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Information Acquisition and the Exclusion of Evidence in Trials

Author

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  • Benjamin Lester
  • Nicola Persico
  • Ludo Visschers

Abstract

A peculiar principle of legal evidence in common law systems is that probative evidence may be excluded in order to increase the accuracy of fact-finding. A formal model is provided that rationalizes this principle. The key assumption is that the fact-finders (jurors) have a cognitive cost of processing evidence. Within this framework, the judge excludes evidence in order to incentivize the jury to focus on other, more probative evidence. Our analysis sheds light on two distinctive characteristics of this type of exclusionary rules. First, that broad exclusionary powers are delegated to the judge. Second, that exclusion on grounds of undue prejudice is peculiar to common law systems. Both features arise in our model. The Author 2009. Published by Oxford University Press on behalf of Yale University. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

Suggested Citation

  • Benjamin Lester & Nicola Persico & Ludo Visschers, 2012. "Information Acquisition and the Exclusion of Evidence in Trials," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 28(1), pages 163-182.
    • Handle: RePEc:oup:jleorg:v:28:y::i:1:p:163-182
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    File URL: http://hdl.handle.net/10.1093/jleo/ewp040
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    Citations

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    Cited by:

    1. Dhammika Dharmapala & Thomas J. Miceli, 2013. "Search, seizure and false (?) arrest: an analysis of fourth amendment remedies when police can plant evidence," Chapters, in: Thomas J. Miceli & Matthew J. Baker (ed.), Research Handbook on Economic Models of Law, chapter 11, pages 208-234, Edward Elgar Publishing.
    2. Taneva, Ina A, 2015. "Information Design," SIRE Discussion Papers 2015-50, Scottish Institute for Research in Economics (SIRE).
    3. Aditya Kuvalekar & João Ramos & Johannes Schneider, 2023. "The wrong kind of information," RAND Journal of Economics, RAND Corporation, vol. 54(2), pages 360-384, June.
    4. Jesse Bull & Joel Watson, 2019. "Statistical evidence and the problem of robust litigation," RAND Journal of Economics, RAND Corporation, vol. 50(4), pages 974-1003, December.
    5. Lipnowski, Elliot & Mathevet, Laurent & Wei, Dong, 2022. "Optimal attention management: A tractable framework," Games and Economic Behavior, Elsevier, vol. 133(C), pages 170-180.
    6. Taneva, Ina A, 2015. "Information Design," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-50, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Ina Taneva, 2019. "Information Design," American Economic Journal: Microeconomics, American Economic Association, vol. 11(4), pages 151-185, November.
    8. Aditya Kuvalekar & Jo~ao Ramos & Johannes Schneider, 2021. "The Wrong Kind of Information," Papers 2111.04172, arXiv.org, revised Jun 2022.
    9. Lundberg, Alexander & Mungan, Murat, 2022. "The effect of evidentiary rules on conviction rates," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 563-576.

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