Real-Time Forecasting with a Mixed-Frequency VAR

Frank Schorfheide and Dongho Song

No 19712, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: C11 C32 C53 (search for similar items in EconPapers)
Date: 2013-12
New Economics Papers: this item is included in nep-for and nep-mst
Note: EFG ME
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (58)

Published as Frank Schorfheide & Dongho Song, 2015. "Real-Time Forecasting With a Mixed-Frequency VAR," Journal of Business & Economic Statistics, vol 33(3), pages 366-380.

Downloads: (external link)
http://www.nber.org/papers/w19712.pdf (application/pdf)

Related works:
Journal Article: Real-Time Forecasting With a Mixed-Frequency VAR (2015)
Working Paper: Real-time forecasting with a mixed-frequency VAR (2012)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nbr:nberwo:19712

Ordering information: This working paper can be ordered from
http://www.nber.org/papers/w19712

Access Statistics for this paper

More papers in NBER Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().