中国建筑业碳生产率变化驱动因素
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摘要
绿色发展要求下,中国建筑业碳生产率变化的驱动因素需要进行深入分析。本文测算了2005—2016年中国各省(市、区)各年的建筑业单要素碳生产率(SFCP)和全局全要素碳生产率(GTFCP),应用相关性检验实证了SFCP和GTFCP之间的关系,分别应用加和式对数平均迪氏指数分解方法 I(A-LMDI-I)和数据包络分析(DEA)分解方法对SFCP和GTFCP变化的驱动因素进行识别和分析。结果显示:①SFCP和GTFCP之间显著正相关。②技术创新正向驱动SFCP,地区调整负向驱动SFCP;2008—2011年是技术创新和地区调整对SFCP影响最大的时段;四川省的技术创新、广东省的地区调整对SFCP的影响最大。③技术进步正向驱动GTFCP,管理效率和规模效率负向驱动GTFCP;2011—2014年是技术进步和管理效率影响最大的时段;2005—2008年是规模效率对GTFCP影响最大的时段;江西的技术进步、海南的规模效率和贵州的管理效率对GTFCP的影响最大。基于以上结果总结出相应的管理启示和不足。
Under the requirements of green development, the driving factors for the change of carbon productivity in China's construction industry should be analyzed in great depth. This study measured single factor carbon productivity(SFCP) and global total factor carbon productivity(GTFCP) of the construction industry in China from 2005 to 2016. Correlation test was used to verify the relationship between SFCP and GTFCP, additive logarithmic mean Divisia index(ALMDI) method was applied to decompose the driving factors of SFCP changes, and data envelopment analysis(DEA) method was applied to decompose the driving factors of GTFCP changes. The results show that:(1) There is a significant positive correlation between SFCP and GTFCP.(2) Technological innovation was the positive driving force, and regional adjustment was the negative driving force of SFCP. Between 2008 and 2011, technological innovation and regional adjustment had the greatest impact on SFCP. Technological innovation in Sichuan Province and regional adjustment in Guangdong Province had the greatest impact on SFCP.(3) Technological progress was the positive driving force, and management efficiency and scale efficiency were the negative driving forces of GTFCP. Between 2011 and 2014, technological progress and management efficiency had the greatest impact on GTFCP. Between 2005 and 2008, scale efficiency had the greatest impact on GTFCP. Technological progress in Jiangxi Province, scale efficiency in Hainan Province, and management efficiency in Guizhou Province had the greatest impact on GTFCP. Based on the above conclusions, corresponding management implications and limitation were summarized.
Under the requirements of green development, the driving factors for the change of carbon productivity in China's construction industry should be analyzed in great depth. This study measured single factor carbon productivity(SFCP) and global total factor carbon productivity(GTFCP) of the construction industry in China from 2005 to 2016. Correlation test was used to verify the relationship between SFCP and GTFCP, additive logarithmic mean Divisia index(ALMDI) method was applied to decompose the driving factors of SFCP changes, and data envelopment analysis(DEA) method was applied to decompose the driving factors of GTFCP changes. The results show that:(1) There is a significant positive correlation between SFCP and GTFCP.(2) Technological innovation was the positive driving force, and regional adjustment was the negative driving force of SFCP. Between 2008 and 2011, technological innovation and regional adjustment had the greatest impact on SFCP. Technological innovation in Sichuan Province and regional adjustment in Guangdong Province had the greatest impact on SFCP.(3) Technological progress was the positive driving force, and management efficiency and scale efficiency were the negative driving forces of GTFCP. Between 2011 and 2014, technological progress and management efficiency had the greatest impact on GTFCP. Between 2005 and 2008, scale efficiency had the greatest impact on GTFCP. Technological progress in Jiangxi Province, scale efficiency in Hainan Province, and management efficiency in Guizhou Province had the greatest impact on GTFCP. Based on the above conclusions, corresponding management implications and limitation were summarized.
