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Normal Approximation in Large Network Models

Michael P. Leung, Hyungsik Roger Moon

arXiv 24 Apr 2019 · Econometrics · publishedThe Review of Economic Studies (2019) · 6 citations (OpenAlex)

arXiv:1904.11060 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We prove a central limit theorem for network formation models with strategic interactions and homophilous agents. Since data often consists of observations on a single large network, we consider an asymptotic framework in which the network size diverges. We argue that a modification of “stabilization” conditions from the literature on geometric graphs provides a useful high-level formulation of weak dependence which we utilize to establish an abstract central limit theorem. Using results in branching process theory, we derive interpretable primitive conditions for stabilization. The main conditions restrict the strength of strategic interactions and equilibrium selection mechanism. We discuss practical inference procedures justified by our results.

Citation extraction

49
references
125
in-text mentions
49
distinct cited
6
self-citations
16,469
main-text words

appendix boundary found by appendix_command · 47% of the source is main text. Read the extracted text to check this.

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
1Leung (2019) A Weak Law for Moments of Pairwise-Stable Networks self0.96510690%
2Sheng (2020) A Structural Econometric Analysis of Network Formation Games Through Subnetworks0.9619589%
3Leung (2022) Dependence-Robust Inference Using Resampled Statistics self0.87462100%
4Leung (2019) Inference in Models of Discrete Choice with Social Interactions Using Network Data self0.84333100%
5Penrose and Yukich (2008) Normal Approximation in Geometric Probability0.7948350%
6Penrose (2007) Gaussian Limits for Random Geometric Measures0.77313346%
7Hoff, Raftery and Handcock (2002) Latent Space Approaches to Social Network Analysis0.73732100%
8Jackson (2010)0.73732100%
9Menzel (2024) Strategic Network Formation with Many Agents0.73732100%
10Ridder and Sheng (2022) Two-Step Estimation of a Strategic Network Formation Model with Clustering0.73732100%

Showing the top 10 of 49 scored citations.

Cited by, within the corpus

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

Citing paperIntensityMentionsSections
1Inference in Models of Discrete Choice with Social Interactions Using Network Data0.689529
2Dependence-Robust Inference Using Resampled Statistics0.64422
31 Linear Regression with Centrality Measures0.64422
4Graph Neural Networks for Causal Inference Under Network Confounding0.64422
5Limit Theorems for Network Data without Metric Structure0.64422
6Tractable Identification of Strategic Network Formation Models with Unobserved Heterogeneity0.64422
7Network Data0.40511
8Two-Step Estimation of a Strategic Network Formation Model with Clustering0.40511
9Who Should Get Vaccinated? Individualized Allocation of Vaccines Over SIR Network0.40511
10Social Interactions in Endogenous Groups0.40511