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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 publié
Date
2019
Journal name
Econometric Reviews
Volume
38
Number
7
Publisher
Taylor & Francis
Pages
711-32
Publication identifier
10.1080/07474938.2017.1397837
Metadata
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Author(s)
Bessec, Marie

Laboratoire d'Economie de Dauphine [LEDa]
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.
Subjects / Keywords
Business cycles; Markov-switching; mixed-frequency data
JEL
E32 - Business Fluctuations; Cycles
E37 - Forecasting and Simulation: Models and Applications
C22 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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