arXiv 4 Nov 2025 · Econometrics
arXiv:2511.02764 · PDF · DOI · OpenAlex · Extracted main text
I study peer effects that arise from irreversible decisions in the absence of a standard social equilibrium. I model a latent sequence of decisions in continuous time and obtain a closed-form expression for the likelihood, which allows to estimate proposed causal estimands. The method avoids linear-in-means regression by modeling the (possibly unobserved) realized direction of causality, whose probability is identified. I provide identification and estimation results under two settings, several networks and one large network, while allowing for various forms of peer effect heterogeneity. Under (strong) data requirements, it is possible to separate endogenous, contextual, and correlated effects while allowing for full heterogeneity and maximum likelihood methods where parameters lend themselves to standard inference.
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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 | Manski, Charles F (1993) Identification of endogenous social effects: The reflection problem | 0.737 | 4 | 2 | 75% |
| 2 | Bramoullé, Yann and Djebbari, Habiba and Fortin, Bernard (2009) Identification of peer effects through social networks | 0.737 | 3 | 2 | 100% |
| 3 | Angrist, Joshua D (2014) The perils of peer effects | 0.644 | 5 | 2 | 40% |
| 4 | Boucher, Vincent and Rendall, Michelle and Ushchev, Philip and Zenou… (2024) Toward a general theory of peer effects | 0.644 | 2 | 2 | 100% |
| 5 | Blume, Lawrence E and Brock, William A and Durlauf, Steven N and Jay… (2015) Linear social interactions models | 0.585 | 3 | 1 | 100% |
| 6 | Hayes, Alex and Levin, Keith (2024) Peer effects in the linear-in-means model may be inestimable even when identified | 0.511 | 2 | 1 | 100% |
| 7 | Aronow, Peter M and Samii, Cyrus (2017) Estimating average causal effects under general interference, with application to a social network experiment | 0.405 | 1 | 1 | 100% |
| 8 | Arpino, Bruno and Benedictis, Luca De and Mattei, Alessandra (2017) Implementing propensity score matching with network data: the effect of the General Agreement on Tariffs and Trade on bilateral… | 0.405 | 1 | 1 | 100% |
| 9 | Athey, Susan and Imbens, Guido W (2022) Design-based analysis in difference-in-differences settings with staggered adoption | 0.405 | 1 | 1 | 100% |
| 10 | Auerbach, Eric (2022) Identification and estimation of a partially linear regression model using network data | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 36 scored citations.