This paper examines occupational choices using a discrete choice model that accounts for the fact that self-reported occupation data is measured with error. Despite evidence from validation studies which suggests that there is a substantial amount of measurement error in self-reported...

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....

This paper explores the difficulties involved in quantitative measurement of operational risk and proposes simulation methods as a practical solution to obtain the distribution of total losses. It also introduces an example of the estimation of expected and unexpected losses, as well as...

Structural discrete choice dynamic programming models have been shown to be a valuable tool for analyzing a wide range of economic behavior. A major limitation on the complexity and applicability of these models is the computational burden associated with computing the high dimensional integrals...

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 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....

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...