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This paper has used a stirpat model to investigate the synergistic effect of CO2 emission, energy consumption, energy intensity, economic growth, population, urbanization and trade openness to demonstrate growthenvironment nexus in four selected developing Asian economies. Taking a panel data set from Bangladesh, China, India and Indonesia this study applies Autoregressive Distributed Lag (ardl) model and vec Granger Causality/Block Exogeneity Wald Tests. The empirical results show that energy intensity, urbanization, population, and per capita gdp growth are the raison d'être of CO2 emissions whereas trade openness is found to be negatively related to CO2 emissions. Conversely, energy consumption, urbanization, population and trade openness are positively related to per capita gdp. In addition, it also investigates the Environmental Kuznets Curve (EKC) hypothesis and the findings substantiate an inverted Ushaped relationship. Cross-section short-run coefficients of country-level data are inquired into to check the robustness of the panel outcomes. [ABSTRACT FROM AUTHOR]

This paper has used a stirpat model to investigate the synergistic effect of CO2 emission, energy consumption, energy intensity, economic growth, population, urbanization and trade openness to demonstrate growthenvironment nexus in four selected developing Asian economies. Taking a panel data set from Bangladesh, China, India and Indonesia this study applies Autoregressive Distributed Lag (ardl) model and vec Granger Causality/Block Exogeneity Wald Tests. The empirical results show that energy intensity, urbanization, population, and per capita gdp growth are the raison d'être of CO2 emissions whereas trade openness is found to be negatively related to CO2 emissions. Conversely, energy consumption, urbanization, population and trade openness are positively related to per capita gdp. In addition, it also investigates the Environmental Kuznets Curve (ekc) hypothesis and the findings substantiate an inverted Ushaped relationship. Cross-section short-run coefficients of country-level data are inquired into to check the robustness of the panel outcomes. [ABSTRACT FROM AUTHOR]