引文
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[5]张丽峰.基于DEA模型的全要素碳生产率与影响因素研究[J].工业技术经济,2013,(3):142-149.[Zhang L F.Research of total factor carbon productivity and influence factors based on the DEAmodel[J].Industrial Technological Economics,2013,(3):142-149.]
[6]Beinhocker E,Oppenheim J,Irons B,et al.The Carbon Productivity Challenge:Curbing Climate Change and Sustaining Economic Growth[R].Sydney:Mckinsey Global Institute,2008.
[7]李小平,王洋.“一带一路”沿线主要国家碳生产率收敛性及其影响因素分析[J].武汉大学学报(哲学社会科学版),2017,70(3):58-76.[Li X P,Wang Y.A study on the convergence of carbon productivity in the major countries of the Belt and Road and the analysis of its influencing factors[J].Wuhan University Journal(Social Science),2017,70(3):58-76.]
[8]中华人民共和国国家统计局.中华人民共和国2017年国民经济和社会发展统计公报[EB/OL].(2018-02-28)[2018-07-09].http://www.stats.gov.cn/tjsj/zxfb/201802/t20180228_1585631.html.[National Bureau of Statistics of the People’s Republic of China.The Statistical Bulletin of the People’s Republic of China on National Economic and Social Development in 2017[EB/OL].(2018-02-28)[2018-07-09].http://www.stats.gov.cn/tjsj/zxfb/201802/t20180228_1585631.html.]
[9]滕泽伟,胡宗彪,蒋西艳.中国服务业碳生产率变动的差异及收敛性研究[J].数量经济技术经济研究,2017,34(3):78-94.[Teng Z W,Hu Z B,Jiang X Y.Study on the difference and convergence of carbon productivity in China’s service industry[J].The Journal of Quantitative&Technical Economics,2017,34(3):78-94.]
[10]Wu Y,Chau K W,Lu W S,et al.Decoupling relationship between economic output and carbon emission in the Chinese construction industry[J].Environmental Impact Assessment Review,2018,71:60-69.
[11]冯博,王雪青.中国各省建筑业碳排放脱钩及影响因素研究[J].中国人口·资源与环境,2015,25(4):28-34.[Feng B,Wang X Q.Research on carbon decoupling effect and influence factors of provincial construction industry in China[J].China Population,Resources and Environment,2015,25(4):28-34.]
[12]Hu X C,Liu C L.Carbon productivity:A case study in the Australian construction industry[J].Journal of Cleaner Production,2016,112:2354-2362.
[13]杜强,陆欣然,冯新宇,等.中国各省建筑业碳排放特征及影响因素研究[J].资源开发与市场,2017,33(10):1201-1208.[Du Q,Lu X R,Feng X Y,et al.Provincial carbon emissions of China’s construction industry:Characteristics and influencing factors[J].Resource Development&Market,2017,33(10):1201-128.]
[14]罗剑,牟绍波,杨贵中.基于LMDIⅠ的我国建筑业动态竞争力实证研究[J].宏观经济研究,2017,(8):175-181.[Luo J,Mou SB,Yang G Z.An empirical study on the dynamic competitiveness of construction industry in China based on LMDI I[J].Macroeconomics,2017,(8):175-181.]
[15]Liang L F,Hu X C,Tivendale L,et al.The log mean divisia index based carbon productivity in the Australian construction industry[J].Construction Economics and Building,2017,17(3):68-84.
[16]赵良仕,孙才志.基于Global-Malmquist-Luenberger指数的中国水资源全要素生产率增长评价[J].资源科学,2013,35(6):1229-1237.[Zhao L S,Sun C Z.Water resource total factor productivity efficiency in China using the Global-Malmquist-Luenberger index[J].Resources Science,2013,35(6):1229-1237.]
[17]Feng C,Wang M.Analysis of energy efficiency and energy savings potential in China’s provincial industrial sectors[J].Journal of Cleaner Production,2017,164:1531-1541.
