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The Allocation of Time in Decision-Making

Author

Listed:
  • Christopher F. Chabris
  • David Laibson
  • Carrie L. Morris
  • Jonathon P. Schuldt
  • Dmitry Taubinsky

Abstract

We study the allocation of time across decision problems. If a decision-maker (1) has noisy estimates of value, (2) improves those estimates the longer she analyzes a choice problem, and (3) allocates time optimally, then the decision-maker should spend less time choosing when the value gap between two options is relatively large. To test this prediction we asked subjects to make 27 binary incentive-compatible intertemporal choices, and measure response time for each decision. Our time allocation model explains 54% of the variance in average decision time. These results support the view that decision-making is a cognitively costly activity that uses time as an input allocated according to cost-benefit principles. (JEL: C0, D01, D03, D87, D9) (c) 2009 by the European Economic Association.

Suggested Citation

  • Christopher F. Chabris & David Laibson & Carrie L. Morris & Jonathon P. Schuldt & Dmitry Taubinsky, 2009. "The Allocation of Time in Decision-Making," Journal of the European Economic Association, MIT Press, vol. 7(2-3), pages 628-637, 04-05.
    • Handle: RePEc:tpr:jeurec:v:7:y:2009:i:2-3:p:628-637
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    References listed on IDEAS

    as
    1. Xavier Gabaix & David Laibson & Guillermo Moloche & Stephen Weinberg, 2006. "Costly Information Acquisition: Experimental Analysis of a Boundedly Rational Model," American Economic Review, American Economic Association, vol. 96(4), pages 1043-1068, September.
    2. Xavier Gabaix & David Laibson & Guillermo Moloche & Stephen Weinberg, 2005. "Information Acquisition: Experimental Analysis of a Boundedly Rational Model," Levine's Bibliography 666156000000000480, UCLA Department of Economics.
    3. Christopher Chabris & David Laibson & Carrie Morris & Jonathon Schuldt & Dmitry Taubinsky, 2008. "Individual laboratory-measured discount rates predict field behavior," Journal of Risk and Uncertainty, Springer, vol. 37(2), pages 237-269, December.
    4. Christopher F. Chabris & David Laibson & Carrie L. Morris & Jonathon P. Schuldt & Dmitry Taubinsky, 2008. "Measuring intertemporal preferences using response times," NBER Working Papers 14353, National Bureau of Economic Research, Inc.
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    More about this item

    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D87 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Neuroeconomics
    • D9 - Microeconomics - - Micro-Based Behavioral Economics

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