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Inequality Convergence: How Sensitive are Results to the Choice of Data?

Author

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  • Nora Lustig

    () (Department of Economics, Tulane University)

  • Daniel Teles

    () (Department of Economics, Tulane University)

Abstract

This paper examines the extent to which estimates of inequality convergence are sensitive to the choice of welfare concept, inequality indicator, database, country coverage, and time period. Moreover, we explore the sensitivity of the estimated rate of convergence by testing five hypotheses using a series of pair-wise F-tests. The main takeaways are as follows. First, estimates appear to be more sensitive to the choice of welfare concept than to the choice of inequality measure. Second, different international inequality databases frequently produce different results, even when the countries, the welfare concept, the inequality measure, and the time period are held constant. Third, while there is a rather large amount of evidence that estimated rates of convergence differ by region and by time, even this result is sensitive to the database that is used to perform the analysis.

Suggested Citation

  • Nora Lustig & Daniel Teles, 2016. "Inequality Convergence: How Sensitive are Results to the Choice of Data?," Working Papers 1613, Tulane University, Department of Economics.
  • Handle: RePEc:tul:wpaper:1613
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    File URL: http://econ.tulane.edu/RePEc/pdf/tul1613.pdf
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    References listed on IDEAS

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    1. repec:ebl:ecbull:v:15:y:2007:i:15:p:1-9 is not listed on IDEAS
    2. Deininger, Klaus & Squire, Lyn, 1996. "A New Data Set Measuring Income Inequality," World Bank Economic Review, World Bank Group, vol. 10(3), pages 565-591, September.
    3. Quah, Danny, 1993. " Galton's Fallacy and Tests of the Convergence Hypothesis," Scandinavian Journal of Economics, Wiley Blackwell, vol. 95(4), pages 427-443, December.
    4. François Bourguignon, 2015. "The Globalization of Inequality," Economics Books, Princeton University Press, edition 1, number 10433.
    5. Nora Lustig & Carola Pessino & John Scott, 2014. "The Impact of Taxes and Social Spending on Inequality and Poverty in Argentina, Bolivia, Brazil, Mexico, Peru, and Uruguay," Public Finance Review, , vol. 42(3), pages 287-303, May.
    6. Partridge, Mark D. & Rickman, Dan S. & Levernier, William, 1996. "Trends in U.S. income inequality: Evidence from a panel of states," The Quarterly Review of Economics and Finance, Elsevier, vol. 36(1), pages 17-37.
    7. Deininger, Klaus & Squire, Lyn, 1996. "A New Data Set Measuring Income Inequality," World Bank Economic Review, World Bank Group, vol. 10(3), pages 565-591, September.
    8. Michael Bleaney & Akira Nishiyama, 2003. "Convergence in income inequality: differences between advanced and developing countries," Economics Bulletin, AccessEcon, vol. 4(22), pages 1-10.
    9. Fábio Gomes, 2007. "Convergence in Income Inequality: the Case of Brazilian Municipalities," Economics Bulletin, AccessEcon, vol. 15(15), pages 1-9.
    10. Roberto Ezcurra & Pedro Pascual, 2009. "Convergence in income inequality in the United States: a nonparametric analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 16(13), pages 1365-1368.
    11. Li, Hongyi & Zou, Heng-fu, 1998. "Income Inequality Is Not Harmful for Growth: Theory and Evidence," Review of Development Economics, Wiley Blackwell, vol. 2(3), pages 318-334, October.
    12. Nora Lustig, 2016. "Commitment to Equity Handbook. A Guide to Estimating the Impact of Fiscal Policy on Inequality and Poverty," Commitment to Equity (CEQ) Working Paper Series 1301, Tulane University, Department of Economics.
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    15. Mark W. Frank, 2009. "Inequality And Growth In The United States: Evidence From A New State-Level Panel Of Income Inequality Measures," Economic Inquiry, Western Economic Association International, vol. 47(1), pages 55-68, January.
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    Cited by:

    1. Nora Lustig, 2018. "Measuring the Distribution of Household Income, Consumption and Wealth: State of Play and Measurement Challenges," Working Papers 1801, Tulane University, Department of Economics.

    More about this item

    Keywords

    Inequality convergence; Inequality databases; Sensitivity analysis.;

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement

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