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Incentive-Compatible Elicitation of Quantiles

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  • Kiefer, Nicholas M.

    (Cornell University)

Abstract

Incorporation of expert information in inference or decision settings is often important, especially in cases where data are unavailable, costly or unreliable. One approach is to elicit prior quantiles from an expert and then to fit these to a statistical distribution and proceed according to Bayes rule. An incentive-compatible elicitation method using an external randomization is available.

Suggested Citation

  • Kiefer, Nicholas M., 2009. "Incentive-Compatible Elicitation of Quantiles," Working Papers 09-13, Cornell University, Center for Analytic Economics.
    • Handle: RePEc:ecl:corcae:09-13
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    File URL: https://cae.economics.cornell.edu/09-13.pdf
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    References listed on IDEAS

    as
    1. Kiefer, Nicholas M., 2009. "Default estimation for low-default portfolios," Journal of Empirical Finance, Elsevier, vol. 16(1), pages 164-173, January.
    2. Edi Karni, 2009. "A Mechanism for Eliciting Probabilities," Econometrica, Econometric Society, vol. 77(2), pages 603-606, March.
    3. Kiefer, Nicholas M., 2010. "Default Estimation and Expert Information," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 320-328.
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