A Study On Bayesian Panel Quantile Measurement Of The Impact Of Foreign Direct Investment On Carbon Emissions

Environmental pollution has become a global problem;climate change and global warming become one of the most concerns of the international community.Greenhouse gases,especially those related to human activities,are the main contributors to the greenhouse effect.The increase in greenhouse gases has also led to climate change and accelerated environmental degradation.Such as the melting of glaciers,the rise of sea level,the frequent occurrence of natural disasters.Therefore,it is of practical significance to study the main factors affecting carbon dioxide emissions.Previous studies focused on the impact of economic growth and energy consumption on carbon emissions,but with the rapid development of the global economy,the exchanges between countries around the world become closer,so that a non-negligible factor is foreign direct investment(FDI).So far,FDI has no consensus on the impact of carbon emissions.In this paper,Bayesian panel quantile regression model is used to study the effect of FDI on carbon emission in order to understand the effect of FDI on carbon emission at different levels.This paper follows the research from the relevant theoretical analysis to the model construction,and then applies the constructed model to the empirical research.First,the theory of FDI on carbon dioxide emissions is analyzed.These related theories are divided into two aspects:the positive impact of FDI on carbon emissions theory,the negative impact of FDI on carbon emissions theory.Then,we construct the Bayesian panel quantile regression model.Under the framework of Bayesian theory,a priori distribution is established,and a posterior distribution function is obtained,combining the panel quantile regression model.Finally,select the five ASEAN countries(Indonesia,Malaysia,the Philippines,Singapore,Thailand)1981-2012 data as a sample.The independent variables are FDI,economic growth,energy consumption,and the dependent variable is carbon dioxide emissions.In addition,the relevant control variables are added to the model.First,the statistical characteristics of the sample data are analyzed,and the stationability test is carried out.Then the Bayesian panel quantile regression model was used to estimate the parameters and the results were compared and analyzed.The results show that the effect of the independent variable on the dependent variable is heterogeneous at the whole level.Compared with the OLS regression model,Bayesian panel quantile regression model results are more comprehensive,more detailed and more effective.In five ASEAN countries,the impact of FDI on carbon emissions is negative.That is,the growth of FDI is beneficial to the local environment and in the five ASEAN countries to support the "pollution halo effect hypothesis".In terms of economic growth,its coefficient is negative at the low quintile level and positive at the middle and high.This also reflects the heterogeneity of the independent variables at different levels.It is said that in low-emission countries,economic growth is beneficial to the environment,and in high-emission countries is detrimental.In addition,the result of the square coefficient of GDP shows that the coefficient is negative and is statistically insignificant.Thus,there is insufficient evidence that the ASEAN countries are in line with the inverted U curve in the EKC hypothesis.The impact of energy consumption on carbon emissions is positive,the greater the energy consumption,the more serious environmental pollution.