Journal Article

Detecting and Predicting Forecast Breakdowns

Raffaella Giacomini and Barbara Rossi

in The Review of Economic Studies

Published on behalf of Review of Economic Studies Ltd

Volume 76, issue 2, pages 669-705
Published in print April 2009 | ISSN: 0034-6527
Published online April 2009 | e-ISSN: 1467-937X | DOI: http://dx.doi.org/10.1111/j.1467-937X.2009.00545.x
Detecting and Predicting Forecast Breakdowns

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  • Monetary Policy, Central Banking, and the Supply of Money and Credit
  • Prices, Business Fluctuations, and Cycles
  • Econometric Modelling

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We propose a theoretical framework for assessing whether a forecast model estimated over one period can provide good forecasts over a subsequent period. We formalize this idea by defining a forecast breakdown as a situation in which the out-of-sample performance of the model, judged by some loss function, is significantly worse than its in-sample performance. Our framework, which is valid under general conditions, can be used not only to detect past forecast breakdowns but also to predict future ones. We show that main causes of forecast breakdowns are instabilities in the data-generating process and relate the properties of our forecast breakdown test to those of structural break tests. The empirical application finds evidence of a forecast breakdown in the Phillips' curve forecasts of U.S. inflation, and links it to inflation volatility and to changes in the monetary policy reaction function of the Fed.

Keywords: C53; E31; E37; E52

Journal Article.  12604 words.  Illustrated.

Subjects: Monetary Policy, Central Banking, and the Supply of Money and Credit ; Prices, Business Fluctuations, and Cycles ; Econometric Modelling

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