Deborah Kim
arXiv 10 Aug 2026 · Econometrics
arXiv:2608.10294 · PDF · Extracted main text
This article considers the problem of testing sign agreement among a finite number of parameters. This problem arises in empirical settings such as detecting treatment effects with opposite signs across subgroups, outcomes, or time periods, and testing instrument validity for local average treatment effects. For the null hypothesis that the parameters are either all non-negative or all non-positive, I propose two novel tests: a least favorable test and a conditional test. The least favorable test uses a worst-case null critical value, while the conditional test first screens components with large positive or negative estimates and then tests the remaining sign-unresolved components conditional on the screening event. Unlike existing sign agreement tests, both procedures accommodate arbitrary dependence among estimators; in the special case of independent estimators, the critical values depend only on the dimension and testing levels. We show that both tests control asymptotic size uniformly over a large class of nonparametric distributions. Local asymptotic power analysis reveals a tradeoff: the least favorable test is more powerful near boundary configurations where sign restrictions bind, whereas the conditional test is more powerful when some components are well separated from zero. Simulation evidence supports these theoretical predictions in finite samples.
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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 | Romano, J. P. and A. M. Shaikh (2012) On the uniform asymptotic validity of subsampling and the bootstrap | 1.000 | 15 | 3 | 100% |
| 2 | Piantadosi, S. and M. Gail (1993) A comparison of the power of two tests for qualitative interactions | 1.000 | 8 | 4 | 100% |
| 3 | Romano, J. P., A. M. Shaikh, and M. Wolf (2014) A practical two-step method for testing moment inequalities | 1.000 | 8 | 4 | 100% |
| 4 | Gail, M. and R. Simon (1985) Testing for qualitative interactions between treatment effects and patient subsets | 1.000 | 7 | 4 | 100% |
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| 6 | Lee, J. D., D. L. Sun, Y. Sun, and J. E. Taylor (2016) Exact post-selection inference, with application to the lasso | 0.928 | 4 | 4 | 100% |
| 7 | Andrews, D. W. K. and G. Soares (2010) Inference for parameters defined by moment inequalities using generalized moment selection | 0.928 | 4 | 3 | 100% |
| 8 | Zhao, Q., D. S. Small, and W. Su (2019) Multiple testing when many p-values are uniformly conservative, with application to testing qualitative interaction in education… | 0.928 | 4 | 3 | 100% |
| 9 | Russek-Cohen, E. and R. M. Simon (1993) Qualitative interactions in multifactor studies | 0.874 | 7 | 2 | 100% |
| 10 | Wolfers, J (2006) Did unilateral divorce laws raise divorce rates? A reconciliation and new results | 0.874 | 7 | 2 | 100% |
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