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Growth, inequality, and poverty: Prospects for pro-poor economic development

Several literatures are there investigating the relationship between different combinations of openness, growth, inequality and poverty (Sachs and Werner 1995; Dollar and Kraay 2001a; Person and Tabellini 1994; Deininger and Squire 1998; Goudie and Ladd 1999; van der Hoeven and Shorrocks 2003). In general they found a positive relationship between openness and growth but the differences between and within countries in the impacts of growth on the poor can be large. In recent years the research and debate has focused on the extent to benefit the poor from this economic growth (Ravallion 1998 and 2001; Ravallion and Chen 2003; Ravallion and Datt 2000; Quah 2001). One extreme of the debate argues that the potential benefits of economic growth to the poor are undermined or offset by the inadequate redistributive policies and by increases in inequality that accompany economic growth. The second extreme argues that despite increased inequality in the liberal economic policies and open markets raise incomes of everyone in the society inclusive the poor which proportionally reduce the incidence of poverty. The poor in developing countries often defined as the bottom quintile of the income distribution. This paper discusses the causal relationship between inequality and the numbers of macroeconomic variables frequently found in the inequality and growth literature are also in relation with pro-poor growth issues. These include growth, openness, wages, liberalisation, etc.1 Here the existing cross-country empirical evidence on the inequality effects of growth and the extent to which the poorest in society benefit from economic growth is reviewed. In the review of literature mainly empirical examples from 1990s are taken. In addition we test the conditional and unconditional relationship between inequality and growth post the World War II period based on the WIDER inequality database. The results from the literature will also be compared with those based on the WIID database. Empirical results suggest that the outcomes of policy measures are heterogeneous in their impacts.