环境规制能够改善技术学习的绿色绩效吗?——一个带调节效应的环境学习曲线模型
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摘要
环境规制政策是解决环境污染问题的重要制度保障。然而,学者们对环境规制是否能够达到预期效果莫衷一是。为了进一步验证环境规制实施效果,建立了包含环境规制的多要素环境学习曲线模型,基于2001-2016年我国省域工业企业面板数据,从新视角研究了不同类型环境规制对不同技术学习模式绿色绩效的调节作用。研究结果表明:与经济环境规制相比,行政环境规制对提升工业企业技术学习绿色绩效的作用更显著;在干中学、研发中学和引进中学3种技术学习模式中,行政环境规制可以促进研发中学的绿色绩效;行政环境规制及经济环境规制的非线性调节效应都不显著。上述结论对合理设计和选择不同类型环境法规、促进企业技术学习和减少大气污染物排放具有重要意义。
The Porter hypothesis has triggered a large number of empirical studies on the impact of environmental regulations on enterprises' technological innovation.This paper investigate the effect of environmental regulations from a new perspective that we study the moderating effect of different types of environmental regulations(command-and-control and market-based regulations)on the green performance of different technological learning patterns by building an environmental learning curve model,based on the panel data from China's industrial enterprises over 2001-2016.The results show that the command-and-control regulations provide stronger incentives for improving the green performance of enterprises' technological leaning than market-based regulations.Moreover,only the green performance of enterprises' learning-by-researching can be improved by the command-and-control regulations among three technological leaning patterns analyzed.In addition,the nonlinear moderating effect of these two types of environmental regulations are insignificant.These findings yields important implications for reasonably designing and choosing different types of environmental regulations to encourage enterprises' technological learning and reduce air pollutants emissions.
The Porter hypothesis has triggered a large number of empirical studies on the impact of environmental regulations on enterprises' technological innovation.This paper investigate the effect of environmental regulations from a new perspective that we study the moderating effect of different types of environmental regulations(command-and-control and market-based regulations)on the green performance of different technological learning patterns by building an environmental learning curve model,based on the panel data from China's industrial enterprises over 2001-2016.The results show that the command-and-control regulations provide stronger incentives for improving the green performance of enterprises' technological leaning than market-based regulations.Moreover,only the green performance of enterprises' learning-by-researching can be improved by the command-and-control regulations among three technological leaning patterns analyzed.In addition,the nonlinear moderating effect of these two types of environmental regulations are insignificant.These findings yields important implications for reasonably designing and choosing different types of environmental regulations to encourage enterprises' technological learning and reduce air pollutants emissions.
引文
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[20]孙根年,李静,魏艳旭.环境学习曲线与我国碳减排目标的地区分解[J].环境科学研究,2011(24):1194-1202.
[21]韩亚芬,孙根年,李琦.中国省际SO2排放的环境学习曲线及减排潜力[J].环境科学研究,2008,21(3):201-206.
[22]YU S,ZHANG J,ZHENG S,et al.Provincial carbon intensity abatement potential estimation in China:a PSO-GA-optimized multi-factor environmental learning curve method[J].Energy Policy,2015,77:46-55.
[23]GUO F,ZHAO T,WANG Y,et al.Estimating the abatement potential of provincial carbon intensity based on the environmental learning curve model in China[J].Natural Hazards,2016(4):1-21.
[24]YU S,AGBEMABIESE L,ZHANG J.Estimating the carbon abatement potential of economic sectors in China[J].Applied Energy,2016,165:107-118.
[25]WANG W,YU B,YAO X,et al.Can technological learning significantly reduce industrial air pollutants intensity in China?---based on a multi-factor environmental learning curve[J].Journal of Cleaner Production,2018,185:137-147.
[26]GARDINER D,PORTNEY P R.Does environmental policy conflict with economic growth[J].Resources,2001,115:859-881.
[27]WRIGHT T P.Factors affecting the cost of airplanes[J].Journal of the Aeronautical Sciences,1936,3:122-128.
[28]CHEN J,QUW G.A new technological learning in China[J].Technovation,2003,23:861-867.
[29]YU C F,SARK W G J H,ALSEMA E A.Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects[J].Renewable&Sustainable Energy Reviews,2011,15:324-337.
[30]JARAMILLO P,MULLER N Z.Air pollution emissions and damages from energy production in the U.S.:2002-2011[J].Energy Policy,2016,90:202-211.
[31]魏巍贤,杨芳.技术进步对中国二氧化碳排放的影响[J].统计研究,2010,27(7):36-44.
