The most familiar fixed effects (FE) and random effects (RE) panel data treatments for count data were proposed by Hausman, Hall and Griliches (HHG) (1984). The Poisson FE model is particularly simple and is one of a small few known models in which the incidental parameters problem is, in fact,...

This study presents several extensions of the most familiar models for count data, the Poisson and negative binomial models. We develop an encompassing model for two well known variants of the negative binomial model (the NB1 and NB2 forms). We then propose some alternative approaches to the...

We propose a dynamic factor model for the analysis of multivariate time series count data. Our model allows for idiosyncratic as well as common serially correlated latent factors in order to account for potentially complex dynamic interdependence between series of counts. The model is estimated...

This work aims to identify the determinants of health care utilization in Portugal and to quantify their effects. A clear idea about this may help the policy debate on the delivery and organization of health services. Toward this end, we developed an approach based on count data models. We found...

Purpose – The purpose of this paper is to examine the use of single vs multiple lenders by Kansas farms. Previous studies suggest that as the risk level of the firm changes, borrowers desire to enhance the probability of obtaining credit at the lowest possible cost may cause them to use...

In this paper, we propose an alternative approach for forecasting mortality for multiple populations jointly. Our contribution is developed upon the generalized linear models introduced by Renshaw et al., (1996) and Sithole et al., (2000), in which mortality forecasts are generated within the...