Gregory Fletcher Cox, Xiaoxia Shi, Yuya Shimizu
arXiv 31 Oct 2025 · Statistics — Methodology
arXiv:2510.27633 · PDF · DOI · OpenAlex · Extracted main text
This paper proposes a new test for inequalities that are linear in possibly partially identified nuisance parameters. This type of hypothesis arises in a broad set of problems, including subvector inference for linear unconditional moment (in)equality models, specification testing of such models, and inference for parameters bounded by linear programs. The new test uses a two-step test statistic and a chi-squared critical value with data-dependent degrees of freedom that can be calculated by an elementary formula. Its simple structure and tuning-parameter-free implementation make it attractive for practical use. We establish uniform asymptotic validity of the test, demonstrate its finite-sample size and power in simulations, and illustrate its use in an empirical application that analyzes women's labor supply in response to a welfare policy reform.
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arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Testing the Solvability of Systems of Linear Inequalities | 1.000 | 9 | 3 |
| 2 | Inference for Linear Systems with Unknown Coefficients | 1.000 | 9 | 4 |
| 3 | Synthetic Parallel Trends | 0.737 | 3 | 2 |
| 4 | Identification in Multiple Treatment Models under Discrete Variation | 0.644 | 5 | 2 |