Arbeitspapier
Likelihood-based Analysis for Dynamic Factor Models
We present new results for the likelihood-based analysis of the dynamic factor model that possibly includes intercepts and explanatory variables. The latent factors are modelled by stochastic processes. The idiosyncratic disturbances are specified as autoregressive processes with mutually correlated innovations. The new results lead to computationally efficient procedures for the estimation of the factors and parameter estimation by maximum likelihood and Bayesian methods. An illustration is provided for the analysis of a large panel of macroeconomic time series.
- Language
-
Englisch
- Bibliographic citation
-
Series: Tinbergen Institute Discussion Paper ; No. 08-007/4
- Classification
-
Wirtschaft
Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models
Index Numbers and Aggregation; Leading indicators
- Subject
-
EM algorithm
Kalman Filter
Forecasting
Latent Factors
Markov chain Monte Carlo
Principal Components
State Space
Maximum-Likelihood-Methode
Faktorenanalyse
Zustandsraummodell
Monte-Carlo-Methode
Markovscher Prozess
Theorie
- Event
-
Geistige Schöpfung
- (who)
-
Jungbacker, Borus
Koopman, Siem Jan
- Event
-
Veröffentlichung
- (who)
-
Tinbergen Institute
- (where)
-
Amsterdam and Rotterdam
- (when)
-
2008
- Handle
- Last update
- 10.03.2025, 11:42 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Jungbacker, Borus
- Koopman, Siem Jan
- Tinbergen Institute
Time of origin
- 2008
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