
Revisiting the transitional dynamics of business-cycle phases with mixed frequency data
Bessec, Marie (2015-05), Revisiting the transitional dynamics of business-cycle phases with mixed frequency data, AFSE 2015 64th Congress, 2015-06, Rennes, France
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Communication / ConférenceDate
2015-05Conference title
AFSE 2015 64th CongressConference date
2015-06Conference city
RennesConference country
FrancePages
34
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Show full item recordAbstract (EN)
This paper introduces a Markov-Switching model where transition probabilities depend on higher frequency indicators and their lags, through polynomial weighting schemes. The MSV-MIDAS model is estimated via maximum likel ihood methods. The estimation relies on a slightly modified version of Hamilton’s recursive filter. We use Monte Carlo simulations to assess the robustness of the estimation procedure and related test-statistics. The results show that ML provides accurate estimates, but they suggest some caution in the tests on the parameters involved in the transition probabilities. We apply this new model to the detection and forecast of business cycle turning points. We properly detect recessions in United States and United Kingdom by exploiting the link between GDP growth and higher frequency variables from financial and energy markets. Spread term is a particularly useful indicator to predict recessions in the United States, while stock returns have the strongest explanatory power around British turning points.Subjects / Keywords
Markov-Switching; mixed frequency data; business cyclesRelated items
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