Forecast Comparisons in Unstable Environments
Abstract
We propose new methods for comparing the relative out-of-sample forecasting performance of two competing models in the presence of possible instabilities. The main idea is to develop a measure of the relative ìlocal forecasting performanceî for the two models, and to investigate its stability over time by means of statistical tests. We propose two tests (the ìFluctuation testî and the test against a ìOne-time Reversalî) that analyze the evolution of the modelsí relative performance over historical samples. In contrast to previous approaches to forecast comparison, which are based on measures of ìglobal performanceî, we focus on the entire time path of the modelsí relative performance, which may contain useful information that is lost when looking for the model that forecasts best on average. We apply our tests to the analysis of the time variation in the out-of-sample forecasting performance of monetary models of exchange rate determination relative to the random walk.Download Info
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Paper provided by Duke University, Department of Economics in its series Working Papers with number 08-04.
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Length: 30 Pages
Date of creation: 2008
Date of revision:
Handle: RePEc:duk:dukeec:08-4
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Postal: Department of Economics Duke University 213 Social Sciences Building Box 90097 Durham, NC 27708-0097
Phone: (919) 660-1800
Fax: (919) 684-8974
Web page: http://econ.duke.edu/
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Related research
Keywords: Predictive Ability Testing; Instability; Structural Change; Forecast Evaluation;Other versions of this item:
- Raffaella Giacomini & Barbara Rossi, 2010. "Forecast comparisons in unstable environments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 595-620.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting Models; Simulation Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-04-12 (All new papers)
- NEP-CBA-2008-04-12 (Central Banking)
- NEP-ECM-2008-04-12 (Econometrics)
- NEP-FOR-2008-04-12 (Forecasting)
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
- Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.
- Domenico Ferraro & Ken Rogoff & Barbara Rossi, 2011.
"Can oil prices forecast exchange rates?,"
Working Papers
11-34, Federal Reserve Bank of Philadelphia.
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- Domenico Ferraro & Ken Rogoff & Barbara Rossi, 2011. "Can Oil Prices Forecast Exchange Rates?," Working Papers 11-05, Duke University, Department of Economics.
- Domenico Ferraro & Kenneth S. Rogoff & Barbara Rossi, 2012. "Can Oil Prices Forecast Exchange Rates?," NBER Working Papers 17998, National Bureau of Economic Research, Inc.
- Douglas, Christopher C. & Kolar, Marek, 2009. "Capturing the time dynamics of central bank intervention," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(5), pages 950-968, December.
- Katja Drechsel & Rolf Scheufele, 2010. "Should We Trust in Leading Indicators? Evidence from the Recent Recession," IWH Discussion Papers 10, Halle Institute for Economic Research.
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"Understanding models' forecasting performance,"
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