This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

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

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Dieter von Fintel () (Department of Economics, Stellenbosch University)

Additional information is available for the following registered author(s):

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.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.ekon.sun.ac.za/wpapers/2006/wp082006/wp-08-2006.pdf
File Format: application/pdf
File Function: First version, 2006
Download Restriction: no

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

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: 2006
Date of revision:
Handle: RePEc:sza:wpaper:wpapers22

Contact details of provider:
Postal: Private Bag X1, 7602 Matieland
Phone: 021-8082247
Fax: +27 (0)21-808 2409
Email:
Web page: http://www.ekon.sun.ac.za
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (Melt van Schoor).

Related research
Keywords: Labour; household surveys; earnings;

Other versions of this item:

Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models
C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
J01 - Labor and Demographic Economics - - General - - - Labor Economics: General
C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Microeconomic Data

This paper has been announced in the following NEP Reports:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, vol. 47(1), pages 153-61, January. [Downloadable!] (restricted)
  2. John K. Dagsvik and Bjørn H. Vatne, 1999. "Is the Distribution of Income Compatible with a Stable Distribution?," Discussion Papers 246, Research Department of Statistics Norway. [Downloadable!]
  3. Murray Leibbrandt & Haroon Bhorat, 1999. "Modelling Vulnerability and Low Earnings in the South African Labour Market," Working Papers 9690, University of Cape Town, Development Policy Research Unit. [Downloadable!]
  4. 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. [Downloadable!]
  5. Mette Wik & Tewodros Aragie Kebede & Olvar Bergland & Stein T. Holden, 2004. "On the measurement of risk aversion from experimental data," Applied Economics, Taylor and Francis Journals, vol. 36(21), pages 2443-2451, December. [Downloadable!] (restricted)
  6. 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. [Downloadable!] (restricted)
  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. [Downloadable!] (restricted)
  8. Reza Daniels & Sandrine Rospabé, 2005. "Estimating an Earnings Function from Coarsened Data by an Interval Censored Regression Procedure," Working Papers 9632, University of Cape Town, Development Policy Research Unit. [Downloadable!]
Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  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. [Downloadable!]
  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. [Downloadable!]
Statistics
Access and download statistics

Did you know? The yearly budget of IDEAS is exactly $0: it relies entirely on volunteer work.

This page was last updated on 2009-12-15.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.