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Signal extraction: experimental evidence

Author

Listed:
  • Te Bao

    (Nanyang Technological University)

  • John Duffy

    (University of California)

Abstract

We report on an experiment examining whether individuals can solve a simple signal extraction problem of the type found in models with imperfect information. In one treatment, subjects must form point predictions based on observing both public and private signals, while in another they receive the same information but must decide on the weight to attach to each signal, which then determines their point prediction. We find that, at the aggregate level, signal extraction provides a good characterization of subjects’ behavior in both treatments, but at the individual level, there is considerable heterogeneity in subjects’ ability to perform signal extraction.

Suggested Citation

  • Te Bao & John Duffy, 2021. "Signal extraction: experimental evidence," Theory and Decision, Springer, vol. 90(2), pages 219-232, March.
  • Handle: RePEc:kap:theord:v:90:y:2021:i:2:d:10.1007_s11238-020-09785-x
    DOI: 10.1007/s11238-020-09785-x
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    References listed on IDEAS

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    Cited by:

    1. 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).
    2. Rocco Caferra & Gabriele Tedeschi & Andrea Morone, 2023. "Agents interaction and price dynamics: evidence from the laboratory," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(2), pages 251-274, April.
    3. Rocco Caferra & Simone Nuzzo & Andrea Morone, 2023. "“Less is more” or “more is better”? The effect of asymmetric information distribution on market efficiency and wealth inequality," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(2), pages 233-250, April.
    4. Bao, Te & Corgnet, Brice & Hanaki, Nobuyuki & Riyanto, Yohanes E. & Zhu, Jiahua, 2023. "Predicting the unpredictable: New experimental evidence on forecasting random walks," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).

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