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)

Abstract

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.

Keywords

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.

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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

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