[18]Feng C,Wang M.The economy-wide energy efficiency in China’s regional building industry[J].Energy,2017,141:1869-1879.
[19]Liu C.Energy productivity and total-factor productivity in the Australian construction industry[J].Architectural Science Review,2015,99(5):1-13.
[20]Oh D H.A global Malmquist-Luenberger productivity index[J].Journal of Productivity Analysis,2010,34(3):183-197.
[21]Farrell M J.The measurement of productive efficiency[J].Journal of the Royal Statistical Society Series A(General),1957,120(3):253-290.
[22]Banker R D,Charnes A,Cooper W W.Some models for estimating technical and scale inefficiencies in data envelopment analysis[J].Management Science,1984,30(9):1078-1092.
[23]Meng M,Niu D X.Three-dimensional decomposition models for carbon productivity[J].Energy,2012,46(1):179-187.
[24]Ang B W,Choi K H.Decomposition of aggregate energy and gas emission intensities for industry:A refined divisia index method[J].Energy Journal,1997,18(3):59-73.
[25]Ang B W.Decomposition methodology in industrial energy demand analysis[J].Energy,1995,20(11):1081-1095.
[26]Zhang P W,You J X,Jia G S,et al.Estimation of carbon efficiency decomposition in materials and potential material savings for China’s construction industry[J].Resources Policy,2018,59:148-159.
[27]周媛,郑丽凤,周新年,等.基于行业标准的木材生产作业系统碳排放[J].北华大学学报(自然科学版),2014,15(6):815-820.[Zhou Y,Zheng L F,Zhou X N,et al.Carbon emission of timber production operating system based on industry standards[J].Journal of Beihua University(Natural Science),2014,15(6):815-820.]
[28]严玉廷,刘晶茹,丁宁,等.中国平板玻璃生产碳排放研究[J].环境科学学报,2017,37(8):3213-3219.[Yan Y T,Liu J R,Ding N,et al.Investigation on CO2emissions from flat glass production in China[J].Acta Scientiae Circumstantiae,2017,37(8):3213-3219.]
[29]Gao T M,Shen L,Shen M,et al.Evolution and projection of CO2emissions for China’s cement industry from 1980 to 2020[J].Renewable&Sustainable Energy Reviews,2017,74:522-537.
[30]Hao H,Geng Y,Hang W.GHG emissions from primary aluminum production in China:Regional disparity and policy implications[J].Applied Energy,2016,166:264-272.
[31]Jing R,Cheng J C P,Gan V J L,et al.Comparison of greenhouse gas emission accounting methods for steel production in China[J].Journal of Cleaner Production,2014,83:165-172.
[32]王曦,陆荣.危机下四万亿投资计划的短期作用与长期影响[J].中山大学学报(社会科学版),2009,49(4):180-188.[Wang X,Lu R.Four trillion investment plan under crisis:Short-term effects and long-term influence[J].Journal of Sun Yatsen University(Social Science Edition),2009,49(4):180-188.]
[33]Li W,Sun W,Li G M,et al.Temporal and spatial heterogeneity of carbon intensity in China’s construction industry[J].Resources,Conservation and Recycling,2017,126:162-173.
(1)2011年,国家发展和改革委员会应对气候变化司制定,详见http://cdm.ccchina.org.cn/WebSite/CDM/UpFile/File2720.pdf。
(2)2011年7月,国务院机关事务管理局制定,国家统计局审批。
(3)2006年,政府间气候变化专门委员会(IPCC)制定。
[2]唐志鹏,刘卫东,宋涛.基于混合地理加权回归的中国省域碳生产率影响因素分析[J].资源科学,2017,39(12):2223-2232.[Tang Z P,Liu W D,Song T.Factors affecting China’s provincial carbon productivity based on mixed geographically weighted regression modeling[J].Resources Science,2017,39(12):2223-2232.]
