浙江省大气环境效率评价及区域差异
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摘要
合理评估区域大气环境效率是落实污染物减排政策和提升环境管理水平的关键环节,基于Malmquist指数的非径向DEA模型,从静态和动态2个维度测算了2006—2015年浙江省11个城市的大气环境效率及区域差异。结果表明,在2006—2015年间,浙江省大气环境静态效率的平均值为0. 592 4,污染减排治理的潜力依然巨大。浙江省大气环境动态效率实现了年均6. 47%、累计75. 81%的增长,且增速存在显著城市差异,杭州最快,宁波、嘉兴次之;大气环境效率的提升主要由技术进步和规模效率扩大的"双轮驱动"影响。11个城市在4种高低环境效率矩阵中的分布数量相对均匀,没有出现H/H、L/L两极分化的"马太效应"。未来,需充分考虑到不同城市的实际状况,制定差异化的大气污染防治措施,有效提升大气环境效率。
This paper is inclined to calculate and work out the atmospheric environmental efficiency and its regional differences in Zhejiang Province and its 11 cities during the period from 2006 to 2015 from the point of view both of static and dynamic dimensions And,for the said purpose,we have done a reasonable evaluation of the regional atmospheric environmental efficiency based on the non-radical directional distance function of the DEA model. As compared with the currently adopted achievements,the atmospheric environmental efficiency evaluation system constructed in this paper has not only taken into account of the development of the regional economy,but also focused on the air quality output,so as to constrain the input of the atmospheric environmental pollutant emissions. Thus,the results of the above mentioned environmental pollutant emission calculations indicate that the average value of the static efficiency of the atmospheric environment in Zhejiang is equal to 0. 592 4 in the past decade with a 41 percentage difference from the production frontier. It also means that there reamins a huge improvement space of pollution reduction and control. What is more,the pure technical efficiency can also be taken as the main factor for regulating the static efficiency in improving the atmospheric environment in the province. Besides,the dynamic efficiency of the atmospheric environment in the province has reached an average annual rate of6. 47%,with a cumulative increase of 75. 81%. And,needless to say,there still exist significant urban differences in the growth rate,the fastest example can be said in Hangzhou,which is follwoed by Ningbo and Jiaxing. However,the atmospheric environmental efficiency has been mainly affected by the technical and technological progress and the scale efficiency expansion. Although the distribution of the 11 cities in the 4 high and low environmental efficiency matrices seem to be relatively uniform,there remains no "Matthew Effect " of H/H or L/L polarization.Therefore,it is necessary to take into full account the actual and potential conditions of the different cities,so as to take different measures in accordance with the actual needs of the province in the future. For,it is only by strengthening the environmental management exchanges and collaboration among the different urban and rural areas that would be possible to control the atmospheric pollution more effectively and,in turn,heighten the overall atmospheric environment control level and promote the efficiency.
This paper is inclined to calculate and work out the atmospheric environmental efficiency and its regional differences in Zhejiang Province and its 11 cities during the period from 2006 to 2015 from the point of view both of static and dynamic dimensions And,for the said purpose,we have done a reasonable evaluation of the regional atmospheric environmental efficiency based on the non-radical directional distance function of the DEA model. As compared with the currently adopted achievements,the atmospheric environmental efficiency evaluation system constructed in this paper has not only taken into account of the development of the regional economy,but also focused on the air quality output,so as to constrain the input of the atmospheric environmental pollutant emissions. Thus,the results of the above mentioned environmental pollutant emission calculations indicate that the average value of the static efficiency of the atmospheric environment in Zhejiang is equal to 0. 592 4 in the past decade with a 41 percentage difference from the production frontier. It also means that there reamins a huge improvement space of pollution reduction and control. What is more,the pure technical efficiency can also be taken as the main factor for regulating the static efficiency in improving the atmospheric environment in the province. Besides,the dynamic efficiency of the atmospheric environment in the province has reached an average annual rate of6. 47%,with a cumulative increase of 75. 81%. And,needless to say,there still exist significant urban differences in the growth rate,the fastest example can be said in Hangzhou,which is follwoed by Ningbo and Jiaxing. However,the atmospheric environmental efficiency has been mainly affected by the technical and technological progress and the scale efficiency expansion. Although the distribution of the 11 cities in the 4 high and low environmental efficiency matrices seem to be relatively uniform,there remains no "Matthew Effect " of H/H or L/L polarization.Therefore,it is necessary to take into full account the actual and potential conditions of the different cities,so as to take different measures in accordance with the actual needs of the province in the future. For,it is only by strengthening the environmental management exchanges and collaboration among the different urban and rural areas that would be possible to control the atmospheric pollution more effectively and,in turn,heighten the overall atmospheric environment control level and promote the efficiency.
