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...

This paper develops maximum score estimation of preference parameters in the binary choice model under uncertainty in which the decision rule is affected by conditional expectations. The preference parameters are estimated in two stages: we estimate conditional expectations nonparametrically in...

We analyse stated preference data over nursing jobs collected from two leading types of best-worst discrete choice experiments (DCEs): a traditional DCE involving choice over alternative jobs (BWL) and a newly-developed DCE where respondents choose best and worst job attributes (BWT). The latter...

Discrete choice models are usually derived from the assumption of random utility maximization. We consider the reverse problem, whether choice probabilities are consistent with maximization of random utilities. This leads to tests that consider the variation of these choice probabilities with...

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...

In multinomial choice settings, Daly-Zachary (1978) and Armstrong-Vickers (2015) provided closed-form conditions, under which choice probability functions can be rationalized via random utility models. A key condition is Slutsky symmetry. We first show that in the multinomial context,...

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...

In this paper we analyze the potential demand for privately used alternative fuel vehicles (AFVs), based on a nationwide survey in Germany among (potential) car buyers. For this purpose, we applied a stated preference discrete choice experiment, using a wide range of vehicle alternatives...

The idea of identifying structural parameters via heteroskedasticity is explored in the context of binary choice models with an endogenous regressor. Sufficient conditions for parameter identification are derived for probit models without relying on instruments or additional restrictions. The...

The idea of identifying structural parameters via heteroskedasticity is explored in the context of binary choice models with an endogenous regressor. Sufficient conditions for parameter identification are derived for probit models without relying on instruments or additional restrictions. The...