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The Relationship Between Risk Attitudes and Heuristics in Search Tasks: A Laboratory Experiment

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  • Daniel Schunk

    ()

  • Joachim Winter

    () (Munich Center for the Economics of Aging (MEA))

Abstract

The existing evidence from laboratory experiments suggests that relatively simple heuristics describe observed search behavior better than the optimal stopping rule derived under risk neutrality. Such behavior could be generated by two entirely different classes of decision rules: (i) rules that are optimal conditional on utility functions that depart from risk neutrality or (ii) heuristics that derive from limited cognitive processing capacities and satisfycing. In this paper, we develop and test search models that depart from the standard assumption of risk neutrality in order to distinguish these two possibilities. In our experiment, we present subjects not only with a standard search task, but also with a series of lottery tasks that serve to elicit the shape of their utility functions. We do not find a relationship between behavior in the search task and measures of risk aversion. Our data suggest, however, that loss aversion is important for explaining search behavior.

Suggested Citation

  • Daniel Schunk & Joachim Winter, 2005. "The Relationship Between Risk Attitudes and Heuristics in Search Tasks: A Laboratory Experiment," MEA discussion paper series 05077, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    • Handle: RePEc:mea:meawpa:05077
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    2. Sugden, Robert & Wang, Mengjie & Zizzo, Daniel John, 2019. "Take it or leave it: Experimental evidence on the effect of time-limited offers on consumer behaviour," Journal of Economic Behavior & Organization, Elsevier, vol. 168(C), pages 1-23.
    3. Miura, Takahiro & Inukai, Keigo & Sasaki, Masaru, 2019. "Testing the Reference-Dependent Model: A Laboratory Search Experiment," IZA Discussion Papers 12378, Institute of Labor Economics (IZA).
    4. Gil-Lacruz, Ana I. & Gil-Lacruz, Marta, 2011. "Internal Inconsistency and Risk Aversion: Implications on Smoking Decisions/Consistencia interna y aversión al riesgo: implicaciones en la decisión de fumar," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 29, pages 387(18á.)-3, Abril.
    5. Arnaud Reynaud & Stéphane Couture, 2012. "Stability of risk preference measures: results from a field experiment on French farmers," Theory and Decision, Springer, vol. 73(2), pages 203-221, August.
    6. Schunk, Daniel, 2005. "Search behaviour with reference point preferences : theory and experimental evidence," Papers 05-12, Sonderforschungsbreich 504.
    7. Inukai, Keigo & Kawata, Keisuke & Sasaki, Masaru, 2017. "Committee Search with Ex-ante Heterogeneous Agents: Theory and Experimental Evidence," IZA Discussion Papers 10760, Institute of Labor Economics (IZA).
    8. Imen Bouhlel & Michela Chessa & Agnès Festré & Eric Guerci, 2019. "When to Stop? A Theoretical and Experimental Investigation of an Individual Search Task," GREDEG Working Papers 2019-40, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    9. Hizen, Yoichi & Kawata, Keisuke & Sasaki, Masaru, 2013. "An experimental test of a committee search model," European Economic Review, Elsevier, vol. 61(C), pages 59-76.
    10. Börsch-Supan, Axel & Coppola, Michela & Reil-Held, Anette, 1970. "Riester Pensions in Germany: Design, Dynamics, Targetting Success and Crowding-In," MEA discussion paper series 201220, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    11. Vincent Mak & Darryl A. Seale & Amnon Rapoport & Eyran J. Gisches, 2019. "Voting Rules in Sequential Search by Committees: Theory and Experiments," Management Science, INFORMS, vol. 65(9), pages 4349-4364, September.
    12. Fu, Jingcheng & Sefton, Martin & Upward, Richard, 2019. "Social comparisons in job search," Journal of Economic Behavior & Organization, Elsevier, vol. 168(C), pages 338-361.
    13. Therese Grijalva & Jayson Lusk & W. Shaw, 2014. "Discounting the Distant Future: An Experimental Investigation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 59(1), pages 39-63, September.
    14. Daniela Cagno & Tibor Neugebauer & Carlos Rodriguez-Palmero & Abdolkarim Sadrieh, 2014. "Recall searching with and without recall," Theory and Decision, Springer, vol. 77(3), pages 297-311, October.
    15. Schunk, Daniel, 2009. "Behavioral heterogeneity in dynamic search situations: Theory and experimental evidence," Journal of Economic Dynamics and Control, Elsevier, vol. 33(9), pages 1719-1738, September.
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    17. Charness, Gary & Kuhn, Peter, 2011. "Lab Labor: What Can Labor Economists Learn from the Lab?," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 3, pages 229-330, Elsevier.
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    20. Goecke, Henry & Luhan, Wolfgang J. & Roos, Michael W.M., 2013. "Rational inattentiveness in a forecasting experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 94(C), pages 80-89.
    21. Yuta KITTAKA & Ryo MIKAMI, 2020. "Consumer Search and Stock-out: A Laboratory Experiment," ISER Discussion Paper 1104, Institute of Social and Economic Research, Osaka University.
    22. Takao Asano & Hiroko Okudaira & Masaru Sasaki, 2015. "An Experimental Test of a Search Model under Ambiguity," KIER Working Papers 913, Kyoto University, Institute of Economic Research.

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    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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