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Testing independence conditions in the presence of errors and splitting effects

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  • Birnbaum, Michael H.
  • Schmidt, Ulrich
  • Schneider, Miriam D.

Abstract

This paper presents an experimental test of several independence conditions implied by expected utility and alternative models. We perform a repeated choice experiment and fit an error model that allows us to discriminate between true violations of independence and those that can be attributed to errors. In order to investigate the role of event splitting effects, we present each choice problem not only in coalesced form (as in most previous studies) but also in split form. It turns out previously reported violations of independence and splitting effects remain significant even when controlling for errors. Splitting effects have a substantial influence on the tests of independence conditions. When choices are presented in canonical split form, in which probabilities on corresponding probability-consequence ranked branches are equal, violations of the independence conditions we tested become either reversed, insignificant or unsystematic.

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  • Birnbaum, Michael H. & Schmidt, Ulrich & Schneider, Miriam D., 2010. "Testing independence conditions in the presence of errors and splitting effects," Kiel Working Papers 1614, Kiel Institute for the World Economy (IfW Kiel).
  • Handle: RePEc:zbw:ifwkwp:1614
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    2. Adrian Bruhin & Maha Manai & Luis Santos-Pinto, 2019. "Risk and Rationality:The Relative Importance of Probability Weighting and Choice Set Dependence," Cahiers de Recherches Economiques du Département d'économie 19.01new, Université de Lausanne, Faculté des HEC, Département d’économie.
    3. Michael H. Birnbaum & Lucy Wan, 2020. "MARTER: Markov True and Error model of drifting parameters," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 15(1), pages 47-73, January.
    4. Meng, Jingyi & Webb, Craig S. & Zank, Horst, 2024. "Mixture independence foundations for expected utility," Journal of Mathematical Economics, Elsevier, vol. 111(C).
    5. Andreas Glöckner & Baiba Renerte & Ulrich Schmidt, 2020. "Violations of coalescing in parametric utility measurement," Theory and Decision, Springer, vol. 89(4), pages 471-501, November.
    6. Adrian Bruhin & Maha Manai & Luis Santos-Pinto, 2018. "Risk and Rationality:The Relative Importance of Probability Weighting and Choice Set Dependence," Cahiers de Recherches Economiques du Département d'économie 18.04, Université de Lausanne, Faculté des HEC, Département d’économie.
    7. Michael D. Lee, 2018. "Bayesian methods for analyzing true-and-error models," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 13(6), pages 622-635, November.
    8. repec:cup:judgdm:v:13:y:2018:i:5:p:428-440 is not listed on IDEAS
    9. Wakker, Peter P., 2023. "A criticism of Bernheim & Sprenger's (2020) tests of rank dependence," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 107(C).
    10. repec:cup:judgdm:v:13:y:2018:i:6:p:622-635 is not listed on IDEAS
    11. Michael H. Birnbaum & Edika G. Quispe-Torreblanca, 2018. "TEMAP2.R: True and Error model analysis program in R," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 13(5), pages 428-440, September.
    12. Michael H. Birnbaum, 2019. "Bayesian and frequentist analysis of True and Error models," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 14(5), pages 608-616, September.
    13. repec:cup:judgdm:v:14:y:2019:i:5:p:608-616 is not listed on IDEAS
    14. repec:cup:judgdm:v:15:y:2020:i:1:p:47-73 is not listed on IDEAS
    15. Pavlo Blavatskyy & Valentyn Panchenko & Andreas Ortmann, 2023. "How common is the common-ratio effect?," Experimental Economics, Springer;Economic Science Association, vol. 26(2), pages 253-272, April.

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    More about this item

    Keywords

    Independence axiom; splitting effects; coalescing; errors; experiment;
    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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