Hartl, Tobias and Jucknewitz, Roland (2020) Approximate state space modelling of unobserved fractional components. ECONOMETRIC REVIEWS. ISSN 0747-4938, 1532-4168
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We propose convenient inferential methods for potentially nonstationary multivariate unobserved components models with fractional integration and cointegration. Based on finite-order ARMA approximations in the state space representation, maximum likelihood estimation can make use of the EM algorithm and related techniques. The approximation outperforms the frequently used autoregressive or moving average truncation, both in terms of computational costs and with respect to approximation quality. Monte Carlo simulations reveal good estimation properties of the proposed methods for processes of different complexity and dimension.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | MAXIMUM-LIKELIHOOD-ESTIMATION; LONG-MEMORY PROCESSES; DYNAMIC FACTOR; COINTEGRATION; ALGORITHM; SYSTEMS; ARMA; Fractional cointegration; long memory; state space; unobserved components; C32; C51; C53; C58 |
| Subjects: | 300 Social sciences > 330 Economics |
| Divisions: | Business, Economics and Information Systems > Institut für Volkswirtschaftslehre und Ökonometrie > Lehrstuhl für Ökonometrie (Prof. Dr. Rolf Tschernig) |
| Depositing User: | Petra Gürster |
| Date Deposited: | 21 Apr 2021 07:31 |
| Last Modified: | 21 Apr 2021 07:31 |
| URI: | https://pred.uni-regensburg.de/id/eprint/43410 |
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