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Dynamic Factor Models: a Genealogy

Matteo Barigozzi, Marc Hallin

arXiv 26 Oct 2023 · Econometrics · 3 citations (OpenAlex)

arXiv:2310.17278 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Dynamic factor models have been developed out of the need of analyzing and forecasting time series in increasingly high dimensions. While mathematical statisticians faced with inference problems in high-dimensional observation spaces were focusing on the so-called spiked-model-asymptotics, econometricians adopted an entirely and considerably more effective asymptotic approach, rooted in the factor models originally considered in psychometrics. The so-called dynamic factor model methods, in two decades, has grown into a wide and successful body of techniques that are widely used in central banks, financial institutions, economic and statistical institutes. The objective of this chapter is not an extensive survey of the topic but a sketch of its historical growth, with emphasis on the various assumptions and interpretations, and a family tree of its main variants.

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Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review0.40511
2From Many Models, One: Macroeconomic Forecasting with Reservoir Ensembles0.40511