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 … class of models that includes static discrete choice models, the Heckman (1976) selection model, and all of the Heckman …

estimation, (2) computational methods for multinomial probit models, and (3) computational methods for Bayesian stimation. This …

In the present document it is exposed in an abstract way the models of credit portfolioes CreditMetricsTM, KMV … portfolio by means of the provisions, the economic capital and limits to the amounts of the credits. For which the models apply … of loss of a portfolio from the models of latent variables, mixture and credit concentration. …

many female heads receive both food stamps and AFDC. As we will show, recently developed techniques of "simulation …

unstructured body of numeric evidence, for example from Monte Carlo simulation, in a form ready for introducing to scientific …, and organize content into a productive tool. Graphs confirm the advantage when put to work in a standard simulation …

simple statistical models, such as the multinomial logit (MNL), in which choice probabilities could be evaluated quickly on a … make it possible to estimate richer behavioral models that generate very complex choice probability expressions. This paper …

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 surveys those methods and presents two empirical applications …