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Forecaster (Mis-)Behavior

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  • Broer, Tobias
  • Kohlhas, Alexandre

Abstract

Professional forecasts are often used to gauge the expectations of households and firms. Recently, the average of such forecasts have been argued to support rational expectation formation with noisy private information. We document that individual forecasts of US GDP and inflation in the Survey of Professional Forecasters overrespond to both private and public information, contradicting, prima facie, the assumption of noisy rational expectation formation. We generalize two alternative models of forecaster behavior that focus on strategic diversification and behavioral overconfidence, respectively, to dynamic environments with noisy private information. We find that both models predict overresponses, but only the overconfidence model is simultaneously consistent with a substantial overreaction to public information.

Suggested Citation

  • Broer, Tobias & Kohlhas, Alexandre, 2018. "Forecaster (Mis-)Behavior," CEPR Discussion Papers 12898, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:12898
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    as
    1. Ottaviani, Marco & Sorensen, Peter Norman, 2006. "The strategy of professional forecasting," Journal of Financial Economics, Elsevier, vol. 81(2), pages 441-466, August.
    2. Markus K. Brunnermeier & Jonathan A. Parker, 2005. "Optimal Expectations," American Economic Review, American Economic Association, vol. 95(4), pages 1092-1118, September.
    3. Manuel Amador & Pierre-Olivier Weill, 2010. "Learning from Prices: Public Communication and Welfare," Journal of Political Economy, University of Chicago Press, vol. 118(5), pages 866-907.
    4. N. Gregory Mankiw & Ricardo Reis & Justin Wolfers, 2004. "Disagreement about Inflation Expectations," NBER Chapters, in: NBER Macroeconomics Annual 2003, Volume 18, pages 209-270, National Bureau of Economic Research, Inc.
    5. Cutler, David M & Poterba, James M & Summers, Lawrence H, 1990. "Speculative Dynamics and the Role of Feedback Traders," American Economic Review, American Economic Association, vol. 80(2), pages 63-68, May.
    6. repec:bla:jfinan:v:53:y:1998:i:6:p:1839-1885 is not listed on IDEAS
    7. Barberis, Nicholas & Greenwood, Robin & Jin, Lawrence & Shleifer, Andrei, 2018. "Extrapolation and bubbles," Journal of Financial Economics, Elsevier, vol. 129(2), pages 203-227.
    8. Olivier Coibion & Yuriy Gorodnichenko, 2012. "What Can Survey Forecasts Tell Us about Information Rigidities?," Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 116-159.
    9. Ryan Chahrour & Kyle Jurado, 2018. "News or Noise? The Missing Link," American Economic Review, American Economic Association, vol. 108(7), pages 1702-1736, July.
    10. Lamont, Owen A., 2002. "Macroeconomic forecasts and microeconomic forecasters," Journal of Economic Behavior & Organization, Elsevier, vol. 48(3), pages 265-280, July.
    11. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2018. "Diagnostic Expectations and Credit Cycles," Journal of Finance, American Finance Association, vol. 73(1), pages 199-227, February.
    12. Garcí­a, Juan Angel, 2003. "An introduction to the ECB's survey of professional forecasters," Occasional Paper Series 8, European Central Bank.
    13. Andreas Fuster & Ricardo Perez-Truglia & Mirko Wiederholt & Basit Zafar, 2022. "Expectations with Endogenous Information Acquisition: An Experimental Investigation," The Review of Economics and Statistics, MIT Press, vol. 104(5), pages 1059-1078, December.
    14. Juan Angel Garcia, 2003. "An introduction to the ECB’s survey of professional forecasters," Occasional Paper Series 08, European Central Bank.
    15. Nicola Gennaioli & Andrei Shleifer, 2010. "What Comes to Mind," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(4), pages 1399-1433.
    16. Dovern, Jonas & Fritsche, Ulrich & Loungani, Prakash & Tamirisa, Natalia, 2015. "Information rigidities: Comparing average and individual forecasts for a large international panel," International Journal of Forecasting, Elsevier, vol. 31(1), pages 144-154.
