arXiv 4 Aug 2026 · Econometrics
arXiv:2608.03847 · PDF · Extracted main text
Empirical work often removes fixed effects, latent factors, or high-dimensional controls before estimating structural relationships. These transformations reduce confounding but may also remove identifying variation. We study linear panel IV after one equation-compatible nuisance projection under two-way dependence. The projected Jacobian determines which structural directions remain visible; the projected-score law determines their precision; and, on Gaussian fixed-rank strata, they combine in a Projected Information Matrix. We derive weak-identification limits with dimension-specific information accumulation, feasible factor-transfer conditions, identification-robust tests, bootstrap procedures for non-Gaussian interaction limits, and inference for the projected spectrum, rank, subspaces, and information matrix. Simulations show that a raw first-stage statistic above 500 can support the wrong sign while projected diagnostics reveal weak valid information. In an international monetary application, common projection substantially attenuates apparent foreign-output persistence, while Gaussian-reference Anderson--Rubin sets remain unbounded. Identification should therefore be assessed after nuisance removal.
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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 | Hounyo, U. and Lin, J (2026) Bootstrap inference under general two-way clustering with serially and spatially dependent common effects self | 0.920 | 9 | 3 | 78% |
| 2 | Dufour, J.-M (1997) Some impossibility theorems in econometrics with applications to structural and dynamic models | 0.843 | 4 | 3 | 75% |
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Showing the top 10 of 34 scored citations.