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Using Tax Data to Better Capture Top Incomes in Official UK Income Inequality Statistics

In: Measuring Distribution and Mobility of Income and Wealth

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  • Dominic Webber
  • Richard Tonkin
  • Martin Shine

Abstract

It is widely recognised that household surveys do not fully capture the incomes of the very richest individuals and households, particularly those among the so-called “top 1%”, for reasons including non-response and under-reporting. As a consequence, estimates based on survey data alone typically understate true levels of inequality. This paper presents new research and analysis to develop a methodology for improving the measurement of the upper tail of the distribution, which is suitable for use in ONS’s official statistics on household income, in terms of being methodologically sound and based on robust academic research; transparent and understandable by users; and an approach where adjustments are made to underlying microdata rather than aggregates. The methods presented in the paper build upon the work of both the UK Department for Work and Pensions (DWP) and Burkhauser et al. (2018a) in employing methods in which survey-based mean incomes for quantile groups at the top of the distribution are replaced by equivalent figures from tax data. The analysis examines two sets of methods developed from these approaches, with variants of each tested to determine the most appropriate methodology to apply in future official statistical releases by ONS.
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Suggested Citation

  • 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.
    • Handle: RePEc:nbr:nberch:14442
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    References listed on IDEAS

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    1. 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.
    2. repec:hal:spmain:info:hdl:2441/3gpul0a2209cuatfpgqv8qt14j is not listed on IDEAS
    3. Marcelo Medeiros & Juliana Castro Galvão & Luísa Azevedo Nazareno, 2018. "Correcting the Underestimation of Top Incomes: Combining Data from Income Tax Reports and the Brazilian 2010 Census," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 233-244, January.
    4. 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.
    5. 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.
    6. Joseph Stiglitz & Jean-Paul Fitoussi & Martine Durand, 2018. "For Good Measure," SciencePo Working papers Main hal-03393118, HAL.
    7. 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.
    8. Raymundo M. Campos-Vázquez & Nora Lustig, 2017. "Labour income inequality in Mexico: Puzzles solved and unsolved," WIDER Working Paper Series wp-2017-186, World Institute for Development Economic Research (UNU-WIDER).
    9. Anthony Atkinson & Tahnee Ooms, 2015. "UK Estimates of Top Income Shares 2012-2013: Note on Methods," Technical Notes 201504, World Inequality Lab.
    10. Richard V Burkhauser & Nicolas Hérault & Stephen P Jenkins & Roger Wilkins, 2018. "Top incomes and inequality in the UK: reconciling estimates from household survey and tax return data," Oxford Economic Papers, Oxford University Press, vol. 70(2), pages 301-326.
    11. Raymundo M. Campos-Vazquez & Nora Lustig, 2017. "Labour income inequality in Mexico: Puzzles solved and unsolved," Working Papers 1719, Tulane University, Department of Economics.
    12. Facundo Alvaredo, 2017. "UK Estimates of Top Income Shares 2013-2014 and 2014-2015," Technical Notes 201702, World Inequality Lab.
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    Citations

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    Cited by:

    1. Arun Advani, 2022. "Who does and doesn't pay taxes?," Fiscal Studies, John Wiley & Sons, vol. 43(1), pages 5-22, March.
    2. Nicolas Herault & Stephen P. Jenkins, 2021. "Redistributive effect and the progressivity of taxes and benefits: evidence for the UK, 1977–2018," Working Papers 592, ECINEQ, Society for the Study of Economic Inequality.
    3. Hérault, Nicolas & Jenkins, Stephen P., 2021. "Redistributive effect and the progressivity of taxes and benefits: evidence for the UK, 1977–2018," LSE Research Online Documents on Economics 112679, London School of Economics and Political Science, LSE Library.
    4. Andrew Aitken & Martin Weale, 2022. "Measuring National Income Growth Democratically: Methods and Estimates for the United Kingdom," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-17, Economic Statistics Centre of Excellence (ESCoE).
    5. Richard Tonkin & Sean White & Sofiya Stoyanova & Aly Youssef & Sunny Valentineo Sidhu & Chris Payne, 2020. "Developing Indicators of Inequality and Poverty Consistent with National Accounts," NBER Chapters, in: Measuring Distribution and Mobility of Income and Wealth, pages 605-624, National Bureau of Economic Research, Inc.
    6. 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.
    7. Stephen P. Jenkins, 2022. "Top-income adjustments and official statistics on income distribution: the case of the UK," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 151-168, March.
    8. Wynnona Steyn & Alexius Sithole & Winile Ngobeni & Eva Muwanga-Zake & Helen Barnes & Michael Noble & David McLennan & Gemma Wright & Katrin Gasior, 2021. "Simulating personal income tax in South Africa using administrative data and survey data: A comparison of PITMOD and SAMOD for tax year 2018," WIDER Working Paper Series wp-2021-120, World Institute for Development Economic Research (UNU-WIDER).

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    More about this item

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • H31 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - Household

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