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Estimating a Dynamic Factor Model in EViews Using the Kalman Filter and Smoother
Stockholm University, Faculty of Social Sciences, Department of Statistics. Ministry of Finance, Sweden.
Number of Authors: 22020 (English)In: Computational Economics, ISSN 0927-7099, E-ISSN 1572-9974, Vol. 55, no 3, p. 875-900Article in journal (Refereed) Published
Abstract [en]

Dynamic factor models have become very popular for analyzing high-dimensional time series, and are now standard tools in, for instance, business cycle analysis and forecasting. Despite their popularity, most statistical software do not provide these models within standard packages. We briefly review the literature and show how to estimate a dynamic factor model in EViews. A subroutine that estimates the model is provided. In a simulation study, the precision of the estimated factors are evaluated, and in an empirical example, the usefulness of the model is illustrated.

Place, publisher, year, edition, pages
2020. Vol. 55, no 3, p. 875-900
Keywords [en]
Dynamic factor model, State space, Kalman filter, EViews
National Category
Probability Theory and Statistics Economics
Identifiers
URN: urn:nbn:se:su:diva-181066DOI: 10.1007/s10614-019-09912-zISI: 000519585100006OAI: oai:DiVA.org:su-181066DiVA, id: diva2:1427773
Available from: 2020-05-01 Created: 2020-05-01 Last updated: 2022-03-23Bibliographically approved

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Spånberg, Erik

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