1. Introduction There is extended research analyzing relationship between income inequality and selected macroeconomic variables such as growth rate, inflation rate, openness etc. Azzoni (2001) has analyzed regional inequality in Brazil using data from period 1939-1995. Barro (2000) has used a panel data approach to investigate 100 countries for period 1960-1990. Bandelj and Mahutga (2010) have presented one of cross-national analyses of Central and Eastern European States after fall of communistic regimes. While Azzoni (2001) and Barro (2000) have focused on linkage of inequality and growth, Bandelj and Mahutga (2010) have assessed inequality and socio-economic changes. Beckfield (2009) has developed an argument that regional integration in Europe has affected economic inequality. Also Forbes (2000) has investigated relationship between inequality and growth. In this research data from 13 EU4 countries have been used from period 2000-2009 in an attempt to investigate relationship between income inequality and inflation. The paper is organized as follows: Section 2 gives a brief introduction to income inequality and inflation and outlines some related theoretical and empirical literature. Section 3 presents methodology and results while section 4 concludes research. 2. Inequality and Inflation The GINI coefficient is a widely used statistic for measuring inequality. It is derived from Lorenz curve and defined as ratio of area between Lorenz curve and perfect equality line. The Lorenz curve plots relation between cumulative percentage of population and proportion of total income earned by each cumulative percentage. The dependent variable is GINI coefficient; a common measure of inequality that varies from 0 to 1, where 0 presents perfect equality and 1 perfect inequality. As it is stated in Duro (2004) the GINI coefficient is more sensitive to income changes occurred at middle of income distribution, treating symmetrically lower and upper tails of incomes ranking. Due to fact that income distribution may have long run effects policy makers should be concerned with distributional implications of government policies. Also extent of inequality-inflation link is important in designing of stabilization programs as it is stated in Al-Mahrubi (2000). When unemployment rates increase it usually affect more people in lower tail of personal income distribution, thus lowering average per capita income (Levernier, et al., 1995). Checchi and Garcia-Penalosa (2008) argue that when unemployment rate is not too high unemployment and inequality linkage is positive. Beetsma and Van Der Ploeg (1996), Al-Mahrubi (1997), Romer and Romer (1998) and Albanesi (2001, 2007) have found a strong positive relation between inflation and inequality. Cardoso (1992) has concluded that inflation shifts wage profile. Bulif (1998) has used a cross-sectional approach regressing GINI coefficients and has found that higher inflation is associated with more inequality (Crowe, 2004). Milanovic (1994) argues about factors which determine income distribution. Factors are in short run, from point of view of policy makers or society as a whole given and by social (or public policy) choice. Milanovic (1994) tests hypothesis according to which government policies can significantly change income distribution and Kuznet holds. Al-Marhubi (1997) investigates inflation-inequality link by using positive political-economy approach and finds that countries which have a greater inequality have a higher average rate of inflation. The dependent variable which is used in Al-Mahrubi model is average annual inflation rate in log form and independents are GINI coefficient, openness, political instability, turnover of Central Bank Governors and legal Central Bank independence. …
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