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Earnings bracket obstacles in household surveys – How sharp are the tools in the shed?

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  • Dieter von Fintel

    ()
    (Department of Economics, Stellenbosch University)

Abstract

Earnings functions form the basis of numerous labour market analyses. Non-response (particularly among higher earners) may, however, lead to the exclusion of a significant proportion of South Africa’s earnings base. Earnings brackets have been built into surveys to maintain sufficient response rates, but also to capture information from those who are unsure about the earnings of fellow household members. This data type gives a rough indication of where the respondent lies in the income distribution, however exact figures are not available for estimation purposes. To overcome the mixed categorical and point nature of the dependent variable, researchers have traditionally applied midpoints to bracket earnings. Is this method too rudimentary? It is important to establish whether the brackets are too broad in South African Household surveys to be able to make reliable inferences. Here, midpoints are imputed to interval-coded responses alongside theoretical conditional means from the Pareto and lognormal distributions. The interval regression is implemented as a basis case, as it soundly incorporates point and bracket data in its likelihood function. Monte-Carlo simulation evidence suggests that interval regressions are least sensitive to bracket size, however midpoint imputation suffers distortions once brackets are too broad. Coefficient differences are investigated to distinguish similar from different results given the chosen remedy, and to establish whether midpoint imputations are credibly similar to applying interval regressions. To this end, testing procedures require adjustment, with due consideration of the heteroskedasticity introduced by Heckman 2-step estimates. Bootstrapping enhances conclusions, which shows that coefficients are virtually invariant to the proposed methods. Given that the bracket structure of South African Household Surveys has remained largely unchanged, midpoints can be applied without introducing coefficient bias.

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File URL: http://www.ekon.sun.ac.za/wpapers/2006/wp082006/wp-08-2006.pdf
File Function: First version, 2006
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Bibliographic Info

Paper provided by Stellenbosch University, Department of Economics in its series Working Papers with number 08/2006.

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Date of creation: 2006
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Handle: RePEc:sza:wpaper:wpapers22

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Keywords: Labour; household surveys; earnings;

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References

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  1. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
  2. John K. Dagsvik & Bjørn H. Vatne, 1999. "Is the Distribution of Income Compatible with a Stable Distribution?," Discussion Papers 246, Research Department of Statistics Norway.
  3. Sandrine Rospabéa, 2002. "How Did Labour Market Racial Discrimination Evolve After The End Of Apartheid?," South African Journal of Economics, Economic Society of South Africa, vol. 70(1), pages 185-217, 03.
  4. Reza Daniels & Sandrine Rospabé, 2005. "Estimating an Earnings Function from Coarsened Data by an Interval Censored Regression Procedure," Working Papers 05091, University of Cape Town, Development Policy Research Unit.
  5. Lawrence Dacuycuy, 2005. "Is the earnings-schooling relationship linear? a semiparametric analysis," Economics Bulletin, AccessEcon, vol. 3(37), pages 1-8.
  6. Murray Leibbrandt & Haroon Bhorat, 1999. "Modelling Vulnerability and Low Earnings in the South African Labour Market," Working Papers 99032, University of Cape Town, Development Policy Research Unit.
  7. Malcolm Keswell & Laura Poswell, 2004. "Returns To Education In South Africa: A Retrospective Sensitivity Analysis Of The Available Evidence," South African Journal of Economics, Economic Society of South Africa, vol. 72(4), pages 834-860, 09.
  8. Doubell Chamberlain & Servaas van der Berg, 2002. "Earnings functions, labour market discrimination and quality of education in South Africa," Working Papers 02/2002, Stellenbosch University, Department of Economics.
  9. repec:ebl:ecbull:v:3:y:2005:i:37:p:1-8 is not listed on IDEAS
  10. Mette Wik & Tewodros Aragie Kebede & Olvar Bergland & Stein Holden, 2004. "On the measurement of risk aversion from experimental data," Applied Economics, Taylor & Francis Journals, vol. 36(21), pages 2443-2451.
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Cited by:
  1. Derek Yu, 2007. "The comparability of the Statistics South Africa October Household Surveys and Labour Force Surveys," Working Papers 17/2007, Stellenbosch University, Department of Economics.
  2. Paula Armstrong & Janca Steenkamp, 2008. "South African Trade Unions: an Overview for 1995 to 2005," Working Papers 10/2008, Stellenbosch University, Department of Economics.
  3. Derek Yu, 2013. "Some factors influencing the comparability and reliability of poverty estimates across household surveys," Working Papers 03/2013, Stellenbosch University, Department of Economics.

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