Macroeconomic forecasting with real-time data: an empirical comparison
Dick van Dijk () and
Patrick Groenen ()
No EI 2009-27, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute
Macroeconomic forecasting is not an easy task, in particular if future growth rates are forecasted in real time. This paper compares various methods to predict the growth rate of US Industrial Production (IP) and of the Composite Coincident Index (CCI) of the Conference Board, over the coming month, quarter, and half year. It turns out that future IP growth rates can be forecasted in real time from ten leading indicators, by means of the Composite Leading Index (CLI) or, even somewhat better, by principal components regression. This amends earlier negative findings for IP by Diebold and Rudebusch. For CCI, on the other hand, simple autoregressive models do not provide significantly less accurate forecasts than single-equation and bivariate vector autoregressive models with the CLI. This amends some of the more positive results for CCI recently reported by the Conference Board. Not surprisingly, all forecast methods improve considerably if `ex post' data are used, after possible data updates and revisions.
Keywords: composite coincident index; forecast evaluation; industrial production; leading indicators; recessions; vintage date (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
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:ems:eureir:17018
Access Statistics for this paper
More papers in Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute Contact information at EDIRC.
Bibliographic data for series maintained by RePub ().