Real-Time Forecasting with a Mixed-Frequency VAR / Frank Schorfheide, Dongho Song.

Format:

Book

Author/Creator:

Schorfheide, Frank.

Contributor:

National Bureau of Economic Research.

Song, Dongho.

Series:

Working Paper Series (National Bureau of Economic Research) no. w19712.

NBER working paper series no. w19712

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2013.

Summary:

This paper develops a vector autoregression (VAR) for time series which are observed at mixed frequencies - quarterly and monthly. The model is cast in state-space form and estimated with Bayesian methods under a Minnesota-style prior. We show how to evaluate the marginal data density to implement a data-driven hyperparameter selection. Using a real-time data set, we evaluate forecasts from the mixed-frequency VAR and compare them to standard quarterly-frequency VAR and to forecasts from MIDAS regressions. We document the extent to which information that becomes available within the quarter improves the forecasts in real time.

Notes:

Print version record

December 2013.