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Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?

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Author Info
Graham Elliott
Ivana Komunjer
Allan Timmermann

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Abstract

Empirical studies using survey data on expectations have frequently observed that forecasts are biased and have concluded that agents are not rational. We establish that existing rationality tests are not robust to even small deviations from symmetric loss and hence have little ability to tell whether the forecaster is irrational or the loss function is asymmetric. We quantify the trade-off between forecast inefficiency and asymmetric loss leading to identical outcomes of standard rationality tests and explore new and more general methods for testing forecast rationality jointly with flexible families of loss functions that embed squared loss as a special case. Empirical applications to survey data on forecasts of real output growth and inflation suggest that rejections of rationality may largely have been driven by the assumption of squared loss. Moreover, our results suggest that agents are averse to "bad" outcomes such as lower-than-expected real output growth and higher-than-expected inflation and that they incorporate such loss aversion into their forecasts. (JEL: C22, C53, E37) (c) 2008 by the European Economic Association.

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Article provided by MIT Press in its journal Journal of the European Economic Association.

Volume (Year): 6 (2008)
Issue (Month): 1 (03)
Pages: 122-157
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Handle: RePEc:tpr:jeurec:v:6:y:2008:i:1:p:122-157

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Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

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Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Clements, Michael P., 2008. "Explanations of the inconsistencies in survey respondents'forecasts," The Warwick Economics Research Paper Series (TWERPS) 870, University of Warwick, Department of Economics. [Downloadable!]
  2. Carlos Capistrán-Carmona, 2005. "Bias in Federal Reserve Inflation Forecasts: Is the Federal Reserve Irrational or Just Cautious?," Computing in Economics and Finance 2005 127, Society for Computational Economics. [Downloadable!]
    Other versions:
  3. Stanislav Anatolyev, 2006. "Dynamic modeling under linear-exponential loss," Working Papers w0092, Center for Economic and Financial Research (CEFIR). [Downloadable!]
    Other versions:
  4. Nazaria Solferino & Robert J. Waldmann, 2008. "Predicting the Signs of Forecast Errors," CEIS Research Paper 135, Tor Vergata University, CEIS, revised 24 Nov 2008. [Downloadable!]
  5. Karlyn Mitchell & Douglas K. Pearce, 2004. "Professional Forecasts of Interest Rates and Exchange Rates: Evidence from the Wall Street Journal's Panel of Economists," Working Paper Series 004, North Carolina State University, Department of Economics. [Downloadable!]
    Other versions:
  6. Pesaran, M.H. & Weale, M., 2005. "Survey Expectations," Cambridge Working Papers in Economics 0536, Faculty of Economics, University of Cambridge. [Downloadable!]
    Other versions:
  7. Carlos Capistrán & Allan Timmermann, 2008. "Forecast Combination With Entry and Exit of Experts," CREATES Research Papers 2008-55, School of Economics and Management, University of Aarhus. [Downloadable!]
    Other versions:
  8. Clements, Michael P, 2006. "Internal consistency of survey respondents.forecasts : Evidence based on the Survey of Professional Forecasters," The Warwick Economics Research Paper Series (TWERPS) 772, University of Warwick, Department of Economics. [Downloadable!]
  9. Joerg Doepke & Ulrich Fritsche & Boriss Siliverstovs, 2009. "Evaluating German Business Cycle Forecasts Under an Asymmetric Loss Function," Macroeconomics and Finance Series 200905, Hamburg University, Department Wirtschaft und Politik. [Downloadable!]
    Other versions:
  10. George A. Christodoulakis, 2005. "The European Union GDP Forecast Rationality under Asymmetric Preferences," Working Papers 30, Bank of Greece. [Downloadable!]
  11. Sean D. Campbell, 2005. "Stock market volatility and the Great Moderation," Finance and Economics Discussion Series 2005-47, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  12. Carlos Capistrán & Allan Timmermann, 2008. "Disagreement and Biases in Inflation Expectations," CREATES Research Papers 2008-56, School of Economics and Management, University of Aarhus. [Downloadable!]
    Other versions:
  13. Yang Yang & Tae-Hwy Lee, 2004. "Bagging Binary Predictors for Time Series," Econometric Society 2004 Far Eastern Meetings 512, Econometric Society. [Downloadable!]
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