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On the suitability of income inequality measures for regional analysis: Some evidence from simulation analysis and bootstrapping tests

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  • Portnov, Boris A.
  • Felsenstein, Daniel

Abstract

The paper looks at the sensitivity of commonly used income inequality measures to changes in the ranking, size and number of regions into which a country is divided. During the analysis, several test distributions of populations and incomes are compared with a 'reference' distribution, characterized by an even distribution of population across regional subdivisions. Random permutation tests are also run to determine whether inequality measures commonly used in regional analysis produce meaningful estimates when applied to regions of different population size. The results show that only the population weighted coefficient of variation (Williamson's index) and population-weighted Gini coefficient may be considered sufficiently reliable inequality measures, when applied to countries with a small number of regions and with varying population sizes.

Suggested Citation

  • Portnov, Boris A. & Felsenstein, Daniel, 2010. "On the suitability of income inequality measures for regional analysis: Some evidence from simulation analysis and bootstrapping tests," Socio-Economic Planning Sciences, Elsevier, vol. 44(4), pages 212-219, December.
    • Handle: RePEc:eee:soceps:v:44:y:2010:i:4:p:212-219
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    1. Gluschenko, Konstantin, 2015. "‘Williamson’s Fallacy’ in Estimation of Inter-Regional Inequality," MPRA Paper 71075, University Library of Munich, Germany, revised 03 May 2016.
    2. Lu, Haiyan & Zhao, Pengjun & Hu, Haoyu & Zeng, Liangen & Wu, Kai Sheng & Lv, Di, 2022. "Transport infrastructure and urban-rural income disparity: A municipal-level analysis in China," Journal of Transport Geography, Elsevier, vol. 99(C).
    3. Presiana Nenkova, 2019. "An Analysis of Equalizing Capacity of State Transfers for Local Government Activities in Bulgaria," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 4, pages 627-640, December.
    4. Domenica Panzera & Paolo Postiglione, 2020. "Measuring the Spatial Dimension of Regional Inequality: An Approach Based on the Gini Correlation Measure," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 148(2), pages 379-394, April.
    5. Thomas Wieland, 2020. "REAT: A Regional Economic Analysis Toolbox for R," REGION, European Regional Science Association, vol. 7, pages 1-57.
    6. Konstantin Gluschenko, 2018. "Measuring regional inequality: to weight or not to weight?," Spatial Economic Analysis, Taylor & Francis Journals, vol. 13(1), pages 36-59, January.
    7. Kowalik Paweł, 2014. "Horizontal Fiscal Imbalance In The United States," Folia Oeconomica Stetinensia, Sciendo, vol. 14(2), pages 140-151, December.
    8. Stefano Magrini & Margherita Gerolimetto & Hasan Engin Duran, 2011. "Distortions in Cross-Sectional Convergence Analysis when the Aggregate Business Cycle is Incomplete," Working Papers 2011_07, Department of Economics, University of Venice "Ca' Foscari".

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