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Nonparametric Tests of Panel Conditioning and Attrition Bias in Panel Surveys

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Author Info

  • 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.

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Bibliographic Info

Article provided by in its journal Sociological Methods & Research.

Volume (Year): 40 (2011)
Issue (Month): 1 (February)
Pages: 32-56

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Handle: RePEc:sae:somere:v:40:y:2011:i:1:p:32-56

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Keywords: panel conditioning; attrition bias; measurement error; panel surveys;

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References

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  1. 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.
  2. 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.
  3. John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of income Dynamics," Economics Working Paper Archive 379, The Johns Hopkins University,Department of Economics.
  4. 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.
  5. Guido Imbens & Charles F. Manski, 2003. "Confidence intervals for partially identified parameters," CeMMAP working papers CWP09/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  6. Keisuke Hirano & Guido W. Imbens & Geert Ridder & Donald B. Rubin, 1998. "Combining Panel Data Sets with Attrition and Refreshment Samples," Tinbergen Institute Discussion Papers 98-033/4, Tinbergen Institute.
  7. 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.
  8. Das, M., 2004. "Simple estimators for nonparametric panel data models with sample attrition," Journal of Econometrics, Elsevier, vol. 120(1), pages 159-180, May.
  9. 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.
  10. 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.
  11. Bhattacharya, Debopam, 2008. "Inference in panel data models under attrition caused by unobservables," Journal of Econometrics, Elsevier, vol. 144(2), pages 430-446, June.
  12. 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.
  13. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
  14. Charles F. Manski, 1989. "Anatomy of the Selection Problem," Journal of Human Resources, University of Wisconsin Press, vol. 24(3), pages 343-360.
  15. Nicoletti, Cheti, 2006. "Nonresponse in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 132(2), pages 461-489, June.
  16. 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.
  17. 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 455-73, March.
  18. 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.
  19. 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.
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Citations

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Cited by:
  1. Mark Wooden & Ning Li, 2014. "Panel Conditioning and Subjective Well-being," Social Indicators Research, Springer, vol. 117(1), pages 235-255, May.
  2. Thomas Crossley & Jochem de Bresser & Liam Delaney & Joachim Winter, 2014. "Can survey participation alter household saving behavior?," IFS Working Papers W14/06, Institute for Fiscal Studies.
  3. Nic Baigrie & Katherine Eyal, 2013. "An evaluation of the determinants and implications of panel attrition in the National Income Dynamics Survey (2008 – 2010)," SALDRU Working Papers 103, Southern Africa Labour and Development Research Unit, University of Cape Town.
  4. Robert Metcalfe & John Feddersen & Mark Wooden, 2012. "Subjective Well-Being: Weather Matters; Climate Doesn't," Economics Series Working Papers 627, University of Oxford, Department of Economics.
  5. Bert Van Landeghem, 2012. "Panel Conditioning and Self-Reported Satisfaction: Evidence from International Panel Data and Repeated Cross-Sections," SOEPpapers on Multidisciplinary Panel Data Research 484, DIW Berlin, The German Socio-Economic Panel (SOEP).
  6. André van Stel & Werner Liebregts & Nardo de Vries, 2013. "Explaining entrepreneurial performance of solo self-employed from a motivational perspective," Scales Research Reports H201308, EIM Business and Policy Research.

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