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What is your level of overconfidence? A strictly incentive compatible measurement of absolute and relative overconfidence

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  • D. Urbig
  • J. Stauf
  • G.U. Weitzel

Abstract

This study contributes to the ongoing discussion on the appropriate measurement of overconfidence, in particular, its strictly incentive compatible measurement in experiments. Despite a number of significant advances in recent research, several important issues remain to be solved. These relate to the strictness of incentive compatibility, the identification of well-calibrated participants, the trichotomous classification into over- or underconfident and well-calibrated participants, and the generalization to measuring beliefs about the performance relative to other people. This paper develops a measurement of overconfidence that is improved regarding all four of these issues. We theoretically prove that our method is strictly incentive compatible and robust to risk attitudes within the framework of Cumulative Prospect Theory. Furthermore, our method allows the measurement of various levels of overconfidence and the direct comparison of absolute and relative confidence. We tested our method, and the results meet our expectations, replicate recent results, and show that a population can be simultaneously overconfident, well-calibrated, and underconfident. In our specific case, we find that more than ninety-five percent of the population believe to be better than twenty-five percent; about fifty percent believe to be better than fifty percent; and only seven percent believe to be better than seventy-five percent.

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File URL: http://dspace.library.uu.nl/bitstream/handle/1874/36720/09-20.pdf
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Bibliographic Info

Paper provided by Utrecht School of Economics in its series Working Papers with number 09-20.

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Length: 40 pages
Date of creation: 2009
Date of revision:
Handle: RePEc:use:tkiwps:0920

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Keywords: Belief elicitation; Overconfidence; Better than average; Incentive compatibility;

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References

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  1. Jinkwon Lee, 2008. "The effect of the background risk in a simple chance improving decision model," Journal of Risk and Uncertainty, Springer, vol. 36(1), pages 19-41, February.
  2. Selten,Reinhard & Mitzkewitz,Michael & Uhlich,Gerald, . "Duopoly strategies programmed by experienced players," Discussion Paper Serie B 106, University of Bonn, Germany.
  3. Peter Wakker & Daniel Deneffe, 1996. "Eliciting von Neumann-Morgenstern Utilities When Probabilities Are Distorted or Unknown," Management Science, INFORMS, vol. 42(8), pages 1131-1150, August.
  4. Mohammed Abdellaoui & Frank Vossmann & Martin Weber, 2005. "Choice-Based Elicitation and Decomposition of Decision Weights for Gains and Losses Under Uncertainty," Management Science, INFORMS, vol. 51(9), pages 1384-1399, September.
  5. Thomas Dohmen & Armin Falk & David Huffman & Uwe Sunde & Juergen Schupp & Gert Wagner, 2005. "Individual Risk Attitudes: New Evidence from a Large, Representative, Experimentally-Validated Survey," Working Papers 2096, The Field Experiments Website.
  6. Marion Eberlein & Sandra Ludwig & Julia Nafziger, 2011. "The Effects Of Feedback On Self‐Assessment," Bulletin of Economic Research, Wiley Blackwell, vol. 63(2), pages 177-199, 04.
  7. Dan Lovallo & Colin Camerer, 1999. "Overconfidence and Excess Entry: An Experimental Approach," American Economic Review, American Economic Association, vol. 89(1), pages 306-318, March.
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Cited by:
  1. Sandra Ludwig & Julia Nafziger, 2011. "Beliefs about overconfidence," Theory and Decision, Springer, vol. 70(4), pages 475-500, April.
  2. Koellinger, Ph.D. & Treffers, T., 2012. "Joy leads to Overconfidence, and a Simple Remedy," ERIM Report Series Research in Management ERS-2012-001-STR, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  3. Zahra Murad & Chris Starmer & Martin Sefton, . "How do risk attitudes affect measured confidence?," Discussion Papers 2014-05, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.

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