Does the effect of corruption on carbon emissions vary in different countries?

Attention to the economic consequences of environmental degradation and analyzing the environmental impacts of economic developments, in form of the environmental Kuznets curve (EKC), has been established before the global consensus on the necessity of reducing carbon emissions. The pollution haven hypothesis (PHH) also follows the capital transfer from developed economies to developing ones and the analyzing of consequences of its environmental impacts. Recently, the impact of corruption on carbon emissions has been raised as the main objective of empirical studies on the environmental economy. Several attempts have been made, in which assumptions of the EKC and PHH are explained with the help of theoretical foundations on the impact of corruption on environmental quality. In this context, it is argued that based on the PHH hypothesis, corruption, with the weakening of regulatory and monitoring institutions, led to environmental degradation by reducing carbon emission costs and, consequently, the entry of dirty industries from developed countries to developing countries and less developed to follow. On the other hand, corruption, according to EKC, by distorting the income distribution system and undermining productive economic activities, delays the maximum per capita of the gross domestic product, after which the downward trend of carbon emission is begun, resulting in the increased environmental degradation. Recently, a theoretical discussion has taken place about the significant impact of reducing the level of corruption on improving the environmental quality in developing countries rather than in developed ones. It is claimed that in developing and less developed economies, the decline in the level of corruption has more significant effects on reducing carbon emissions. The purpose of this study is to empirically investigate this claim. In this study, we have empirically investigated this claim using panel data including 61 countries during 2003-2016 and the method of threshold panel model in STATA. We analyzed the coefficient of the effect of corruption on carbon emissions via the Human Development Index as a threshold variable for dividing countries into developed and developing. In this framework, at first, using the relevant tests, the thresholds were identified and then based on that, the model including variables like carbon emission, per capita gross domestic product, human development index, urban population growth, primary energy consumption, commodity trade, and corruption index was estimated. The coefficient for developing countries was estimated negative, significant and larger than developed countries. On the other hand, the coefficient for the developed countries was positive, smaller and not significant. In developing countries, per every unit increase in the index of corruption (which means reducing the level of corruption), the carbon emission will be reduced by 0.08 units, while in developed countries, the effectiveness of carbon emission from corruption has been stopped. The reduction of corruption in these countries does not have a significant effect on the reduction of carbon emissions. As it was mentioned, corruption was a common issue in both developed and developing countries, but comparatively, it had a greater effect on CO2 emissions in developing countries than that in developed ones.