The dynamic relationship between regional corruption and carbon emissions in China
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ORIGINAL PAPER
The dynamic relationship between regional corruption and carbon emissions in China Yuanhua Yang1 · Xi Yang2 · Dengli Tang3 Received: 24 June 2020 / Accepted: 10 October 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Does regional corruption exacerbate regional carbon emissions? To answer this, based on the spatial Durbin model, this study empirically examines the impact of regional corruption on carbon emission, using panel data from 30 provinces in China during the period 2002–2017. The results show that: (1) there is an indistinctive N-shaped relationship between regional corruption and carbon emissions at the national level. Regional corruption tends to initially aggravate carbon emissions, then contributes to emission reduction, and then finally boosts carbon emissions. However, this effect is not statistically significant. The results suggest that the role of regional corruption on carbon emissions is twofold. Corruption can exacerbate and can also inhibit regional carbon emissions. (2) Pronounced regional heterogeneity exists with regard to the influence of corruption on carbon emissions. Regional corruption and carbon emissions show a significant N-shaped dynamic relationship in China’s central region, while the relationship is not significant in the eastern and western regions. (3) The impact of regional corruption on carbon emissions varies with time. For 2002–2009, regional corruption did not have a significant effect on carbon emissions. For 2010–2017, the direct effect became significant, and an apparent N-shaped relationship formed between regional corruption and carbon emissions. Based on the empirical results, this paper proposes several policy recommendations regarding corruption and carbon governance. Graphic abstract
1. Does regional corruption exacerbate carbon emissions? 2. Are there regional heterogeneity and period difference in the impact of regional corruption on carbon emissions?
Research Questions
1. Spatial econometric method 2. Spatial Durbin Model 3. Panel data from 30 provinces in China from 2002 to 2017
Method and Data
1. There is an indistinctive Nshaped relationship between regional corruption and carbon emissions on the national level. 2. Regional corruption can exacerbate regional carbon emissions, and it also can inhibit regional carbon emissions. 3. Obvious regional and time heterogeneity exists in the influence of corruption on carbon emissions.
Results
Keywords Regional corruption · Carbon emissions · Spatial Durbin model · Regional heterogeneity
* Yuanhua Yang [email protected] Extended author information available on the last page of the article
Abbreviations Ce Carbon emissions Rc Regional corruption Er Environmental regulation GDP Gross domestic product FDI Foreign direct investment
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Vol.:(0123456789)
Is Industrial structure laec Labor-average energy consumption Isde Industrial smoke and dust emissions List of symbols Y Dependent variable X Explanatory variable W Spatial weight matrix δ The slope
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