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Bayes Factors with an Application to Experimental Economics

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  • Gary Bolton
  • Duncan Fong
  • Paul Mosquin

Abstract

We describe Bayes factor, an explicit measure of the strength of the evidence, the extent to which the data increase or decrease the odds a given hypothesis or model is true. Issues and techniques for deriving a Bayes factor are outlined. We illustrate the technique with data from an ultimatum game experiment that looked for an experimenter observation effect. We show that the evidence increases the odds of an effect, but not by enough to convince someone with a skeptical prior. Copyright Kluwer Academic Publishers 2003

Suggested Citation

  • Gary Bolton & Duncan Fong & Paul Mosquin, 2003. "Bayes Factors with an Application to Experimental Economics," Experimental Economics, Springer;Economic Science Association, vol. 6(3), pages 311-325, November.
    • Handle: RePEc:kap:expeco:v:6:y:2003:i:3:p:311-325
    DOI: 10.1023/A:1026281504189
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    References listed on IDEAS

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    8. Fong, Duncan K H & Bolton, Gary E, 1997. "Analyzing Ultimatum Bargaining: A Bayesian Approach to the Comparison of Two Potency Curves under Shape Constraints," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 335-344, July.
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    2. Duncan Fong & Wayne DeSarbo & Zhe Chen & Zhuying Xu, 2015. "A Bayesian Vector Multidimensional Scaling Procedure Incorporating Dimension Reparameterization with Variable Selection," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 1043-1065, December.
    3. Rolando Gonzales Martínez & Gabriela Aguilera‐Lizarazu & Andrea Rojas‐Hosse & Patricia Aranda Blanco, 2020. "The interaction effect of gender and ethnicity in loan approval: A Bayesian estimation with data from a laboratory field experiment," Review of Development Economics, Wiley Blackwell, vol. 24(3), pages 726-749, August.

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