Time-varying mixed frequency forecasting : a real-time experiment

Stefan Neuwirth

This paper tests the usefulness of time-varying parameters when forecasting with mixed-frequency data. For this we compare the forecast performance of bridge equations and unrestriced MIDAS models with constant and time-varying parameters. An out-of-sample forecasting exercise with US real-time data shows that the use of time-varying parameters does not improve forecasts significantly over all vintages. However, since the Great Recession, forecast errors are smaller when forecasting with bridge equations due to the ability of time-varying parameters to incorporate gradual structural changes faster.

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Year of publication:	June 12, 2017
Authors:	Neuwirth, Stefan
Publisher:	Zurich, Switzerland : KOF
Subject:	Forecasting \| Bayesian \| mixed frequency data \| time-varying parameters \| Prognoseverfahren \| Forecasting model \| Bayes-Statistik \| Bayesian inference \| Zeitreihenanalyse \| Time series analysis \| VAR-Modell \| VAR model \| Theorie \| Theory \| Frühindikator \| Leading indicator \| Prognose \| Forecast