Examining the effects of income inequality on CO2 emissions: Evidence from non-spatial and spatial perspectives

Abstract

Over the past three decades, China has witnessed spectacular economic growth. However, behind this economic success, the country also faces serious challenges, including pressures to reduce emissions and to address imbalances in its growth. Increasing attention is thus being paid to the task of exploring the relationship between income inequality and CO2 emissions. The majority of previous studies have engaged with this question on the basis of conventional inequality measurements, neglecting the use of indexes that explicitly take into account spatial effects. In this paper, we employed two measures, the Gini coefficient and Global Moran’s I, in order to estimate income inequality from non-spatial and spatial perspectives, using income data for 403 prefecture-level cities. Under the framework of Environmental Kuznets Curve hypothesis, we investigated how the level of income distribution within 30 Chinese provinces influenced that province’s CO2 emissions, using panel data from 1996 to 2014 to estimate both the Gini coefficient and Global Moran’s I. The empirical results show that income growth increased China’s CO2 emissions during the study period, but that an inverted U-shaped relationship existed between income and emissions, thereby confirming the Environmental Kuznets Curve hypothesis. The continuously widening income gap, and especially the uneven spatial distribution of income, can thus be expected to deteriorate environmental quality and increase CO2 emissions. The effect of the self-reinforcing agglomeration of income on emissions was clearly evident. Other control factors were also shown to maintain a positive relation with CO2 emissions. Our results shed new light on the relationship between income inequality and CO2 emissions and provide support for policy makers in tackling the dual tasks of income redistribution and emissions mitigation. A more equitable income distribution, our findings suggest, may exert positive effects in relation to the mitigation of CO2 emissions in China.