引文
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[3] WANG K,WEI Y M,HUANG Z. Environmental efficiency and abatement efficiency measurements of China's thermal power industry:a data envelopment analysis based materials balance approach[J]. European Journal of Operational Research,2018,269(1):35-50.
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[12] WANG Bo(王波),ZHANG Qun(张群). Analysis of various firm productive efficiency with environmental constraints[J]. Systems Engineering-Theory&Practice(系统工程理论与实践),2002(1):1-8.
[13] WANG Keliang(汪克亮),YANG Li(杨力),MENG Xiangrui(孟祥瑞). Spatial differences,dynamic evolution and driving mechanism of China’s air environmental performance—an empirical analysis based on provincial panel data during 2006-2014[J]. Journal of Shanxi University of Finance and Economics(山西财经大学学报),2016,38(9):357-364.
[14] WANG Keliang(汪克亮),WANG Dandan(王丹丹),MENG Xiangrui(孟祥瑞). Heterogeneous technology,technology gap and China’s regional air environmental efficiency[J]. East China Economic Management(华东经济管理),2017,31(5):48-55.
[15] XIE H,SHEN M,WEI C. Technical efficiency,shadow price and substitutability of Chinese industrial SO2emissions:a parametric approach[J]. Journal of Cleaner Production,2016,112:1386-1394.
[16] WANG Keliang(汪克亮),MENG Xiangrui(孟祥瑞),YANG Li(杨力),et al. The regional differences,changing trends and causes decomposition of atmospheric pollution emissions efficiency of China’s major industrial provinces[J]. China Environmental Science(中国环境科学),2017,37(3):888-898.
[17] WANG Keliang(汪克亮),MENG Xiangrui(孟祥瑞),YANG Baochen(杨宝臣),et al. Regional differences and influencing factors of China’s air pollution emission efficiency considering technological heterogeneity[J]. China Population,Resources and Environment(中国人口·资源与环境),2017,27(1):101-110.
[18] PERKINS R,NEUMAYER E. Fostering environment efficiency through transnational linkages? Trajectories of CO2and SO2,1980-2000[J]. Environment and Planning A,2008,40(12):2970-2989.
[19] HU J L,WANG S C. Total-factor energy efficiency of regions in China[J]. Energy Policy,2006,34(17):3206-3217.
[20] LI L B,HU J L. Ecological total-factor energy efficiency of regions in China[J]. Energy Policy,2012,46:216-224.
[21] CHARNES A,COOPER W W,RHODES E. Measuring the efficiency of decision making units[J]. European Journal of Operational Research,1978,2(6):429-444.
[22] TONE K. A slacks-based measure of efficiency in data envelopment analysis[J]. European Journal of Operational Research,2001,130(3):498-509.
[23] TONE K. A slacks-based measure of super-efficiency in data envelopment analysis[J]. European Journal of Operational Research,2002,143(1),32-41.
[24] FANG H H,LEE H S,HWANG S N,et al. A slacksbased measure of super-efficiency in data envelopment analysis:an alternative approach[J]. Omega,2013,41(4):731-734.
[25] FARE R,GROSSKOPF S,NORRIS M,et al. Productivity growth,technical progress,and efficiency change in industrialized countries[J]. American Economic Review,1994,84(1):66-83.
[26] HUANG J,DU D,HAO Y. The driving forces of the change in China's energy intensity:an empirical research using DEA-Malmquist and spatial panel estimations[J].Economic Modelling,2017,65:41-50.
[27] KAPELO M,HORTA I M,CAMANHO A S,et al.Measurement of input-specific productivity growth with an application to the construction industry in Spain and Portugal[J]. International Journal of Production Economics,2015,166:64-71.
[28] WANG Bing(王兵),WU Yanrui(吴延瑞),YAN Pengfei(颜鹏飞). Environmental efficiency and environmental total factor productivity growth in China’s regional economies[J]. Economic Research Journal(经济研究),2010,45(5):95-109.
[29] WANG Junneng(王俊能),XU Zhencheng(许振成),HU Xibang(胡习邦),et al. Analysis of environmental efficiencies and their changes in China based on DEA theory[J]. China Environmental Science(中国环境科学),2010,30(4):565-570.
