 .

[48]  Kyunam Kim,et al.  Role of policy in innovation and international trade of renewable energy technology: Empirical study of solar PV and wind power technology , 2015 .

[49]  W. T. Tsai,et al.  Overview of environmental impacts, prospects and policies for renewable energy in Taiwan , 2005 .

[50]  Tobias Stucki,et al.  The Impact of Energy Prices onGreen Innovation , 2016 .

[51]  F. Shi,et al.  Realizing low-carbon development in a developing and industrializing region: Impacts of industrial structure change on CO2 emissions in southwest China. , 2019, Journal of environmental management.

[52]  H. T. Chen,et al.  Optimal design of subsidy to stimulate renewable energy investments: The case of China , 2017 .

[53]  P. Pedroni PANEL COINTEGRATION: ASYMPTOTIC AND FINITE SAMPLE PROPERTIES OF POOLED TIME SERIES TESTS WITH AN APPLICATION TO THE PPP HYPOTHESIS , 2004, Econometric Theory.

[54]  Boqiang Lin,et al.  Energy and carbon intensity in China during the urbanization and industrialization process: A panel VAR approach , 2017 .

[55]  L. Proskuryakova,et al.  Updating energy security and environmental policy: Energy security theories revisited. , 2018, Journal of environmental management.

[56]  Qiang Wang,et al.  A framework for evaluating global national energy security , 2017 .

[57]  Jingzheng Ren,et al.  Enhancing China's energy security: determining influential factors and effective strategic measures , 2014 .

[58]  Boqiang Lin,et al.  Analyzing cost of grid-connection of renewable energy development in China , 2015 .

[59]  Zhuang Miao,et al.  Improvement pathway of energy consumption structure in China's industrial sector: From the perspective of directed technical change , 2018 .

[60]  Giovanni Peri,et al.  The International Dynamics of R&D and Innovation in the Long Run and in the Short Run , 2007 .

[61]  Christopher F. Baum,et al.  How to do Xtabond2: An Introduction to Difference and System GMM in Stata , 2006 .

[62]  A. López-Menéndez,et al.  Environmental costs and renewable energy: re-visiting the Environmental Kuznets Curve. , 2014, Journal of environmental management.

[63]  Chihwa Kao,et al.  Spurious Regression and Residual-Based Tests for Cointegration in Panel Data When the Cross-Section and Time-Series Dimensions are Comparable , 1996 .

[64]  E. Dumitrescu,et al.  Testing for Granger Non-causality in Heterogeneous Panels , 2012 .

[65]  Hsin-Chia Fu,et al.  Clean energy, non-clean energy, and economic growth in the MIST countries , 2014 .

[66]  N. Johnstone,et al.  Directing Technological Change while Reducing the Risk of (not) Picking Winners: The Case of Renewable Energy , 2010 .

[67]  M. Jaforullah,et al.  Does the use of renewable energy sources mitigate CO2 emissions? A reassessment of the US evidence , 2015 .

[68]  Boqiang Lin,et al.  An application of a double bootstrap to investigate the effects of technological progress on total-factor energy consumption performance in China , 2017 .

[69]  Anis Omri,et al.  Modeling the causal linkages between nuclear energy, renewable energy and economic growth in developed and developing countries , 2015 .

[70]  D. Popp,et al.  Renewable Energy Policies and Technological Innovation: Evidence Based on Patent Counts , 2008 .