the conditional logit model. The solution draws on the postestimation distribution of the models stochastic component …

In the paper we describe in detail how to build linked CGE-microsimulation models (using fictitious data) following … the three models. Results show that all three approaches yield different results especially in terms of income … distribution and poverty, although analysed within the same economy and under the same policy simulation. We then analyse in more …

We propose a simulated maximum likelihood estimator for dynamic models based on non-parametric kernel methods. Our … method is designed for models without latent dynamics from which one can simulate observations but cannot obtain a closed … dynamic models that this nonparametric simulated maximum likelihood (NPSML) estimator is consistent and asymptotically …

We propose a simulated maximum likelihood estimator for dynamic models based on non-parametric kernel methods. Our … method is designed for models without latent dynamics from which one can simulate observations but cannot obtain a closed … dynamic models that this nonparametric simulated maximum likelihood (NPSML) estimator is consistent and asymptotically …

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 …