# Network Data

arXiv: https://arxiv.org/abs/1912.06346 · HTML: https://mlsanity.com/paper/1912.06346/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Dec 2019.

## Built on by (most cited first, 9 of 9)

- [The Local Approach to Causal Inference under Network Interference](https://mlsanity.com/paper/2105.03810/) (2021)
- [Evaluating the Quality of Finite Element Meshes with Machine Learning](https://mlsanity.com/paper/2107.10507/) (2021)
- [Confidence Intervals for Error Rates in 1:1 Matching Tasks: Critical Statistical Analysis and Recommendations](https://mlsanity.com/paper/2306.01198/) (2023)
- [Habitat Classification from Ground-Level Imagery Using Deep Neural Networks](https://mlsanity.com/paper/2507.04017/) (2025)
- [Variational Inference: Posterior Threshold Improves Network Clustering Accuracy in Sparse Regimes](https://mlsanity.com/paper/2301.04771/) (2023)
- [Impart: An Imperceptible and Effective Label-Specific Backdoor Attack](https://mlsanity.com/paper/2403.13017/) (2024)
- [Estimating Dyadic Treatment Effects with Unknown Confounders](https://mlsanity.com/paper/2405.16547/) (2024)
- [LOD: Latent Objective Discovery in Heterogeneous Multi-Agent Reinforcement Learning](https://mlsanity.com/paper/2505.09756/) (2025)
- [DALI: LLM-Agent Enhanced Dual-Stream Adaptive Leadership Identification for Group Recommendations](https://mlsanity.com/paper/2603.19909/) (2026)

## Abstract (arXiv)

Many economic activities are embedded in networks: sets of agents and the (often) rivalrous relationships connecting them to one another. Input sourcing by firms, interbank lending, scientific research, and job search are four examples, among many, of networked economic activities. Motivated by the premise that networks' structures are consequential, this chapter describes econometric methods for analyzing them. I emphasize (i) dyadic regression analysis incorporating unobserved agent-specific heterogeneity and supporting causal inference, (ii) techniques for estimating, and conducting inference on, summary network parameters (e.g., the degree distribution or transitivity index); and (iii) empirical models of strategic network formation admitting interdependencies in preferences. Current research challenges and open questions are also discussed.