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Lottery pricing under time pressure

Author

Listed:
  • Pavlo R. Blavatskyy
  • Wolfgang R. K�hler

Abstract

This paper investigates how subjects determine minimum selling prices for lotteries. We design an experiment where subjects have at every moment an incentive to state their minimum selling price and to adjust the price if they believe that the price that they stated initially was not optimal. We observe frequent and sizeable price adjustments. We find that random pricing models can not explain the observed price patterns. We show that earlier prices contain information about future price adjustments. We propose a model of Stochastic Pricing that offers an intuitive explanation for these price adjustment patterns.

Suggested Citation

  • Pavlo R. Blavatskyy & Wolfgang R. K�hler, 2009. "Lottery pricing under time pressure," IEW - Working Papers 422, Institute for Empirical Research in Economics - University of Zurich.
    • Handle: RePEc:zur:iewwpx:422
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    File URL: https://www.zora.uzh.ch/id/eprint/51874/1/iewwp422.pdf
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    References listed on IDEAS

    as
    1. Pavlo Blavatskyy & Wolfgang Köhler, 2009. "Range effects and lottery pricing," Experimental Economics, Springer;Economic Science Association, vol. 12(3), pages 332-349, September.
    2. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
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    Cited by:

    1. Ulrich Schmidt & Stefan Trautmann, 2014. "Common consequence effects in pricing and choice," Theory and Decision, Springer, vol. 76(1), pages 1-7, January.

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    More about this item

    Keywords

    Time pressure; certainty equivalent; experiment; stochastic; Becker-DeGroot- Marschak (BDM) method;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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