Estimating Multinomial Logit Models with Samples of Alternatives

Bibliographic Data

ID6170001
AuthorsBenjamin F Jarvis (0000-0001-8127-4051, Linköping University, Norrköping, Sweden, corresponding author)
Year2018
Volume49
Issue1
Pages341-348
Publication date2018-08-30
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSociological Methodology (JOURNAL)
Journal identifiersISSN: 0081-1750 • E-ISSN: 1467-9531
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1177/0081175018793460
PMID33986555
OpenAlexW2889045286
LanguageEN
Citations received6
References cited4

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

Advice (programming · Econometrics · Logistic regression · Multinomial distribution · Multinomial logistic regression · Sample (material · Sampling (signal processing · Sampling design · Simple (philosophy · Simple random sample · Statistics · Stratified sampling · Computer Science · Demography · Economic and Environmental Valuation · Mathematics · Urban Transport and Accessibility · Urban, Neighborhood, and Segregation Studies

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