Paul Goldsmith-Pinkham, Peter Hull, Michal Kolesár
arXiv 5 Nov 2025 · Econometrics · 2 citations (OpenAlex)
arXiv:2511.03572 · PDF · DOI · OpenAlex · Extracted main text
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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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Farre-Mensa, Joan, Hegde, Deepak, Ljungqvist, Alexander (2020) What Is a Patent Worth? Evidence from the U.S. Patent “Lottery” | 1.000 | 15 | 4 | 100% |
| 2 | Imbens, Guido W., Angrist, Joshua D (1994) Identification and Estimation of Local Average Treatment Effects | 0.961 | 9 | 5 | 89% |
| 3 | Frandsen, Brigham, Lefgren, Lars, Leslie, Emily (2023) Judging Judge Fixed Effects | 0.941 | 6 | 3 | 83% |
| 4 | Kolesár, Michal (2013) Estimation in an Instrumental Variables Model With Treatment Effect Heterogeneity self | 0.928 | 4 | 3 | 100% |
| 5 | Mikusheva, Anna, Sun, Liyang (2022) Inference with Many Weak Instruments | 0.811 | 4 | 2 | 100% |
| 6 | Kitagawa, Toru (2015) A Test for Instrument Validity | 0.811 | 4 | 2 | 100% |
| 7 | Abadie, Alberto (2002) Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models | 0.737 | 3 | 2 | 100% |
| 8 | Bekker, Paul A (1994) Alternative Approximations to the Distributions of Instrumental Variable Estimators | 0.693 | 6 | 3 | 33% |
| 9 | Yap, Luther (2025) Inference with Many Weak Instruments and Heterogeneity | 0.644 | 4 | 1 | 100% |
| 10 | Angrist, Joshua, Kolesár, Michal (2024) One Instrument to Rule Them All: The Bias and Coverage of Just-ID IV self | 0.644 | 3 | 2 | 67% |
Showing the top 10 of 57 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Cluster-Robust Inference for Quadratic Forms | 0.644 | 2 | 2 |
| 2 | A Practical Guide to Instrumental Variables Methods with Heterogeneous Treatment Effects | 0.644 | 2 | 2 |
| 3 | Representativeness and Efficiency in Overidentified IV | 0.405 | 1 | 1 |
| 4 | Inference on the TSLS Estimand with Weak Instruments and Treatment Effect Heterogeneity | 0.405 | 1 | 1 |