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Revisiting the transitional dynamics of business-cycle phases with mixed-frequency data

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Date
2019
Dewey
Macroéconomie
Sujet
Business cycles; Markov-switching; mixed-frequency data
JEL code
E.E3.E32; E.E3.E37; C.C2.C22
Journal issue
Econometric Reviews
Volume
38
Number
7
Publication date
2019
Article pages
711-32
Publisher
Taylor & Francis
DOI
http://dx.doi.org/10.1080/07474938.2017.1397837
URI
https://basepub.dauphine.fr/handle/123456789/19228
Collections
  • LEDa : Publications
Metadata
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Author
Bessec, Marie
status unknown
Type
Article accepté pour publication ou publié
Abstract (EN)
This paper introduces a Markov-switching model in which transition probabilities depend on higher frequency indicators and their lags through polynomial weighting schemes. The MSV-MIDAS model is estimated through maximum likelihood (ML) methods with a slightly modified version of Hamilton’s filter. Monte Carlo simulations show that ML provides accurate estimates, but they suggest some caution in interpreting the tests of the parameters in the transition probabilities. We apply this new model to forecast business cycle turning points in the United States. We properly detect recessions by exploiting the link between GDP growth and higher frequency variables from financial and energy markets.

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