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

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  • Schunk, Daniel
  • Winter, Joachim

Abstract

Experimental studies of search behavior suggest that individuals stop searching earlier than predicted by the optimal, risk-neutral stopping rule. Such behavior could be generated by two different classes of decision rules: rules that are optimal conditional on utility functions departing from risk neutrality, or heuristics derived from limited cognitive processing capacities and satisfycing. To discriminate among these two possibilities, we conduct an experiment that consists of a standard search task as well as a lottery task designed to elicit utility functions. We find that search heuristics are not related to measures of risk aversion, but to measures of loss aversion.

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Bibliographic Info

Paper provided by University of Munich, Department of Economics in its series Discussion Papers in Economics with number 1377.

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Date of creation: Feb 2007
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Handle: RePEc:lmu:muenec:1377

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Keywords: search; heuristics; utility function elicitation; risk attitudes; prospect theory;

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Citations

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Cited by:
  1. Arnaud Reynaud & Stephane Couture, 2010. "Stability of Risk Preference Measures: Results From a Field Experiment on French Farmers," LERNA Working Papers 10.10.316, LERNA, University of Toulouse.
  2. Eriksson, Kimmo & Strimling, Pontus, 2010. "The devil is in the details: Incorrect intuitions in optimal search," Journal of Economic Behavior & Organization, Elsevier, vol. 75(2), pages 338-347, August.
  3. 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.
  4. Charness, Gary & Kuhn, Peter, 2011. "Lab Labor: What Can Labor Economists Learn from the Lab?," Handbook of Labor Economics, Elsevier.
  5. 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 Economía Aplicada, Estudios de Economía Aplicada, vol. 29, pages 387 (18 pá, Abril.
  6. 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.
  7. 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.
  8. Ibanez, Marcela & Czermak, Simon & Sutter, Matthias, 2008. "Searching for a better deal - on the influence of group decision making, time pressure and gender in a search experiment," Working Papers in Economics 296, University of Gothenburg, Department of Economics.
  9. Franz Rothlauf & Daniel Schunk & Jella Pfeiffer, 2005. "Classification of Human Decision Behavior: Finding Modular Decision Rules with Genetic Algorithms," MEA discussion paper series 05079, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
  10. Daniela Di Cagno & Tibor Neugebauer & Carlos Rodriguez-Palmero & Abdolkarim Sadrieh, 2014. "Recall Searching with and without Recall," Working Papers 2014/14, Economics Department, Universitat Jaume I, Castellón (Spain).

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