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 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...

This paper establishes conditions for nonparametric identification of dynamic optimization models in which agents make both discrete and continuous choices. We consider identification of both the payoff function and the distribution of unobservables. Models of this kind are prevalent in applied...

Using UK longitudinal data on dual-earner couples, this paper estimates a model of intrahousehold housework decisions, which combines a randomized experimental framework eliciting counterfactual choices with gender norms differences across ethnicities and cohorts to identify the impacts of...

Using UK longitudinal data on dual-earner couples, this paper estimates a model of intrahousehold housework decisions, which combines a randomized experimental framework eliciting counterfactual choices with gender norms differences across ethnicities and cohorts to identify the impacts of...

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...

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...