[3]Kaya Y,Yokobori K.Environment,Energy,and Economy:Strategies for Sustainability[M].Tokyo:United Nations University Press,1997.
[4]张成,王建科,史文悦,等.中国区域碳生产率波动的因素分解[J].中国人口·资源与环境,2014,24(10):41-47.[Zhang C,Wang J K,Shi W Y,et al.Decomposition on the fluctuation of China’s regional carbon productivity growth[J].China Population,Resources and Environment,2014,24(10):41-47.]
[5]张丽峰.基于DEA模型的全要素碳生产率与影响因素研究[J].工业技术经济,2013,(3):142-149.[Zhang L F.Research of total factor carbon productivity and influence factors based on the DEAmodel[J].Industrial Technological Economics,2013,(3):142-149.]
[6]Beinhocker E,Oppenheim J,Irons B,et al.The Carbon Productivity Challenge:Curbing Climate Change and Sustaining Economic Growth[R].Sydney:Mckinsey Global Institute,2008.
[7]李小平,王洋.“一带一路”沿线主要国家碳生产率收敛性及其影响因素分析[J].武汉大学学报(哲学社会科学版),2017,70(3):58-76.[Li X P,Wang Y.A study on the convergence of carbon productivity in the major countries of the Belt and Road and the analysis of its influencing factors[J].Wuhan University Journal(Social Science),2017,70(3):58-76.]
[8]中华人民共和国国家统计局.中华人民共和国2017年国民经济和社会发展统计公报[EB/OL].(2018-02-28)[2018-07-09].http://www.stats.gov.cn/tjsj/zxfb/201802/t20180228_1585631.html.[National Bureau of Statistics of the People’s Republic of China.The Statistical Bulletin of the People’s Republic of China on National Economic and Social Development in 2017[EB/OL].(2018-02-28)[2018-07-09].http://www.stats.gov.cn/tjsj/zxfb/201802/t20180228_1585631.html.]
[9]滕泽伟,胡宗彪,蒋西艳.中国服务业碳生产率变动的差异及收敛性研究[J].数量经济技术经济研究,2017,34(3):78-94.[Teng Z W,Hu Z B,Jiang X Y.Study on the difference and convergence of carbon productivity in China’s service industry[J].The Journal of Quantitative&Technical Economics,2017,34(3):78-94.]
[10]Wu Y,Chau K W,Lu W S,et al.Decoupling relationship between economic output and carbon emission in the Chinese construction industry[J].Environmental Impact Assessment Review,2018,71:60-69.
[11]冯博,王雪青.中国各省建筑业碳排放脱钩及影响因素研究[J].中国人口·资源与环境,2015,25(4):28-34.[Feng B,Wang X Q.Research on carbon decoupling effect and influence factors of provincial construction industry in China[J].China Population,Resources and Environment,2015,25(4):28-34.]
[12]Hu X C,Liu C L.Carbon productivity:A case study in the Australian construction industry[J].Journal of Cleaner Production,2016,112:2354-2362.
[13]杜强,陆欣然,冯新宇,等.中国各省建筑业碳排放特征及影响因素研究[J].资源开发与市场,2017,33(10):1201-1208.[Du Q,Lu X R,Feng X Y,et al.Provincial carbon emissions of China’s construction industry:Characteristics and influencing factors[J].Resource Development&Market,2017,33(10):1201-128.]
[14]罗剑,牟绍波,杨贵中.基于LMDIⅠ的我国建筑业动态竞争力实证研究[J].宏观经济研究,2017,(8):175-181.[Luo J,Mou SB,Yang G Z.An empirical study on the dynamic competitiveness of construction industry in China based on LMDI I[J].Macroeconomics,2017,(8):175-181.]
[15]Liang L F,Hu X C,Tivendale L,et al.The log mean divisia index based carbon productivity in the Australian construction industry[J].Construction Economics and Building,2017,17(3):68-84.
