Dynamic factors driving PM2.5 concentrations: Fresh evidence at the global level.

This paper analyzes the dynamic impact of economic, social, and governance factors on PM2.5 concentrations in 89 countries from 2006 to 2019. Using the GMM-PVAR approach and Impulse-Response Functions, we examine how shocks to specific variables affect PM2.5 concentrations over a 10-year period. Our findings reveal that the influence of these factors on PM2.5 levels varies over time. For example, a shock in urbanization has no effect on PM2.5 concentrations in the first year, but in the second year, pollution increases significantly. In the third period, PM2.5 levels decrease, but they rise again in the fourth period, albeit not significantly. By the fifth period, pollution decreases until a new equilibrium is reached in the sixth period. Additionally, a shock in financial development, government effectiveness, industrialization, trade openness, or GDP has no effect on PM2.5 concentrations in the initial period. However, during the second period, air pollution decreases, followed by an increase in the third period and a decrease again in the fourth period. These dynamic patterns highlight the need for environmental policies that consider the evaluation time horizon. Our analysis is supplemented by the Granger causality test, guiding specific policy recommendations based on our findings.