Bayesian Panel Model of Urbanization, Economic Growth, and Globalization on Environmental Degradation in South Asia

Abstract

Increasing industrialization and urbanization in South Asia have contributed to severe environmental issues and especially through increased CO2 emission. This paper focuses on economic indicators like trade, financial development, GDP per capita and urban population growth and how they influence the emission of CO2 in South Asia. We estimate the model using a Bayesian Two-Stage Least Squares (2SLS) estimation, which allows us to use secondary panel data published by international organizations and governmental publications, covering the period between 2000 and 2020 to overcome the issue of endogeneity and to obtain more accurate estimates. The important results of our findings are that trade and GDP per capita are positively proportional to the CO2 emission, whereas financial development is negatively proportional to it, implying that more developed financial structures can help in reducing the emission. The growth of urban populations, however, does not have a statistically significant impact on the CO2 emissions. This work adds to the knowledge of economic-environmental nexus in South Asia and highlights that the policies that should be implemented must promote a balance between economic growth and the sustainability of the environment. This study is unique in that it utilizes Bayesian 2SLS to overcome endogeneity issue when estimating the effect of economic activities on CO2 emissions in the area.