Revisiting the transitional dynamics of business-cycle phases with mixed-frequency data
Bessec, Marie (2019), Revisiting the transitional dynamics of business-cycle phases with mixed-frequency data, Econometric Reviews, 38, 7, p. 711-32. 10.1080/07474938.2017.1397837
Type
Article accepté pour publication ou publiéDate
2019Journal name
Econometric ReviewsVolume
38Number
7Publisher
Taylor & Francis
Pages
711-32
Publication identifier
Metadata
Show full item recordAbstract (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.Subjects / Keywords
Business cycles; Markov-switching; mixed-frequency dataRelated items
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