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Long-run expectations in a Learning-to-Forecast Experiment

Author

Listed:
  • Annarita Colasante

    (LEE and Department of Economics, Universitat Jaume I, Castellón, Spain)

  • Simone Alfarano

    (LEE and Department of Economics, Universitat Jaume I, Castellón, Spain)

  • Eva Camacho-Cuena

    (LEE and Department of Economics, Universitat Jaume I, Castellón, Spain)

  • Mauro Gallegati

    (Department of Economics, Università Politecnica delle Marche, Ancona, Italy)

Abstract

We conduct a Learning to Forecast Experiment (LtFE) using a novel setting in which we elicit subjects' short and long-run expectations on the future price of an asset. We find that: (i) the rational expectations equilibrium (REE) is not a meaningful description for subjects' expectations, (ii) which are, instead, better described by an adaptive learning scheme. (iii) Subjects exhibit a higher degree of inertia when revising long-run expectations vis-à-vis short-run expectations.

Suggested Citation

  • Annarita Colasante & Simone Alfarano & Eva Camacho-Cuena & Mauro Gallegati, 2016. "Long-run expectations in a Learning-to-Forecast Experiment," Working Papers 2016/26, Economics Department, Universitat Jaume I, Castellón (Spain).
    • Handle: RePEc:jau:wpaper:2016/26
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    References listed on IDEAS

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    1. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1295-1328.
    2. Hommes, Cars, 2011. "The heterogeneous expectations hypothesis: Some evidence from the lab," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 1-24, January.
    3. Michael Woodford, 2007. "The Case for Forecast Targeting as a Monetary Policy Strategy," Journal of Economic Perspectives, American Economic Association, vol. 21(4), pages 3-24, Fall.
    4. Marimon, Ramon & Sunder, Shyam, 1993. "Indeterminacy of Equilibria in a Hyperinflationary World: Experimental Evidence," Econometrica, Econometric Society, vol. 61(5), pages 1073-1107, September.
    5. Ernan Haruvy & Yaron Lahav & Charles N. Noussair, 2007. "Traders' Expectations in Asset Markets: Experimental Evidence," American Economic Review, American Economic Association, vol. 97(5), pages 1901-1920, December.
    6. Heemeijer, Peter & Hommes, Cars & Sonnemans, Joep & Tuinstra, Jan, 2009. "Price stability and volatility in markets with positive and negative expectations feedback: An experimental investigation," Journal of Economic Dynamics and Control, Elsevier, vol. 33(5), pages 1052-1072, May.
    7. Stephen Morris & Hyun Song Shin, 2002. "Social Value of Public Information," American Economic Review, American Economic Association, vol. 92(5), pages 1521-1534, December.
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    Citations

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    Cited by:

    1. Anita Kopányi-Peuker & Matthias Weber & Lauren Cohen, 2021. "Experience Does Not Eliminate Bubbles: Experimental Evidence," The Review of Financial Studies, Society for Financial Studies, vol. 34(9), pages 4450-4485.
    2. Zhou Lu & Te Bao & Xiaohua Yu, 2021. "Gender and Bubbles in Experimental Markets with Positive and Negative Expectation Feedback," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1307-1326, April.
    3. 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.
    4. Annarita Colasante & Simone Alfarano & Eva Camacho-Cuena & Mauro Gallegati, 2020. "Long-run expectations in a learning-to-forecast experiment: a simulation approach," Journal of Evolutionary Economics, Springer, vol. 30(1), pages 75-116, January.
    5. 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.
    6. Bao, Te & Hommes, Cars & Pei, Jiaoying, 2021. "Expectation formation in finance and macroeconomics: A review of new experimental evidence," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    7. Makarewicz, Tomasz, 2021. "Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 626-673.
    8. Makarewicz, Tomasz, 2019. "Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics," BERG Working Paper Series 141, Bamberg University, Bamberg Economic Research Group.
    9. Morone, Andrea & Caferra, Rocco, 2020. "Inequalities in financial markets: Evidences from a laboratory experiment," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 88(C).
    10. Biondo, Alessio Emanuele, 2018. "Learning to forecast, risk aversion, and microstructural aspects of financial stability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 12, pages 1-21.
    11. 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

    Experiment; Expectations; Coordination;
    All these keywords.

    JEL classification:

    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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