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Who Really Wants to be a Millionaire? Estimates of Risk Aversion from Gameshow Data

Author

Listed:
  • Gauthier Lanot

    (Keele University, Centre for Economic Research and School of Economic and Management Studies)

  • Roger Hartley

    (Department of Economics, University of Manchester)

  • Ian Walker

    (Department of Economics, University of Warwick, Coventry CV4 7AL, UK.)

Abstract

This paper analyses the behaviour of TV gameshow contestants to estimate risk aversion. We are able to show that the gameshow participants are broadly representative of the population as a whole. The gameshow has a number of features that makes it well suited for our analysis: the format is extremely straightforward, it involves no strategic decision-making, we have a large number of observations, and the prizes are cash and paid immediately, and cover a large range - from £100 up to £1 million. Even though the CRRA model is extremely restrictive we find that a coefficient or relative risk aversion which is close to unity fits the data across a wide range of wealth remarkably well.

Suggested Citation

  • Gauthier Lanot & Roger Hartley & Ian Walker, 2006. "Who Really Wants to be a Millionaire? Estimates of Risk Aversion from Gameshow Data," Keele Economics Research Papers KERP 2006/07, Centre for Economic Research, Keele University.
    • Handle: RePEc:kee:kerpuk:2006/07
    Note: We are grateful to Celador PLC, the gameshow's creator and the UK production company, for their help with gathering the data, and their permission to use it. We are particularly grateful to Ruth Settle who provided detailed advice that helped our understanding of the game. The research was supported by grant R000239740 from the Economic and Social Research Council. However, the views expressed herein are those of the authors alone. The data used in the analysis, and the GAUSS programs developed to conduct the estimation, can be obtained from g.lanot@econ.keele.ac.uk.
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    Keywords

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    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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