1489 words - 6 pages

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 capita, education, inflation, government expenditure, trade and growth rates. Consequently these are the independent variables used. Additionally, there are other factors that contribute to income inequality. Andres & Ramlogan-Dobson (2011) demonstrate innovative evidence regarding the relationship between corruption and income inequality using panel data methodology.

This study will use a panel data analysis where a pooled OLS regression will be estimated. The strengths of using panel data analysis are that it incorporates both time series and cross-sectional observations. There will be an estimation of N × T observations where N equals the number of observations and T equals the time span thus the idea of multi-collinearity is eliminated.

This paper will be divided into six different sections; the next section, the literature review, compares and analyses past research papers and its contribution to this study. The third section, will include a discussion of the data obtained and preliminary analysis in the form of descriptive statistics and a correlation matrix. The penultimate section will outline the methodology used and the reasoning behind the econometric regressions run. There will also be an in-depth analysis on the...

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