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Macroeconomic forecasting with real-time data: an empirical comparison

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Author Info
Heij, C.
Dijk, D.J.C. van
Groenen, P.J.F. (Erasmus Econometric Institute)
Abstract

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.

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File URL: http://hdl.handle.net/1765/17018
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Publisher Info
Paper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number EI 2009-27 Revision_Date: 2009-11-06.

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Date of creation: 19 Oct 2009
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Handle: RePEc:dgr:eureir:1765017018

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Related research
Keywords: vintage date; leading indicators; forecast evaluation; recessions; industrial production; composite coincident index;

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This page was last updated on 2009-12-23.


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