节能减排背景下长三角制造业生产率与产业结构的门限研究
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摘要
采用面板数据分析方法,将制造业按结构属性分组考察了生产率与能源、环境的关系及门限效应。研究发现,资本和技术密集型行业的能耗系数为正、环境系数为负。劳动密集型行业的能耗系数不稳定。结果表明,在密集型行业分类组别下,在资本和出口交货门限范围之内,资本密集和技术密集型行业能源影响为正,环境影响为负,且影响程度大,超越门限范围则影响程度减小,在外资占比门限条件下,两类行业能耗、环境系数表现为超越门限后统计显著。劳动密集型行业存在在一定门限范围内环境影响为正的情况。区域分组后,在行业出口交货值门限下上海和浙江表现为能源为正、环境为负,且小于门限时影响程度最大。外资比例江苏与上海在一定门限区间内,能源为正,环境为负向影响,且两个系数在整个区间内最大,浙江则表现为低于第一门限时,能耗和环境影响的显著且均为正的特点。资本额门限条件下,江苏表现为能耗为正、环境为负,且资本大于门限值时,影响最大;浙江在第一和第二门限之间时,仅能源影响显著系数为正。
In this paper,the panel data method was used to group the structural attributes of manufacturing industry and to study the threshold effect and relationship between productivity,energy,and environment.The study found that in capital and technical intensive industry,the coefficient of energy consumption was positive while the coefficient of environment was negative,and the energy consumption coefficient of labor-intensive industry was unstable.The results of the threshold effects were shown as follows:under the category of intensive-industry and within the threshold of capital and export delivery,the energy impact,in the capital-intensive and technology-intensive industries,was largely positive while the environment impact was largely negative,and the influence was reduced when the threshold was exceeded;under the threshold on foreign investment ratio,the two industries' energy consumption and environmental factors were statistically significant beyond the threshold.Within a certain threshold,the environmental impact of labor-intensive industries was positive.Under the threshold of industry export delivery value,Shanghai and Zhejiang showed positive energy and negative environment impacts,and the impact was the greatest within threshold after regional grouping.Within a certain threshold on the foreign investment,the energy impact of Jiangsu and Shanghai was positive while the environment one was negative,both of which were the highest in the whole interval.And the foreign investment in Zhejiang was below the first threshold characterized by the significantly positive energy consumption and environmental impacts.Under the threshold of capital,the impact of energy consumption in Jiangsu was positive while the environment was negative,both of which was the largest when the capital was beyond the threshold.When the capital of Zhejiang manufacture industry was between the first and second thresholds,only the coefficient of energy influence was significantly positive.
In this paper,the panel data method was used to group the structural attributes of manufacturing industry and to study the threshold effect and relationship between productivity,energy,and environment.The study found that in capital and technical intensive industry,the coefficient of energy consumption was positive while the coefficient of environment was negative,and the energy consumption coefficient of labor-intensive industry was unstable.The results of the threshold effects were shown as follows:under the category of intensive-industry and within the threshold of capital and export delivery,the energy impact,in the capital-intensive and technology-intensive industries,was largely positive while the environment impact was largely negative,and the influence was reduced when the threshold was exceeded;under the threshold on foreign investment ratio,the two industries' energy consumption and environmental factors were statistically significant beyond the threshold.Within a certain threshold,the environmental impact of labor-intensive industries was positive.Under the threshold of industry export delivery value,Shanghai and Zhejiang showed positive energy and negative environment impacts,and the impact was the greatest within threshold after regional grouping.Within a certain threshold on the foreign investment,the energy impact of Jiangsu and Shanghai was positive while the environment one was negative,both of which were the highest in the whole interval.And the foreign investment in Zhejiang was below the first threshold characterized by the significantly positive energy consumption and environmental impacts.Under the threshold of capital,the impact of energy consumption in Jiangsu was positive while the environment was negative,both of which was the largest when the capital was beyond the threshold.When the capital of Zhejiang manufacture industry was between the first and second thresholds,only the coefficient of energy influence was significantly positive.
引文
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[14]林伯强.电力消费与中国经济增长:基于生产函数的研究[J].管理世界,2003,(11):18-27.
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[16]魏楚,沈满洪.能源效率及其影响因素:DEA的实证分析[J].管理世界,2007,(8):66-75.
