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Department of Economics, The Johns Hopkins University >
Working Papers, Department of Economics, The Johns Hopkins University >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10419/49877
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Full metadata record
| DC Field | | Value | | Language |
| dc.contributor.author | | Hu, Yingyao | | en_US |
| dc.contributor.author | | Kayaba, Yutaka | | en_US |
| dc.contributor.author | | Shum, Matt | | en_US |
| dc.date.accessioned | | 2011-09-27T15:21:12Z | | - |
| dc.date.available | | 2011-09-27T15:21:12Z | | - |
| dc.date.issued | | 2010 | | en_US |
| dc.identifier.uri | | http://hdl.handle.net/10419/49877 | | - |
| dc.description.abstract | | How do people learn? We assess, in a distribution-free manner, subjects' learning and choice rules in dynamic two-armed bandit (probabilistic reversal learning) experiments. To aid in identification and estimation, we use auxiliary measures of subjects' beliefs, in the form of their eye-movements during the experiment. Our estimated choice probabilities and learning rules have some distinctive features; notably that subjects tend to update in a non-smooth manner following choices made in accordance with current beliefs. Moreover, the beliefs implied by our nonparametric learning rules are closer to those from a (non-Bayesian) reinforcement learning model, than a Bayesian learning model. | | en_US |
| dc.language.iso | | eng | | en_US |
| dc.publisher | | Johns Hopkins Univ., Dep. of Economics Baltimore, Md. | | en_US |
| dc.relation.ispartofseries | | Working papers // the Johns Hopkins University, Department of Economics 560 | | en_US |
| dc.subject.jel | | D83 | | en_US |
| dc.subject.jel | | C91 | | en_US |
| dc.subject.jel | | C14 | | en_US |
| dc.subject.ddc | | 330 | | en_US |
| dc.subject.keyword | | Learning | | en_US |
| dc.subject.keyword | | experiments | | en_US |
| dc.subject.keyword | | eye-tracking | | en_US |
| dc.subject.keyword | | Bayesian vs. non-Bayesian learning | | en_US |
| dc.subject.keyword | | nonparametric estimation | | en_US |
| dc.subject.stw | | Schätztheorie | | en_US |
| dc.subject.stw | | Lernen | | en_US |
| dc.subject.stw | | Nichtparametrisches Verfahren | | en_US |
| dc.subject.stw | | Simulation | | en_US |
| dc.subject.stw | | Dynamisches Modell | | en_US |
| dc.title | | Nonparametric learning rules from bandit experiments: The eyes have it! | | en_US |
| dc.type | | Working Paper | | en_US |
| dc.identifier.ppn | | 635252643 | | en_US |
| dc.rights | | http://www.econstor.eu/dspace/Nutzungsbedingungen | | en_US |
| Appears in Collections: | | Working Papers, Department of Economics, The Johns Hopkins University
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