A new class of regression type models termed essentially linear models is proposed. The class is characterized by geometric considerations. Within the class the distribution of the maximum likelihood estimator is easily approximated by a natural extension of the p-formula even though the MLE...

The purpose of this paper is twofold: 1) to highlight the widely ignored but fundamental problem of ‘superpopulations’ for the use of inferential statistics in development studies. We do not to dwell on this problem however as it has been sufficiently discussed in older papers by...

We take a fresh look at Theil's BLUS residuals and ask why they have gone out of fashion.All our simulation experiments indicate that tests based on BLUS residuals have higher power than those based on the more popular recursive residuals, even in those cases (structural breaks) where intuition...

We describe in this paper a method allowing to order submodels in linear regression. A real function is attached to each submodel, allowing to graphically compare and order them. Our procedure defines an objective function depending on two factors (lack of fit and multicolinearity) with the...

This paper explains how the Gibbs sampler can be used to perform Bayesian inference on GARCH models. Although the Gibbs sampler is usually based on the analytical knowledge of the full conditional posterior densities, such knowledge is not available in regression models with GARCH errors. We...

Adopting a system approach, the paper evaluates results of empirical research on money demand recently obtained at the Bank of Italy in a single equation context.

We propose in this paper a Bayesian approach with a noninformative prior distribution developed in Mengersen and Robert (1996) and Robert and Titterington (1996) in the setup of mixtures of distributions and hidden Markov models, respectively.

The estimation of the noncentrality parameter of a chi-squared distribution, although simple to state, leads to difficulties, both for frequentist and Bayesian inferences. We propose in this paper a family of admissible improper Bayes estimators and study the minimax behavior of these estimators...

In this paper, we study maximum likelihood estimation and Lagrange multiplier testing of a one-way error components regression model suitable for incomplete panel and including parametrically specified variance functions for both individual-specific and general error disturbances.