A bivariate Poisson count data model using conditional probabilities

The applied econometrics of bivariate count data predominantly focus on a bivariate Poisson density with a correlation structure that is very restrictive. The main limitation is that this bivariate distribution excludes zero and negative correlation. This paper introduces a new model which allows for a more flexible correlation structure. To this end the joint density is decomposed by means of the multiplication rule in marginal and conditional densities. Simulation experiments and an application of the model to recreational data are presented.

[1]  C. Gourieroux,et al.  Pseudo Maximum Likelihood Methods: Applications to Poisson Models , 1984 .

[2]  Jeffrey M. Wooldridge,et al.  Solutions Manual and Supplementary Materials for Econometric Analysis of Cross Section and Panel Data , 2003 .

[3]  Zvi Griliches,et al.  Patents and R&D: is There a Lag? , 1984 .

[4]  G. King,et al.  A Seemingly Unrelated Poisson Regression Model , 1989 .

[5]  A. Colin Cameron,et al.  Bivariate Count Data Regression Using Series Expansions: With Applications , 1997 .

[6]  S. Chib,et al.  Markov Chain Monte Carlo Analysis of Correlated Count Data , 2001 .

[7]  T Barmby,et al.  MODELLING TRIP FREQUENCY AS A POISSON VARIABLE , 1989 .

[8]  N. L. Johnson,et al.  Distributions in Statistics: Discrete Distributions. , 1970 .

[9]  A. Cameron,et al.  Econometric models based on count data. Comparisons and applications of some estimators and tests , 1986 .

[10]  Pravin K. Trivedi,et al.  Regression Analysis of Count Data , 1998 .

[11]  Z. Griliches,et al.  Patents and R and D: Is There a Lag? , 1986 .

[12]  J. Mullahy.  Specification and testing of some modified count data models , 1986 .

[13]  Rainer Winkelmann,et al.  Two aspects of labor mobility: A bivariate Poisson regression approach , 1993 .

[14]  R. Winkelmann,et al.  RECENT DEVELOPMENTS IN COUNT DATA MODELLING: THEORY AND APPLICATION , 1995 .

[15]  Hans van Ophem,et al.  A GENERAL METHOD TO ESTIMATE CORRELATED DISCRETE RANDOM VARIABLES , 1999, Econometric Theory.

[16]  Murat K. Munkin,et al.  Simulated maximum likelihood estimation of multivariate mixed‐Poisson regression models, with application , 1999 .

[17]  S. Kocherlakota,et al.  Bivariate discrete distributions , 1992 .