[17]王群伟,周德群.中国全要素能源效率变动的实证研究[J].系统工程,2008,(7):74-80.
[18]王玲.节能减排、全要素能源生产率及行业异质性研究[J].当代财经,2013,(10):5-16.
[19]魏一鸣.中国能源报告[M].北京:科学出版社,2006.
[20]董锋,谭清美,周德群,等.技术进步对能源效率的影响——基于考虑环境因素的全要素生产率指数和面板计量分析[J].科学学与科学技术管理,2010,31(6):53-58.
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[22]袁晓玲,张宝山,杨万平.基于环境污染的中国全要素能源效率研究[J].中国工业经济,2009,(2):76-86.
[23]王维国,范丹.中国区域全要素能源效率收敛性及影响因素分析——基于Malmqulist-Luenberger指数法[J].资源科学,2012,(10):16-24.
[24]Tone K.A slacks-based measure of efficiency in data envelopment analysis[J].European Journal of Operational Research, 2001, 130(3):498-509.
[25]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.
[26]Raymond E Miles, Charles C Snow.Organizational Strategy, Structure, and Process [J].The Academy of Management Review, 1978,3(3):546-562.
[27]王文普.环境规制.空间溢出与地区产业竞争力[J].中国人口·资源与环境,2013,23(8):123-130.
[28]浙江统计局.浙江科技统计年鉴[M].杭州: 浙江统计出版社,2005-2017.
[29]上海统计局.上海科技统计年鉴[M].上海: 上海统计出版社,2005-2017.
[30]国家统计局.中国环境统计年鉴[M].北京: 中国统计出版社,2005-2017.
[31]国家统计局.中国能源统计年鉴[M].北京: 中国统计出版社,2005-2016.
[32]国家统计局.中国工业统计年鉴[M].北京: 中国统计出版社,2005-2017.
[33]约翰M波利梅尼,真弓浩三.杰文斯悖论:技术进步能解决资源难题吗[M].上海:上海世纪出版集团,2014.
[34]韩纪琴,夏梦.环境规制对产业竞争力影响的研究——基于江苏制造业数据的分析[J].价格理论与实践,2018,(8):135-138.
[35]郝晓艳,吴学花.环境规制对中国制造业全要素生产率的影响研究[J].特区经济,2018,(9):32-35.
[36]张海洋,金则杨.中国工业TFP的新产品动能变化研究[J].经济研究,2017,52(9):72-85.
[37]李金凯,张同斌.中国城市生产率增长中FDI的分层影响和非对称效应研究[J].产业经济研究,2018,(4):14-25.
[38]Hansen B E.Threshold effects in non-dynamic panels:Estimation, testing, and inference [J].Journal of Econometrics,1999,93(2):345-368.
(1)因篇幅问题,生产率的结果及计算过程不在文中列示,如有需要,请向作者索取。
(2)该研究将环境排放作为坏的产出带入生产率计算模型。
(3)该研究的高分位数城市即为经济发达城市,长三角大部分城市属于其覆盖范围。
[2]Singh,Lakhwinder.Technological Progress, Structural Change and Productivity Growth in Manufacturing Sector of South Korea[J].World Review of Science Technology & Sustainable Development,2004,1(1):37-49.
[3]Timmer M.The dynamics of Asian manufacturing[M].Edward Elgar,2000.
[4]郑玉歆.80年代中国制造业生产率变动及其来源[M]北京:社会科学文献出版社,1992
[5]吕铁.制造业结构变化对生产率增长的影响研究[J].管理世界,2002,(2):87-94.
[6]干春晖,郑若谷.改革开放以来产业结构演进与生产率增长研究——对中国1978—2007年“结构红利假说”的检验[J].中国工业经济,2009,(2):55-65.
[7]HSIEH Changtai,Peter J Klenow.Development Accounting[J].American Economic Journal:Macroeconomics,2010,2(1):207-223.
[8]Chen S, Jefferson G H, Zhang J.Structural change, productivity growth and industrial transformation in China [J].China Economic Review,2011,22(1):133-150.
[9]栾大鹏,欧阳日辉.生产要素内部投入结构与中国经济增长[J].世界经济,2012,35(6):78-92.
