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Standard approaches to decomposing how much group differences contribute to inequality rarely show significant between-group inequality, and are of limited use in comparing populations with different numbers of groups. This study applies an adaptation to the standard approach that remedies these problems to longitudinal household data from two Indian villages - Palanpur in the north, and Sugao in the west. The authors find that in Palanpur the largest scheduled caste group failed to share in the gradual rise in village prosperity. This would not have emerged from standard decomposition analysis. However, in Sugao the alternative procedure did not yield any additional insights because income gains applied relatively evenly across castes.
Average income --- Between-group inequality --- Decomposable inequality measures --- Decomposition analysis --- Decomposition techniques --- Economic development --- Economic inequality --- Empirical application --- Equity and Development --- Household data --- Income --- Income distribution --- Income inequality --- Income levels --- Inequality --- Inequality decomposition --- Inequality measurement --- Inequality will increase --- Policy research --- Population share --- Population sub-groups --- Population subgroup --- Poverty Impact Evaluation --- Poverty Reduction --- Rural Poverty Reduction --- Services & Transfers to Poor
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The authors propose a modification to the conventional approach of decomposing income inequality by population sub-groups. Specifically, they propose a measure that evaluates observed between-group inequality against a benchmark of maximum between-group inequality that can be attained when the number and relative sizes of groups under examination are fixed. The authors argue that such a modification can provide a complementary perspective on the question of whether a particular population breakdown is salient to an assessment of inequality in a country. As their measure normalizes between-group inequality by the number and relative sizes of groups, it is also less subject to problems of comparability across different settings. The authors show that for a large set of countries their assessment of the importance of group differences typically increases substantially on the basis of this approach. The ranking of countries (or different population groups) can also differ from that obtained using traditional decomposition methods. Finally, they observe an interesting pattern of higher levels of overall inequality in countries where their measure finds higher between-group contributions.
Between-Group Inequality --- Differences In Income --- Economic Inequality --- Economic Policy --- Equity and Development --- Group Inequality --- Group Means --- Income --- Income Differences --- Income Distribution --- Income Inequality --- Incomes --- Inequality --- Inequality Aversion --- Inequality Decomposition --- Inequality Measurement --- Mean Differences --- Mean Income --- Mean Incomes --- Measurement Error --- Policy Research --- Population Sub-Groups --- Poverty Impact Evaluation --- Poverty Reduction --- Rural Development --- Rural Poverty Reduction --- Services and Transfers to Poor
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Standard approaches to decomposing how much group differences contribute to inequality rarely show significant between-group inequality, and are of limited use in comparing populations with different numbers of groups. This study applies an adaptation to the standard approach that remedies these problems to longitudinal household data from two Indian villages - Palanpur in the north, and Sugao in the west. The authors find that in Palanpur the largest scheduled caste group failed to share in the gradual rise in village prosperity. This would not have emerged from standard decomposition analysis. However, in Sugao the alternative procedure did not yield any additional insights because income gains applied relatively evenly across castes.
Average income --- Between-group inequality --- Decomposable inequality measures --- Decomposition analysis --- Decomposition techniques --- Economic development --- Economic inequality --- Empirical application --- Equity and Development --- Household data --- Income --- Income distribution --- Income inequality --- Income levels --- Inequality --- Inequality decomposition --- Inequality measurement --- Inequality will increase --- Policy research --- Population share --- Population sub-groups --- Population subgroup --- Poverty Impact Evaluation --- Poverty Reduction --- Rural Poverty Reduction --- Services & Transfers to Poor
Choose an application
The authors propose a modification to the conventional approach of decomposing income inequality by population sub-groups. Specifically, they propose a measure that evaluates observed between-group inequality against a benchmark of maximum between-group inequality that can be attained when the number and relative sizes of groups under examination are fixed. The authors argue that such a modification can provide a complementary perspective on the question of whether a particular population breakdown is salient to an assessment of inequality in a country. As their measure normalizes between-group inequality by the number and relative sizes of groups, it is also less subject to problems of comparability across different settings. The authors show that for a large set of countries their assessment of the importance of group differences typically increases substantially on the basis of this approach. The ranking of countries (or different population groups) can also differ from that obtained using traditional decomposition methods. Finally, they observe an interesting pattern of higher levels of overall inequality in countries where their measure finds higher between-group contributions.
Between-Group Inequality --- Differences In Income --- Economic Inequality --- Economic Policy --- Equity and Development --- Group Inequality --- Group Means --- Income --- Income Differences --- Income Distribution --- Income Inequality --- Incomes --- Inequality --- Inequality Aversion --- Inequality Decomposition --- Inequality Measurement --- Mean Differences --- Mean Income --- Mean Incomes --- Measurement Error --- Policy Research --- Population Sub-Groups --- Poverty Impact Evaluation --- Poverty Reduction --- Rural Development --- Rural Poverty Reduction --- Services and Transfers to Poor
Listing 1 - 4 of 4 |
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