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Forecast Optimality Tests in the Presence of Instabilities

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  • Barbara Rossi
  • Tatevik Sekhposyan

Abstract

This 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.

Suggested Citation

  • Barbara Rossi & Tatevik Sekhposyan, 2011. "Forecast Optimality Tests in the Presence of Instabilities," Working Papers 11-18, Duke University, Department of Economics.
  • Handle: RePEc:duk:dukeec:11-18
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    File URL: http://ssrn.com/abstract=1916249
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    Cited by:

    1. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, Elsevier.
    2. Barbara Rossi, 2014. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 510-514, October.
    3. González-Rivera, Gloria & Sun, Yingying, 2017. "Density forecast evaluation in unstable environments," International Journal of Forecasting, Elsevier, vol. 33(2), pages 416-432.
    4. El-Shagi, Makram & Giesen, Sebastian & Jung, Alexander, 2012. "Does Central Bank Staff Beat Private Forecasters?," IWH Discussion Papers 5/2012, Halle Institute for Economic Research (IWH).
    5. Jung, Alexander & El-Shagi, Makram & Giesen, Sebastian, 2014. "Does the federal reserve staff still beat private forecasters?," Working Paper Series 1635, European Central Bank.
    6. Gürkaynak, Refet S. & Kisacikoglu, Burçin & Rossi, Barbara, 2013. "Do DSGE Models Forecast More Accurately Out-of-Sample than VAR Models?," CEPR Discussion Papers 9576, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    Forecasting; forecast optimality; regression-based tests of forecasting ability; Greenbook forecasts; survey forecasts; real-time data;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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

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