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Detecting and Predicting Forecast Breakdowns

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  • Rossi, Barbara
  • Giacomini, Raffaella

Abstract

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 existing structural break tests. The main differences are that our test is robust to the presence of unstable regressors and that it has greater power than previous tests to capture systematic forecast errors caused by recurring breaks that are ignored by the forecast model. As a by-product, we show that our results can be applied to forecast rationality tests and provide the appropriate asymptotic variance estimator that corrects the size distortions of previous forecast rationality tests. The empirical application finds evidence of a forecast breakdown in the Phillipsí curve forecasts of U.S. inflation, and links it to inflation volatility and to changes in the monetary policy reaction function of the Fed.

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Bibliographic Info

Paper provided by Duke University, Department of Economics in its series Working Papers with number 06-01.

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Length: 41 pages
Date of creation: 2006
Date of revision:
Handle: RePEc:duk:dukeec:06-01

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  1. Peter F. Christoffersen & Francis X. Diebold, 1997. "Optimal prediction under asymmetric loss," Working Papers 97-11, Federal Reserve Bank of Philadelphia.
  2. Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
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  13. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
  14. Rossi, Barbara, 2002. "Optimal Tests for Nested Model Selection with Underlying Parameter Instability," Working Papers 02-05, Duke University, Department of Economics.
  15. Hansen, Bruce E., 2000. "Testing for structural change in conditional models," Journal of Econometrics, Elsevier, vol. 97(1), pages 93-115, July.
  16. Clarida, R. & Gali, J. & Gertler, M., 1998. "Monetary Policy Rules and Macroeconomic Stability: Evidence and some Theory," Working Papers 98-01, C.V. Starr Center for Applied Economics, New York University.
  17. Donald W.K. Andrews, 1990. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Cowles Foundation Discussion Papers 943, Cowles Foundation for Research in Economics, Yale University.
  18. Mc Cracken, Michael W., 2000. "Robust out-of-sample inference," Journal of Econometrics, Elsevier, vol. 99(2), pages 195-223, December.
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  21. repec:cup:etheor:v:13:y:1997:i:6:p:808-17 is not listed on IDEAS
  22. repec:cup:etheor:v:11:y:1995:i:4:p:699-720 is not listed on IDEAS
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