Estimation of Discrete Choice Models in Retrospective Samples

Barry V. Bye, Salvatore J. Gallicchio and Jesse M. Levy
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Barry V. Bye: Social Security Administration
Salvatore J. Gallicchio: Social Security Administration
Jesse M. Levy: Social Security Administration

Sociological Methods & Research, 1987, vol. 15, issue 4, 467-492

Abstract: The estimation of the parameters of discrete choice models in retrospective samples is often more complex than in prospective studies. In prospective studies estimation usually employs classical maximum likelihood techniques; however, when samples are stratified on the outcome variable, classical maximum likelihood estimators are often biased in large samples. A number of alternative consistent estimators have been proposed by Manski and McFadden (1981). We have found one of their estimators to be applicable to a wide variety of problems and easy to implement. In this article we describe the Manski and McFadden approach, give a variation of the approach when modeling sets of retrospectively sampled outcomes, and present an example of the application of these techniques in a survey research context.

Date: 1987
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Persistent link: https://EconPapers.repec.org/RePEc:sae:somere:v:15:y:1987:i:4:p:467-492

DOI: 10.1177/0049124187015004007

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