On Estimation of the Bivariate Poisson INAR Process

Abstract

In a recent article, Pedeli and Karlis (2010) examined the extension of the classical Integer–valued Autoregressive (INAR) model to the bivariate case. In the present article, we examine estimation methods for the case of bivariate Poisson innovations. This is a simple extension of the classical INAR model allowing for two discrete valued time series to be correlated. Properties of different estimators are given. We also compare their properties via a small simulation experiment. Extensions to incorporate covariate information is discussed. A real data application is also provided.

Keywords:

• BINAR model
• Count data
• Bivariate Poisson distribution
• Discrete valued time series

Mathematics Subject Classification:

• Primary 62M10
• Secondary 62F99