This paper examines the impact of increased trade among nations on the components of environment, a dynamic relationship which has evolved over time and has far reaching multi-dimensional consequences. Skimming the broad horizon of trade, this paper takes into account the impact of Foreign Direct Investment (FDI), a relatively modern phenomenon representing increased trade liberalization, on the environment and GDP growth rates of the host nations. Representing almost the two sides of the same coin, GDP growth and environmental degradation form the core implications of FDI among other subsidiary factors. Although an insignificant causal impact of FDI on GDP growth is ascertained, an attempt has been made to derive a marginal sector-specific positive correlation between FDI and CO2 emissions especially in the context of developing countries. From across the globe, USA and India are taken as two countries representing the first and third world respectively with a significant inflow of FDI in the recent years. In fact, India has emerged fourth highest all over the world in the ranking of CO2 emissions while USA is the highest recipient of FDI all over the world. The paper studies how the nature of FDI’s impact on GDP growth and especially on environment is different in the economic realm of a global giant as compared to India, an emerging superpower. So is FDI detrimental to the growth of recipient nations in terms of environmental decadence or is it a major catalyst responsible for triggering a surge of economic activity measured by a rise in GDP growth rates? The last two decades have seen a paramount increase in FDI in developing countries which has altered to some extent the economic structure of the host nations. So are the countries better off than before with this increase in external sources of investment? This paper addresses the above questions in an intuitively economic and statistical backdrop. The proposition of a positive correlation between sector specific FDI inflow and CO2 emissions and GDP growth is supported by a multiple regression model using dummy variable technique and Ordinary Least Squares (OLS) estimation.
Main file is the full text of the actual paper. Accompanying file is the Power Point presentation that was given.