arXiv 9 Mar 2024 · Econometrics · 1 citations (OpenAlex)
arXiv:2403.05999 · PDF · DOI · OpenAlex · Extracted main text
This paper considers hypothesis testing in semiparametric models which may be non-regular. I show that C($\alpha$) style tests are locally regular under mild conditions, including in cases where locally regular estimators do not exist, such as models which are (semiparametrically) weakly identified. I characterise the appropriate limit experiment in which to study local (asymptotic) optimality of tests in the non-regular case and generalise classical power bounds to this case. I give conditions under which these power bounds are attained by the proposed C($\alpha$) style tests. The application of the theory to a single index model and an instrumental variables model is worked out in detail.
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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 | van der Vaart, A. W (1998) Asymptotic Statistics | 0.953 | 15 | 5 | 87% |
| 2 | Andrews, I. and Mikusheva, A (2022) Optimal Decision Rules for Weak GMM | 0.928 | 4 | 3 | 100% |
| 3 | Choi, S., Hall, W. J., and Schick, A (1996) Asymptotically uniformly most powerful tests in parametric and semiparametric models | 0.874 | 6 | 2 | 100% |
| 4 | Lee, A. and Mesters, G (2024) b), Supplement to `Locally Robust Inference for Non-Gaussian Linear Simultaneous Equations Models' self | 0.843 | 5 | 3 | 60% |
| 5 | Neyman, J (1959) Optimal Asymptotic Tests of Composite Statistical Hypotheses, in | 0.811 | 4 | 2 | 100% |
| 6 | Neyman, J (1979) C($$) Tests and Their Use | 0.811 | 4 | 2 | 100% |
| 7 | Kaji, T (2021) Theory of Weak Identification in Semiparametric Models | 0.737 | 3 | 2 | 100% |
| 8 | Moreira, M. J (2009) Tests with correct size when instruments can be arbitrarily weak | 0.737 | 3 | 2 | 100% |
| 9 | Bickel, P. J., Klaassen, C. A. J., Ritov, Y., and Wellner, J. A (1998) Efficient and Adaptive Estimation for Semiparametric Models | 0.721 | 8 | 5 | 38% |
| 10 | Hornung, E (2014) Immigration and the Diffusion of Technology: The Huguenot Diaspora in Prussia | 0.693 | 6 | 1 | 100% |
Showing the top 10 of 72 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Debiased Machine Learning for Unobserved Heterogeneity: High-Dimensional Panels and Measurement Error Models | 0.928 | 4 | 3 |