Maximilian Kasy, Elizabeth Linos, Sanaz Mobasseri
arXiv 20 Apr 2026 · Econometrics
arXiv:2604.17952 · PDF · DOI · OpenAlex · Extracted main text
This paper develops a framework for identification, estimation, and inference on the causal mechanisms driving endogenous social network formation. Identification is challenging because of unobserved confounders and reverse causality; inference is complicated by questions of equilibrium and sampling. We leverage repeated observations of a network over time and random variation in initial ties to address challenges to causal identification. Our design-based approach sidesteps questions of sampling and asymptotics by treating both the set of nodes (individuals) and potential outcomes as non-random. We apply our approach to data from a large professional services firm, where new hires are randomly assigned to project teams within offices. We estimate the causal effect on tie formation of indirect ties, network degree, and local network density. Indirect ties have a strong and significant positive effect on tie formation, while the effects of degree and density are smaller and less robust.
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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 | Tian, Pengfei and Yang, Fan and Ding, Peng (2025) Stratified Permutational Berry–Esseen Bounds and Their Applications to Statistics | 0.874 | 6 | 2 | 100% |
| 2 | Guillaume Basse AND Peng Ding AND Avi Feller AND Panos Toulis (2024) Randomization tests for peer effects in group formation experiments | 0.811 | 4 | 2 | 100% |
| 3 | Abadie, Alberto and Athey, Susan and Imbens, Guido W and Wooldridge,… (2020) Sampling-Based versus Design-Based Uncertainty in Regression Analysis | 0.737 | 3 | 2 | 100% |
| 4 | De Paula, Áureo (2020) Econometric models of network formation | 0.737 | 3 | 2 | 100% |
| 5 | Graham, Bryan and De Paula, Áureo (2020) The econometric analysis of network data | 0.737 | 3 | 2 | 100% |
| 6 | Mukerjee, Rahul and Dasgupta, Tirthankar and Rubin, Donald B (2018) Using standard tools from finite population sampling to improve causal inference for complex experiments | 0.737 | 3 | 2 | 100% |
| 7 | Neyman, Jerzy (1923) On the application of probability theory to agricultural experiments. Essay on principles | 0.737 | 3 | 2 | 100% |
| 8 | Barabasi, A L and Albert, R (1999) Emergence of scaling in random networks | 0.644 | 2 | 2 | 100% |
| 9 | Burt, Ronald S (2009) Structural Holes: The Social Structure of Competition | 0.644 | 2 | 2 | 100% |
| 10 | Coleman, James S (1988) Social capital in the creation of human capital | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 53 scored citations.