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The Rich Underreport their Income: Assessing Bias in Inequality Estimates and Correction Methods using Linked Survey and Tax Data

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Listed:
  • Sean Higgins

    (UC Berkeley)

  • Nora Lustig

    (Tulane University)

  • Andrea Vigorito

    (Instituto de Economía, FCEA, Universidad de la República (Uruguay))

Abstract

Do survey respondents misreport their income? If so, how does misreporting correlate with income, how does this affect estimates of income inequality, and how well do existing methods correct for bias? We use a novel database in which a subsample of Uruguay's official household survey has been linked to tax records to document the extent and distribution of labor income underreporting and to assess the performance of various existing methods to correct inequality estimates. Individuals in the upper half of the income distribution tend to report less labor income in household surveys than those same individuals earn according to tax returns, and underreporting is increasing in income. Using simulations, we find that this leads to downward-biased inequality estimates. Correction methods that rely only on survey data barely affect the biased inequality estimates, while methods that combine survey and tax data can lead to over-correction and overestimation of inequality.

Suggested Citation

  • Sean Higgins & Nora Lustig & Andrea Vigorito, 2018. "The Rich Underreport their Income: Assessing Bias in Inequality Estimates and Correction Methods using Linked Survey and Tax Data," Working Papers 1808, Tulane University, Department of Economics.
  • Handle: RePEc:tul:wpaper:1808
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    Cited by:

    1. Arthur Charpentier & Emmanuel Flachaire, 2022. "Pareto models for top incomes and wealth," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 1-25, March.
    2. Diego Winkelried & Bruno Escobar, 2022. "Declining inequality in Latin America? Robustness checks for Peru," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 223-243, March.
    3. Gabriel Burdín & Mauricio de Rosa & Andrea Vigorito & Joan Vilá, 2019. "Was falling inequality in all Latin American countries a data-driven illusion? Income distribution and mobility patterns in Uruguay 2009-2016," Documentos de Trabajo (working papers) 19-30, Instituto de Economía - IECON.
    4. Luis Ayala & Ana Pérez & Mercedes Prieto-Alaiz, 2022. "The impact of different data sources on the level and structure of income inequality," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(3), pages 583-611, September.
    5. Osvaldo Larrañaga & Benjamín Echecopar & Nicolás Grau, 2022. "Una nueva estimación de la desigualdad de ingresos en Chile," Estudios Públicos, Centro de Estudios Públicos, vol. 0(167), pages 45-76.
    6. Burdín, Gabriel & De Rosa, Mauricio & Vigorito, Andrea & Vilá, Joan, 2022. "Falling inequality and the growing capital income share: Reconciling divergent trends in survey and tax data," World Development, Elsevier, vol. 152(C).
    7. Mathias Silva, 2023. "Parametric models of income distributions integrating misreporting and non-response mechanisms," AMSE Working Papers 2311, Aix-Marseille School of Economics, France.
    8. Arthur Charpentier & Emmanuel Flachaire, 2019. "Pareto Models for Top Incomes," Working Papers hal-02145024, HAL.
    9. Pablo Gutiérrez Cubillos, 2022. "Gini and undercoverage at the upper tail: a simple approximation," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 29(2), pages 443-471, April.
    10. Benjamin Ching & Tayla Forward & Oscar Parkyn, 2023. "Estimating the Distribution of Wealth in New Zealand," Treasury Working Paper Series 23/01, New Zealand Treasury.
    11. Emmanuel Flachaire & Nora Lustig & Andrea Vigorito, 2023. "Underreporting of Top Incomes and Inequality: A Comparison of Correction Methods using Simulations and Linked Survey and Tax Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 69(4), pages 1033-1059, December.
    12. Nora Lustig, 2020. "The ``missing rich'' in household surveys: causes and correction approaches," Working Papers 520, ECINEQ, Society for the Study of Economic Inequality.
    13. Jan Vandemoortele, 2021. "The open‐and‐shut case against inequality," Development Policy Review, Overseas Development Institute, vol. 39(1), pages 135-151, January.
    14. Nora Lustig, 2019. "The “Missing Rich” in Household Surveys: Causes and Correction Approaches," Commitment to Equity (CEQ) Working Paper Series 75, Tulane University, Department of Economics.
    15. 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.
    16. Masca, Simona-Gabriela & Chis, Diana-Maria, 2023. "Distributional implications of informal economy in the EU countries: Accounting for the spread of tax evasion benefits and cultural characteristics," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).

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    More about this item

    Keywords

    inequality; income underreporting; tax records; household surveys;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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