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Hjellvik, Vidar
Tjostheim, Dag
Year of Publication: 
Series/Report no.: 
SFB 373 Discussion Paper 1998,42
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.
Time series
Burg-type estimates
Panel data
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Document Type: 
Working Paper

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