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The Rich Underreport Their Income: Assessing Biases In Inequality Estimates And Correction Methods Using Linked Survey And Tax Data

Author

Listed:
  • Sean Higgins

    (Department of Economics, Tulane University)

  • Nora Lustig

    (Stone Center for Latin American Studies, Department of Economics, Tulane University, Commitment to Equity Institute)

  • Andrea Vigorito

    (Instituto de Economia)

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 downwardbiased 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 overcorrection and overestimation of inequality.

Suggested Citation

  • Sean Higgins & Nora Lustig & Andrea Vigorito, 2018. "The Rich Underreport Their Income: Assessing Biases In Inequality Estimates And Correction Methods Using Linked Survey And Tax Data," Commitment to Equity (CEQ) Working Paper Series 70, Tulane University, Department of Economics.
  • Handle: RePEc:tul:ceqwps:70
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    Cited by:

    1. 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.
    2. 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 Economia - IECON.
    3. 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.
    4. Osvaldo Larranaga & Benajamin Echecopar & Nicolas Grau, 2021. "Una nueva estimacion de la desigualdad de ingresos en Chile," Working Papers wp523, University of Chile, Department of Economics.
    5. 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).
    6. Arthur Charpentier & Emmanuel Flachaire, 2019. "Pareto Models for Top Incomes," Working Papers hal-02145024, HAL.
    7. 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.
    8. 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.
    9. Nora Lustig, 2020. "The ``missing rich'' in household surveys: causes and correction approaches," Working Papers 520, ECINEQ, Society for the Study of Economic Inequality.
    10. Jan Vandemoortele, 2021. "The open‐and‐shut case against inequality," Development Policy Review, Overseas Development Institute, vol. 39(1), pages 135-151, January.

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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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