A Sharp Test for the Judge Leniency Design

Mohamed Coulibaly, Yu-Chin Hsu, Ismael Mourifie and Yuanyuan Wan

Working Papers from University of Toronto, Department of Economics

Abstract: We propose a new specification test to assess the validity of the judge leniency design. We characterize a set of sharp testable implications, which exploit all the relevant information in the observed data distribution to detect violations of the judge leniency design assumptions. The proposed sharp test is asymptotically valid and consistent and will not make discordant recommendations. When the judge's leniency design assumptions are rejected, we propose a way to salvage the model using partial monotonicity and exclusion assumptions, under which a variant of the Local Instrumental Variable (LIV) estimand can recover the Marginal Treatment Effect. Simulation studies show our test outperforms existing non-sharp tests by significant margins. We apply our test to assess the validity of the judge leniency design using data from Stevenson (2018), and it rejects the validity for three crime categories: robbery, drug selling, and drug possession.

Keywords: Judge Leniency Design; Instrumental Variables; Specification Test; Moment Inequalities. (search for similar items in EconPapers)
JEL-codes: C12 C14 C21 C26 (search for similar items in EconPapers)
Pages: Unknown pages
Date: 2024-04-19
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Related works:
Working Paper: A Sharp Test for the Judge Leniency Design (2024)
Working Paper: A Sharp Test for the Judge Leniency Design (2024)
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