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Shanghai Energy Intensity Factor Decomposition And Prediction Model

Posted on:2009-10-19Degree:MasterType:Thesis
Country:ChinaCandidate:L JiaoFull Text:PDF
GTID:2199360272959342Subject:Quantitative Economics
Abstract/Summary:PDF Full Text Request
In the 11th Five-year project,Shanghai makes the plan of reducing its energy intensity(energy consumption per GDP) by 20%compared to that of 2005.This is both a challenge and an opportunity for the city of Shanghai.This paper focuses on the factors that affect the energy intensity of Shanghai, especially industrial structure shift and efficiency improvement of energy consumption in the sectors.The structure decomposition analysis is used in the paper to find which factor contributes more to the declining energy intensity.The result shows that in different period these two factors had different influences;however,the efficiency improvement of energy consumption is the main factor.As the industrial sector consumes most energy,this paper also looks at the energy intensity of industrial sector.Structure decomposition analysis is used to find the main cause of the decreasing energy intensity of industrial sector.The result shows that the structure shift in industrial sector,rather than efficiency improvement of energy consumption,contributes more to the decreasing energy intensity of industrial sector.The links between the industries are constraints in considering changing structure of industrial sector to reduce energy intensity.By introducing input-output method, some high energy intensity industries are found to have more connections with other industries.A time series model is used to forecast the energy intensity in the period of the 11th Five-year project.The result of the model indicates that the energy-saving goal of 11th Five-year can be possibly achieved for the city of Shanghai.The last part of the paper presents the conclusion of this paper and some policy suggestions as well.
Keywords/Search Tags:Energy Intensity, Structure Decomposition Analysis, Industrial Structure Shift, Efficiency Improvement of Energy Consumption, Forecast Model
PDF Full Text Request
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