Our goal in this chapter is to explain concretely how to implement simulation methods in a very general class of models that are extremely useful in applied work: dynamic discrete choice models where one has available a panel of multinomial choice histories and partially observed payoffs....

Simulation estimation in the context of panel data, limited dependent-variable (LDV) models poses formidable problems that are not present in the crosssection case. Nevertheless, a number of practical simulation estimation methods have been proposed and implemented for panel data LDV models....

Let U be an unobserved random variable with compact support and let e_t be unobserved i.i.d. random errors also with compact support. Observe the random variables V_t, X_t, and Y_t = 1{U +d X_t+e_t V_t}, t = T, where d is an unknown parameter. This type of model is relevant for many stated...

This pdf contains a do file that shows how to estimate a latent class discrete choice panel data model in Stata via Maximum Likelihood and an EM algorithm.

The purpose of this paper is to present a new approach to model capacity constraints in discrete choice with at least some capacity-related variables missing, like e.g. the price of a commodity. Airport choice models often do not contain air fares because of measurement difficulties as air fares...

This paper considers the path choice problem, formulating and discussing an econometric random utility model for the choice of path in a network with no restriction on the choice set. Starting from a dynamic specification of link choices we show that it is equivalent to a static model of the...

This paper estimates the demand for flights in an international air travel market using a unique dataset with detailed information not only on flight choices but also on contemporaneous prices and characteristics of all the alternative non-booked flights. The estimation strategy employs a simple...

We formulate a family of direct utility functions for the consumption of a differentiated good. This is used to generate a family of demand systems with flexible substitution patterns. Demand models for market shares can be estimated by regression enabling the use of instrumental variables....

Microeconometric treatments of discrete choice under risk are typically homoscedastic latent variable models. Specifically, choice probabilities are given by preference functional differences (given by expected utility, rank-dependent utility, etc.) embedded in cumulative distribution functions....

We search for evidence against the hypothesis of a non-linear relationship between inflation and growth rates for 1993-2012 Peruvian data. A family of dichotomous models provide the way to model the relationship between the those two variables' cycles. Given the acceleration/de-acceleration...