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Survey Under‐Coverage of Top Incomes and Estimation of Inequality: What is the Role of the UK's SPI Adjustment?

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  • Richard V. Burkhauser
  • Nicolas Hérault
  • Stephen P. Jenkins
  • Roger Wilkins

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, 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.
  • Handle: RePEc:wly:fistud:v:39:y:2018:i:2:p:213-240
    DOI: 10.1111/1475-5890.12158
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    1. 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.
    2. Richard Burkhauser & Shuaizhang Feng & Stephen 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 09-26, Center for Economic Studies, U.S. Census Bureau.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Richard V. Burkhauser & Markus H. Hahn & Roger Wilkins, 2016. "Top Incomes and Inequality in Australia: Reconciling Recent Estimates from Household Survey and Tax Return Data," Melbourne Institute Working Paper Series wp2016n19, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
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    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Survey Under-Coverage of Top Incomes and Estimation of Inequality: What Is the Role of the UK’s SPI Adjustment?
      by maximorossi in NEP-LTV blog on 2018-04-09 18:33:55
    2. Survey Under-Coverage of Top Incomes and Estimation of Inequality: What is the Role of the UK’s SPI Adjustment?
      by maximorossi in NEP-LTV blog on 2017-08-11 17:42:47

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    Cited by:

    1. Justin van de Ven & Nicolas Hérault, 2019. "The evolution of tax implicit value judgements, redistribution and income inequality in the UK: 1968 to 2015," Working Papers 498, ECINEQ, Society for the Study of Economic Inequality.
    2. Franzini, Maurizio & Raitano, Michele, 2019. "Earnings inequality and workers’ skills in Italy," Structural Change and Economic Dynamics, Elsevier, vol. 51(C), pages 215-224.
    3. Richard V. Burkhauser & Nicolas Herault & Stephen P. Jenkins & Roger Wilkins, 2020. "What accounts for the rising share of women in the top 1\%?," Working Papers 544, ECINEQ, Society for the Study of Economic Inequality.
    4. Advani, Arun & Koenig, Felix & Pessina, Lorenzo & Summers, Andy, 2020. "Importing Inequality: Immigration and the Top 1 Percent," IZA Discussion Papers 13731, Institute of Labor Economics (IZA).
    5. Zachary Parolin, 2019. "The Effect of Benefit Underreporting on Estimates of Poverty in the United States," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(2), pages 869-898, July.
    6. Thomas Blanchet & Ignacio Flores & Marc Morgan, 2018. "The Weight of the Rich: Improving Surveys Using Tax Data," Working Papers hal-02878315, HAL.
    7. Dominic Webber & Richard P. 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, National Bureau of Economic Research, Inc.
    8. 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.
    9. Milanovic, Branko, 2020. "After the financial crisis: the evolution of the global income distribution between 2008 and 2013," MPRA Paper 101560, University Library of Munich, Germany.
    10. Nora Lustig, 2020. "The ``missing rich'' in household surveys: causes and correction approaches," Working Papers 520, ECINEQ, Society for the Study of Economic Inequality.
    11. , Stone Center & Lustig, Nora, 2020. "The “Missing Rich” in Household Surveys: Causes and Correction Approaches," SocArXiv j23pn, Center for Open Science.

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    More about this item

    JEL classification:

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

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