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

Author

Listed:
  • 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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    References listed on IDEAS

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    Citations

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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.
    2. Francesco Savoia & Ioannis Bournakis & Mona Said & Antonio Savoia, 2024. "Regional income inequality in Egypt: evolution and implications for Sustainable Development Goal 10," Oxford Development Studies, Taylor & Francis Journals, vol. 52(1), pages 17-33, January.
    3. Francesco Savoia, 2020. "Income Inequality Convergence Across EU Regions," LIS Working papers 760, LIS Cross-National Data Center in Luxembourg.
    4. Savoia, Francesco, 2024. "Income inequality convergence among EU regions," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    5. Mauricio de Rosa & Joan Vilá, 2020. "Distributing the missing third: growth and falling inequality in Uruguay 2009-2016," Documentos de Trabajo (working papers) 20-05, Instituto de Economía - IECON.
    6. Mauricio De Rosa & Joan Vilá, 2022. "Beyond tax-survey combination: inequality and the blurry household-firm border," Documentos de Trabajo (working papers) 22-10, Instituto de Economía - IECON.

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    More about this item

    Keywords

    Inequality convergence; Inequality databases; Sensitivity analysis.;
    All these keywords.

    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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