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Measurement of earnings: Comparing South African tax and survey data

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  • Martin Wittenberg

    (Southern Africa Labour and Development Research Unit, School of Economics, DataFirst, University of Cape Town)

Abstract

Comparing earnings in the tax assessment data to those in the QLFS, it appears that earnings of employees in the QLFS are underreported by perhaps 40%, with bigger gaps near the top of the distribution. Benefits and annual bonuses contribute substantially to the gap. In the case of self-employment incomes it is also the case that high earnings are missing or underreported in the QLFS, but the tax data seems to miss many mid- and low-income self-employed earners. These differences make sense when one considers the incentives for reporting accurately to SARS versus to Statistics South Africa. These errors mean that earnings inequality as measured by the Gini coefficient is probably underestimated in the surveys by three percentage points.

Suggested Citation

  • Martin Wittenberg, 2017. "Measurement of earnings: Comparing South African tax and survey data," SALDRU Working Papers 212, Southern Africa Labour and Development Research Unit, University of Cape Town.
    • Handle: RePEc:ldr:wpaper:212
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    References listed on IDEAS

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    1. Fiona Tregenna & Mfanafuthi Tsela, 2012. "Inequality in South Africa: The distribution of income, expenditure and earnings," Development Southern Africa, Taylor & Francis Journals, vol. 29(1), pages 35-61, March.
    2. Reza C. Daniels, 2012. "Questionnaire Design and Response Propensities for Employee Income Micro Data," SALDRU Working Papers 89, Southern Africa Labour and Development Research Unit, University of Cape Town.
    3. Wittenberg, Martin & Pirouz, Farah, 2013. "The measurement of earnings in the post-Apartheid period: An overview," SALDRU Working Papers 108, Southern Africa Labour and Development Research Unit, University of Cape Town.
    4. Martin Wittenberg, 2017. "Economics and Transformation: Measurements, Models, Maths and Myths," SALDRU Working Papers 211, Southern Africa Labour and Development Research Unit, University of Cape Town.
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    Cited by:

    1. Andrew Kerr & Martin Wittenberg, 2019. "Earnings and employment microdata in South Africa," WIDER Working Paper Series wp-2019-47, World Institute for Development Economic Research (UNU-WIDER).
    2. Gemma Wright & Helen Barnes & Michael Noble & David McLennan & Faith Masekesa, 2018. "Assessing the quality of the income data used in SAMOD, a South African tax-benefit microsimulation model," WIDER Working Paper Series wp-2018-173, World Institute for Development Economic Research (UNU-WIDER).
    3. Amina Ebrahim & Christopher Axelson, 2019. "The creation of an individual panel using administrative tax microdata in South Africa," WIDER Working Paper Series wp-2019-27, World Institute for Development Economic Research (UNU-WIDER).
    4. Ihsaan Bassier & Ingrid Woolard, 2021. "Exclusive Growth? Rapidly Increasing Top Incomes Amid Low National Growth in South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 89(2), pages 246-273, June.
    5. Helen Barnes & Gemma Wright & Michael Noble & David McLennan & Faith Masekesa, 2018. "Assessing the quality of the income data used in SAMOD, a South African tax-benefit microsimulation model," WIDER Working Paper Series 173, World Institute for Development Economic Research (UNU-WIDER).
    6. Jacqueline Mosomi & Mrtin Wittenberg, 2020. "The labor market in South Africa, 2000–2017," IZA World of Labor, Institute of Labor Economics (IZA), pages 475-475, April.
    7. Rocco Zizzamia & Simone Schotte & Murray Leibbrandt, 2019. "Snakes and ladders and loaded dice: Poverty dynamics and inequality in South Africa, 2008-2017," WIDER Working Paper Series wp-2019-25, World Institute for Development Economic Research (UNU-WIDER).
    8. Amina Ebrahim & Kezia Lilenstein, 2019. "Gender and the South African labour market: Policy relevant research possibilities using South African tax data," WIDER Working Paper Series wp-2019-31, World Institute for Development Economic Research (UNU-WIDER).
    9. 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).
    10. Andrew Kerr, 2020. "Earnings in the South African Revenue Service IRP5 data," WIDER Working Paper Series wp-2020-62, World Institute for Development Economic Research (UNU-WIDER).

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