The main purpose of this paper is to find the effects of financial development, income inequality, energy usage, and per capita GDP on carbon dioxide (CO) emissions as well the environmental Kuznets curve (EKC) for the three developing Asian countries-Bangladesh, India, and Pakistan. Panel data during the period 1980-2014 and the Stochastic Impacts by Regression on Population, Affluence, and Technology model with fully modified ordinary least squares (FMOLS) are employed for empirical investigation. The results show that financial development has a significant negative relationship with CO emission in the three selected Asian countries with the exception of India. The results further reveal that income inequality in Pakistan and India reduce CO emission, while the result for Bangladesh is opposite. Likewise, energy usage has a significant positive effect on CO emission in Bangladesh, Pakistan, and India. Our empirical analysis based on long-run and short-run elasticity appraisal suggests the validation of the EKC in Pakistan and India. The study findings recommend an important policy insinuation. The study suggests introducing a motivational campaign for the inhabitant towards utilization of high-efficiency electrical appliances, constructing mutual cooperation for economic development rather involve in winning development race, and introducing effective pollution absorption measures along with big projects.
The main purpose of this work is to analyze the impact of environmental degradation proxied by CO2 emissions per capita along with some other explanatory variables namely energy use, trade, and human capital on economic growth in selected higher CO2 emissions economies namely China, the USA, India, and Japan. For empirical analysis, annual data over the period spanning between 1971 and 2013 are used. After using relevant and suitable tests for checking data properties, the panel fully modified ordinary least squares (FMOLS) method is employed as an analytical technique for parameter estimation. The panel group FMOLS results reveal that almost all variables are statistically significant, whereby test rejects the null hypotheses of non cointegration, demonstrating that all variables play an important role in affecting the economic growth role across countries. Where two regressors namely CO2 emissions and energy use show significantly negative impacts on economic growth, for trade and human capital, they tend to show the significantly positive impact on economic growth. However, for the individual analysis across countries, the panel estimate suggests that CO2 emissions have a significant positive relationship with economic growth for China, Japan, and the USA, while it is found significantly negative in case of India. The empirical findings of the study suggest that appropriate and prudent policies are required in order to control pollution emerging from areas other than liquefied fuel consumption. The ultimate impact of shrinking pollution will help in supporting sustainable economic growth and maturation as well as largely improve society welfare.
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