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Statistical Inference in Large Multi-way Networks

Lucas Resende, Guillaume Lecué, Lionel Wilner, Philippe Choné

arXiv 1 Dec 2025 · Econometrics

arXiv:2512.02203 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We propose a new method to estimate structural parameters in multi-way networks while controlling for rich structures of fixed effects. The method is based on a series of classification tasks and is agnostic to both the number and structure of fixed effects. In contrast to full maximum likelihood approaches, our estimator does not suffer from the incidental parameter problem. For sparsely connected networks, it is also computationally faster than PPML. We provide empirical evidence that our estimator yields more reliable confidence intervals than PPML and its bias-correction strategies. These improvements hold even under model misspecification and are more pronounced in sparse settings. While PPML remains competitive in dense, low-dimensional data, our approach offers a robust alternative for multi-way models that scales efficiently with sparsity. The method is applied to study the causal effect of a policy reform on spatial accessibility to health care in France.

Citation extraction

41
references
126
in-text mentions
42
distinct cited
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self-citations
16,145
main-text words

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Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Weidner, Martin and Zylkin, Thomas (2021) Bias and consistency in three-way gravity models1.000104100%
2Jochmans, Koen (2018) Semiparametric analysis of network formation0.9209478%
3Graham, Bryan S (2017) An econometric model of network formation with degree heterogeneity0.90319574%
4Jochmans, Koen (2017) Two-way models for gravity0.81142100%
5Haberman, Shelby J (1989) Concavity and estimation0.7373367%
6Niemiro, Wojciech (1992) Asymptotics for $M$-estimators defined by convex minimization0.7373367%
7Brunel, Victor-Emmanuel (2020) Asymptotic statistics0.7373367%
8Charbonneau, Karyne (2012) Multiple fixed effects in nonlinear panel data models0.73732100%
9Correia, S and Guimarães, P and Zylkin, T (2019) ppmlhdfe: Fast Poisson estimation with high-dimensional fixed effects, arXiv. org0.73732100%
10Fernández-Val, Iván and Weidner, Martin (2016) Individual and time effects in nonlinear panel models with large N, T0.73732100%

Showing the top 10 of 42 scored citations.