Responses of carbon emissions to corruption across Chinese provinces

Abstract

In response to the recent growth of multitudes of theoretical literature analysing the corruption impact on the economy and environment, this paper subjects the corruption–carbon emission relationship in China to a detailed empirical examination through the autoregressive distributed lag modelling approach and panel quantile regressions. Based on panel data from Chinese provinces, spanning the period 1998–2016, this study explores the impact of long- and short-term corruption on per capita carbon emissions by considering the heterogeneous distribution of those emissions. The results document that corruption increases per capita carbon emissions in Chinese provinces in the short run, reducing per capita carbon emissions in the long run. Moreover, an increase in corruption leads to an increase in carbon emissions per capita in all quantiles, indicating that these emissions increase with corruption severity. The coefficients in low quantiles are slightly larger than those in high quantiles, indicating that corruption leads to more carbon emissions in provinces with lower per capita carbon emissions.