Multiply-Imputed Sampling Weights for Consistent Inference with Panel Attrition

  • David Brownstone
  • Xuehao Chu
Part of the Transportation Research, Economics and Policy book series (TRES)


This chapter demonstrates a new methodology for correcting panel data models for attrition bias. The method combines Rubin’s Multiple Imputations technique with Manski and Lerman’s Weighted Exogenous Sample Maximum Likelihood Estimator (WESMLE). Simple Hausman tests for the presence of attrition bias are also derived. We demonstrate the technique using a dynamic commute mode choice model estimated from the University of California Transportation Center’s Southern California Transportation Panel. The methodology is simpler to use than standard maximum likelihood-based procedures. It can be easily modified for use with many panel data estimation and forecasting procedures.


Multiple Imputation Mode Choice Policy Simulation Panel Data Estimation Multiple Imputation Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Brownstone, D. (1991) Multiple Imputations for Linear Regression Models. Technical Report MBS 91–37, Research Unit in Mathematical Behavioral Sciences, University of California, Irvine, California.Google Scholar
  2. Brownstone, D. and Gown, T.F. (1992) The effectiveness of ridesharing incentives: Discrete-choice models of commuting in Southern California. Regional Science and Urban Economics, 22, 5–24.CrossRefGoogle Scholar
  3. Chow, G.C. (1983) Econometrics. McGraw-Hill, New York, New York.Google Scholar
  4. Hausman, J.A. (1978) Specification tests in econometrics. Econometrica, 46, 1251–1272.CrossRefGoogle Scholar
  5. Imbens, G. (1992) An efficient method of moments estimator for discrete choice models with choice-based sampling. Econometrica, 60, 1187–1214.CrossRefGoogle Scholar
  6. Mansii, C.F. and Lerman. S. (1977) The estimation of choice probabilities from choice-based samples. Econometrica, 45, 1977–1988.CrossRefGoogle Scholar
  7. Rubi, D.B. (1986) Statistical matching using file concatenation with adjusted weights and multiple imputations. Journal of Business and Economic Statistics, 4, 87–94.Google Scholar
  8. Rubi, D.B. (1987) Multiple Imputation for Nonresponse in Surveys. John Wiley and Sons, New York, New York.Google Scholar
  9. Uhlaner, C.J. and Kim. S. (1993) Designing and Implementing a Panel Study of Commuter Behavior: Lessons for Future Research. Working Paper 93–2, Institute of Transportation Studies, University of California, Irvine, California.Google Scholar
  10. Horowitz, J.L. and Manski, C.F. (1995) Censoring of Outcomes and Regressors Due to Survey Non-response: Identification and Estimation Using Weights and Imputations. Working Paper No. 95–12. Department of Economics, University of Iowa, Iowa City.Google Scholar
  11. Manski, C.F. (1994) The selection problem, in C. Sims (ed.), Advances in Econometrics: Sixth World Congress. Cambridge University Press, Cambridge, England.Google Scholar
  12. Manski, C.F. and Lerman, S. (1977) The estimation of choice probabilities from choice-based samples. Econometrica, 45, 1977–1988.Google Scholar

Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • David Brownstone
    • 1
  • Xuehao Chu
    • 2
  1. 1.Department of EconomicsUniversity of CaliforniaIrvineUSA
  2. 2.Center for Urban Transportation ResearchUniversity of South FloridaTampaUSA

Personalised recommendations