Random Effects Models for Panel Count Data

This paper discusses the specification and extimation of random effects count data models. A new multivariate count data model with negative binomial marginals is derived. In contrast to the existing multivariate Poisson model, this model allows for over-dispersion, a phenomenon that is frequently encountered in real data applications. In addition, a multi-factor Poisson model with general individual specific covariance structure is formulated, and an algorithm for estimating the parameters of the model by Simulated Maximum Likelihood is presented.


Issue Date:
Sep 01 1998
Publication Type:
Working or Discussion Paper
Language:
English
Total Pages:
23
JEL Codes:
C23; C25
Series Statement:
9811




 Record created 2017-09-29, last modified 2017-09-29

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