Observation-driven models provide a flexible framework for modelling time series of counts. They are able to capture a wide range of dependence structures. Many applications in this field of research are concerned with count series whose conditional distribution given past observations and...

The paper makes three contributions to the economics literature on entrepreneurship. We offer a new measure of entrepreneurship which accounts for variations in persistence in self-employment. We outline an econometric methodology to account for this approach and find that it is superior to...

This paper compares various models for time series of counts which can account for discreetness, overdispersion and serial correlation. Besides observation- and parameter-driven models based upon corresponding conditional Poisson distributions, we also consider a dynamic ordered probit model as...

This paper extends the truncated and endogenously stratified Poisson and negative binomial models to three alternative discrete distributions, namely the generalized Poisson, geometric, and Borel distributions. Our primary intention here is to demonstrate how improper treatment of the data...

We deal with two kinds of Cox regression models with varying coefficients. The coefficients vary with time in one model. In the other model, there is an important random variable called an index variable and the coefficients vary with the variable. In both models, we have p-dimensional...