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Strategic coordination in forecasting – An experimental study

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  • Meub, Lukas
  • Proeger, Till
  • Bizer, Kilian
  • Spiwoks, Markus

Abstract

While reputational herding has been shown to contribute to poor economic forecasting, the underlying behavioral mechanisms have not yet been empirically investigated. We run a forecasting experiment with contradictory incentives for accuracy and coordination, finding subjects’ forecasts to be inaccurate and driven by the coordination motive. Coordination is achieved through the salient, risk-dominant equilibrium, i.e. merely forecasting the current values. Subjects succeeding in coordinating earn significantly more than those striving for accuracy. Our results emphasize that reputational herding should be considered as a driving force for persistently poor prediction accuracy and systematically biased forecasts towards consensus values.

Suggested Citation

  • Meub, Lukas & Proeger, Till & Bizer, Kilian & Spiwoks, Markus, 2015. "Strategic coordination in forecasting – An experimental study," Finance Research Letters, Elsevier, vol. 13(C), pages 155-162.
  • Handle: RePEc:eee:finlet:v:13:y:2015:i:c:p:155-162
    DOI: 10.1016/j.frl.2015.02.001
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    Cited by:

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    2. Filiz, Ibrahim & Judek, Jan René & Lorenz, Marco & Spiwoks, Markus, 2021. "Reducing algorithm aversion through experience," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
    3. Daskalova, Vessela & Vriend, Nicolaas J., 2020. "Categorization and coordination," European Economic Review, Elsevier, vol. 129(C).
    4. Christoph Buehren & Tim Meyer & Christian Pierdzioch, 2020. "Experimental Evidence on Forecaster (anti-) Herding in Sports Markets," MAGKS Papers on Economics 202038, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    5. Lindner, Thomas & Muellner, Jakob & Puck, Jonas, 2016. "Cost of Capital in an International Context: Institutional Distance, Quality, and Dynamics," Journal of International Management, Elsevier, vol. 22(3), pages 234-248.
    6. Zulia Gubaydullina & Jan René Judek & Marco Lorenz & Markus Spiwoks, 2022. "Comparing Different Kinds of Influence on an Algorithm in Its Forecasting Process and Their Impact on Algorithm Aversion," Businesses, MDPI, vol. 2(4), pages 1-23, October.

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    More about this item

    Keywords

    Forecasting; Laboratory experiment; Reputational herding; Sunspot coordination;
    All these keywords.

    JEL classification:

    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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