GENERALIZED INTEGER-VALUED AUTOREGRESSION |
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Abstract: | The integer-valued AR1 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. |
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Keywords: | Characterization Dependence Time series model Estimation Forecasting Entry and exit JEL Classification: C12, C13, C22, C25, C51 |
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