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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

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Bibliographic Info

Article provided by Springer in its journal Experimental Economics.

Volume (Year): 8 (2005)
Issue (Month): 4 (December)
Pages: 369-388

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Handle: RePEc:kap:expeco:v:8:y:2005:i:4:p:369-388

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Web page: http://www.springerlink.com/link.asp?id=102888

Related research

Keywords: risky choice; rank dependent theory; random effects; decision times;

References

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  1. Wilcox, Nathaniel T, 1993. " On a Lottery Pricing Anomaly: Time Tells the Tale," Journal of Risk and Uncertainty, Springer, Springer, vol. 7(3), pages 311-24, December.
  2. Loomes, G. & Moffatt, P.G. & Sugden, R., 1998. "A Microeconometric Test of Alternative Stochastic Theories of Risky Choice," University of East Anglia Discussion Papers in Economics 9806, School of Economics, University of East Anglia, Norwich, UK..
  3. John Hey, . "Does Repetition Improve Consistency?," Discussion Papers 99/28, Department of Economics, University of York.
  4. Hey, John D & Orme, Chris, 1994. "Investigating Generalizations of Expected Utility Theory Using Experimental Data," Econometrica, Econometric Society, Econometric Society, vol. 62(6), pages 1291-1326, November.
  5. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, Econometric Society, vol. 66(3), pages 497-528, May.
  6. 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, Springer, vol. 19(1-3), pages 7-42, 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. Peter Moffatt & Simon Peters, 2001. "Testing for the Presence of a Tremble in Economic Experiments," Experimental Economics, Springer, Springer, vol. 4(3), pages 221-228, December.
  9. Loomes, Graham & Sugden, Robert, 1998. "Testing Different Stochastic Specifications of Risky Choice," Economica, London School of Economics and Political Science, London School of Economics and Political Science, vol. 65(260), pages 581-98, November.
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Citations

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Cited by:
  1. Gaudecker, Hans-Martin von & van Soest, Arthur & Wengström, Erik, 2009. "Heterogeneity in Risky Choice Behaviour in a Broad Population," IZA Discussion Papers 4022, Institute for the Study of Labor (IZA).
  2. Anna Conte & John D Hey & Peter G Moffatt, 2007. "Mixture Models of Choice Under Risk," Discussion Papers 07/06, Department of Economics, University of York.
  3. Kocher, Martin G. & Pahlke, Julius & Trautmann, Stefan T., 2011. "Tempus Fugit: Time Pressure in Risky Decisions," Discussion Papers in Economics 12221, University of Munich, Department of Economics.
  4. Wilcox, Nathaniel T., 2011. "'Stochastically more risk averse:' A contextual theory of stochastic discrete choice under risk," Journal of Econometrics, Elsevier, Elsevier, vol. 162(1), pages 89-104, May.
  5. Buschena, David E. & Atwood, Joseph A., 2011. "Evaluation of similarity models for expected utility violations," Journal of Econometrics, Elsevier, Elsevier, vol. 162(1), pages 105-113, May.
  6. Klaus Moeltner & James J. Murphy & John K. Stranlund & Maria Alejandra Velez, 2012. "Institutional Heterogeneity in Social Dilemma Games: A Bayesian Examination," Working Papers 2012-04, University of Alaska Anchorage, Department of Economics.
  7. Guido Baltussen & G. Post & Martijn Assem & Peter Wakker, 2012. "Random incentive systems in a dynamic choice experiment," Experimental Economics, Springer, Springer, vol. 15(3), pages 418-443, September.

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