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What do household surveys suggest about the top 1% incomes and inequality in OECD countries?

Author

Listed:
  • Nicolas Ruiz

    (OECD)

  • Nicolas Woloszko
Abstract
Standard income inequality figures, based on official household survey statistics covering most of the population, report a steady rise of inequality across a majority of advanced countries. The usefulness of these data sources in providing a timely and internationally comparable picture of inequality is undisputed, but one well-known limitation is their under-reporting of top incomes. This matters insofar as separate data sources devoted specifically to top incomes evolution report substantially faster inequality growth in recent years compared to conventional statistics. This paper proposes a methodology to adjust household survey data for the under-reporting of top incomes. More specifically, the analysis delivers a set of top incomes-adjusted income distribution series that bring together the bottom 99% and the top 1%. Unsurprisingly, the results point to a significant increase of the level of inequality measured by standard statistics based on official figures: the Gini coefficient adjusted for top incomes was in 2011 on average 6 percentage points higher, moving from 0.31 to 0.37 for the average OECD country; similarly, the gap between the mean income of the richest and the poorest 10% rises from 10 to 15 as a result from the adjustment. Inequality trends are also significantly altered, albeit in ways that differ across countries. Que peut-on apprendre des hauts revenus à partir de données d'enquêtes dans les pays de l'OCDE ? Les chiffres sur les inégalités de revenus, basés sur les enquêtes auprès des ménages, couvrent la plupart de la population et font état d'une augmentation constante de l'inégalité dans la majorité des pays avancés. L'utilité de ces sources afin de fournir une image satisfaisante et comparables à l'échelle internationale de l'inégalité est reconnue, mais une limite bien connue est leur sous-déclaration des hauts revenus. Cela importe dans la mesure où des sources de données distinctes consacrées spécifiquement aux hauts revenus décrivent une évolution de l'inégalité sensiblement plus rapide au cours des dernières années par rapport aux statistiques classiques. Cet article propose une méthodologie pour ajuster les données d'enquêtes auprès des ménages pour la sous-déclaration des hauts revenus. Plus précisément, l'analyse fournit un ensemble de série sur la répartition des revenus ajustés pour les hauts revenus et qui rassemblent ainsi les 99% et les 1% des ménages les plus riches. Les résultats montrent une augmentation significative du niveau de l'inégalité par rapport aux statistiques standard basées sur des chiffres officiels: le coefficient de Gini corrigé des hauts revenus a été en 2011 en moyenne de 6 points de pourcentage supérieur, passant de 0,31 à 0,37 pour la moyenne des pays de l'OCDE ; De même, l'écart entre le revenu moyen des plus riches et les plus pauvres passe de 10 à 15 suite à l'ajustement. L'évolution des inégalités est également modifiée de façon significative, quoique de manière hétérogène selon les pays.

Suggested Citation

  • Nicolas Ruiz & Nicolas Woloszko, 2016. "What do household surveys suggest about the top 1% incomes and inequality in OECD countries?," OECD Economics Department Working Papers 1265, OECD Publishing.
    • Handle: RePEc:oec:ecoaaa:1265-en
    DOI: 10.1787/5jrs556f36zt-en
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    Citations

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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. Jose De Gregorio & Manuel Taboada, 2022. "Median Labor Income in Chile Revised: Insights from Distributional National Accounts," Working Papers wp532, University of Chile, Department of Economics.
    3. Richard V. Burkhauser & Nicolas Hérault & Stephen P. Jenkins & Roger Wilkins, 2018. "Survey Under‐Coverage of Top Incomes and Estimation of Inequality: What is the Role of the UK's SPI Adjustment?," Fiscal Studies, John Wiley & Sons, vol. 39(2), pages 213-240, June.
    4. 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.
    5. Engel, Janina & Riera, Pau Gayà & Grilli, Joseph & Sola, Pierre, 2022. "Developing reconciled quarterly distributional national wealth – insight into inequality and wealth structures," Working Paper Series 2687, European Central Bank.
    6. Arun Advani, 2022. "Who does and doesn't pay taxes?," Fiscal Studies, John Wiley & Sons, vol. 43(1), pages 5-22, March.
    7. Engel, Janina & Ohlwerter, Dennis & Scherer, Matthias, 2023. "On the estimation of distributional household wealth: addressing under-reporting via optimization problems with invariant Gini coefficient," Working Paper Series 2865, European Central Bank.
    8. Bental, Benjamin & Kragl, Jenny, 2021. "Inequality and incentives with societal other-regarding preferences," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 1298-1324.
    9. Safari, Muhammad Aslam Mohd & Masseran, Nurulkamal & Ibrahim, Kamarulzaman, 2018. "A robust semi-parametric approach for measuring income inequality in Malaysia," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1-13.
    10. Callan, Tim & Doorley, Karina & McTague, Alyvia, 2020. "Top Incomes in Ireland: Reconciling Evidence from Tax Records and Household Survey Data," IZA Discussion Papers 13585, Institute of Labor Economics (IZA).
    11. Thomas Goda & Santiago Sanchez, 2018. "Market and Disposable Top Income Shares adjusted by National Accounts Data," Journal of Income Distribution, Ad libros publications inc., vol. 26(2), pages 1-22, July.
    12. 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.
    13. Oguzhan Akgun & Boris Cournède & Jean-Marc Fournier, 2017. "The effects of the tax mix on inequality and growth," OECD Economics Department Working Papers 1447, OECD Publishing.
    14. Monica Brezzi & Luiz de Mello, 2016. "Inequalities in Latin America: Trends and implications for Policy," Hacienda Pública Española / Review of Public Economics, IEF, vol. 219(4), pages 93-120, December.
    15. Corlet Walker, Christine & Druckman, Angela & Jackson, Tim, 2021. "Welfare systems without economic growth: A review of the challenges and next steps for the field," Ecological Economics, Elsevier, vol. 186(C).
    16. Dominic Webber & Richard Tonkin & Martin Shine, 2020. "Using Tax Data to Better Capture Top Incomes in Official UK Income Inequality Statistics," NBER Chapters, in: Measuring Distribution and Mobility of Income and Wealth, pages 679-700, National Bureau of Economic Research, Inc.
    17. 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.
    18. Richard V. Burkhauser & Nicolas Hérault & Stephen P. Jenkins & Roger Wilkins, 2017. "Survey Under-Coverage of Top Incomes and Estimation of Inequality: What Is the Role of the UK’s SPI Adjustment?," Melbourne Institute Working Paper Series wp2017n16, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    19. Li, Chengyou & Yu, Yangcheng & Li, Qinghai, 2021. "Top-income data and income inequality correction in China," Economic Modelling, Elsevier, vol. 97(C), pages 210-219.
    20. Cyrille Schwellnus & Andreas Kappeler & Pierre-Alain Pionnier, 2017. "The Decoupling of Median Wages from Productivity in OECD Countries," International Productivity Monitor, Centre for the Study of Living Standards, vol. 32, pages 44-60, Spring.
    21. Nora Lustig, 2020. "The ``missing rich'' in household surveys: causes and correction approaches," Working Papers 520, ECINEQ, Society for the Study of Economic Inequality.
    22. Colacce, Maira & Amarante, Verónica, 2018. "More unequal or less? A review of global, regional and national income inequality," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), April.

    More about this item

    Keywords

    enquête auprès des ménages; hauts revenus; household survey; income; inequality; inégalité; revenu; top incomes;
    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
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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