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Stochastic Choice and the Allocation of Cognitive Effort

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  • Peter Moffatt

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Abstract

Data from a risky choice experiment are used to estimate a fully parametric stochastic model of risky choice. As is usual with such analyses, Expected Utility Theory is rejected in favour of a form of Rank Dependent Theory. Then an estimate of the risk aversion parameter is deduced for each subject, and this is used to construct a measure of the “closeness to indifference'' of each subject in each choice problem. This measure is then used as an explanatory variable in a random effects model of decision time, with other explanatory variables being the complexity of the problem, the financial incentives, and the amount of experience accumulated at the time of performing the task. The most interesting finding is that significantly more effort is allocated to problems in which subjects are close to indifference. This presents us with another reason (in addition to statistical information considerations) why such tasks should play a prominent role in experiments. Copyright Springer Science + Business Media, Inc. 2005

Suggested Citation

  • Peter Moffatt, 2005. "Stochastic Choice and the Allocation of Cognitive Effort," Experimental Economics, Springer;Economic Science Association, vol. 8(4), pages 369-388, December.
  • Handle: RePEc:kap:expeco:v:8:y:2005:i:4:p:369-388
    DOI: 10.1007/s10683-005-5375-6
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    References listed on IDEAS

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    1. Loomes, Graham & Moffatt, Peter G & Sugden, Robert, 2002. "A Microeconometric Test of Alternative Stochastic Theories of Risky Choice," Journal of Risk and Uncertainty, Springer, vol. 24(2), pages 103-130, March.
    2. Loomes, Graham & Sugden, Robert, 1998. "Testing Different Stochastic Specifications of Risky Choice," Economica, London School of Economics and Political Science, vol. 65(260), pages 581-598, November.
    3. Wilcox, Nathaniel T, 1993. "On a Lottery Pricing Anomaly: Time Tells the Tale," Journal of Risk and Uncertainty, Springer, vol. 7(3), pages 311-324, December.
    4. Camerer, Colin F & Hogarth, Robin M, 1999. "The Effects of Financial Incentives in Experiments: A Review and Capital-Labor-Production Framework," Journal of Risk and Uncertainty, Springer, vol. 19(1-3), pages 7-42, December.
    5. Hey, John D & Orme, Chris, 1994. "Investigating Generalizations of Expected Utility Theory Using Experimental Data," Econometrica, Econometric Society, vol. 62(6), pages 1291-1326, November.
    6. Peter Moffatt & Simon Peters, 2001. "Testing for the Presence of a Tremble in Economic Experiments," Experimental Economics, Springer;Economic Science Association, vol. 4(3), pages 221-228, December.
    7. Hey, John D., 1995. "Experimental investigations of errors in decision making under risk," European Economic Review, Elsevier, vol. 39(3-4), pages 633-640, April.
    8. John Hey, 2001. "Does Repetition Improve Consistency?," Experimental Economics, Springer;Economic Science Association, vol. 4(1), pages 5-54, June.
    9. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
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    Citations

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    Cited by:

    1. Carlos Alós-Ferrer & Ðura-Georg Granić & Johannes Kern & Alexander K. Wagner, 2016. "Preference reversals: Time and again," Journal of Risk and Uncertainty, Springer, vol. 52(1), pages 65-97, February.
    2. Hans-Martin von Gaudecker & Arthur van Soest & Erik Wengstrom, 2011. "Heterogeneity in Risky Choice Behavior in a Broad Population," American Economic Review, American Economic Association, vol. 101(2), pages 664-694, April.
    3. Ubeda, Paloma, 2014. "The consistency of fairness rules: An experimental study," Journal of Economic Psychology, Elsevier, vol. 41(C), pages 88-100.
    4. Wilcox, Nathaniel T., 2011. "'Stochastically more risk averse:' A contextual theory of stochastic discrete choice under risk," Journal of Econometrics, Elsevier, vol. 162(1), pages 89-104, May.
    5. Guido Baltussen & G. Post & Martijn Assem & Peter Wakker, 2012. "Random incentive systems in a dynamic choice experiment," Experimental Economics, Springer;Economic Science Association, vol. 15(3), pages 418-443, September.
    6. Martin G. Kocher & Julius Pahlke & Stefan T. Trautmann, 2013. "Tempus Fugit : Time Pressure in Risky Decisions," Management Science, INFORMS, vol. 59(10), pages 2380-2391, October.
    7. Duffy, Sean & Naddeo, JJ & Owens, David & Smith, John, 2016. "Cognitive load and mixed strategies: On brains and minimax," MPRA Paper 71878, University Library of Munich, Germany.
    8. Arkady Konovalov & Ian Krajbich, 2016. "Revealed Indifference: Using Response Times to Infer Preferences," Working Papers 16-01, Ohio State University, Department of Economics.
    9. Navarro-Martinez, Daniel & Loomes, Graham & Isoni, Andrea & Butler, David & Alaoui, Larbi, 2017. "Boundedly Rational Expected Utility Theory," MPRA Paper 79893, University Library of Munich, Germany.
    10. Buschena, David E. & Atwood, Joseph A., 2011. "Evaluation of similarity models for expected utility violations," Journal of Econometrics, Elsevier, vol. 162(1), pages 105-113, May.
    11. Conte, Anna & Hey, John D. & Moffatt, Peter G., 2011. "Mixture models of choice under risk," Journal of Econometrics, Elsevier, vol. 162(1), pages 79-88, May.
    12. Klaus Moeltner & James J. Murphy & John K. Stranlund & Maria Alejandra Velez, 2013. "Institutional heterogeneity in social dilemma games: a Bayesian examination," Chapters,in: Handbook on Experimental Economics and the Environment, chapter 2, pages 67-88 Edward Elgar Publishing.
    13. Jan Hausfeld & Sven Resnjanskij, 2017. "Risky Decisions and the Opportunity Costs of Time," TWI Research Paper Series 108, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    14. repec:gam:jgames:v:9:y:2018:i:1:p:4-:d:127477 is not listed on IDEAS

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