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Crime and Mismeasured Punishment: Marginal Treatment Effect with Misclassification

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  • Vitor Possebom

Abstract

I partially identify the marginal treatment effect (MTE) when the treatment is misclassified. I explore two restrictions, allowing for dependence between the instrument and the misclassification decision. If the signs of the derivatives of the propensity scores are equal, I identify the MTE sign. If those derivatives are similar, I bound the MTE. To illustrate, I analyze the impact of alternative sentences (fines and community service v. no punishment) on recidivism in Brazil, where Appeals processes generate misclassification. The estimated misclassification bias may be as large as 10% of the largest possible MTE, and the bounds contain the correctly estimated MTE.

Suggested Citation

  • Vitor Possebom, 2021. "Crime and Mismeasured Punishment: Marginal Treatment Effect with Misclassification," Papers 2106.00536, arXiv.org, revised Jul 2023.
  • Handle: RePEc:arx:papers:2106.00536
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    2. Santiago Acerenza, 2021. "Partial Identification of Marginal Treatment Effects with discrete instruments and misreported treatment," Papers 2110.06285, arXiv.org, revised Mar 2023.

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