Forecast Optimality Tests in the Presence of Instabilities
AbstractThis paper proposes forecast optimality tests that can be used in unstable environments. They include tests for forecast unbiasedness, efficiency, encompassing, serial uncorrelation, and, in general, regression-based tests of forecasting ability. The proposed tests are applied to evaluate the rationality of the Federal Reserve Greenbook forecasts as well as a variety of survey-based private forecasts. In addition, we consider whether Money Market Services forecasts are rational. Our robust tests suggest more empirical evidence against forecast rationality than previously found but con firm that the Federal Reserve has additional information about current and future states of the economy relative to market participants.
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Bibliographic InfoPaper provided by Duke University, Department of Economics in its series Working Papers with number 11-18.
Date of creation: 2011
Date of revision:
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Forecasting; forecast optimality; regression-based tests of forecasting ability; Greenbook forecasts; survey forecasts; real-time data;
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- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-09-05 (All new papers)
- NEP-CBA-2011-09-05 (Central Banking)
- NEP-ECM-2011-09-05 (Econometrics)
- NEP-ETS-2011-09-05 (Econometric Time Series)
- NEP-FOR-2011-09-05 (Forecasting)
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- Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
- Makram El-Shagi & Sebastian Giesen & A. Jung, 2012. "Does Central Bank Staff Beat Private Forecasters?," IWH Discussion Papers 5, Halle Institute for Economic Research.
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