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The Influencing Factors Of Chinese Carbon Emissions And Forecast

Posted on:2017-04-28Degree:MasterType:Thesis
Country:ChinaCandidate:M H WangFull Text:PDF
GTID:2311330488965880Subject:Statistics
Abstract/Summary:PDF Full Text Request
The excessive emissions of carbon dioxide is the main cause of global warming.Many countries have further research into it.At present,China is the second largest economy in the word.The GDP of China has increased to 63 trillion Yuan in 2014.At the same time,the rapid development of the economics leads to all kinds of pollutions.China has raised the proposal about how to deal with the global warming for two five-year plan.Studying on the Chinese carbon emissions is essential.In this paper,we build a model based on a classical STIRPAT to find the relationship between carbon emissions from energy and a series of human activities including the unit GDP energy consumption,the third industry ratio,urbanization level,total primary energy production.The parameters of STIRPAT model,with the multi-collinearity among the variables,are estimated by principal component regression.The results show that urbanization level,per capita GDP,the unit GDP energy consumption,total primary energy production promote the carbon emissions in China.For every 1% increase in urbanization level,per capita GDP,the unit GDP energy consumption,total primary energy production,there is 0.430%,(0.076+0.014 lnX2)%,0.031%,0.501% increase in carbon emissions.However,every 1% increase in the third industry ratio leads to 0.457% carbon emissions reduction.We proceed the forecasting for Chinese carbon emissions based on the combined model of the ARIMA model and BP neural network,in the future.Firstly,we select carbon emissions of China from 1980 to 2007 as the train sample for deciding the parameter of the combined model.Secondly,we test the combined model using the data of the carbon emissions of China from 2008 to 2013,and find that the combined model has a minimum error.Thirdly,we discuss the trend of the carbon emissions of China by the forecasted values of the carbon emissions of China from 2014 to 2020.According to the study,we draw three conclusions:(1)The Chinese carbon emissions has been influenced by several factors.We control urbanization level and improve the skill level and so on to reduce the carbon emissions.(2)China should continue to adjust the energy structure and pay more attention to the clean energy.(3)Carbon emissions and per capita GDP of China does not exist the environmental Kuznets curve relationship.Chinese carbon emissions will still continue to increase with the development of economy.
Keywords/Search Tags:Carbon emissions, STIRPAT, ARIMA, BP neural network, Combined model
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