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Environmental Kuznets Curves in the People's Republic of China: [推广有奖]

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tyn 发表于 2009-7-17 20:05:33 |AI写论文

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Environmental Kuznets Curves in the People's Republic of China :Turning Points and Regional Differences
ADB Economics Working Paper Series
Yi Jiang, Tun Lin, and Juzhong Zhuang
December 2008
Contents
Abstract v
I. Introduction 1
II. The Environmental Kuznets Curve: A Brief Literature Review 3
III. Methodology and Data 5
IV. Results 8
V. Conclusions and Policy Implications 12
Appendix A. Region Definitions 15
References 15
Abstract
This paper examines the relationship between economic growth and
environmental sustainability in the People’s Republic of China by empirically
estimating environmental Kuznets curve (EKC) models using provincial-level
panel data from 1985 to 2005. The results show that there exists an
inverted-U shaped relationship as hypothesized by the EKC model between per
capita income and per capita emissions (or discharges) in the cases of waste
gas from fuel burning and waste water, with a turning point at per capita gross
domestic product of $12,903 and $3,226, respectively, in 2005 purchasing power
parity terms. This relationship does not hold in the case of waste gas from
production or solid waste. The estimation results from the model allowing regionspecific
slope coefficients show that the EKCs of the more developed coastal
region have a flatter rising portion with turning points occurring at a higher
income level than those of the less developed central and western regions. The
paper argues that this may reflect technology diffusion and leapfrogging and
institution imitation across regions at different stages of development. Policy
implications of these findings are discussed.
s Republic of China :Turning Points and Regional Differences.pdf (569.16 KB)

附:Energy Conservation in the People's Republic of China:Fiscal Measures
abbr_61234851fee37cb30a1c8cd6cca63ed1.pdf (1.69 MB)

附:Electric Bikes in the People’s Republic of China: Impact on the Environment and Prospects for Growth
abbr_61234851fee37cb30a1c8cd6cca63ed1.pdf (1.69 MB)
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