An empirical study on correlation among poverty, inclusive finance, and CO₂ emissions in China

This paper explores the nonlinear relationship between poverty and CO₂ 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 CO₂ emissions in the short run and a positive impact in the long run, while both effects of inclusive finance on CO₂ 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 CO₂ emissions diminishes with the moderation of inclusive finance. When inclusive finance crosses the threshold value (IFI = 0.2696), the impact of poverty on CO₂ emissions will change from negative to positive gradually, which verifies the applicability of the "Poverty-CO₂ Paradox" in China and provides an empirical basis for breaking the "Poverty-CO₂ Paradox." Consequently, deepening poverty reduction and pushing the region's inclusive finance to the threshold level are proposed as effective ways to promote CO₂ emission reduction.