Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/62653
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dc.contributor.authorde Clippely, Geoffroyen_US
dc.contributor.authorRozen, Kareenen_US
dc.date.accessioned2012-09-04en_US
dc.date.accessioned2012-09-17T11:31:50Z-
dc.date.available2012-09-17T11:31:50Z-
dc.date.issued2012en_US
dc.identifier.urihttp://hdl.handle.net/10419/62653-
dc.description.abstractTheories of bounded rationality are typically characterized over an exhaustive data set. This paper aims to operationalize some leading theories when the available data is limited, as is the case in most practical settings. How does one tell if observed choices are consistent with a theory of bounded rationality if the data is incomplete? What information can be identified about preferences? How can out-of-sample predictions be made? Our approach is contrasted with earlier attempts to examine bounded rationality theories on limited data, showing their notion of consistency is inappropriate for identifiability and out-of-sample prediction.en_US
dc.language.isoengen_US
dc.publisher|aBrown University, Department of Economics |cProvidence, RIen_US
dc.relation.ispartofseries|aWorking Paper, Brown University, Department of Economics |x2012-7en_US
dc.subject.ddc330en_US
dc.titleBounded rationality and limited datasets: Testable implications, identifiability, and out-of-sample predictionen_US
dc.typeWorking Paperen_US
dc.identifier.ppn723784310en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US

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