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The dynamics of poverty in the first four waves of NIDS

Author

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  • Arden Finn

    (Southern Africa Labour and Development Research Unit, University of Cape Town.)

  • Murray Leibbrandt

    (Southern Africa Labour and Development Research Unit, University of Cape Town.)

Abstract

We analyse the determinants of South Africans moving into and out of poverty over the first four waves of the National Income Dynamics Study (NIDS) for the years 2008 to 2014/2015. We focus on the balanced panel of NIDS respondents and find that a relatively high poverty exit rate was accompanied by a substantial proportion of the population being trapped in severe poverty. The roles of demographic versus income changes over time reveal that changing household composition is the largest trigger of poverty entry and exit, and that increasing income from government grants is the main trigger precipitating poverty exit for about one quarter of our sample. Regression analysis shows that access to the labour market within the household is the single most important determinant of poverty entry and exit after race. We calculate multidimensional poverty rates and find that although MPI poverty is far lower than money-metric poverty, being chronically MPI poor over the four waves is closely matched by being chronically income poor.

Suggested Citation

  • Arden Finn & Murray Leibbrandt, 2016. "The dynamics of poverty in the first four waves of NIDS," SALDRU Working Papers 174, Southern Africa Labour and Development Research Unit, University of Cape Town.
  • Handle: RePEc:ldr:wpaper:174
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    References listed on IDEAS

    as
    1. Josh Budlender & Murray Leibbrandt & Ingrid Woolard, 2015. "South African poverty lines: a review and two new money-metric thresholds," SALDRU Working Papers 151, Southern Africa Labour and Development Research Unit, University of Cape Town.
    2. Ingrid Woolard & Stephan Klasen, 2005. "Determinants of Income Mobility and Household Poverty Dynamics in South Africa," Journal of Development Studies, Taylor & Francis Journals, vol. 41(5), pages 865-897.
    3. Alkire, Sabina & Foster, James, 2011. "Counting and multidimensional poverty measurement," Journal of Public Economics, Elsevier, vol. 95(7), pages 476-487.
    4. Jorge Agüero & Michael R. Carter & Julian May, 2007. "Poverty and Inequality in the First Decade of South Africa's Democracy: What can be Learnt from Panel Data from KwaZulu-Natal?," Journal of African Economies, Centre for the Study of African Economies (CSAE), vol. 16(5), pages 782-812, November.
    5. Jenkins, Stephen P., 2011. "Changing Fortunes: Income Mobility and Poverty Dynamics in Britain," OUP Catalogue, Oxford University Press, number 9780199226436, Decembrie.
    6. Özler, Berk, 2007. "Not Separate, Not Equal: Poverty and Inequality in Post-apartheid South Africa," Economic Development and Cultural Change, University of Chicago Press, vol. 55(3), pages 487-529, April.
    7. Murray Leibbrandt & Ingrid Woolard & Arden Finn & Jonathan Argent, 2010. "Trends in South African Income Distribution and Poverty since the Fall of Apartheid," OECD Social, Employment and Migration Working Papers 101, OECD Publishing.
    8. Finn, Arden & Leibbrandt, Murray, 2013. "The dynamics of poverty in the first three waves of NIDS," SALDRU Working Papers 119, Southern Africa Labour and Development Research Unit, University of Cape Town.
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    Cited by:

    1. Simone Schotte & Rocco Zizzamia & Murray Leibbrandt, 2022. "Snakes and ladders and loaded dice: Poverty dynamics and inequality in South Africa between 2008 and 2017," South African Journal of Economics, Economic Society of South Africa, vol. 90(2), pages 214-242, June.
    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. 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).
    4. Marisa von Fintel, 2021. "Chronic Child Poverty and Health Outcomes in South Africa Using a Multidimensional Poverty Measure," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 14(4), pages 1571-1596, August.
    5. Simone Schotte & Rocco Zizzamia & Murray Leibbrandt, 2017. "Social stratification, life chances and vulnerability to poverty in South Africa," SALDRU Working Papers 208, Southern Africa Labour and Development Research Unit, University of Cape Town.
    6. 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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