[32]RUBIN E S,AZEVEDO I M L,JARAMILLO P,et al.Areview of learning rates for electricity supply technologies[J].Energy Policy,2015,86:198-218.
[33]WITAJEWSKI-BALTVILKS J,VERDOLINI E,TAVONIM.Bending the learning curve[J].Energy Economics,2015,52:S86-S99.
[34]EDWARDS J R,LAMBERT L S.Methods for integrating moderation and mediation:ageneral analytical framework using moderated path analysis[J].Psychological Methods,2007,12:1-22.
[35]JOHNSTONE N,MANAGI S,RODRIGUEZ M C,et al.Environmental policy design,innovation and efficiency gains in electricity generation[J].Energy Economics,2017,63:106-115.
[36]POPP D.Induced innovation and energy prices[J].American Economic Review,2002,92:160-180.
[37]吴延兵.自主研发、技术引进与生产率---基于中国地区工业的实证研究[J].经济研究,2008(8):51-64.
[38]NEMET G F.Beyond the learning curve:factors influencing cost reductions in photovoltaics[J].Energy Policy,2006,34:3218-3232.
[39]王书斌,徐盈之.环境规制与雾霾脱钩效应---基于企业投资偏好的视角[J].中国工业经济,2015(8):18-30.
[40]DECHEZLEPRETRE A,SATO M.The impacts of environmental regulations on competitiveness[J].Review of Environmental Economics and Policy,2017,11:183-206.
[41]ARIMURA T H,SUGINO M.The impact of environmental regulation on technological innovation:an assessment of the porter hypothesis with firm level environmental R&D data(innovation and sustainability)[J].Journal of Science Policy&Research Management,2009,23:201-211.
[42]BERCHICCI L.Towards an open R&D system:internal R&D investment,external knowledge acquisition and innovative performance[J].Research Policy,2013,42:117-127.
[43]张平,张鹏鹏,蔡国庆.不同类型环境规制对企业技术创新影响比较研究[J].中国人口·资源与环境,2016,26(4):8-13.
[2]ALBRIZIO S,KOZLUK T,ZIPPERER V.Environmental policies and productivity growth:evidence across industries and firms[J].Journal of Environmental Economics and Management,2017,81:209-226.
[3]ANTONIETTI R,DE MARCHI V,DI MARIA E.Governing offshoring in a stringent environmental policy setting:Evidence from Italian manufacturing firms[J].Journal of Cleaner Production,2017,155:103-113.
[4]MOHR R D.Technical change,external economies,and the porter hypothesis[J].Journal of Environmental Economics&Management,2002,43(1):158-168.
[5]JAFFE A B,PALMER K.Environmental regulation and innovation:apanel data study[J].Review of Economics and Statistics,1997,79:610-619.
[6]AGHION P,DECHEZLEPRETRE A,HEMOUS D,et al.Carbon taxes,path dependency,and directed technical change:evidence from the auto industry[J].Journal of Political Economy,2016,124:1-51.
[7]CALEL R,DECHEZLEPRETRE A.Environmental policy and directed technological change:evidence from the European carbon market[J].Review of economics and statistics,2016,98:173-191.
[8]HAMAMOTO M.Environmental regulation and the productivity of Japanese manufacturing industries[J].Resource&Energy Economics,2006,28(4):299-312.
[9]ZHANG C,LIU H,BRESSERS H T A,et al.Productivity growth and environmental regulations-accounting for undesirable outputs:analysis of China's thirty provincial regions using the Malmquist-Luenberger index[J].Ecological Economics,2011,70:2369-2379.
[10]RASSIER D G,EARNHART D.Effects of environmental regulation on actual and expected profitability[J].Ecological Economics,2015,112:129-140.
[11]KNELLER R,MANDERSON E.Environmental regulations and innovation activity in UK manufacturing industries[J].Resource&Energy Economics,2012,34(2):211-235.
[12]XIE R,YUAN Y,HUANG J.Different types of environmental regulations and heterogeneous influence on"green"productivity:evidence from China[J].Ecological Economics,2017,132:104-112.
[13]CHENG Z,LI L,LIU J.The emissions reduction effect and technical progress effect of environmental regulation policy tools[J].Journal of Cleaner Production,2017,149:191-205.
[14]TESTA F,IRALDO F,FREY M.The effect of environmental regulation on firms'competitive performance:the case of the building&construction sector in some EU regions[J].Journal of Environmental Management,2011,92:2136.
[15]RENNINGS K,REXHAUSER S.Long-term impacts of environmental policy and eco-innovative activities of firms[J].International Journal of Technology,Policy and Management,2011,11:274-290.
