Macroeconomic Forecasting With Mixed-Frequency Data
Michael Clements and
GalvÃ£o, Ana Beatriz
Authors registered in the RePEc Author Service: Ana Beatriz Galvão ()
Journal of Business & Economic Statistics, 2008, vol. 26, 546-554
Many macroeconomic series, such as U.S. real output growth, are sampled quarterly, although potentially useful predictors are often observed at a higher frequency. We look at whether a mixed data-frequency sampling (MIDAS) approach can improve forecasts of output growth. The MIDAS specification used in the comparison uses a novel way of including an autoregressive term. We find that the use of monthly data on the current quarter leads to significant improvement in forecasting current and next quarter output growth, and that MIDAS is an effective way to exploit monthly data compared with alternative methods.
References: Add references at CitEc
Citations: View citations in EconPapers (91) Track citations by RSS feed
Downloads: (external link)
http://pubs.amstat.org/doi/abs/10.1198/073500108000000015 full text (application/pdf)
Access to full text is restricted to subscribers.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:bes:jnlbes:v:26:y:2008:p:546-554
Ordering information: This journal article can be ordered from
Access Statistics for this article
Journal of Business & Economic Statistics is currently edited by Jonathan H. Wright and Keisuke Hirano
More articles in Journal of Business & Economic Statistics from American Statistical Association
Bibliographic data for series maintained by Christopher F. Baum ().