GMM and M Estimation under Network Dependence

arXiv 1 Mar 2025 · Econometrics

arXiv:2503.00290 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper presents GMM and M estimators and their asymptotic properties for network-dependent data. To this end, I build on Kojevnikov, Marmer, and Song (KMS, 2021) and develop a novel uniform law of large numbers (ULLN), which is essential to ensure desired asymptotic behaviors of nonlinear estimators (e.g., Newey and McFadden, 1994, Section 2). Using this ULLN, I establish the consistency and asymptotic normality of both GMM and M estimators. For practical convenience, complete estimation and inference procedures are also provided.

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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.

	Reference	Intensity	Mentions	Sections	Main text
1	Kojevnikov, D., V. Marmer, and K. Song (2021) Limit theorems for network dependent random variables	0.950	7	5	86%
2	Newey, W. and D. McFadden (1994) Large sample estimation and hypothesis testing	0.843	10	5	60%
3	Gao, M. and P. Ding (2023) Causal inference in network experiments: Regression‑based analysis and design‑based properties	0.644	2	2	100%
4	Hoshino, T. and T. Yanagi (2024) Causal inference with noncompliance and unknown interference	0.644	2	2	100%
5	Leung, M. P (2022) Dependence‐robust inference using resampled statistics	0.644	2	2	100%
6	Graham, B. S (2020) Dyadic regression	0.405	1	1	100%
7	Babii, A., E. Ghysels, and J. Striaukas (2022) Machine learning time series regressions with an application to nowcasting	0.405	1	1	100%
8	Chiang, H. D., K. Kato, and Y. Sasaki (2023) Inference for high-dimensional exchangeable arrays	0.405	1	1	100%
9	Davezies, L., X. D’Haultfuille, and Y. Guyonvarch (2021) Inference for exchangeable arrays with application to random effects models	0.405	1	1	100%
10	Doukhan, P. and S. Louhichi (1999) A new weak dependence condition and applications to moment inequalities	0.405	1	1	100%

Showing the top 10 of 16 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

	Citing paper	Intensity	Mentions	Sections
1	Coupling and Maximal Inequalities for Graph-Dependent Empirical Processes	0.405	1	1
2	A Design-Based Approach to Testing and Inference in (Quasi-)Experiments with Spillovers	0.405	1	1