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As hypothesized by Gerschenkron (1962), lower income countries would tend to grow at a faster rate than higher income countries and, as a result, their average incomes would converge in the long run. In addition to that hypothesis, theoretical studies to assess the impact of globalization on international economic convergence remain ambiguous. To address both the issues simultaneously, this study attempts to analyze the trend and possible association between the two, i.e., cross-country per capita income differential and globalization. This study incorporates a long list of countries (160 Countries) for a fairly long period of time (from 1990 to 2019). As expected, the study found a steady rise in global trade to GDP ratio, indicating a rising level of globalization in the assessment period. In addition to that, the study also found a rising level of average cross-country per capita real GDP (based on purchasing power parity (PPP)) differential in the given time horizon, contradicting Gerschenkron hypothesis. Finally, applying the ARDL bounds testing procedure, the study finds that cross-country per capita income differential and globalization are cointegrated; and the net effect of globalization on income differential is positive. Therefore, given the data, the study concludes that, over the years, along with rising level of globalization, per capita income differential diverges which causes cross-country per capita income inequality to rise.

The goal of sustainable economic growth is achievable only when economic growth and development occur without environmental degradation. The Environmental Kuznets Curve (EKC) hypothesis explains the inverted U-shaped association between economic activity and environmental degradation. The primary objective of this study is to empirically test the truth behind the EKC hypothesis. In addition to that, the study is intended to analyze the variation in the shape of the EKC; that is, cross-country variation, as well as variation over time. In order to achieve the stated objectives, the study analyzed a long list of countries (75 countries) for a fairly long period of time (1960–2016, i.e., 57 years). The empirical literature in this area estimated the EKC using some form of a polynomial regression equation. This study also used a similar kind of modeling structure to understand cross-country as well as dynamic variation in the shape of the EKC. In this study, firstly the selected countries are grouped on the basis of the shape of the EKC. Secondly, the dynamic behavior of each parameter in the polynomial equation is analyzed to understand the degree of association between economic activity and environmental degradation. This study suggests a decline in degree of association between the two over time.