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 …

In this paper we discuss parameter identification and likelihood evaluation for multinomial multiperiod Probit models …

. We find that there are no relevant differences in point estimates given by the two models, even for small sample size …

In this paper R2-type measures of the explanatory power of multivariate linear and categorical probit models proposed … indifferent to components not explicitely modeled. Based on this view three different measures for multivariate probit models are … proposed. Results of a simulation study are presented designed to compare two measures in various situations and evaluate the …

frequently used nonlinear probit model in the style of Hey and Orme (1994) and base our analysis on a simulation stud. In detail …, we simulate trading sequences for a set of utility models and try to identify the underlying utility model and its … parameterization used to generate these sequences by maximum likelihood. We find that for a very broad classification of utility models …

In this paper R2-type measures of the explanatory power of multivariate linear and categorical probit models proposed … indifferent to components not explicitely modeled. Based on this view three different measures for multivariate probit models are … proposed. Results of a simulation study are presented designed to compare two measures in various situations and evaluate the …

proposed class of regression models is not only less complex but can account for more versatile dependence structures and still … allow for an intuitive explanation. We examine some of the properties possessed by this class of regression models and show … its connections to several other models. For fitting purposes, we use the expectation-maximization (EM) algorithm which we …

. We find that there are no relevant differences in point estimates given by the two models, even for small sample size …