Abstract
Count data play an important role in modern microeconometric models. However, a proper dynamic specification in case of panel data has not yet been discussed: So far only variance components have been specified which show constant autocorrelation over time. In the present paper an autoregressive process for count data is considered as suggested independently by Al-Osh and Alzaid (Journal of Time Series Analysis 1987) and McKenzie (Advances in Applied Probability 1988). Simulation results demonstrate that it is necessary to take proper account of the ’initial conditions’ of the stochastic process when small sample sizes (about 5 or 10) are considered which is the typical number of waves in panel data collected for econometric reseach.
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© 1992 Springer-Verlag New York, Inc.
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Ronning, G., Jung, R.C. (1992). Estimation of a First Order Autoregressive Process with Poisson Marginals for Count Data. In: Fahrmeir, L., Francis, B., Gilchrist, R., Tutz, G. (eds) Advances in GLIM and Statistical Modelling. Lecture Notes in Statistics, vol 78. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2952-0_29
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DOI: https://doi.org/10.1007/978-1-4612-2952-0_29
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