Umeå Economic Studies,
Umeå University, Department of Economics

Abstract: The integer-valued AR(1) model is generalized to encompass some of the more likely features of economic time series of count data. The generalizations come at the price of loosing exact distributional properties. For most specifications the first and second order both conditional and unconditional moments can be obtained. Hence estimation, testing and forecasting are feasible and can be based on least squares or GMM techniques. An illustration based on the number of plants within an industrial sector is considered.

Keywords: Characterization; Dependence; Time series model; Estimation; Forecasting; Entry and exit

JEL-codes: C12; C13; C22; C25; C51

21 pages, April 14, 1999

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Published as

Kurt Brännäs and Jörgen Hellström, (2001), 'Generalized Integer-Valued Autoregression', Econometric Reviews, vol Vol 20, no 4, pages 425-443

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