[10]张少辉.产业结构调控与中国区域全要素生产率增长[J].管理学报,2014,(6):898-904.
[11]Gollop M,Roberts M J.Cost-Minimizing Regulation of Sulfur Emissions:Regional Gains in Electric Power[J].Review of Economics and Statistics,1985,(67):81-90.
[12]Coggins J S,Swinton J R.The Price of Pollution:A Dual Approach to Valuing SO2 Allowances[J].Journal of Environmental Economics and Management,1996,30(1):58-72.
[13]陈诗一.节能减排与中国工业的双赢发展:2009—2049[J].经济研究,2010,(3):129-144.
[14]林伯强.电力消费与中国经济增长:基于生产函数的研究[J].管理世界,2003,(11):18-27.
[15]Hu J L,Wang,S C.Total factor energy efficiency of regions in China [J].Energy Policy, 2006, 34(17): 3206-3217.
[16]魏楚,沈满洪.能源效率及其影响因素:DEA的实证分析[J].管理世界,2007,(8):66-75.
[17]王群伟,周德群.中国全要素能源效率变动的实证研究[J].系统工程,2008,(7):74-80.
[18]王玲.节能减排、全要素能源生产率及行业异质性研究[J].当代财经,2013,(10):5-16.
[19]魏一鸣.中国能源报告[M].北京:科学出版社,2006.
[20]董锋,谭清美,周德群,等.技术进步对能源效率的影响——基于考虑环境因素的全要素生产率指数和面板计量分析[J].科学学与科学技术管理,2010,31(6):53-58.
[21]段文斌,余泳泽.全要素生产率增长有利于提升我国能源效率吗?——基于35个工业行业面板数据的实证研究[J].产业经济研究,2011,(4):78-89.
[22]袁晓玲,张宝山,杨万平.基于环境污染的中国全要素能源效率研究[J].中国工业经济,2009,(2):76-86.
[23]王维国,范丹.中国区域全要素能源效率收敛性及影响因素分析——基于Malmqulist-Luenberger指数法[J].资源科学,2012,(10):16-24.
[24]Tone K.A slacks-based measure of efficiency in data envelopment analysis[J].European Journal of Operational Research, 2001, 130(3):498-509.
[25]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.
[26]Raymond E Miles, Charles C Snow.Organizational Strategy, Structure, and Process [J].The Academy of Management Review, 1978,3(3):546-562.
[27]王文普.环境规制.空间溢出与地区产业竞争力[J].中国人口·资源与环境,2013,23(8):123-130.
[28]浙江统计局.浙江科技统计年鉴[M].杭州: 浙江统计出版社,2005-2017.
[29]上海统计局.上海科技统计年鉴[M].上海: 上海统计出版社,2005-2017.
[30]国家统计局.中国环境统计年鉴[M].北京: 中国统计出版社,2005-2017.
[31]国家统计局.中国能源统计年鉴[M].北京: 中国统计出版社,2005-2016.
[32]国家统计局.中国工业统计年鉴[M].北京: 中国统计出版社,2005-2017.
[33]约翰M波利梅尼,真弓浩三.杰文斯悖论:技术进步能解决资源难题吗[M].上海:上海世纪出版集团,2014.
[34]韩纪琴,夏梦.环境规制对产业竞争力影响的研究——基于江苏制造业数据的分析[J].价格理论与实践,2018,(8):135-138.
[35]郝晓艳,吴学花.环境规制对中国制造业全要素生产率的影响研究[J].特区经济,2018,(9):32-35.
[36]张海洋,金则杨.中国工业TFP的新产品动能变化研究[J].经济研究,2017,52(9):72-85.
[37]李金凯,张同斌.中国城市生产率增长中FDI的分层影响和非对称效应研究[J].产业经济研究,2018,(4):14-25.
[38]Hansen B E.Threshold effects in non-dynamic panels:Estimation, testing, and inference [J].Journal of Econometrics,1999,93(2):345-368.
(1)因篇幅问题,生产率的结果及计算过程不在文中列示,如有需要,请向作者索取。
(2)该研究将环境排放作为坏的产出带入生产率计算模型。
(3)该研究的高分位数城市即为经济发达城市,长三角大部分城市属于其覆盖范围。