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An Optimizing Neuroeconomic Model of Discrete Choice

Author

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  • Michael Woodford
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 partially 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).

Suggested Citation

  • Michael Woodford, 2014. "An Optimizing Neuroeconomic Model of Discrete Choice," NBER Working Papers 19897, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:19897
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    References listed on IDEAS

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    1. Filip Matêjka & Alisdair McKay, 2015. "Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model," American Economic Review, American Economic Association, vol. 105(1), pages 272-298, January.
    2. Woodford, Michael, 2009. "Information-constrained state-dependent pricing," Journal of Monetary Economics, Elsevier, vol. 56(S), pages 100-124.
    3. Anton A. Cheremukhin & Anna Popova & Antonella Tutino, 2011. "Experimental evidence on rational inattention," Working Papers 1112, Federal Reserve Bank of Dallas.
    4. Maxim Pinkovskiy, 2009. "Rational Inattention and Choice Under Risk: Explaining Violations of Expected Utility Through a Shannon Entropy Formulation of the Costs of Rationality," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 37(1), pages 99-112, March.
    5. John D. Hey, 2018. "Experimental investigations of errors in decision making under risk," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 17, pages 381-388, World Scientific Publishing Co. Pte. Ltd..
    6. John D. Hey, 2018. "Does Repetition Improve Consistency?," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 2, pages 13-62, World Scientific Publishing Co. Pte. Ltd..
    7. Wolpert David & Leslie David S., 2012. "Information Theory and Observational Limitations in Decision Making," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 12(1), pages 1-43, January.
    8. Cunningham, Thomas, 2013. "Biases and Implicit Knowledge," MPRA Paper 50292, University Library of Munich, Germany.
    9. Sims, Christopher A., 2010. "Rational Inattention and Monetary Economics," Handbook of Monetary Economics, in: Benjamin M. Friedman & Michael Woodford (ed.), Handbook of Monetary Economics, edition 1, volume 3, chapter 4, pages 155-181, Elsevier.
    10. Cramer,J. S., 2011. "Logit Models from Economics and Other Fields," Cambridge Books, Cambridge University Press, number 9780521188036, September.
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    14. Ian Krajbich & Bastiaan Oud & Ernst Fehr, 2014. "Benefits of Neuroeconomic Modeling: New Policy Interventions and Predictors of Preference," American Economic Review, American Economic Association, vol. 104(5), pages 501-506, May.
    15. Paulo Natenzon, 2019. "Random Choice and Learning," Journal of Political Economy, University of Chicago Press, vol. 127(1), pages 419-457.
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    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Drew Fudenberg & Whitney Newey & Philipp Strack & Tomasz Strzalecki, 2020. "Testing the drift-diffusion model," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(52), pages 33141-33148, December.
    2. Benjamin Hébert & Michael Woodford, 2021. "Neighborhood-Based Information Costs," American Economic Review, American Economic Association, vol. 111(10), pages 3225-3255, October.
    3. Hebert, Benjamin & Woodford, Michael, 2018. "Information Costs and Sequential Information Sampling," Research Papers 3751, Stanford University, Graduate School of Business.
    4. Krajbich Ian & Smith Stephanie M., 2015. "Modeling Eye Movements and Response Times in Consumer Choice," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 13(1), pages 55-72, January.
    5. Michael Woodford, 2014. "Stochastic Choice: An Optimizing Neuroeconomic Model," American Economic Review, American Economic Association, vol. 104(5), pages 495-500, May.
    6. Benjamin Hébert & Michael Woodford, 2017. "Rational Inattention and Sequential Information Sampling," NBER Working Papers 23787, National Bureau of Economic Research, Inc.

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    More about this item

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D87 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Neuroeconomics

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