IDEAS home Printed from https://ideas.repec.org/p/inq/inqwps/ecineq2018-463.html
   My bibliography  Save this paper

Top incomes and inequality measurement: A comparative analysis of correction methods using the EU-SILC data

Author

Listed:
  • Vladimir Hlasny

    (Ewha Womans University)

  • Paolo Verme

    (World Bank)

Abstract

It is sometimes observed and frequently assumed that top incomes in household surveys worldwide are poorly measured and that this problem biases the measurement of income inequality. This paper tests this assumption and compares the performance of reweighting and replacing methods designed to correct inequality measures for top income biases generated by data issues such as unit or item nonresponse. Results for the European Union’s Statistics on Income and Living Conditions survey indicate that survey response probabilities are negatively associated with income and bias the measurement of inequality downward. Correcting for this bias with reweighting, the Gini coefficient for Europe is revised upwards by 3.7 percentage points. Similar results are reached with replacing of top incomes using values from the Pareto distribution when the cut point for the analysis is below the 95th percentile. For higher cut points, results with replacing are inconsistent suggesting that popular parametric distributions do not mimic real data well at the very top of the income distribution.

Suggested Citation

  • Vladimir Hlasny & Paolo Verme, 2018. "Top incomes and inequality measurement: A comparative analysis of correction methods using the EU-SILC data," Working Papers 463, ECINEQ, Society for the Study of Economic Inequality.
    • Handle: RePEc:inq:inqwps:ecineq2018-463
    as

