Multiply Imputed Sampling Weights for Consistent Inference with Panel Attrition

David Brownstone and Xuehao Chu

University of California Transportation Center, Working Papers from University of California Transportation Center

Abstract: This chapter demonstrates a new methodology for correcting panel data models for attrition bias. The method combines Rubin's Multiple Implication 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 formt he University of California Transportation Center's Southern California Transportation Panel. The methodology is simpler to use than standard maximum likehood-based procedures. It can be easily modified to use with many panel data estimation and forecasting procedures.

Keywords: Architecture (search for similar items in EconPapers)
Date: 2003-03-01
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Working Paper: Multiply Imputed Sampling Weights for Consistent Inference with Panel Attrition (2003)
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