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Risk and punishment revisited Errors in variables and in the lab

Author

Listed:
  • Christoph Engel

    (MPI for Research on Collective Goods, Bonn)

  • Oliver Kirchkamp

    (School of Economics and Business Administration, Friedrich-Schiller-University Jena)

Abstract

We provide an example for an errors in variables problem which might be often neglected but which is quite common in lab experimental practice: In one task, attitude towards risk is measured, in another task participants behave in a way that can possibly be explained by their risk attitude. How should we deal with inconsistent behaviour in the risk task? Ignoring these observations entails two biases: An errors in variables bias and a selection bias. We argue that inconsistent observations should be exploited to address the errors in variables problem, which can easily be done within a Bayesian framework.

Suggested Citation

  • Christoph Engel & Oliver Kirchkamp, 2016. "Risk and punishment revisited Errors in variables and in the lab," Jena Economics Research Papers 2016-015, Friedrich-Schiller-University Jena.
    • Handle: RePEc:jrp:jrpwrp:2016-015
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    References listed on IDEAS

    as
    1. Maria Montero & Martin Sefton & Ping Zhang, 2008. "Enlargement and the balance of power: an experimental study," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 30(1), pages 69-87, January.
    2. Engel, Christoph, 2014. "Social preferences can make imperfect sanctions work: Evidence from a public good experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 108(C), pages 343-353.
    3. Catherine C. Eckel & Philip J. Grossman, 2008. "Forecasting Risk Attitudes: An Experimental Study Using Actual and Forecast Gamble Choices," Monash Economics Working Papers archive-01, Monash University, Department of Economics.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Risk; lab experiment; public good; errors in variables; Bayesian inference;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • L41 - Industrial Organization - - Antitrust Issues and Policies - - - Monopolization; Horizontal Anticompetitive Practices

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