Stochastic Choice: An Optimizing Neuroeconomic Model

• Published in: The American economic review Vol. 104; no. 5; pp. 495 - 500
• Main Author: Woodford, Michael
• Format: Journal Article
• Language: English
• Published: Nashville American Economic Association 01.05.2014; American Economic Assoc
• Subjects: 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
• ISSN: 0002-8282; 1944-7981
• DOI: 10.1257/aer.104.5.495

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).