Maximum score estimation of the stochastic utility model of choice

Charles F. Manski*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

436 Scopus citations


This paper introduces a class of robust estimators of the parameters of a stochastic utility function. Existing maximum likelihood and regression estimation methods require the assumption of a particular distributional family for the random component of utility. In contrast, estimators of the 'maximum score' class require only weak distributional assumptions for consistency. Following presentation and proof of the basic consistency theorem, additional results are given. An algorithm for achieving maximum score estimates and some small sample Monte Carlo tests are also described.

Original languageEnglish (US)
Pages (from-to)205-228
Number of pages24
JournalJournal of Econometrics
Issue number3
StatePublished - Jan 1 1975

ASJC Scopus subject areas

  • Economics and Econometrics


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