Literature DB >> 34139496

The two-sided effects of foreign direct investment on carbon emissions performance in China.

Wenfei Song1, Hui Mao2, Xianfeng Han3.   

Abstract

Climate change caused by rapid increases in greenhouse gas concentrations is now a global challenge. Foreign direct investment (FDI), as a key player in global economic growth, is a major contributor to carbon emissions. Based on panel data of 30 provinces in China collected from 2007 to 2018, this paper uses the two-tier stochastic frontier model to analyse the opposing two-sided effects of FDI on carbon emission performance and calculates their combined effects. The empirical study shows that FDI has both a promoting and an inhibiting effect on carbon emission performance, and the overall effect is characterized by less of an inhibiting effect than a promoting effect, resulting in the positive driving characteristic of the combined effect. The average inhibiting effect is 0.0402, and the average promoting effect is 0.1065, causing the comprehensive effect of FDI on carbon emission performance to have an average value of 0.0663. The empirical results also show that the promoting effects of FDI are greater than the inhibiting effects in most regions; however, after 2013, the level of the promoting effect declined overall. There are regional differences in the combined effects of FDI on carbon emission performance, and the driving effects present in the central and western regions of China are significantly lower than that in the eastern region. Based on the research conclusions, while promoting a "green" revolution in FDI utilization patterns, it is necessary to strengthen the interaction mechanism between FDI and low-carbon economic development in China and to enhance the driving effect of FDI on carbon emission performance in China.
Copyright © 2021. Published by Elsevier B.V.

Entities:  

Keywords:  Carbon emissions performance; Climate change; FDI; Sustainable development; Two-tier stochastic frontier model

Year:  2021        PMID: 34139496     DOI: 10.1016/j.scitotenv.2021.148331

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  3 in total

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Authors:  Kai Liu; Ziyi Ni; Mei Ren; Xiaoqing Zhang
Journal:  Int J Environ Res Public Health       Date:  2022-05-25       Impact factor: 4.614

2.  Spatial-Temporal Evolution and Influencing Factors of Urban Green and Smart Development Level in China: Evidence from 232 Prefecture-Level Cities.

Authors:  Lingyan Xu; Dandan Wang; Jianguo Du
Journal:  Int J Environ Res Public Health       Date:  2022-03-25       Impact factor: 3.390

3.  How to Efficiently Reduce the Carbon Intensity of the Heavy Industry in China? Using Quantile Regression Approach.

Authors:  Bin Xu
Journal:  Int J Environ Res Public Health       Date:  2022-10-08       Impact factor: 4.614

  3 in total

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