Replication data for: Stochastic Choice: An Optimizing Neuroeconomic Model
Principal Investigator(s): View help for Principal Investigator(s) Michael Woodford
Version: View help for Version V1
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LICENSE.txt | text/plain | 14.6 KB | 10/11/2019 06:28:PM |
Project Citation:
Woodford, Michael. Replication data for: Stochastic Choice: An Optimizing Neuroeconomic Model. Nashville, TN: American Economic Association [publisher], 2014. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-10-11. https://doi.org/10.3886/E112811V1
Project Description
Summary:
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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).
Scope of Project
JEL Classification:
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D11 Consumer Economics: Theory
D87 Neuroeconomics
D11 Consumer Economics: Theory
D87 Neuroeconomics
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