[16]LEEUWEN G V,MOHNEN P.Revisiting the porter hypothesis:an empirical analysis of green innovation for the Netherlands[J].Economics of Innovation&New Technology,2016,67(2):295-319.
[17]ARROW K J.The economic implications of learning by doing[J].The Review of Economic Studies,1962,29:155-173.
[18]BODDE D L.Riding the experience curve[J].IEEE Engineering Management Review,2007,5(2):29-35.
[19]COHEN W,LEVINTHAL D.Innovation and learning:the two faces of R&D[J].The Economic Journal,1976(99):569-596.
[20]孙根年,李静,魏艳旭.环境学习曲线与我国碳减排目标的地区分解[J].环境科学研究,2011(24):1194-1202.
[21]韩亚芬,孙根年,李琦.中国省际SO2排放的环境学习曲线及减排潜力[J].环境科学研究,2008,21(3):201-206.
[22]YU S,ZHANG J,ZHENG S,et al.Provincial carbon intensity abatement potential estimation in China:a PSO-GA-optimized multi-factor environmental learning curve method[J].Energy Policy,2015,77:46-55.
[23]GUO F,ZHAO T,WANG Y,et al.Estimating the abatement potential of provincial carbon intensity based on the environmental learning curve model in China[J].Natural Hazards,2016(4):1-21.
[24]YU S,AGBEMABIESE L,ZHANG J.Estimating the carbon abatement potential of economic sectors in China[J].Applied Energy,2016,165:107-118.
[25]WANG W,YU B,YAO X,et al.Can technological learning significantly reduce industrial air pollutants intensity in China?---based on a multi-factor environmental learning curve[J].Journal of Cleaner Production,2018,185:137-147.
[26]GARDINER D,PORTNEY P R.Does environmental policy conflict with economic growth[J].Resources,2001,115:859-881.
[27]WRIGHT T P.Factors affecting the cost of airplanes[J].Journal of the Aeronautical Sciences,1936,3:122-128.
[28]CHEN J,QUW G.A new technological learning in China[J].Technovation,2003,23:861-867.
[29]YU C F,SARK W G J H,ALSEMA E A.Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects[J].Renewable&Sustainable Energy Reviews,2011,15:324-337.
[30]JARAMILLO P,MULLER N Z.Air pollution emissions and damages from energy production in the U.S.:2002-2011[J].Energy Policy,2016,90:202-211.
[31]魏巍贤,杨芳.技术进步对中国二氧化碳排放的影响[J].统计研究,2010,27(7):36-44.
[32]RUBIN E S,AZEVEDO I M L,JARAMILLO P,et al.Areview of learning rates for electricity supply technologies[J].Energy Policy,2015,86:198-218.
[33]WITAJEWSKI-BALTVILKS J,VERDOLINI E,TAVONIM.Bending the learning curve[J].Energy Economics,2015,52:S86-S99.
[34]EDWARDS J R,LAMBERT L S.Methods for integrating moderation and mediation:ageneral analytical framework using moderated path analysis[J].Psychological Methods,2007,12:1-22.
[35]JOHNSTONE N,MANAGI S,RODRIGUEZ M C,et al.Environmental policy design,innovation and efficiency gains in electricity generation[J].Energy Economics,2017,63:106-115.
[36]POPP D.Induced innovation and energy prices[J].American Economic Review,2002,92:160-180.
[37]吴延兵.自主研发、技术引进与生产率---基于中国地区工业的实证研究[J].经济研究,2008(8):51-64.
[38]NEMET G F.Beyond the learning curve:factors influencing cost reductions in photovoltaics[J].Energy Policy,2006,34:3218-3232.
[39]王书斌,徐盈之.环境规制与雾霾脱钩效应---基于企业投资偏好的视角[J].中国工业经济,2015(8):18-30.
[40]DECHEZLEPRETRE A,SATO M.The impacts of environmental regulations on competitiveness[J].Review of Environmental Economics and Policy,2017,11:183-206.
[41]ARIMURA T H,SUGINO M.The impact of environmental regulation on technological innovation:an assessment of the porter hypothesis with firm level environmental R&D data(innovation and sustainability)[J].Journal of Science Policy&Research Management,2009,23:201-211.
[42]BERCHICCI L.Towards an open R&D system:internal R&D investment,external knowledge acquisition and innovative performance[J].Research Policy,2013,42:117-127.
[43]张平,张鹏鹏,蔡国庆.不同类型环境规制对企业技术创新影响比较研究[J].中国人口·资源与环境,2016,26(4):8-13.