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Sample Attrition in the Canadian Survey of Labor and Income Dynamics

Author

Listed:
  • Boudarbat, Brahim

    (University of Montreal)

  • Grenon, Lee

    (Statistics Canada)

Abstract

This paper provides an analysis of the effects of attrition and non-response on employment and wages using the Canadian Survey of Labour and Income Dynamics. We consider a structural model composed of three freely correlated equations for non-attrition/response, employment and wages. The model is estimated using microdata from 22,990 individuals who provided sufficient information in the first wave of the 1996-2001 panel. The main findings of the paper are that attrition is not random. Attritors and non-respondents likely are less attached to employment and come from low-income population. The correlation between non-attrition and employment is positive and statistically significant, though small. Also, wage estimates are biased upwards. Observed wages are on average higher than wages that would be observed if all the individuals initially selected in the panel remained in the sample.

Suggested Citation

  • Boudarbat, Brahim & Grenon, Lee, 2013. "Sample Attrition in the Canadian Survey of Labor and Income Dynamics," IZA Discussion Papers 7295, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp7295
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    References listed on IDEAS

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    1. Jeffrey E. Zabel, 1998. "An Analysis of Attrition in the Panel Study of Income Dynamics and the Survey of Income and Program Participation with an Application to a Model of Labor Market Behavior," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 479-506.
    2. Van den Berg, G J & Lindeboom, M & Ridder, G, 1994. "Attrition in Longitudinal Panel Data and the Empirical Analysis of Dynamic Labour Market Behaviour," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(4), pages 421-435, Oct.-Dec..
    3. William Greene, 2004. "Convenient estimators for the panel probit model: Further results," Empirical Economics, Springer, vol. 29(1), pages 21-47, January.
    4. Becketti, Sean & Gould, William & Lillard, Lee & Welch, Finis, 1988. "The Panel Study of Income Dynamics after Fourteen Years: An Evaluatio n," Journal of Labor Economics, University of Chicago Press, vol. 6(4), pages 472-492, October.
    5. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    6. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    7. Lee A. Lillard & Constantijn W. A. Panis, 1998. "Panel Attrition from the Panel Study of Income Dynamics: Household Income, Marital Status, and Mortality," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 437-457.
    8. Gerard J. van den Berg & Maarten Lindeboom, 1998. "Attrition in Panel Survey Data and the Estimation of Multi-State Labor Market Models," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 458-478.
    9. Hausman, Jerry A & Wise, David A, 1979. "Attrition Bias in Experimental and Panel Data: The Gary Income Maintenance Experiment," Econometrica, Econometric Society, vol. 47(2), pages 455-473, March.
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    Cited by:

    1. Lluis, Stephanie & McCall, Brian, 2022. "Spousal labour supply adjustments to extended benefits weeks: Evidence from Canada," CLEF Working Paper Series 42, Canadian Labour Economics Forum (CLEF), University of Waterloo.

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    More about this item

    Keywords

    panel data; attrition; selection; SLID; Canada;
    All these keywords.

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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