Apoorva Lal, Mac Lockhart, Yiqing Xu, Ziwen Zu
arXiv 20 Mar 2023 · Econometrics · 26 citations (OpenAlex)
arXiv:2303.11399 · PDF · DOI · OpenAlex · Extracted main text
Instrumental variable (IV) strategies are widely used in political science to establish causal relationships. However, the identifying assumptions required by an IV design are demanding, and it remains challenging for researchers to assess their validity. In this paper, we replicate 67 papers published in three top journals in political science during 2010-2022 and identify several troubling patterns. First, researchers often overestimate the strength of their IVs due to non-i.i.d. errors, such as a clustering structure. Second, the most commonly used t-test for the two-stage-least-squares (2SLS) estimates often severely underestimates uncertainty. Using more robust inferential methods, we find that around 19-30% of the 2SLS estimates in our sample are underpowered. Third, in the majority of the replicated studies, the 2SLS estimates are much larger than the ordinary-least-squares estimates, and their ratio is negatively correlated with the strength of the IVs in studies where the IVs are not experimentally generated, suggesting potential violations of unconfoundedness or the exclusion restriction. To help researchers avoid these pitfalls, we provide a checklist for better practice.
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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 | Young, Alwyn (2022) Consistency without Inference: Instrumental Variables in Practical Application | 0.874 | 7 | 2 | 100% |
| 2 | Lee, David S, McCrary, Justin, Moreira, Marcelo J, Porter, Jack (2022) Valid t-ratio Inference for IV | 0.874 | 5 | 2 | 100% |
| 3 | Sovey, Allison J, Green, Donald P (2011) Instrumental Variables Estimation in Political Science: A Readers' Guide | 0.874 | 5 | 2 | 100% |
| 4 | Olea, Carolin (2013) A Robust Test for Weak Instruments | 0.737 | 3 | 2 | 100% |
| 5 | Felton, Chris, Stewart, Brandon M (2022) Handle with Care: A Sociologist's Guide to Causal Inference with Instrumental Variables | 0.644 | 2 | 2 | 100% |
| 6 | Andrews, Isaiah, Stock, James H., Sun, Liyang (2019) Weak Instruments in Instrumental Variables Regression: Theory and Practice | 0.644 | 2 | 2 | 100% |
| 7 | Cinelli, Carlos, Hazlett, Chad (2022) An Omitted Variable Bias Framework for Sensitivity Analysis of Instrumental Variables | 0.644 | 2 | 2 | 100% |
| 8 | Jiang, Wei (2017) Have Instrumental Variables Brought Us Closer to the Truth | 0.644 | 2 | 2 | 100% |
| 9 | Mellon, Jonathan (2023) Rain, Rain, Go Away: 195 Potential Exclusion-restriction Violations for Studies using Weather as an Instrumental Variable | 0.644 | 2 | 2 | 100% |
| 10 | Staiger, Douglas, Stock, James H (1997) Instrumental Variables Regression with Weak Instruments | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 66 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Resistant Inference in Instrumental Variable Models | 0.405 | 1 | 1 |