Abstract
The intensified contradiction of economic growth and environmental protection has gained a lot of attention from multidisciplinary scholars. The relationship between socio-economic factors and deadly concentration of PM2.5 remained poorly understood specifically for the developing countries. The study has selected Next-11 countries for the analysis to gauge the influencing factors of PM2.5 concentrations by collecting data from 1995-2017. The cross-sectional dependence test shows mixed results therefore, the study has employed both the first generation and second generation econometric techniques. The results of the panel unit root test indicate that all the variables are stationary at first difference. In Auto-Regressive Distributive Lag (ARDL) estimation, the longrun co-integration vectors show that renewable as well as non-renewable energy have significant long-run co-integration. Gross domestic product is the main influencing factor of PM2.5 concentrations while its quadratic form has a negative association that verifies the existence of the Environmental Kuznets Curve (EKC) in sampled countries. The Westerlund co-integration test also verifies the long-run integration among variables. The results of Fully Modified Least Square (FMOLS) and Dynamic Least Square (DOLS) indicate significant negative relation of industry value-added, trade openness and urbanization. On the other hand, the results of the Dynamic Common Correlated Effect (DCCE) indicate the positive impact of urbanization on PM2.5 concentration. This is the first study that is showing the key contributing factors of PM2.5 concentrations for N-11 countries. Authors have suggested the rational formulation and careful implementation of policies.

Mahjabeen Usman, Sumayya Chughtai. (2021) IMPACT OF SOCIO-ECONOMIC FACTORS AND ENERGY MIX ON PM2.5 CONCENTRATION: AN EMPIRICAL ANALYSIS OF NEXT-11 COUNTRIES, International Journal of Management Research and Emerging Sciences, Volume 11, Issue 2.
  • Views 438
  • Downloads 32

Article Details

Volume
Issue
Type
Language