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Nonparametric Tests of Panel Conditioning and Attrition Bias in Panel Surveys

Author

Listed:
  • Marcel Das

    (CentERdata, Tilburg, The Netherlands, Tilburg University, Tilburg, The Netherlands, das@uvt.nl)

  • Vera Toepoel

    (Tilburg University, Tilburg, The Netherlands)

  • Arthur van Soest

    (Tilburg University, Tilburg, The Netherlands, Netspar, Tilburg, The Netherlands)

Abstract

Over the past decades there has been an increasing use of panel surveys at the household or individual level. Panel data have important advantages compared to independent cross sections, but also two potential drawbacks: attrition bias and panel conditioning effects. Attrition bias arises if dropping out of the panel is correlated with a variable of interest. Panel conditioning arises if responses are influenced by participation in the previous wave(s); the experience of the previous interview(s) may affect the answers to questions on the same topic, such that these answers differ systematically from those of respondents interviewed for the first time. In this study the authors discuss how to disentangle attrition and panel conditioning effects and develop tests for panel conditioning allowing for nonrandom attrition. First, the authors consider a nonparametric approach with assumptions on the sample design only, leading to interval identification of the measures for the attrition and panel conditioning effects. Second, the authors introduce additional assumptions concerning the attrition process, which lead to point estimates and standard errors for both the attrition bias and the panel conditioning effect. The authors illustrate their method on a variety of repeated questions in two household panels. The authors find significant panel conditioning effects in knowledge questions, but not in other types of questions. The examples show that the bounds can be informative if the attrition rate is not too high. In most but not all of the examples, point estimates of the panel conditioning effect are similar for different additional assumptions on the attrition process.

Suggested Citation

  • Marcel Das & Vera Toepoel & Arthur van Soest, 2011. "Nonparametric Tests of Panel Conditioning and Attrition Bias in Panel Surveys," Sociological Methods & Research, , vol. 40(1), pages 32-56, February.
  • Handle: RePEc:sae:somere:v:40:y:2011:i:1:p:32-56
    DOI: 10.1177/0049124110390765
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    References listed on IDEAS

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    1. Golob, Thomas F., 1990. "The Dynamics of Household Travel Time Expenditures and Car Ownership Decisions," University of California Transportation Center, Working Papers qt1676t0bp, University of California Transportation Center.
    2. 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.
    3. 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.
    4. Charles F. Manski, 1989. "Anatomy of the Selection Problem," Journal of Human Resources, University of Wisconsin Press, vol. 24(3), pages 343-360.
    5. Meurs, Henk & Van Wissen, Leo & Visser, Jacqueline, 1989. "Measurement Biases in Panel Data," University of California Transportation Center, Working Papers qt00q1x266, University of California Transportation Center.
    6. John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 251-299.
    7. Golob, Thomas F., 1990. "The Dynamics of Household Travel Time Expenditures and Car Ownership Decisions," University of California Transportation Center, Working Papers qt2t18b4q9, University of California Transportation Center.
    8. Ugo Trivellato, 1999. "Issues in the Design and Analysis of Panel Studies: A Cursory Review," Quality & Quantity: International Journal of Methodology, Springer, vol. 33(3), pages 339-351, August.
    9. James Heckman, 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.
    10. 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.
    11. 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.
    12. Bhattacharya, Debopam, 2008. "Inference in panel data models under attrition caused by unobservables," Journal of Econometrics, Elsevier, vol. 144(2), pages 430-446, June.
    13. Nevo, Aviv, 2003. "Using Weights to Adjust for Sample Selection When Auxiliary Information Is Available," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 43-52, January.
    14. Guido W. Imbens & Charles F. Manski, 2004. "Confidence Intervals for Partially Identified Parameters," Econometrica, Econometric Society, vol. 72(6), pages 1845-1857, November.
    15. Francis Vella, 1998. "Estimating Models with Sample Selection Bias: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 127-169.
    16. Nicoletti, Cheti, 2006. "Nonresponse in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 132(2), pages 461-489, June.
    17. 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.
    18. Meurs, Henk & Van Wissen, Leo & Visser, Jacqueline, 1989. "Measurement Biases in Panel Data," University of California Transportation Center, Working Papers qt4095q216, University of California Transportation Center.
    19. Bartels, Larry M., 1999. "Panel Effects in the American National Election Studies," Political Analysis, Cambridge University Press, vol. 8(1), pages 1-20, January.
    20. Das, M., 2004. "Simple estimators for nonparametric panel data models with sample attrition," Journal of Econometrics, Elsevier, vol. 120(1), pages 159-180, May.
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