Stochastic Choice: An Optimizing Neuroeconomic Model
A model is proposed in which stochastic choice results from noise in cognitive processing rather than random variation in preferences. The mental process used to make a choice is nonetheless optimal, subject to a constraint on available information-processing capacity that is motivated by neurophysi...
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| Published in | The American economic review Vol. 104; no. 5; pp. 495 - 500 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Nashville
American Economic Association
01.05.2014
American Economic Assoc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0002-8282 1944-7981 |
| DOI | 10.1257/aer.104.5.495 |
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| Abstract | A model is proposed in which stochastic choice results from noise in cognitive processing rather than random variation in preferences. The mental process used to make a choice is nonetheless optimal, subject to a constraint on available information-processing capacity that is motivated by neurophysiological evidence. The optimal information-constrained model is found to offer a better fit to experimental data on choice frequencies and reaction times than either a purely mechanical process model of choice (the drift-diffusion model) or an optimizing model with fewer constraints on feasible choice processes (the rational inattention model). |
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| AbstractList | A model is proposed in which stochastic choice results from noise in cognitive processing rather than random variation in preferences. The mental process used to make a choice is nonetheless optimal, subject to a constraint on available information-processing capacity that is motivated by neurophysiological evidence. The optimal information-constrained model is found to offer a better fit to experimental data on choice frequencies and reaction times than either a purely mechanical process model of choice (the drift-diffusion model) or an optimizing model with fewer constraints on feasible choice processes (the rational inattention model). A model is proposed in which stochastic choice results from noise in cognitive processing rather than random variation in preferences. The mental process used to make a choice is nonetheless optimal, subject to a constraint on available information-processing capacity that is motivated by neurophysiological evidence. The optimal information-constrained model is found to offer a better fit to experimental data on choice frequencies and reaction times than either a purely mechanical process model of choice (the drift-diffusion model) or an optimizing model with fewer constraints on feasible choice processes (the rational inattention model). [PUBLICATION ABSTRACT] |
| Author | Woodford, Michael |
| Author_xml | – sequence: 1 givenname: Michael surname: Woodford fullname: Woodford, Michael |
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| Cites_doi | 10.1038/nn.2635 10.1111/j.1468-0297.1997.tb00009.x 10.1016/0014-2921(09)40007-4 10.1257/jep.25.4.3 |
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| SubjectTerms | Algorithms Decision making Economic models Expected utility Experimental data Hypotheses Information Information theory Lagrange multiplier Logistics Modeling Neuroeconomics NEUROECONOMICS OF STOCHASTIC CHOICE Neurosciences Neuroökonomie Observed choices Parametric models Preferences Sensors Stochastic models Stochastic processes Stochastischer Prozess Studies Variance |
| Title | Stochastic Choice: An Optimizing Neuroeconomic Model |
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