In the context of polytomous regression, as with any generalized linear model, robustness issues are well documented. Existing robust estimators designed to protect against misclassification, but do not outlying covariates. It is shown that this can have a much bigger impact on estimation and testing than misclassification alone. To address problem, two new introduced: model-type estimator an o...

Multicollinearity in logistic regression affects the variance of the maximum likelihood estimator negatively. In this study, Liu-type estimators are used to reduce the variance and overcome the multicollinearity by applying some existing ridge regression estimators to the case of logistic regression model. A Monte Carlo simulation is given to evaluate the performances of these estimators when t...

We present estimators for panel data sample selection and switching models where the regression equations are dynamic and it is allowed for the existence of endogenous regressors and correlated individual unobserved heterogeneity. We consider two types of switching models under the names of observed dynamics switching and latent dynamics switching. The dynamic sample selection model implicitly ...