We consider the estimation of dynamic binary choice models in a semiparametric setting, in which the per-period utility functions are known up to a finite number of parameters, but the distribution of utility shocks is left unspecified. This semiparametric setup differs from most of the existing...

This note provides a nonparametric test for dynamic discrete random utility models (DDRUM). The methodology can be used to understand the welfare implications of price changes in demand data when there is no uncertainty for consumers that have preferences over product characteristics or discrete...

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...

We address two issues in nonparametric structural analyses of dynamic binary choice processes (DBCP). First, the DBCP is not testable and decision makers’ single-period payoffs (SPP) cannot be identified even when the distribution of unobservable states (USV) is known. Numerical examples show...