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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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    File URL: http://www.nber.org/papers/w19897.pdf
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    References listed on IDEAS

    as
    1. Woodford, Michael, 2009. "Information-constrained state-dependent pricing," Journal of Monetary Economics, Elsevier, vol. 56(S), pages 100-124.
    2. Anton A. Cheremukhin & Anna Popova & Antonella Tutino, 2011. "Experimental evidence on rational inattention," Working Papers 1112, Federal Reserve Bank of Dallas.
    3. 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..
    4. 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..
    5. Cramer,J. S., 2011. "Logit Models from Economics and Other Fields," Cambridge Books, Cambridge University Press, number 9780521188036, September.
    6. repec:cup:judgdm:v:5:y:2010:i:6:p:437-449 is not listed on IDEAS
    7. 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.
    8. 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.
    9. 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.
    10. Cunningham, Thomas, 2013. "Biases and Implicit Knowledge," MPRA Paper 50292, University Library of Munich, Germany.
    11. 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.
    12. Mervyn Stone, 1960. "Models for choice-reaction time," Psychometrika, Springer;The Psychometric Society, vol. 25(3), pages 251-260, September.
    13. Frederick Mosteller & Philip Nogee, 1951. "An Experimental Measurement of Utility," Journal of Political Economy, University of Chicago Press, vol. 59(5), pages 371-371.
    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.
    16. Ballinger, T Parker & Wilcox, Nathaniel T, 1997. "Decisions, Error and Heterogeneity," Economic Journal, Royal Economic Society, vol. 107(443), pages 1090-1105, July.
    Full references (including those not matched with items on IDEAS)

    Citations

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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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