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Survey Under-Coverage of Top Incomes and Estimation of Inequality: What Is the Role of the UK’s SPI Adjustment?

Author

Listed:
  • Richard V. Burkhauser

    (Lyndon B. Johnson School of Public Affairs, University of Texas-Austin; Department of Policy Analysis and Management, Cornell University; Melbourne Institute: Applied Economic and Social Research, The University of Melbourne)

  • Nicolas Hérault

    (Melbourne Institute: Applied Economic and Social Research, The University of Melbourne)

  • Stephen P. Jenkins

    (London School of Economics; Institute for Social and Economic Research, University of Essex; and Institute for the Study of Labor (IZA); Melbourne Institute: Applied Economic and Social Research, The University of Melbourne)

  • Roger Wilkins

    (Melbourne Institute: Applied Economic and Social Research, The University of Melbourne)

Abstract

Survey under-coverage of top incomes leads to bias in survey-based estimates of overall income inequality. Using income tax record data in combination with survey data is a potential approach to address the problem; we consider here the UK’s pioneering ‘SPI adjustment’ method that implements this idea. Since 1992, the principal income distribution series (reported annually in Households Below Average Income) has been based on household survey data in which the incomes of a small number of ‘very rich’ individuals are adjusted using information from ‘very rich’ individuals in personal income tax return data. We explain what the procedure involves, reveal the extent to which it addresses survey under-coverage of top incomes, and show how it affects estimates of overall income inequality. More generally, we assess whether the SPI adjustment is fit for purpose and consider whether variants of it could be employed by other countries.

Suggested Citation

  • 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.
    • Handle: RePEc:iae:iaewps:wp2017n16
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    References listed on IDEAS

    as
    1. Richard V. Burkhauser & Shuaizhang Feng & Stephen P. Jenkins & Jeff Larrimore, 2009. "Recent trends in top income shares in the USA: Reconciling estimates from March CPS and IRS tax return data," Working Papers 139, ECINEQ, Society for the Study of Economic Inequality.
    2. 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.
    3. 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.
    4. Richard V. Burkhauser & Shuaizhang Feng & Stephen P. Jenkins & Jeff Larrimore, 2012. "Recent Trends in Top Income Shares in the United States: Reconciling Estimates from March CPS and IRS Tax Return Data," The Review of Economics and Statistics, MIT Press, vol. 94(2), pages 371-388, May.
    5. 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.
    6. Stefan Bach & Giacomo Corneo & Viktor Steiner, 2009. "From Bottom To Top: The Entire Income Distribution In Germany, 1992–2003," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 55(2), pages 303-330, June.
    7. Mike Brewer & Ben Etheridge & Cormac O’Dea, 2017. "Why are Households that Report the Lowest Incomes So Well‐off?," Economic Journal, Royal Economic Society, vol. 127(605), pages 24-49, October.
    8. Mike Brewer & Liam Wren-Lewis, 2016. "Accounting for Changes in Income Inequality: Decomposition Analyses for the UK, 1978–2008," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(3), pages 289-322, June.
    9. repec:hal:pseose:halshs-01313784 is not listed on IDEAS
    10. Burkhauser, Richard V. & Herault, Nicolas & Jenkins, Stephen P. & Wilkins, Roger, 2016. "What Has Been Happening to UK Income Inequality since the Mid-1990s? Answers from Reconciled and Combined Household Survey and Tax Return Data," IZA Discussion Papers 9718, Institute of Labor Economics (IZA).
    11. Chris Belfield & Richard Blundell & Jonathan Cribb & Andrew Hood & Robert Joyce, 2017. "Two Decades of Income Inequality in Britain: The Role of Wages, Household Earnings and Redistribution," Economica, London School of Economics and Political Science, vol. 84(334), pages 157-179, April.
    12. Jeff Larrimore & Jacob Mortenson & David Splinter, 2021. "Household Incomes in Tax Data: Using Addresses to Move from Tax-Unit to Household Income Distributions," Journal of Human Resources, University of Wisconsin Press, vol. 56(2), pages 600-631.
    13. Jeff Larrimore & Richard V. Burkhauser & Gerald Auten & Philip Armour, 2016. "Recent Trends in U.S. Top Income Shares in Tax Record Data Using More Comprehensive Measures of Income Including Accrued Capital Gains," NBER Working Papers 23007, National Bureau of Economic Research, Inc.
    14. Andreas Alfons & Matthias Templ & Peter Filzmoser, 2013. "Robust estimation of economic indicators from survey samples based on Pareto tail modelling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(2), pages 271-286, March.
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Inequality and poverty
      by chris in Stumbling and Mumbling on 2018-04-03 12:54:55

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    Cited by:

    1. Brian A'Hearn & Stefano Chianese & Giovanni Vecchi, 2020. "Aristocracy and Inequality in Italy, 1861-1931," HHB Working Papers Series 18, The Historical Household Budgets Project.
    2. 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.
    3. 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.
    4. Tahnee Christelle Ooms, 2021. "Correcting the Underestimation of Capital Incomes in Inequality Indicators: with an Application to the UK, 1997–2016," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 157(3), pages 929-953, October.
    5. Ooms, Tahnee, 2021. "Correcting the underestimation of capital incomes in inequality indicators: with an application to the UK, 1997–2016," LSE Research Online Documents on Economics 108900, London School of Economics and Political Science, LSE Library.

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    More about this item

    Keywords

    Inequality; income inequality; survey under-coverage; SPI adjustment; top incomes; tax return data; survey data;
    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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