    Download full text from publisher

    File URL: http://www.ecineq.org/milano/WP/ECINEQ2018-463.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Vladimir Hlasny & Paolo Verme, 2018. "Top Incomes and the Measurement of Inequality in Egypt," The World Bank Economic Review, World Bank, vol. 32(2), pages 428-455.
    2. Facundo Alvaredo & Lydia Assouad & Thomas Piketty, 2017. "Appendix to "Measuring Inequality in the Middle East 1990-2016: The World's Most Unequal Region?"," World Inequality Lab Working Papers halshs-02797374, HAL.
    3. Angus Deaton, 2005. "Measuring Poverty in a Growing World (or Measuring Growth in a Poor World)," The Review of Economics and Statistics, MIT Press, vol. 87(1), pages 1-19, February.
    4. Anthony B. Atkinson & Thomas Piketty & Emmanuel Saez, 2011. "Top Incomes in the Long Run of History," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 3-71, March.
    5. James B. McDonald, 2008. "Some Generalized Functions for the Size Distribution of Income," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Duangkamon Chotikapanich (ed.), Modeling Income Distributions and Lorenz Curves, chapter 3, pages 37-55, Springer.
    6. Stephen P. Jenkins, 2017. "Pareto Models, Top Incomes and Recent Trends in UK Income Inequality," Economica, London School of Economics and Political Science, vol. 84(334), pages 261-289, April.
    7. Angus Deaton, 2005. "ERRATUM: Measuring Poverty in a Growing World (or Measuring Growth in a Poor World)," The Review of Economics and Statistics, MIT Press, vol. 87(2), pages 395-395, May.
    8. Reza Modarres & Joseph L. Gastwirth, 2006. "A Cautionary Note on Estimating the Standard Error of the Gini Index of Inequality," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(3), pages 385-390, June.
    9. Jenkins, Stephen P., 2007. "Inequality and the GB2 Income Distribution," IZA Discussion Papers 2831, Institute of Labor Economics (IZA).
    10. Mistiaen, Johan A. & Ravallion, Martin, 2003. "Survey compliance and the distribution of income," Policy Research Working Paper Series 2956, The World Bank.
    11. Davidson, Russell & Flachaire, Emmanuel, 2007. "Asymptotic and bootstrap inference for inequality and poverty measures," Journal of Econometrics, Elsevier, vol. 141(1), pages 141-166, November.
    12. Facundo Alvaredo & Lydia Assouad & Thomas Piketty, 2019. "Measuring lnequality in the Middle East 1990–2016: The World’s Most Unequal Region?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 65(4), pages 685-711, December.
    13. Vladimir Hlasny, 2020. "Nonresponse Bias in Inequality Measurement: Cross‐Country Analysis Using Luxembourg Income Study Surveys," Social Science Quarterly, Southwestern Social Science Association, vol. 101(2), pages 712-731, March.
    14. Michał Brzeziński, 2013. "Parametric Modelling of Income Distribution in Central and Eastern Europe," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 5(3), pages 207-230, September.
    15. Vladimir Hlasny & Paolo Verme, 2022. "The Impact of Top Incomes Biases on the Measurement of Inequality in the United States," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 749-788, August.
    16. Stephen P. Jenkins & Richard V. Burkhauser & Shuaizhang Feng & Jeff Larrimore, 2011. "Measuring inequality using censored data: a multiple‐imputation approach to estimation and inference," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(1), pages 63-81, January.
    17. Cowell, Frank A. & Flachaire, Emmanuel, 2007. "Income distribution and inequality measurement: The problem of extreme values," Journal of Econometrics, Elsevier, vol. 141(2), pages 1044-1072, December.
    18. Christoph Lakner & Branko Milanovic, 2016. "Global Income Distribution: From the Fall of the Berlin Wall to the Great Recession," The World Bank Economic Review, World Bank, vol. 30(2), pages 203-232.
    19. Joachim R. Frick & Kristina Krell, 2010. "Measuring Income in Household Panel Surveys for Germany: A Comparison of EU-SILC and SOEP," SOEPpapers on Multidisciplinary Panel Data Research 265, DIW Berlin, The German Socio-Economic Panel (SOEP).
    20. Butler, Richard J. & McDonald, James B., 1989. "Using incomplete moments to measure inequality," Journal of Econometrics, Elsevier, vol. 42(1), pages 109-119, September.
    21. Richard Burkhauser & Shuaizhang Feng & Stephen Jenkins & Jeff Larrimore, 2011. "Estimating trends in US income inequality using the Current Population Survey: the importance of controlling for censoring," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 9(3), pages 393-415, September.
    22. Metzing, Maria & Bartels, Charlotte, 2016. "An integrated approach for top-corrected Ginis," VfS Annual Conference 2016 (Augsburg): Demographic Change 145818, Verein für Socialpolitik / German Economic Association.
    23. Singh, S K & Maddala, G S, 1976. "A Function for Size Distribution of Incomes," Econometrica, Econometric Society, vol. 44(5), pages 963-970, September.
    24. Korinek, Anton & Mistiaen, Johan A. & Ravallion, Martin, 2007. "An econometric method of correcting for unit nonresponse bias in surveys," Journal of Econometrics, Elsevier, vol. 136(1), pages 213-235, January.
    25. Burkhauser, Richard V. & Feng, Shuaizhang & Larrimore, Jeff, 2010. "Improving imputations of top incomes in the public-use current population survey by using both cell-means and variances," Economics Letters, Elsevier, vol. 108(1), pages 69-72, July.
    26. Cowell, Frank A. & Victoria-Feser, Maria-Pia, 1996. "Poverty measurement with contaminated data: A robust approach," European Economic Review, Elsevier, vol. 40(9), pages 1761-1771, December.
    27. Frank A. Cowell, 2008. "Income Distribution and Inequality," Chapters, in: John B. Davis & Wilfred Dolfsma (ed.), The Elgar Companion to Social Economics, chapter 13, Edward Elgar Publishing.
    28. Facundo Alvaredo & Thomas Piketty, 2014. "Measuring Top Incomes and lnequality in the Middle East: Data Limitations and Illustration with the Case of Egypt," Working Papers 832, Economic Research Forum, revised May 2014.
    29. Anton Korinek & Johan Mistiaen & Martin Ravallion, 2006. "Survey nonresponse and the distribution of income," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 4(1), pages 33-55, April.
    30. Di An & Roderick J. A. Little, 2007. "Multiple imputation: an alternative to top coding for statistical disclosure control," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(4), pages 923-940, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mathias Silva & Michel Lubrano, 2023. "Bayesian correction for missing rich using a Pareto II tail with unknown threshold: Combining EU-SILC and WID data," AMSE Working Papers 2320, Aix-Marseille School of Economics, France.