[16]赵良仕,孙才志.基于Global-Malmquist-Luenberger指数的中国水资源全要素生产率增长评价[J].资源科学,2013,35(6):1229-1237.[Zhao L S,Sun C Z.Water resource total factor productivity efficiency in China using the Global-Malmquist-Luenberger index[J].Resources Science,2013,35(6):1229-1237.]
[17]Feng C,Wang M.Analysis of energy efficiency and energy savings potential in China’s provincial industrial sectors[J].Journal of Cleaner Production,2017,164:1531-1541.
[18]Feng C,Wang M.The economy-wide energy efficiency in China’s regional building industry[J].Energy,2017,141:1869-1879.
[19]Liu C.Energy productivity and total-factor productivity in the Australian construction industry[J].Architectural Science Review,2015,99(5):1-13.
[20]Oh D H.A global Malmquist-Luenberger productivity index[J].Journal of Productivity Analysis,2010,34(3):183-197.
[21]Farrell M J.The measurement of productive efficiency[J].Journal of the Royal Statistical Society Series A(General),1957,120(3):253-290.
[22]Banker R D,Charnes A,Cooper W W.Some models for estimating technical and scale inefficiencies in data envelopment analysis[J].Management Science,1984,30(9):1078-1092.
[23]Meng M,Niu D X.Three-dimensional decomposition models for carbon productivity[J].Energy,2012,46(1):179-187.
[24]Ang B W,Choi K H.Decomposition of aggregate energy and gas emission intensities for industry:A refined divisia index method[J].Energy Journal,1997,18(3):59-73.
[25]Ang B W.Decomposition methodology in industrial energy demand analysis[J].Energy,1995,20(11):1081-1095.
[26]Zhang P W,You J X,Jia G S,et al.Estimation of carbon efficiency decomposition in materials and potential material savings for China’s construction industry[J].Resources Policy,2018,59:148-159.
[27]周媛,郑丽凤,周新年,等.基于行业标准的木材生产作业系统碳排放[J].北华大学学报(自然科学版),2014,15(6):815-820.[Zhou Y,Zheng L F,Zhou X N,et al.Carbon emission of timber production operating system based on industry standards[J].Journal of Beihua University(Natural Science),2014,15(6):815-820.]
[28]严玉廷,刘晶茹,丁宁,等.中国平板玻璃生产碳排放研究[J].环境科学学报,2017,37(8):3213-3219.[Yan Y T,Liu J R,Ding N,et al.Investigation on CO2emissions from flat glass production in China[J].Acta Scientiae Circumstantiae,2017,37(8):3213-3219.]
[29]Gao T M,Shen L,Shen M,et al.Evolution and projection of CO2emissions for China’s cement industry from 1980 to 2020[J].Renewable&Sustainable Energy Reviews,2017,74:522-537.
[30]Hao H,Geng Y,Hang W.GHG emissions from primary aluminum production in China:Regional disparity and policy implications[J].Applied Energy,2016,166:264-272.
[31]Jing R,Cheng J C P,Gan V J L,et al.Comparison of greenhouse gas emission accounting methods for steel production in China[J].Journal of Cleaner Production,2014,83:165-172.
[32]王曦,陆荣.危机下四万亿投资计划的短期作用与长期影响[J].中山大学学报(社会科学版),2009,49(4):180-188.[Wang X,Lu R.Four trillion investment plan under crisis:Short-term effects and long-term influence[J].Journal of Sun Yatsen University(Social Science Edition),2009,49(4):180-188.]
[33]Li W,Sun W,Li G M,et al.Temporal and spatial heterogeneity of carbon intensity in China’s construction industry[J].Resources,Conservation and Recycling,2017,126:162-173.
(1)2011年,国家发展和改革委员会应对气候变化司制定,详见http://cdm.ccchina.org.cn/WebSite/CDM/UpFile/File2720.pdf。
(2)2011年7月,国务院机关事务管理局制定,国家统计局审批。
(3)2006年,政府间气候变化专门委员会(IPCC)制定。