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Dynamic Factor Models

Listed author(s):
  • Stock, James H.
  • Watson, Mark
Registered author(s):

    This article surveys work on a class of models, dynamic factor models (DFMs), that has received considerable attention in the past decade because of their ability to model simultaneously and consistently data sets in which the number of series exceeds the number of time series observations. The aim of this survey is to describe the key theoretical results, applications, and empirical findings in the recent literature on DFMs. The article is organized as follows. The first issue at hand for the econometrician is to estimate the factors and to ascertain how many factors there are; these two topics are covered in Sections 2 and 3. Once one has reliable estimates of the factors, there are a number of things one can do with them beyond using them for forecasting, including using them as instrumental variables, estimating factor-augmented vector autoregressions, and estimating dynamic stochastic general equilibrium models; these applications are covered in Section 4. Section 5 discusses some extensions.

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    Paper provided by Harvard University Department of Economics in its series Scholarly Articles with number 28469541.

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    Date of creation: 2011
    Publication status: Published in Oxford Handbooks Online
    Handle: RePEc:hrv:faseco:28469541
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