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The term structure of cross-sectional dispersion of expectations in a Learning-to-Forecast Experiment

Author

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  • Annarita Colasante

    (Universitat Jaume I)

  • Simone Alfarano

    (Universitat Jaume I)

  • Eva Camacho-Cuena

    (Universitat Jaume I)

Abstract

In this paper, we present the results of a Learning-to-Forecast Experiment (LtFE) where we eliciting short- as well as long-run expectations regarding the future price dynamics in markets with positive and negative expectations feedback. Comparing our results on short-run expectations with the LtFE literature, we prove that eliciting long-run expectations has no impact on the price dynamics nor on short-run expectations formation. In particular, we confirm that the Rational Expectation Equilibrium (REE) is a good benchmark only for the markets with negative feedback. Interestingly, our data show that while the term structure of the cross-sectional dispersion of expectations is convex in positive feedback markets, it is concave in negative feedback markets. Differences in the slope of the term structure stem from diverse degrees of uncertainty regarding the evolution of prices in the two feedback systems: (1) in the negative feedback system, the convergence of the price to the REE reflects a tendency for coordination of long-run expectations around the fundamental value; (2) conversely, oscillatory price dynamics observed in the positive feedback system is responsible for the diverging pattern of long-run expectations. Finally, we propose a new measure of heterogeneity of expectations based on the scaling of the dispersion of expectations over the forecasting horizon.

Suggested Citation

  • Annarita Colasante & Simone Alfarano & Eva Camacho-Cuena, 2019. "The term structure of cross-sectional dispersion of expectations in a Learning-to-Forecast Experiment," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 491-520, September.
  • Handle: RePEc:spr:jeicoo:v:14:y:2019:i:3:d:10.1007_s11403-019-00245-6
    DOI: 10.1007/s11403-019-00245-6
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    Cited by:

    1. Annarita Colasante & Simone Alfarano & Eva Camacho-Cuena, 2020. "Heuristic Switching Model and Exploration-Exploitation Algorithm to Describe Long-Run Expectations in LtFEs: a Comparison," Computational Economics, Springer;Society for Computational Economics, vol. 56(3), pages 623-658, October.
    2. Toshiaki Akinaga & Takanori Kudo & Kenju Akai, 2023. "Interaction between price and expectations in the jar-guessing experimental market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(3), pages 491-532, July.
    3. Alfarano, Simone & Camacho-Cuena, Eva & Colasante, Annarita & Ruiz-Buforn, Alba, 2022. "The effect of time-varying fundamentals in Learning-to-Forecast Experiments," MPRA Paper 113086, University Library of Munich, Germany.

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    More about this item

    Keywords

    Long-run expectations; Heterogeneous expectations; Experiment; Coordination; Convergence; Learning-to-Forecast Experiment;
    All these keywords.

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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