Tracking the economy using FOMC speech transcripts

Battaglia, Laura; Salunina, Maria

Tracking the economy using FOMC speech transcripts

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Battaglia, L, Salunina, M. Tracking the economy using FOMC speech transcripts. 2020. handle: http://hdl.handle.net/10230/46314

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Abstract

In this study, we propose an approach for the extraction of a low-dimensional signal from a collection of text documents ordered over time. The proposed framework foresees the application of Latent Dirichlet Allocation (LDA) for obtaining a meaningful representation of documents as a mixture over a set of topics. Such representations can then be modeled via a Dynamic Linear Model (DLM) as noisy realisations of a limited number of latent factors that evolve with time. We apply this approach to Federal Open Market Committee (FOMC) speech transcripts for the period of Greenspan presidency. We are able to extract a latent factor that fairly resembles the Economic Policy Uncertainty Index for United States.