Kaicheng Chen, Harold D. Chiang
arXiv 11 Feb 2026 · Econometrics
arXiv:2602.11333 · PDF · DOI · OpenAlex · Extracted main text
This paper develops an asymptotic theory for two-step debiased machine learning (DML) estimators in generalised method of moments (GMM) models with general multiway clustered dependence, without relying on cross-fitting. While cross-fitting is commonly employed, it can be statistically inefficient and computationally burdensome when first-stage learners are complex and the effective sample size is governed by the number of independent clusters. We show that valid inference can be achieved without sample splitting by combining Neyman-orthogonal moment conditions with a localisation-based empirical process approach, allowing for an arbitrary number of clustering dimensions. The resulting DML-GMM estimators are shown to be asymptotically linear and asymptotically normal under multiway clustered dependence. A central technical contribution of the paper is the derivation of novel global and local maximal inequalities for general classes of functions of sums of separately exchangeable arrays, which underpin our theoretical arguments and are of independent interest.
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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 | Chiang, Harold D and Kato, Kengo and Sasaki, Yuya (2023) Inference for high-dimensional exchangeable arrays self | 0.888 | 10 | 5 | 70% |
| 2 | Chernozhukov, Victor and Escanciano, Juan Carlos and Ichimura, Hideh… (2022) Locally robust semiparametric estimation | 0.811 | 4 | 2 | 100% |
| 3 | Chen, Xiaohui and Kato, Kengo (2019) Jackknife multiplier bootstrap: finite sample approximations to the U-process supremum with applications | 0.737 | 4 | 4 | 50% |
| 4 | Chiang, Harold D and Kato, Kengo and Ma, Yukun and Sasaki, Yuya (2022) Multiway cluster robust double/debiased machine learning self | 0.737 | 4 | 3 | 50% |
| 5 | Belloni, Alexandre and Chernozhukov, Victor and Kato, Kengo (2015) Uniform post-selection inference for least absolute deviation regression and other Z-estimation problems | 0.737 | 3 | 2 | 100% |
| 6 | Chen, Qizhao and Syrgkanis, Vasilis and Austern, Morgane (2022) Debiased machine learning without sample-splitting for stable estimators | 0.737 | 3 | 2 | 100% |
| 7 | Davezies, Laurent and D'Haultfoeuille, Xavier and Guyonvarch, Yannick (2018) Asymptotic Results under Multiway Clustering | 0.644 | 3 | 2 | 67% |
| 8 | Belloni, Alexandre and Chernozhukov, Victor and Chetverikov, Denis a… (2018) Uniformly valid post-regularization confidence regions for many functional parameters in z-estimation framework | 0.644 | 2 | 2 | 100% |
| 9 | Chernozhukov, Victor and Chetverikov, Denis and Kato, Kengo (2014) Gaussian approximation of suprema of empirical processes | 0.511 | 3 | 2 | 33% |
| 10 | Davezies, Laurent and D'Haultfœuille, Xavier and Guyonvarch, Yannick (2025) Analytic inference with two-way clustering | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 44 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Gaussian Approximation for Maximum Score and Non-Smooth M-Estimators with Multiway Dependence | 0.659 | 7 | 6 |