Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/106602
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Type: | Journal article |
Title: | Learning from inferred foregone payoffs |
Author: | Wu, H. Bayer, R. |
Citation: | Journal of Economic Dynamics and Control, 2015; 51:445-458 |
Publisher: | Elsevier BV |
Issue Date: | 2015 |
ISSN: | 0165-1889 1879-1743 |
Statement of Responsibility: | Hang Wu, Ralph-C Bayer |
Abstract: | A player[U+05F3]s knowledge of her own actions and the corresponding payoffs may enable her to infer or form beliefs about what the payoffs would have been if she had played differently. For quantitative learning models employed in studies of low information environments, players[U+05F3] ex-post inferences and beliefs have been largely ignored. For games with large strategy spaces, this omission can seriously weaken the predictive power of a learning model. We propose a novel method of using players[U+05F3] ex-post inferences and assessments to impute foregone payoffs for unplayed strategies in low-information environments. We then use the resulting learning model to explain the pricing and learning behavior observed in a Bertrand market experiment. Maximum likelihood estimation shows that the extended model organizes the data remarkably well at both the aggregate and individual levels. |
Keywords: | Learning; inferred foregone payoffs; partial information; Bertrand experiment |
Description: | Available online 28 November 2014 |
Rights: | © 2014 Elsevier B.V. All rights reserved. |
DOI: | 10.1016/j.jedc.2014.11.012 |
Grant ID: | http://purl.org/au-research/grants/arc/DP120101831 |
Published version: | http://dx.doi.org/10.1016/j.jedc.2014.11.012 |
Appears in Collections: | Aurora harvest 8 Economics publications |
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RA_hdl_106602.pdf Restricted Access | Restricted Access | 2.36 MB | Adobe PDF | View/Open |
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