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Income Convergence in South Africa: Fact or Measurement Error?

Author

Listed:
  • Tobias Lechtenfeld

    (The World Bank Group)

  • Asmus Zoch

    (Stellenbosch University)

Abstract

This paper asks whether income mobility in South Africa over the last decade has indeed been as impressive as currently thought. Using new national panel data (NIDS), substantial measurement error in reported income data is found, which is further corroborated by a provincial income data panel (KIDS). By employing an instrumental variables approach using two different instruments, measurement error can be quantified. Specifically, self-reported income in the survey data is shown to suffer from mean-reverting measurement bias, leading to sizable overestimations of income convergence in both panel data sets. The preferred estimates indicate that previously published income dynamics may have been largely overestimated by as much as 77% for the national NIDS panel and 39% for the provincial KIDS panel. Overall, income mobility appears much smaller than previously thought, while chronic poverty remains substantial and transitory poverty is still very limited in South Africa.

Suggested Citation

  • Tobias Lechtenfeld & Asmus Zoch, 2014. "Income Convergence in South Africa: Fact or Measurement Error?," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 157, Courant Research Centre PEG.
    • Handle: RePEc:got:gotcrc:157
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    References listed on IDEAS

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    Cited by:

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    2. Dieter Fintel & Dorrit Posel, 2016. "Errors in Recalling Childhood Socio-economic Status: The Role of Anchoring and Household Formation in South Africa," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 126(1), pages 119-140, March.

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    More about this item

    Keywords

    Measurement Error; Income Dynamics; Consumption Dynamics; South Africa;
    All these keywords.

    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
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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