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

Martin Solberger and Erik Spånberg ()
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Erik Spånberg: Ministry of Finance

Computational Economics, 2020, vol. 55, issue 3, No 6, 875-900

Abstract: 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.

Keywords: Dynamic factor model; State space; Kalman filter; EViews (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10614-019-09912-z

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