    2. Cerniauskas Nerijus & Jousten Alain, 2021. "Statutory, effective, and optimal net tax schedules in Lithuania," IZA Journal of Labor Policy, Sciendo & Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 11(1), pages 1-33, May.
    3. Rafael Carranza & Marc Morgan & Brian Nolan, 2023. "Top Income Adjustments and Inequality: An Investigation of the EU‐SILC," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 69(3), pages 725-754, September.
    4. Brunori, Paolo & Salas-Rojo, Pedro & Verme, Paolo, 2022. "Estimating Inequality with Missing Incomes," GLO Discussion Paper Series 1138, Global Labor Organization (GLO).
    5. Nishant Yonzan & Branko Milanovic & Salvatore Morelli & Janet Gornick, 2022. "Drawing a Line: Comparing the Estimation of Top Incomes between Tax Data and Household Survey Data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 67-95, March.
    6. Mathias Silva, 2023. "Parametric models of income distributions integrating misreporting and non-response mechanisms," AMSE Working Papers 2311, Aix-Marseille School of Economics, France.
    7. Vladimir Hlasny & Paolo Verme, 2022. "The Impact of Top Incomes Biases on the Measurement of Inequality in the United States," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 749-788, August.
    8. Thomas Blanchet & Ignacio Flores & Marc Morgan, 2022. "The weight of the rich: improving surveys using tax data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 119-150, March.
    9. Vladimir Hlasny, 2021. "Parametric representation of the top of income distributions: Options, historical evidence, and model selection," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1217-1256, September.
    10. Lidia Ceriani & Paolo Verme, 2019. "The inequality of extreme incomes," Working Papers 490, ECINEQ, Society for the Study of Economic Inequality.
    11. João Nicolau & Pedro Raposo & Paulo M. M. Rodrigues, 2023. "Measuring wage inequality under right censoring," Economic Inquiry, Western Economic Association International, vol. 61(2), pages 377-401, April.
    12. 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.
    13. 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.
    14. Pablo A. Mitnik & Anne-Line Helsø & Victoria L. Bryant, 2020. "Inequality of Opportunity for Income in Denmark and the United States: A Comparison Based on Administrative Data," NBER Chapters, in: Measuring Distribution and Mobility of Income and Wealth, pages 317-382, National Bureau of Economic Research, Inc.
    15. Mariusz J. Ligarski & Maciej Wolny, 2021. "Quality of Life Surveys as a Method of Obtaining Data for Sustainable City Development—Results of Empirical Research," Energies, MDPI, vol. 14(22), pages 1-20, November.
    16. 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.
    17. Nora Lustig, 2020. "The ``missing rich'' in household surveys: causes and correction approaches," Working Papers 520, ECINEQ, Society for the Study of Economic Inequality.
    18. Stefano Boscolo, 2022. "The contribution of tax-benefit instruments to income redistribution in Italy," ECONOMIA PUBBLICA, FrancoAngeli Editore, vol. 2022(2), pages 181-231.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vladimir Hlasny & Paolo Verme, 2022. "The Impact of Top Incomes Biases on the Measurement of Inequality in the United States," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 749-788, August.
    2. Vladimir Hlasny, 2021. "Parametric representation of the top of income distributions: Options, historical evidence, and model selection," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1217-1256, September.
    3. Nora Lustig, 2020. "The ``missing rich'' in household surveys: causes and correction approaches," Working Papers 520, ECINEQ, Society for the Study of Economic Inequality.
    4. Vladimir Hlasny, 2019. "Redistributive Impacts of Fiscal Policies in Mexico: Corrections for Top Income Measurement Problems," LIS Working papers 765, LIS Cross-National Data Center in Luxembourg.
    5. 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.
    6. Vladimir Hlasny & Paolo Verme, 2018. "Top Incomes and the Measurement of Inequality in Egypt," The World Bank Economic Review, World Bank, vol. 32(2), pages 428-455.
    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. Lidia Ceriani & Paolo Verme, 2022. "Population Changes and the Measurement of Inequality," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 162(2), pages 549-575, July.
    9. 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.
    10. Rafael Carranza & Marc Morgan & Brian Nolan, 2023. "Top Income Adjustments and Inequality: An Investigation of the EU‐SILC," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 69(3), pages 725-754, September.
    11. 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.
    12. Jordá, Vanesa & Niño-Zarazúa, Miguel, 2019. "Global inequality: How large is the effect of top incomes?," World Development, Elsevier, vol. 123(C), pages 1-1.
    13. 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.
    14. Christoph Lakner & Branko Milanovic, 2016. "Global Income Distribution: From the Fall of the Berlin Wall to the Great Recession," The World Bank Economic Review, World Bank, vol. 30(2), pages 203-232.
    15. Brunori, Paolo & Salas-Rojo, Pedro & Verme, Paolo, 2022. "Estimating Inequality with Missing Incomes," GLO Discussion Paper Series 1138, Global Labor Organization (GLO).
    16. Arthur Charpentier & Emmanuel Flachaire, 2019. "Pareto Models for Top Incomes," Working Papers hal-02145024, HAL.
    17. Martin Ravallion, 2022. "Missing Top Income Recipients," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 205-222, March.
    18. 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.
    19. Frank A. Cowell & Philippe Kerm, 2015. "Wealth Inequality: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(4), pages 671-710, September.
    20. Bartels, Charlotte & Waldenström, Daniel, 2021. "Inequality and top incomes," GLO Discussion Paper Series 959, Global Labor Organization (GLO).

    More about this item

    Keywords

    Top incomes; inequality measures; survey nonresponse; Pareto distribution; parametric estimation; EU SILC.;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • N35 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - Asia including Middle East

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inq:inqwps:ecineq2018-463. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Maria Ana Lugo (email available below). General contact details of provider: https://edirc.repec.org/data/ecineea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.