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Antonio Guarino

Biographic Data

ID6411040
NAMEAntonio Guarino
GIVEN NAMESAntonio
FAMILY NAMEGuarino
SIGNATUREGUARINO A
AFFILIATIONSUniversity College London
ORCID0000-0001-5241-5855
VERIFIEDYes
TOTAL WORKS4
TOTAL CITATIONS0
AUTHOR COUNT4
EDITOR COUNT0
FIRST PUBLICATION YEAR2017
LATEST PUBLICATION YEAR2022
H-INDEX0
  • Information redundancy neglect versus overconfidence

    Marco Angrisani, Antonio Guarino et al.•REPORT•2022

    We study social learning in a continuous action space experiment. Subjects, acting in sequence, state their belief about the value of a good, after observing their predecessors' statements and a private signal. We compare the behavior in the laboratory with the Perfect Bayesian Equilibrium prediction and the predictions of bounded rationality models of decision making: the redundancy of information neglect model and the overconfidence model. The …

  • Non-Bayesian updating in a social learning experiment

    Open Access•Roberta De Filippis, Antonio Guarino et al.•ARTICLE•Journal of Economic Theory•2021

  • Non-Bayesian updating in a social learning experiment

    Roberta De Filippis, Antonio Guarino et al.•REPORT•2020

    In our laboratory experiment, subjects, in sequence, have to predict the value of a good. The second subject in the sequence makes his prediction twice: first ("first belief"), after he observes his predecessor's prediction; second ("posterior belief"), after he observes his private signal. We find that the second subjects weigh their signal as a Bayesian agent would do when the signal confirms their first belief; they overweight the signal when …

  • Updating ambiguous beliefs in a social learning experiment

    Roberta De Filippis, Antonio Guarino et al.•REPORT•2017

    We present a novel experimental design to study social learning in the laboratory. Subjects have to predict the value of a good in a sequential order. We elicit each subject's belief twice: first ("prior belief"), after he observes his predecessors' action; second ("posterior belief"), after he observes a private signal on the value of the good. We are therefore able to disentangle social learning from learning from a private signal. Our main res…

No prominent works on this page.

  • Updating ambiguous beliefs in a social learning experiment

    Roberta De Filippis, Antonio Guarino et al.•REPORT•2017

    We present a novel experimental design to study social learning in the laboratory. Subjects have to predict the value of a good in a sequential order. We elicit each subject's belief twice: first ("prior belief"), after he observes his predecessors' action; second ("posterior belief"), after he observes a private signal on the value of the good. We are therefore able to disentangle social learning from learning from a private signal. Our main res…

  • Non-Bayesian updating in a social learning experiment

    Roberta De Filippis, Antonio Guarino et al.•REPORT•2020

    In our laboratory experiment, subjects, in sequence, have to predict the value of a good. The second subject in the sequence makes his prediction twice: first ("first belief"), after he observes his predecessor's prediction; second ("posterior belief"), after he observes his private signal. We find that the second subjects weigh their signal as a Bayesian agent would do when the signal confirms their first belief; they overweight the signal when …

  • Non-Bayesian updating in a social learning experiment

    Open Access•Roberta De Filippis, Antonio Guarino et al.•ARTICLE•Journal of Economic Theory•2021

  • Information redundancy neglect versus overconfidence

    Marco Angrisani, Antonio Guarino et al.•REPORT•2022

    We study social learning in a continuous action space experiment. Subjects, acting in sequence, state their belief about the value of a good, after observing their predecessors' statements and a private signal. We compare the behavior in the laboratory with the Perfect Bayesian Equilibrium prediction and the predictions of bounded rationality models of decision making: the redundancy of information neglect model and the overconfidence model. The …

Artificial Intelligence (4 works) · Computer Science (4 works) · Experimental Behavioral Economics Studies (3 works) · Opinion Dynamics and Social Influence (3 works) · Bayesian inference (2 works) · Bayesian probability (2 works) · Cognitive psychology (2 works) · Game Theory and Applications (2 works) · Machine learning (2 works) · Psychology (2 works)

Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae