Determinants of globalization and its impacts on income inequality and economic growth

This dissertation consists of three empirical exercises, all of which are related to globalisations and its impacts on economic activities. The first objective of this dissertation is to examine the impact of globalisation on income inequality in developing countries. It formally tests whether globalisation has differential impacts on income at different level using a panel data set from 50 developing countries during the 1990-2017 period. Methodologically, it departs from the existing literature by exploiting panel quantile regression analysis. This methodological approach allows us to test the impact of globalisation on income at different level. There are three indicators of globalisation used in this study namely, economic globalisation (i.e., trade plus finance), trade globalisation, financial globalisation. Overall, the results reveal that the impact of economic globalisation on income gap is negative such that as countries become more globalised, income gap becomes narrower. However, further analyses on disaggregated index suggest that trade globalisation widens the income gap but financial globalisation appears to have a reducing effect on income gap. The uncertainty surrounding FDI theories and empirical approaches has created the notion that few FDI determinants are truly robust. Economic freedom to be seen as an important determinant of FDI, yet a variety of economic freedom components exist and their influences on FDI remain uncertain. Therefore, the second objective of this dissertation aims to identify robust determinants of foreign direct investment (FDI) inflows. Exploiting a panel of 94 countries covering the 1980 to 2017 period, this study deals with model uncertainty using Sala i-Martin’s Extreme Bounds Analysis (EBA) to identify factors that are robustly related to FDI inflows. The results reveal there exist a robust relationship between a few variables and FDI inflows, with average coefficient signs consistent with the Sala-i-Martin’s Cumulative Distribution Function (CDF) criteria. In total, this study considers 19 potential determinants and the results suggest that education, debt, outward FDI, trade, trade freedom and tax revenue are robust determinants of FDI inflows in the countries. It has been widely accepted that the impact of FDI inflows on growth is not automatic but depends on other factors available in the host countries. Therefore, the third objective of this study is to examine the role of intelligence (i.e., IQ scores) in moderating the impact of FDI on economic growth. It hypothesizes that only countries with sufficiently high level of intelligence would benefit from FDI inflows. To test the hypothesis, a data set from 58 countries over the 1976-2017 period is utilised. Methodologically, this study adopts a regression specification which rely on threshold-effect that permits FDI to have a nonlinear impact on growth. The findings reveal that the positive impacts of FDI on growth “kick in” only after a given threshold level of IQ scores is attained by the host countries. Below the threshold level, FDI has no impact on growth. This finding is consistent with absorptive capacity hypothesis. In this context, high level of intelligence seems to foster a healthy economic environment that facilitates the adoption and diffusion of new technology associated with FDI inflows, thereby nurturing the economic ingredients necessary for economic development.

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