A Sharp Test for the Judge Leniency Design

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

No 32456, NBER Working Papers from National Bureau of Economic Research, Inc

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.

JEL-codes: C1 C12 C18 C26 (search for similar items in EconPapers)
Date: 2024-05
New Economics Papers: this item is included in nep-ecm and nep-ind
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Citations: View citations in EconPapers (1)

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Working Paper: A Sharp Test for the Judge Leniency Design (2025)
Working Paper: A Sharp Test for the Judge Leniency Design (2024)
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