Jackknife Inference for Fixed Effects Models

Ayden Higgins

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arXiv · 2602.21903

Jackknife Inference for Fixed Effects Models

Ayden Higgins

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Abstract

This paper develops a general method of inference for fixed effects models which is (i) automatic, (ii) computationally inexpensive, (iii) tuning parameter-free, and (iv) highly model agnostic. Specifically, we show how to combine a collection of subsample estimators into a jackknife $t$-statistic, from which hypothesis tests, confidence intervals, and $p$-values are readily obtained.

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Ayden Higgins. 2026-02-25. Jackknife Inference for Fixed Effects Models. https://arxiv.org/abs/2602.21903

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