[30] HE Wei(何为),LIU Changyi(刘昌义),GUO Shulong(郭树龙). Empirical study on evaluation and determinants of atmospheric environmentalefficiency of Tianjin[J]. Journal of Arid Land Resources and Environment(干旱区资源与环境),2016,30(1):31-35.
[31] DING Lei(丁镭),LIU Chao(刘超),HUANG Yalin(黄亚林),et al. Spatial and temporal characteristics of urban ambient air quality and its main influence factors in Hubei Province[J]. Economic Geography(经济地理),2016,36(3):170-178.
[32] BANER R D,THRALL R M. Estimation of returns to scale using data envelopment analysis[J]. European Journal of Operational Research,1992,62(1):74-84.
[33] CAVES D W,CHRISTENSEN L R,DIEWERT W E.Multilateral comparisons of output,input,and productivity using superlative index numbers[J]. The Economic Journal,1982,92(365):73-86.
[34] CHEN Y,ALI A I. DEA Malmquist productivity measure:new insights with an application to computer industry[J]. European Journal of Operational Research,2004,159(1):239-249.
[35] KLUMPP M. Do forwarders improve sustainability efficiency? Evidence from a European DEA Malmquist index calculation[J]. Sustainability,2017,9(5):842.
[2] REINHARD S,LOVELL C A K,THIJSSEN G J. Environmental efficiency with multiple environmentally detrimental variables; estimated with SFA and DEA[J]. European Journal of Operational Research,2000,121(2):287-303.
[3] WANG K,WEI Y M,HUANG Z. Environmental efficiency and abatement efficiency measurements of China's thermal power industry:a data envelopment analysis based materials balance approach[J]. European Journal of Operational Research,2018,269(1):35-50.
[4] WANG Qi(王奇),LI Mingquan(李明全). Study on air pollution abatement efficiency of China by using DEA[J].China Environmental Science(中国环境科学),2012,32(5):942-946.
[5] WANG Keliang(汪克亮),SHI Lijuan(史利娟),LIU Lei(刘蕾),et al. Study on the temporal-spatial heterogeneity and driving factors of air environmental efficiency for Yangtze River economic zone[J]. Resources and Environment in the Yangtze Basin(长江流域资源与环境),2018,27(3):453-462.
[6] WANG Keliang(汪克亮),MENG Xiangrui(孟祥瑞),YANG Baochen(杨宝臣),et al. Study on the heterogeneity,dynamic evolution and cause recognition of China’s regional air environmental efficiency[J]. Statistics&Information Forum(统计与信息论坛),2017,32(6):55-63
[7] LEE T,YEO G T,THAI V V. Environmental efficiency analysis of port cities:slacks-based measure data envelopment analysis approach[J]. Transport Policy,2014,33:82-88.
[8] ZOFIO J L,PRIETO A M. Environmental efficiency and regulatory standards:the case of CO2emissions from OECD industries[J]. Resource and Energy Economics,2001,23(1):63-83.
[9] ZHANG J,ZENG W,WANG J,et al. Regional low-carbon economy efficiency in China:analysis based on the Super-SBM model with CO2emissions[J]. Journal of Cleaner Production,2017,163:202-211.
[10] WANG Keliang(汪克亮),MENG Xiangrui(孟祥瑞),YANG Baochen(杨宝臣),et al. Study on the atmospheric environmental performance of China’s regional economic development[J]. The Journal of Quantitative&Technical Economics(数量经济技术经济研究),2016,33(11):59-76.
[11] HE Q,HAN J,GUAN D,et al. The comprehensive environmental efficiency of socioeconomic sectors in China:an analysis based on a non-separable bad output SBM[J]. Journal of Cleaner Production, 2018, 176:1091-1110.
[12] WANG Bo(王波),ZHANG Qun(张群). Analysis of various firm productive efficiency with environmental constraints[J]. Systems Engineering-Theory&Practice(系统工程理论与实践),2002(1):1-8.
[13] WANG Keliang(汪克亮),YANG Li(杨力),MENG Xiangrui(孟祥瑞). Spatial differences,dynamic evolution and driving mechanism of China’s air environmental performance—an empirical analysis based on provincial panel data during 2006-2014[J]. Journal of Shanxi University of Finance and Economics(山西财经大学学报),2016,38(9):357-364.
[14] WANG Keliang(汪克亮),WANG Dandan(王丹丹),MENG Xiangrui(孟祥瑞). Heterogeneous technology,technology gap and China’s regional air environmental efficiency[J]. East China Economic Management(华东经济管理),2017,31(5):48-55.
