An empirical study on correlation among poverty, inclusive finance, and CO emissions in China.

This paper explores the nonlinear relationship between poverty and CO emissions based on the panel data of 30 provinces in China from 2005 to 2019. In this study, the autoregressive distributed lag (ARDL) model is first used. Findings confirm that poverty has a negative impact on CO emissions in the short run and a positive impact in the long run, while both effects of inclusive finance on CO emissions are negative. In order to explore the reasons for the change in the coefficient of poverty, we introduce a moderating effect (ME) model and a dynamic panel threshold (DPT) model. The result shows that the negative effect of poverty on CO emissions diminishes with the moderation of inclusive finance. When inclusive finance crosses the threshold value (IFI = 0.2696), the impact of poverty on CO emissions will change from negative to positive gradually, which verifies the applicability of the "Poverty-CO Paradox" in China and provides an empirical basis for breaking the "Poverty-CO Paradox." Consequently, deepening poverty reduction and pushing the region's inclusive finance to the threshold level are proposed as effective ways to promote CO emission reduction.