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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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Type
Communication / Conférence
Date
2015-05
Conference title
AFSE 2015 64th Congress
Conference date
2015-06
Conference city
Rennes
Conference country
France
Pages
34
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Author(s)
Bessec, Marie
Laboratoire d'Economie de Dauphine [LEDa]
Abstract (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 cycles
JEL
C22 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
E32 - Business Fluctuations; Cycles
E37 - Forecasting and Simulation: Models and Applications

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