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An Empirical Study On The Impact Of Export Trade On Haze Pollution In China

Posted on:2023-09-11Degree:MasterType:Thesis
Country:ChinaCandidate:Y F ZhaoFull Text:PDF
GTID:2531307097984799Subject:International business
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With the accelerated pace of global economic integration,China has issued a package of policies and measures to accelerate its integration into the global economic system,and the scale of foreign trade has been expanding.Especially since the implementation of the reform and opening-up policy,China’s export volume has increased by about a thousand times.However,under China’s extensive economic growth model,export trade has a direct impact on the environment due to the use of domestic environmental resources as inputs for production activities.The situation of environmental pollution in China is becoming more and more serious,especially the problem of haze pollution has aroused widespread concern.In recent years,haze pollution events characterized by "explosion" of PM2.5concentration have occurred frequently.In 2013,China suffered the widest and longest-lasting haze weather in 52 years.In May 2016,the report released by the second United Nations Environment Conference showed that 25% of the global deaths were related to environmental pollution,of which about 7 million died from air pollution.Haze has not only seriously affected people’s life and health,but also caused heavy economic losses.On September 7,2006,the first Research Report that included environmental pollution in GDP Accounting jointly released by the National Bureau of statistics and the former State Environmental Protection Administration showed that in 2004,economic losses and virtual governance costs caused by environmental pollution reached 518.8 billion and 287.4 billion respectively,accounting for 3.05% and 1.8% of GDP in that year.From 2014 to2016,haze was selected as one of the annual top ten science and technology buzzwords released by global science for three consecutive years,indicating that haze has become the focus of global common attention.Therefore,this paper studies the impact of export trade on haze pollution,which is of great practical significance for China to realize the coordinated development of export trade an d environment.Firstly,this paper reviews the relevant literature on the impact of export trade on air pollution at home and abroad,and makes a qualitative analysis on the mechanism of export trade on haze pollution.Next,the paper analyzes the current situation of China’s export trade and haze pollution from three levels: the whole country,prefecture-level cities and four regions,and preliminarily analyzes the correlation between them from the national level and prefecture-level city level.Then,the spatial weight matrix is constructed based on spatial geographic data,and the spatial correlation between export trade and haze pollution is discussed by using exploratory spatial data analysis method(ESDA).After that,the static and dynamic spatial panel data models are respectively constructed based on spatial lag and time lag dual-effect perspectives,and the LM test,LR test and Hausman test were used to effectively select the model’s spatial effect type and panel data type.Subsequently,the maximum likelihood(ML)estimation method is used to estimate the regression of spatial Durbin model and spatial lag model respectively from static and dynamic perspectives,and the total effect of each variable is decomposed.The empirical results show that export trade has a significant inhibitory effect on the haze pollution in the region and its adjacent areas,and haze pollution has significant spatial agglomeration characteristics,and haze pollution of the current period has an obvious path-dependent feature on haze pollution of the previous period.Finally,according to the results of the previous research and analysis,this paper puts forward relevant countermeasures and suggestions to promote the coordinated development of export trade and haze pollution.
Keywords/Search Tags:Export trade, Haze pollution, Spatial correlation, Spatial panel data model
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