Empirical Analysis of Factors Affecting Income Inequality

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This paper empirically analyses the factors affecting income inequality in 15 developed and developing economies over the period of 1996 to 2010. Evidence from a panel dataset using an OLS regression confirms the presence of the Kuznets’ inverted-U hypothesis for developed economies, indicating that there is a negative relationship between income per capita and income inequality. The relationship between the growth rate and income inequality, is also found to be negative. In relation to education, the paper finds a significant negative relationship between the education enrolment rate and income inequality, where the effect is greater in developing economies. Furthermore, the effects of government expenditure and trade on inequality are found to be insignificant for developing economies. The determinants of income inequality varying from developed to developing countries, have intrigued economists over the decades, initiating them to conduct several studies on the topic. This paper examines the determinants of income inequality over a 15 year period between 1996 to 2010 in two specific regions; developed economies from Europe and developing economies with majority of them consisting of South American countries. This paper will cross-compare findings to distinguish correlations and differences between the two sets of countries. As a result, this study will incorporate the Gini coefficient as the dependent variable. The purpose of using this measure is to determine the levels of income inequality between the two cohorts discussed above. Prior studies look into health and income inequality and use the Gini coefficient concentration index; this is evident in (Podder, 1995). The main determinants of income inequality are GDP per capit... ... middle of paper ... ...lity when GDP per capita is higher than $2000. Barro’s paper also supported the Kuznets curve when looked across countries and over time, stating that it was a ‘clear empirical regularity’ that inequality decreases in the long run. Other studies challenged the idea that inequality has a negative relationship with economic growth, notably the likes of Forbes (2000), who found a strong positive relation between the two variables. He used a panel data approach, focusing on 45 countries over a period of 30 years. Forbes’ study highlighted that in the short and medium run, an increase in income inequality had a strong positive effect on economic growth, thus increasing the gap between rich and poor individuals. However, he stated that due to insufficient long run data at the time of researching the paper, he was only able to focus on a short and medium term timescale.
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