The Impact of Urban Population and Inequality on Environment Degradation: Empirical Evidence from Panel Data Analysis
DOI:
https://doi.org/10.47067/real.v3i1.25Keywords:
Environment Degradation, Real GDP, Population, Inequality, Developing Countries Granger Causality, GMM, Common-Effect Model, Fixed-Effect Model, Randon-Effect ModelAbstract
This study aims to empirically analyze population, inequality, and environmental degradation in developing countries. A panel data is used for D-8 countries for the period from 1990-2015. Unit root test is applied for stationary, Levin, Lin, and Chu test concluded that all variables are integrated at first difference. Panel Granger causality is applied to check the causality among variables. The results of Granger causality concluded that there is bidirectional causality between GDP and CO2 and also bidirectional causality between the GINI coefficient and CO2. And found unidirectional causality of urban population and trade openness with CO2. GMM estimation technique is used and estimates the common-effect model, fixed-effect model, and random-effect model. Hausman's test concludes that the random-effect is more appropriate. Real GDP, Rural population, and Trade openness are positively influencing the emission of carbon dioxide. While the GINI coefficient (a proxy of inequality) is negatively influencing carbon dioxide in seven developing countries.
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