| edoc-Server der Humboldt-Universität zu Berlin |
| Autor(en): | Vidar Hjellvik; Dag Tjøstheim | Titel: | Modeling Panels of Intercorrelated Autoregressive Time Series |
| Erscheinungsdatum: | 03.04.1998 |
| Erschienen in: |
Sonderforschungsbereich 373: Quantification and Simulation of Economic Processes 42 (SFB 373 Papers) ISSN: 1436-1086 |
| Volltext: | pdf (urn:nbn:de:kobv:11-10056956) |
| Fachgebiet(e): | Wirtschaft |
| Schlagwörter (eng): | Time series, Autoregressive, Burg-type estimates, Intercorrelated, Panel data |
| Herausgeber: | Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät |
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| Abstract (eng): | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| We propose a method of modeling panel time series data with both inter- and intra-individual correlation, and of fitting an autoregressive model to such data. Estimates are obtained by a conditional likelihood argument. If there are few observations in each series, the estimates can be dramatically improved by Burg-type estimates taking edge effects into account. The consequences of ignoring the intercorrelation term are analysed. Partial lack of consistency is demonstrated in this situation. Moreover, a break-even point is found for the strength of the intercorrelation, beyond which a conventional estimate, ignoring correlation, will become increasingly inferior. Asymptotic normality of estimators is established, and our results are illustrated on a real data example, where it is seen that choosing the right type of estimate is of crucial importance. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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