Industrial structural transformation and carbon dioxide emissions in China

被引:408
作者
Zhou, Xiaoyan [1 ]
Zhang, Jie [2 ]
Li, Junpeng [3 ]
机构
[1] Univ Int Business & Econ, Sch Business, Beijing 100029, Peoples R China
[2] Renmin Univ China, Inst Chinas Econ Reform & Dev, Beijing 100872, Peoples R China
[3] Columbia Univ, Dept Sociol, New York, NY 10027 USA
基金
中国国家自然科学基金;
关键词
Industrial structure; Carbon dioxide emissions; Technical progress; CO2; EMISSIONS; ECONOMIC-GROWTH; ENERGY; EFFICIENCY; POLLUTION; ENVIRONMENT; INTENSITY; EDUCATION;
D O I
10.1016/j.enpol.2012.07.017
中图分类号
F [经济];
学科分类号
02 ;
摘要
Using provincial panel data from the period 1995-2009 to analyze the relationship between the industrial structural transformation and carbon dioxide emissions in China, we find that the first-order lag of industrial structural adjustment effectively reduced the emissions; technical progress itself did not reduce the emissions, but indirectly led to decreasing emissions through the upgrading and optimization of industrial structure. Foreign direct investment and intervention by local governments reduced carbon dioxide emissions, but urbanization significantly increased the emissions. Thus, industrial structural adjustment is an important component of the development of a low-carbon economy. In the context of industrial structural transformation, an effective way to reduce a region's carbon dioxide emissions is to promote the upgrading and optimization of industrial structure through technical progress. Tighter environmental access policies, selective utilization of foreign direct investment, and improvements in energy efficiency can help to reduce carbon dioxide emissions. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:43 / 51
页数:9
相关论文
共 56 条
[11]   ANOTHER LOOK AT THE INSTRUMENTAL VARIABLE ESTIMATION OF ERROR-COMPONENTS MODELS [J].
ARELLANO, M ;
BOVER, O .
JOURNAL OF ECONOMETRICS, 1995, 68 (01) :29-51
[12]   SOME MODELS FOR ESTIMATING TECHNICAL AND SCALE INEFFICIENCIES IN DATA ENVELOPMENT ANALYSIS [J].
BANKER, RD ;
CHARNES, A ;
COOPER, WW .
MANAGEMENT SCIENCE, 1984, 30 (09) :1078-1092
[13]   Initial conditions and moment restrictions in dynamic panel data models [J].
Blundell, R ;
Bond, S .
JOURNAL OF ECONOMETRICS, 1998, 87 (01) :115-143
[14]   Dynamic panel data models: a guide to micro data methods and practice [J].
Stephen R. Bond .
Portuguese Economic Journal, 2002, 1 (2) :141-162
[15]   THE GREENHOUSE-EFFECT - THE FALLACIES IN THE ENERGY EFFICIENCY SOLUTION [J].
BROOKES, L .
ENERGY POLICY, 1990, 18 (02) :199-201
[16]   MEASURING EFFICIENCY OF DECISION-MAKING UNITS [J].
CHARNES, A ;
COOPER, WW ;
RHODES, E .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1978, 2 (06) :429-444
[17]   Determinants of economic growth in China: Private enterprise, education, and openness [J].
Chen, BZ ;
Feng, Y .
CHINA ECONOMIC REVIEW, 2000, 11 (01) :1-15
[18]   Industrial activity and the environment in China: An industry-level analysis [J].
Cole, Matthew A. ;
Elliott, Robert J. R. ;
Wu, Shanshan .
CHINA ECONOMIC REVIEW, 2008, 19 (03) :393-408
[19]  
Department of Comprehensive Statistics of the National Economy National Bureau of Statistics of China, 1999, COMPR STAT DAT MAT 5
[20]  
Department of Trade and Industry United Kingdom, 2003, OUR EN FUT CREAT LOW