Binary Response Models: Logits, Probits and Semiparametrics

Joel L. Horowitz and N. E. Savin

Journal of Economic Perspectives, 2001, vol. 15, issue 4, 43-56

Abstract: A binary-response model is a mean-regression model in which the dependent variable takes only the values zero and one. This paper describes and illustrates the estimation of logit and probit binary-response models. The linear probability model is also discussed. Reasons for not using this model in applied research are explained and illustrated with data. Semiparametric and nonparametric models are also described. In contrast to logit and probit models, semi- and nonparametric models avoid the restrictive and unrealistic assumption that the analyst knows the functional form of the relation between the dependent variable and the explanatory variables.

JEL-codes: C25 (search for similar items in EconPapers)
Date: 2001
Note: DOI: 10.1257/jep.15.4.43
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Citations: View citations in EconPapers (51)

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