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宽大处理设计:操作手册

Leniency Designs: An Operator's Manual
Journal of Economic Perspectives · 2026 · Paul S. Goldsmith-Pinkham、Peter Hull、Michal Kolesár

中文摘要

我们借鉴近期计量经济学文献,为宽大处理(亦称法官或审查员工具)设计提供了一份逐步指南。无偏折刀工具变量估计量(UJIVE)专为利用外生宽大处理变异而构建,即使在存在众多决策者或控制变量的情况下,也能避免微妙的偏误。我们展示了UJIVE如何还可用于评估宽大处理设计赖以成立的关键假设,包括准随机分配与平均第一阶段单调性,并探究处理效应估计的外部有效性。我们进一步讨论了统计推断,认为非聚类标准误往往是合适的。对Farre-Mensa等(2020)的再分析——该研究利用准随机审查员分配来估计专利对初创企业的价值——说明了我们的核查清单。

Abstract

We develop a step-by-step guide to leniency (a.k.a. judge or examiner instrument) designs, drawing on recent econometric literatures. The unbiased jackknife instrumental variables estimator (UJIVE) is purpose-built for leveraging exogenous leniency variation, avoiding subtle biases even in the presence of many decision-makers or controls. We show how UJIVE can also be used to assess key assumptions underlying leniency designs, including quasi-random assignment and average first-stage monotonicity, and to probe the external validity of treatment effect estimates. We further discuss statistical inference, arguing that non-clustered standard errors are often appropriate. A reanalysis of Farre-Mensa et al. (2020), using quasi-random examiner assignment to estimate the value of patents to startups, illustrates our checklist.
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