Literature DB >> 31382191

Market segmentation and urban CO2 emissions in China: Evidence from the Yangtze River Delta region.

Shuai Shao1, Yang Chen1, Ke Li2, Lili Yang3.   

Abstract

As the largest CO2 emitter in the world, China plays a crucial role in global CO2 emission reduction. Meanwhile, as the largest developing country, China gives top priority to economic development, especially balanced regional development. In order to narrow regional development inequality, China has formulated some economic zone plannings to weaken market segmentation. However, existing studies pay little attention to the impacts of intra-national trade barrier on CO2 emissions within China. This is the first study to investigate the impact of market segmentation on urban CO2 emissions in China, taking the Yangtze River Delta region as a sample that is the most developed region with a high economic integration in China. Using a city-level panel data set during the period of 1995-2014 and the fixed effect model, we verify the nonlinear relationship between market segmentation and urban CO2 emissions measured by three indicators, i.e., total CO2 emissions, per capita CO2 emissions and CO2 emissions per unit of GDP. We also use the generalized method of moments (GMM) to control the endogeneity problem, and further adopt the threshold regression model to check the robustness of the baseline results. The results show that there is a U-shaped curve relationship between market segmentation and urban CO2 emissions. A low level of market segmentation restrains CO2 emissions, while a high level of market segmentation promotes CO2 emissions. This finding is helpful to understand CO2 emission trends and narrow regional economic inequality accompanied with the implementation of China's economic zone plannings.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  CO(2) emissions; GMM; Market segmentation; Regional inequality; The Yangtze river delta region; Threshold regression model

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Year:  2019        PMID: 31382191     DOI: 10.1016/j.jenvman.2019.109324

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


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