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An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics

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  • J. Fitzgerald
  • P. Gottschalk
  • R. Moffitt

Abstract

By 1989, the Michigan Panel Study on Income Dynamics (PSID) had experienced approximately 50 percent sample loss from its initial 1968 membership due to cumulative attrition. We study the effect of this attrition on the unconditional distributions of several socioeconomic variables and on the estimates of several sets of regression coefficients. We provide a statistical framework for conducting tests for attrition bias that draws a sharp distinction between selection on unobservables and on observables and that shows that weighted least squares can generate consistent parameter estimates when selection is based on observables, even when they are endogenous. Our empirical analysis shows that attrition is highly selective and is concentrated among individuals of lower socioeconomic status. We also show that attrition is concentrated among those with more unstable earnings, marriage, and migration histories. Nevertheless, we find that these variables explain very little of the attrition in the sample and that the selection that occurs is moderated by regression-to-the-mean effects from selection on transitory components that fade over time. Consequently, despite the large amount of attrition, we find no strong evidence that attrition has seriously distorted the representativeness of the PSID through 1989, and considerable evidence that its cross-sectional representativeness has remained roughly intact.

Suggested Citation

  • J. Fitzgerald & P. Gottschalk & R. Moffitt, "undated". "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics," Institute for Research on Poverty Discussion Papers 1156-98, University of Wisconsin Institute for Research on Poverty.
  • Handle: RePEc:wop:wispod:1156-98
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    References listed on IDEAS

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    1. Verbeek, M.J.C.M. & Nijman, T.E., 1992. "Incomplete panels and selection bias : A survey," Discussion Paper 1992-7, Tilburg University, Center for Economic Research.
    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. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444606.
    4. Judith K. Hellerstein & Guido W. Imbens, 1999. "Imposing Moment Restrictions From Auxiliary Data By Weighting," The Review of Economics and Statistics, MIT Press, vol. 81(1), pages 1-14, February.
    5. Manski, C.F., 1990. "The Selection Problem," Working papers 90-12, Wisconsin Madison - Social Systems.
    6. Ridder, Geert, 1992. "An empirical evaluation of some models for non-random attrition in panel data," Structural Change and Economic Dynamics, Elsevier, vol. 3(2), pages 337-355, December.
    7. Nijman, Theo & Verbeek, Marno, 1992. "Nonresponse in Panel Data: The Impact on Estimates of a Life Cycle Consumption Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(3), pages 243-257, July-Sept.
    8. Horowitz, Joel L. & Manski, Charles F., 1998. "Censoring of outcomes and regressors due to survey nonresponse: Identification and estimation using weights and imputations," Journal of Econometrics, Elsevier, vol. 84(1), pages 37-58, May.
    9. MaCurdy, Thomas E., 1982. "The use of time series processes to model the error structure of earnings in a longitudinal data analysis," Journal of Econometrics, Elsevier, vol. 18(1), pages 83-114, January.
    10. 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.
    11. Imbens, Guido W. & Lancaster, Tony, 1996. "Efficient estimation and stratified sampling," Journal of Econometrics, Elsevier, vol. 74(2), pages 289-318, October.
    12. Keisuke Hirano & Guido W. Imbens & Geert Ridder & Donald B. Rubin, 2001. "Combining Panel Data Sets with Attrition and Refreshment Samples," Econometrica, Econometric Society, vol. 69(6), pages 1645-1659, November.
    13. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444590.
    14. Heckman, J.J. & Hotz, V.J., 1988. "Choosing Among Alternative Nonexperimental Methods For Estimating The Impact Of Social Programs: The Case Of Manpower Training," University of Chicago - Economics Research Center 88-12, Chicago - Economics Research Center.
    15. 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.
    16. Guido W. Imbens & Tony Lancaster, 1994. "Combining Micro and Macro Data in Microeconometric Models," Review of Economic Studies, Oxford University Press, vol. 61(4), pages 655-680.
    17. 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.
    18. Colin Cameron, A. & Windmeijer, Frank A. G., 1997. "An R-squared measure of goodness of fit for some common nonlinear regression models," Journal of Econometrics, Elsevier, vol. 77(2), pages 329-342, April.
    19. Heckman, James J. & Robb, Richard Jr., 1985. "Alternative methods for evaluating the impact of interventions : An overview," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 239-267.
    20. Abowd, John M & Card, David, 1989. "On the Covariance Structure of Earnings and Hours Changes," Econometrica, Econometric Society, vol. 57(2), pages 411-445, March.
    21. Duncan, Greg J & Hill, Daniel H, 1989. "Assessing the Quality of Household Panel Data: The Case of the Panel Study of Income Dynamics," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(4), pages 441-452, October.
    22. Bound, John & Brown, Charles & Duncan, Greg J & Rodgers, Willard L, 1994. "Evidence on the Validity of Cross-Sectional and Longitudinal Labor Market Data," Journal of Labor Economics, University of Chicago Press, vol. 12(3), pages 345-368, July.
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    JEL classification:

    • F11 - International Economics - - Trade - - - Neoclassical Models of Trade
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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