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Accounting for regional poverty differences in Croatia: Exploring the role of disparities in average income and inequality

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  • Rubil, Ivica

Abstract

The prevalence of poverty in a given population is determined by both the level of average income and the shape of income distribution. Accordingly, the difference in poverty between two populations can be attributed to disparities in their average incomes and in the levels of income inequality. In this paper, we decompose the differences in relative poverty between each of the twenty-one Croatian counties and Croatia as a whole into the contributions of the mean income and income inequality, using the Household Budget Survey data for 2010. The decomposition framework that we utilize here is one usually applied for decompositions of intertemporal poverty changes, and is based on the concept of Shapley value from cooperative game theory. Poverty is measured by three conventional measures – the headcount ratio, the poverty gap, and the squared poverty gap – and robustness of the results to switching from one measure to another is discussed. The results of decompositions show that in most cases both the mean income and inequality differences contribute to poverty variation across the counties, relative to poverty in Croatia as a whole. When poverty is measured by the headcount ratio, the income contribution dominates the inequality contribution, while when we switch to the other two measures, which give more weight to poorer among the poor, the inequality contribution starts to dominate.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 43827.

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Date of creation: 16 Jan 2013
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Handle: RePEc:pra:mprapa:43827

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Keywords: regional poverty; decomposition; income contribution; inequality contribution; Shapley value; Croatia;

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  1. Datt, Gaurav & Ravallion, Martin, 1992. "Growth and redistribution components of changes in poverty measures : A decomposition with applications to Brazil and India in the 1980s," Journal of Development Economics, Elsevier, vol. 38(2), pages 275-295, April.
  2. Kelly LABAR & Florent BRESSON, 2007. "“Leftist”, “Rightist” and Intermediate Decompositions of Poverty Variations with an Application to China from 1990 to 2003," Working Papers 200727, CERDI.
  3. Zhang, Yin & Wan, Guanghua, 2006. "The Impacts of Growth and Inequality on Rural Poverty in China," Working Paper Series RP2006/94, World Institute for Development Economic Research (UNU-WIDER).
  4. Florent Bresson, 2008. "Erratum to ``The estimation of the growth and redistribution components of changes in poverty: a reassessment'''," Economics Bulletin, AccessEcon, vol. 9(19), pages 1-2.
  5. Stanislav Kolenikov & Anthony Shorrocks, 2005. "A Decomposition Analysis of Regional Poverty in Russia," Review of Development Economics, Wiley Blackwell, vol. 9(1), pages 25-46, 02.
  6. Florent Bresson, 2008. "The estimation of the growth and redistribution components of changes in poverty: a reassessment," Economics Bulletin, AccessEcon, vol. 9(14), pages 1-7.
  7. Deutsch, Joseph & Silber, Jacques, 2011. "On various ways of measuring pro-poor growth," Economics Discussion Papers 2011-13, Kiel Institute for the World Economy.
  8. Francis Menjo Baye, 2006. "Growth, Redistribution and Poverty Changes in Cameroon: A Shapley Decomposition Analysis," Journal of African Economies, Centre for the Study of African Economies (CSAE), vol. 15(4), pages 543-570, December.
  9. Paolo Verme, 2006. "Pro-poor Growth during Exceptional Growth. Evidence from a Transition Economy," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 3(1), pages 3-14, June.
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