    17. Welch, Ivo, 2000. "Herding among security analysts," Journal of Financial Economics, Elsevier, vol. 58(3), pages 369-396, December.
    18. Jean-Pierre Benoît & Juan Dubra & Don A. Moore, 2015. "Does The Better-Than-Average Effect Show That People Are Overconfident?: Two Experiments," Journal of the European Economic Association, European Economic Association, vol. 13(2), pages 293-329, April.
    19. Zarnowitz, Victor, 1985. "Rational Expectations and Macroeconomic Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(4), pages 293-311, October.
    20. Hirshleifer, David & Subrahmanyam, Avanidhar & Titman, Sheridan, 1994. "Security Analysis and Trading Patterns When Some Investors Receive Information before Others," Journal of Finance, American Finance Association, vol. 49(5), pages 1665-1698, December.
    21. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    22. Scharfstein, David S & Stein, Jeremy C, 1990. "Herd Behavior and Investment," American Economic Review, American Economic Association, vol. 80(3), pages 465-479, June.
    23. Andrade, Philippe & Le Bihan, Hervé, 2013. "Inattentive professional forecasters," Journal of Monetary Economics, Elsevier, vol. 60(8), pages 967-982.
    24. Bhattacharya, Sudipto & Pfleiderer, Paul, 1985. "Delegated portfolio management," Journal of Economic Theory, Elsevier, vol. 36(1), pages 1-25, June.
    25. Hellwig, Martin F., 1980. "On the aggregation of information in competitive markets," Journal of Economic Theory, Elsevier, vol. 22(3), pages 477-498, June.
    26. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
    27. David Laster & Paul Bennett & In Sun Geoum, 1999. "Rational Bias in Macroeconomic Forecasts," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(1), pages 293-318.
    28. Alexandre Kohlhas, 2018. "Asymmetric Attention," 2018 Meeting Papers 1040, Society for Economic Dynamics.
    29. Vives, Xavier, 1997. "Learning from Others: A Welfare Analysis," Games and Economic Behavior, Elsevier, vol. 20(2), pages 177-200, August.
    30. Miller, Edward M, 1977. "Risk, Uncertainty, and Divergence of Opinion," Journal of Finance, American Finance Association, vol. 32(4), pages 1151-1168, September.
    31. Michael Woodford, 2001. "Imperfect Common Knowledge and the Effects of Monetary Policy," NBER Working Papers 8673, National Bureau of Economic Research, Inc.
    32. Tilman Ehrbeck & Robert Waldmann, 1996. "Why Are Professional Forecasters Biased? Agency versus Behavioral Explanations," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 111(1), pages 21-40.
    33. Jeffrey C. Fuhrer, 2015. "Expectations as a source of macroeconomic persistence: an exploration of firms' and households' expectation formation," Working Papers 15-5, Federal Reserve Bank of Boston.
    34. Dean Croushore, 1993. "Introducing: the survey of professional forecasters," Business Review, Federal Reserve Bank of Philadelphia, issue Nov, pages 3-15.
    35. John R. Graham, 1999. "Herding among Investment Newsletters: Theory and Evidence," Journal of Finance, American Finance Association, vol. 54(1), pages 237-268, February.
    36. Marinovic, Iván & Ottaviani, Marco & Sorensen, Peter, 2013. "Forecasters’ Objectives and Strategies," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 690-720, Elsevier.
    37. Zarnowitz, Victor & Lambros, Louis A, 1987. "Consensus and Uncertainty in Economic Prediction," Journal of Political Economy, University of Chicago Press, vol. 95(3), pages 591-621, June.
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    Cited by:

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    2. Reslow, André, 2019. "Inefficient Use of Competitors'Forecasts?," Working Paper Series 380, Sveriges Riksbank (Central Bank of Sweden).
    3. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    4. George-Marios Angeletos & Zhen Huo & Karthik A. Sastry, 2021. "Imperfect Macroeconomic Expectations: Evidence and Theory," NBER Macroeconomics Annual, University of Chicago Press, vol. 35(1), pages 1-86.

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    More about this item

    Keywords

    Forecaster behavior; Rational expectations; Bounded rationality;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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