[15] XIE H,SHEN M,WEI C. Technical efficiency,shadow price and substitutability of Chinese industrial SO2emissions:a parametric approach[J]. Journal of Cleaner Production,2016,112:1386-1394.
[16] WANG Keliang(汪克亮),MENG Xiangrui(孟祥瑞),YANG Li(杨力),et al. The regional differences,changing trends and causes decomposition of atmospheric pollution emissions efficiency of China’s major industrial provinces[J]. China Environmental Science(中国环境科学),2017,37(3):888-898.
[17] WANG Keliang(汪克亮),MENG Xiangrui(孟祥瑞),YANG Baochen(杨宝臣),et al. Regional differences and influencing factors of China’s air pollution emission efficiency considering technological heterogeneity[J]. China Population,Resources and Environment(中国人口·资源与环境),2017,27(1):101-110.
[18] PERKINS R,NEUMAYER E. Fostering environment efficiency through transnational linkages? Trajectories of CO2and SO2,1980-2000[J]. Environment and Planning A,2008,40(12):2970-2989.
[19] HU J L,WANG S C. Total-factor energy efficiency of regions in China[J]. Energy Policy,2006,34(17):3206-3217.
[20] LI L B,HU J L. Ecological total-factor energy efficiency of regions in China[J]. Energy Policy,2012,46:216-224.
[21] CHARNES A,COOPER W W,RHODES E. Measuring the efficiency of decision making units[J]. European Journal of Operational Research,1978,2(6):429-444.
[22] TONE K. A slacks-based measure of efficiency in data envelopment analysis[J]. European Journal of Operational Research,2001,130(3):498-509.
[23] TONE K. A slacks-based measure of super-efficiency in data envelopment analysis[J]. European Journal of Operational Research,2002,143(1),32-41.
[24] FANG H H,LEE H S,HWANG S N,et al. A slacksbased measure of super-efficiency in data envelopment analysis:an alternative approach[J]. Omega,2013,41(4):731-734.
[25] FARE R,GROSSKOPF S,NORRIS M,et al. Productivity growth,technical progress,and efficiency change in industrialized countries[J]. American Economic Review,1994,84(1):66-83.
[26] HUANG J,DU D,HAO Y. The driving forces of the change in China's energy intensity:an empirical research using DEA-Malmquist and spatial panel estimations[J].Economic Modelling,2017,65:41-50.
[27] KAPELO M,HORTA I M,CAMANHO A S,et al.Measurement of input-specific productivity growth with an application to the construction industry in Spain and Portugal[J]. International Journal of Production Economics,2015,166:64-71.
[28] WANG Bing(王兵),WU Yanrui(吴延瑞),YAN Pengfei(颜鹏飞). Environmental efficiency and environmental total factor productivity growth in China’s regional economies[J]. Economic Research Journal(经济研究),2010,45(5):95-109.
[29] WANG Junneng(王俊能),XU Zhencheng(许振成),HU Xibang(胡习邦),et al. Analysis of environmental efficiencies and their changes in China based on DEA theory[J]. China Environmental Science(中国环境科学),2010,30(4):565-570.
[30] HE Wei(何为),LIU Changyi(刘昌义),GUO Shulong(郭树龙). Empirical study on evaluation and determinants of atmospheric environmentalefficiency of Tianjin[J]. Journal of Arid Land Resources and Environment(干旱区资源与环境),2016,30(1):31-35.
[31] DING Lei(丁镭),LIU Chao(刘超),HUANG Yalin(黄亚林),et al. Spatial and temporal characteristics of urban ambient air quality and its main influence factors in Hubei Province[J]. Economic Geography(经济地理),2016,36(3):170-178.
[32] BANER R D,THRALL R M. Estimation of returns to scale using data envelopment analysis[J]. European Journal of Operational Research,1992,62(1):74-84.
[33] CAVES D W,CHRISTENSEN L R,DIEWERT W E.Multilateral comparisons of output,input,and productivity using superlative index numbers[J]. The Economic Journal,1982,92(365):73-86.
[34] CHEN Y,ALI A I. DEA Malmquist productivity measure:new insights with an application to computer industry[J]. European Journal of Operational Research,2004,159(1):239-249.
[35] KLUMPP M. Do forwarders improve sustainability efficiency? Evidence from a European DEA Malmquist index calculation[J]. Sustainability,2017,9(5):842.
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