Using count data on the number of bank failures in US states during the 1960 to 2006 period, this paper endeavors to establish how far sources of economic risk (recessions, high interest rates, inflation) or differences in solvency and branching regulation can explain some of the fragility in...

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...

Excess zeros are encountered in many empirical count data applications. We provide a new explanation of extra zeros, related to the underlying stochastic process that generates events. The process has two rates, a lower rate until the first event, and a higher one thereafter. We derive the...

This entry-level text offers clear and concise guidelines on how to select, construct, interpret, and evaluate count data. Written for researchers with little or no background in advanced statistics, the book presents treatments of all major models using numerous tables, insets, and detailed...