Estimating Multinomial Logit Models with Samples of Alternatives

Abstract

This comment reconsiders advice offered by Bruch and Mare regarding sampling choice sets in conditional logistic regression models of residential mobility. Contradicting Bruch and Mare's advice, past econometric research shows that no statistical correction is needed when using simple random sampling of unchosen alternatives to pare down respondents' choice sets. Using data on stated residential preferences contained in the Los Angeles portion of the Multi-City Study of Urban Inequality, it is shown that following Bruch and Mare's advice-to implement a statistical correction for simple random choice set sampling-leads to biased coefficient estimates. This bias is all but eliminated if the sampling correction is omitted.