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Errors and monotonicity in judicial decision-making

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  • Bhuller, Manudeep
  • Sigstad, Henrik

Abstract

Recent literature raises concerns about monotonicity conditions required to interpret IV estimates under heterogeneous effects. A prominent example involves random decision-maker IV designs where decision-makers exhibit systematic differences in both preferences and skills. We develop tests of monotonicity in the context of judicial decision-making using proxies of judicial errors based on appeals and reversals of trial decisions from Norwegian court records. Our tests fail to reject average monotonicity. This suggests that differences in stringencies across judges are not sufficiently driven by skills to raise concerns about the validity of the random judge IV literature.

Suggested Citation

  • Bhuller, Manudeep & Sigstad, Henrik, 2022. "Errors and monotonicity in judicial decision-making," Economics Letters, Elsevier, vol. 215(C).
    • Handle: RePEc:eee:ecolet:v:215:y:2022:i:c:s0165176522001203
    DOI: 10.1016/j.econlet.2022.110486
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    References listed on IDEAS

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    1. Manudeep Bhuller & Gordon B. Dahl & Katrine V. Løken & Magne Mogstad, 2020. "Incarceration, Recidivism, and Employment," Journal of Political Economy, University of Chicago Press, vol. 128(4), pages 1269-1324.
    2. Brigham Frandsen & Lars Lefgren & Emily Leslie, 2023. "Judging Judge Fixed Effects," American Economic Review, American Economic Association, vol. 113(1), pages 253-277, January.
    3. Samuel Norris & Matthew Pecenco & Jeffrey Weaver, 2021. "The Effects of Parental and Sibling Incarceration: Evidence from Ohio," American Economic Review, American Economic Association, vol. 111(9), pages 2926-2963, September.
    4. Will Dobbie & Jacob Goldin & Crystal S. Yang, 2018. "The Effects of Pretrial Detention on Conviction, Future Crime, and Employment: Evidence from Randomly Assigned Judges," American Economic Review, American Economic Association, vol. 108(2), pages 201-240, February.
    5. Rafael Di Tella & Ernesto Schargrodsky, 2013. "Criminal Recidivism after Prison and Electronic Monitoring," Journal of Political Economy, University of Chicago Press, vol. 121(1), pages 28-73.
    6. Anna Aizer & Joseph J. Doyle, 2015. "Juvenile Incarceration, Human Capital, and Future Crime: Evidence from Randomly Assigned Judges," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(2), pages 759-803.
    7. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    8. Jeffrey R. Kling, 2006. "Incarceration Length, Employment, and Earnings," American Economic Review, American Economic Association, vol. 96(3), pages 863-876, June.
    9. Ozkan Eren & Naci Mocan, 2021. "Juvenile Punishment, High School Graduation, and Adult Crime: Evidence from Idiosyncratic Judge Harshness," The Review of Economics and Statistics, MIT Press, vol. 103(1), pages 34-47, March.
    10. Edward Vytlacil, 2002. "Independence, Monotonicity, and Latent Index Models: An Equivalence Result," Econometrica, Econometric Society, vol. 70(1), pages 331-341, January.
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    Cited by:

    1. Alexeev, Sergey & Weatherburn, Don, 2022. "Fines for illicit drug use do not prevent future crime: evidence from randomly assigned judges," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 555-575.

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    More about this item

    Keywords

    Monotonicity; Errors; Random decision-maker design;
    All these keywords.

    JEL classification:

    • K40 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - General
    • K14 - Law and Economics - - Basic Areas of Law - - - Criminal Law
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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