This paper focuses on developing and adapting statistical models of counts (non-negative integers) in the context of panel data and using them to analyze the relationship between patents and R&D expenditures. The model used is an application and generalization of the Poisson distribution to...

Time series of counts are often characterized by high overdispersion and persistence. These extreme features challenge the existing models. We approach this problem by combining the framework of INAR with a latent Markov structure. We call it HMM-INAR since it belongs to the class of hidden...

When modelling insurance claim count data, the actuary often observes overdispersion and an excess of zeros that may be caused by unobserved heterogeneity. A common approach to accounting for overdispersion is to consider models with some overdispersed distribution as opposed to Poisson models....

Predictive modeling is a key technique in auto insurance rate-making and the decision-making involved in the review of rate filings. Unlike an approach based on hypothesis testing, the results from predictive modeling not only serve as statistical evidence for decision-making, they also discover...

This paper explains the gender differences in self-assessed health status by providing a theoretical identification mechanism through a dynamic structural model which allows for heterogeneity in discount factors of individuals. Theoretical predictions are empirically tested and estimation...

Despite the increasing availability of spatial count data in research areas like technology spillovers, patenting activities, insurance payments, and crime forecasting, specialized models for analysing such data have received little attention in econometric literature so far. The few existing...

Hurdle and zero-in ated models are the two foremost methods used to deal with excess zeros. However, their reliance on the nonparticipation assumption is a drawback when applied to recreation demand analysis because there is not a theoretical framework convincingly explaining presence of...

This paper considers the possibility of mission drift in microfinance; a situation where Microfinance Institutions (MFIs) move away from targeting the poor and towards better-off clients. Using two different measures of poverty, the paper examines whether microfinance institutions in Uganda follow...

BACKGROUND: Paying pharmaceuticals out-of-pocket is an important source of financing pharmaceutical consumption. Only limited empirical knowledge is available on the determinants of these expenditures. OBJECTIVES: In this paper we analyze which characteristics of private households influence...

We show how the rootogram - a graphical tool associated with the work of J. W. Tukey and originally used for assessing goodness of fit of univariate distributions - can help to diagnose and treat issues such as overdispersion and/or excess zeros in regression models for count data. Two empirical...

Over-crowding in Emergency Departments (EDs) generates potential inefficiencies. Using regional administrative data, we investigate the impact of an increase in the accessibility of primary care on ED visits in Italy. We test whether extending practice opening hours up to 12 hours/day reduces...

This paper explores the problems associated with the location choice of newly created establishments at the aggregate level. Much work has been done in this domain, however, several issues arise when analyzing involved phenomena, which scholars have yet to fully explore: 1) addressing the excess...

The rootogram is a graphical tool associated with the work of J. W. Tukey that was originally used for assessing goodness of t of univariate distributions. Here we show that rootograms are also useful for diagnosing and treating issues such as overdispersion and/or excess zeros in regression...

Frequent problems in applied research that prevent the application of the classical Poisson log-linear model for analyzing count data include overdispersion, an excess of zeros compared to the Poisson distribution, correlated responses, as well as complex predictor structures comprising...

Generalized additive models for location, scale and shape define a flexible, semi-parametric class of regression models for analyzing insurance data in which the exponential family assumption for the response is relaxed. This approach allows the actuary to include risk factors not only in the...

This paper explores differences in the frequency with which students from different schools reach high levels of math achievement. Data from the American Mathematics Competitions is used to produce counts of high-scoring students from more than two thousand public, coeducational, non-magnet,...