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Research On Carbon Emission Efficiency Of Guangdong Province With Stochastic Frontier Model

Posted on:2015-11-05Degree:MasterType:Thesis
Country:ChinaCandidate:Y LiuFull Text:PDF
GTID:2309330422984464Subject:World economy
Abstract/Summary:PDF Full Text Request
Greenhouse Effect and climate changes caused by carbon dioxide emissionhave become the global focus. As a country of the greatest amount of carbon dioxideemission, China is confronting with pressure from the world to shoulder the missionof carbon dioxide emission cut-down. Simultaneously, the transformation ofhigh-energy and high-emission development mode is demanded by the sustainabledevelopment of the society, which makes it no time to delay.However, there are still problems to solve for the Chinese government in whetherChina is efficient in carbon dioxide emission, how much potential and cost in carbondioxide emission, which is also the prominent task for Guangdong,one of the leadersin industry and economy. Therefor, improving the efficiency of carbon dioxideemission and developing clean energy are a must. This paper will start from theseproblems and conduct an empirical analysis on the efficiency of21cities ofGuangdong with their panel data.The aim of this paper is to analyze the present situation, trend and thedeterminants of carbon emission efficiency of different districts in Guangdongthrough SFA model. And definition of Efficiency of Carbon Emission is provided,macro data and Stochastic Frontier Model (Battese and Coeli,1995) will be used. Theefficiency of carbon emission is measured in three levels: Guangdong, four districts,and21cities with panel data of Guangdong’s21cities, and their feature changes areanalyzed and determinants of carbon emission efficiency are defined. Impact oncarbon dioxide emission efficiency is analyzed from the following aspects: IndustryStructure, Property Right Structure, Power Intensity, Technology Input, EconomicSituation, Openness, Power Structure, Urbanization and Government Interference et.
Keywords/Search Tags:Total factor energy efficiency, carbon emission efficiency, stochasticfrontier analysis
PDF Full Text Request
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