Jung Hyub Lee
arXiv 16 Sep 2026 · Econometrics
arXiv:2609.18150 · PDF · Extracted main text
Instrumental variable analyses often rely on the assumption that instruments affect the outcome only through the endogenous regressor. In many applications, researchers can defend only a plausible range for direct effects of instruments, while conventional sensitivity analyses may be unreliable when instruments are weak. This paper proposes the profiled Anderson--Rubin (pAR) test, which considers all direct effects within a prespecified range and retains a candidate effect whenever at least one admissible direct effect is consistent with the data. Under the maintained sampling assumptions, the procedure controls false rejection for each compatible candidate without requiring strong instruments. The paper provides practical methods for constructing confidence sets and distinguishes substantive bounds from bounds tied to the realized instrument design. Simulations and applications to retirement saving and returns to schooling show that the procedure resembles conventional sensitivity analysis when instruments are strong but preserves substantially more uncertainty when identification is weak.
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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 | Angrist, Joshua D and Krueger, Alan B (1991) Does compulsory school attendance affect schooling and earnings? | 0.737 | 3 | 2 | 100% |
| 2 | Masten, Matthew A and Poirier, Alexandre (2021) Salvaging falsified instrumental variable models | 0.737 | 3 | 2 | 100% |
| 3 | Moreira, Marcelo J (2003) A conditional likelihood ratio test for structural models | 0.737 | 3 | 2 | 100% |
| 4 | Bound, John and Jaeger, David A and Baker, Regina M (1995) Problems with instrumental variables estimation when the correlation between the instruments and the endogenous explanatory vari… | 0.644 | 2 | 2 | 100% |
| 5 | Kleibergen, Frank (2002) Pivotal statistics for testing structural parameters in instrumental variables regression | 0.644 | 2 | 2 | 100% |
| 6 | Mikusheva, Anna (2010) Robust confidence sets in the presence of weak instruments | 0.644 | 2 | 2 | 100% |
| 7 | Moreira, Marcelo J (2009) Tests with correct size when instruments can be arbitrarily weak | 0.644 | 2 | 2 | 100% |
| 8 | Anderson, Theodore W and Rubin, Herman (1949) Estimation of the parameters of a single equation in a complete system of stochastic equations | 0.405 | 1 | 1 | 100% |
| 9 | Apfel, Nicolas (2024) Relaxing the exclusion restriction in shift-share instrumental variable estimation | 0.405 | 1 | 1 | 100% |
| 10 | Bound, John and Jaeger, David A (1996) On the Validity of Season of Birth as an Instrument in Wage Equations: A Comment on Angrist & Krueger's" Does Compulsory School… | 0.405 | 1 | 1 | 100% |
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