We propose using cyclic monotonicity, a convex-analytic property of the random utility choice model, to derive bounds on counterfactual choice probabilities in semiparametric multinomial choice models. These bounds are useful for typical counterfactual exercises in aggregate discrete-choice...

We introduce an approach for semiparametric inference in dynamic binary choice models that does not impose distributional assumptions on the state variables unobserved by the econometrician. The proposed framework combines Bayesian inference with partial identification results. The method is...

We analyze identification of nonseparable models under three kinds of exogeneity assumptions weaker than full statistical independence. The first is based on quantile independence. Selection on unobservables drives deviations from full independence. We show that such deviations based on quantile...

We consider fixed‐effects binary choice models with a fixed number of periods T and regressors without a large support. If the time‐varying unobserved terms are i.i.d. with known distribution F, Chamberlain (2010) shows that the common slope parameter is point identified if and only if F is...

This paper proposes a new approach to identification of the semiparametric multinomial choice model with fixed effects. The framework employed is the semiparametric version of the traditional multinomial logit with the fixed-effects model (Chamberlain (1980)). This semiparametric multinomial...

The purpose of this research is to use measures of willingness to pay derived from random utility models as the basis for evaluating the properties of parametric and nonparametric estimators with binary choice data. Monte Carlo simulations are conducted to evaluate two parametric methods and a...