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Estimating a Dynamic Factor Model in EViews Using the Kalman Filter and Smoother

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  • Martin Solberger

    (Uppsala University
    Ministry of Finance)

  • Erik Spånberg

    (Ministry of Finance
    Stockholm University)

Abstract

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.

Suggested Citation

  • Martin Solberger & Erik Spånberg, 2020. "Estimating a Dynamic Factor Model in EViews Using the Kalman Filter and Smoother," Computational Economics, Springer;Society for Computational Economics, vol. 55(3), pages 875-900, March.
    • Handle: RePEc:kap:compec:v:55:y:2020:i:3:d:10.1007_s10614-019-09912-z
    DOI: 10.1007/s10614-019-09912-z
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    3. Fredy Gamboa-Estrada & José Vicente Romero, 2022. "Common and idiosyncratic movements in Latin-American exchange rates," International Economics, CEPII research center, issue 171, pages 174-190.

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