Behavior in a Dynamic Decision Problem: An Analysis of Experimental Evidence Using a Bayesian Type Classification Algorithm

DSpace/Manakin Repository

Search OPUS


Advanced Search

Browse

My Account

Show simple item record

dc.contributor.author Houser, DE
dc.contributor.author Keane, M
dc.contributor.author McCabe, K
dc.date.accessioned 2009-12-21T02:36:52Z
dc.date.issued 2004-01
dc.identifier.citation Econometrica: journal of the Econometric Society, 2004, 72 (3), pp. 781 - 822
dc.identifier.issn 0012-9682
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/5154
dc.description.abstract Different people may use different strategies, or decision rules, when solving complex decision problems. We provide a new Bayesian procedure for drawing inferences about the nature and number of decision rules present in a population, and use it to analyze the behaviors of laboratory subjects confronted with a difficult dynamic stochastic decision problem. Subjects practiced before playing for money. Based on money round decisions, our procedure classifies subjects into three types, which we label "Near Rational,""Fatalist," and "Confused." There is clear evidence of continuity in subjects' behaviors between the practice and money rounds: types who performed best in practice also tended to perform best when playing for money. However, the agreement between practice and money play is far from perfect. The divergences appear to be well explained by a combination of type switching (due to learning and/or increased effort in money play) and errors in our probabilistic type assignments.
dc.publisher Blackwell Publishing Ltd
dc.relation.isbasedon 10.1111/j.1468-0262.2004.00512.x
dc.title Behavior in a Dynamic Decision Problem: An Analysis of Experimental Evidence Using a Bayesian Type Classification Algorithm
dc.type Journal Article
dc.parent Econometrica: journal of the Econometric Society
dc.journal.volume 3
dc.journal.volume 72
dc.journal.number 3 en_US
dc.publocation United Kingdom en_US
dc.publocation Los Alamitos, USA
dc.identifier.startpage 781 en_US
dc.identifier.endpage 822 en_US
dc.cauo.name BUS.Centre for the Study of Choice en_US
dc.conference Verified OK en_US
dc.conference IEEE Symposium on Computer-Based Medical Systems
dc.for 1401 Economic Theory
dc.personcode 998871
dc.percentage 100 en_US
dc.classification.name Economic Theory en_US
dc.classification.type FOR-08 en_US
dc.date.activity 2006-06-22
dc.location.activity Salt Lake City, UT
dc.description.keywords Dynamic programming ? Gibbs sampling ? Bayesian decision theory ? experimental economics ? behavioral economics ? heuristics en_US
dc.description.keywords N/A
dc.description.keywords Dynamic programming Gibbs sampling Bayesian decision theory experimental economics behavioral economics heuristics
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Business
pubs.organisational-group /University of Technology Sydney/Faculty of Business/Economics
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
utslib.collection.history Closed (ID: 3)


Files in this item

This item appears in the following Collection(s)

Show simple item record