arXiv 28 Sep 2022 · Econometrics
arXiv:2209.14391 · PDF · DOI · OpenAlex · Extracted main text
I establish primitive conditions for unconfoundedness in a coherent model that features heterogeneous treatment effects, spillovers, selection-on-observables, and network formation. I identify average partial effects under minimal exchangeability conditions. If social interactions are also anonymous, I derive a three-dimensional network propensity score, characterize its support conditions, relate it to recent work on network pseudo-metrics, and study extensions. I propose a two-step semiparametric estimator for a random coefficients model which is consistent and asymptotically normal as the number and size of the networks grows. I apply my estimator to a political participation intervention Uganda and a microfinance application in India.
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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 | Johnsson, I., Moon, H. R (2021) Estimation of peer effects in endogenous social networks: control function approach | 1.000 | 6 | 5 | 100% |
| 2 | DiTraglia, F. J., Garcia-Jimeno, C., O'Keefe-O'Donnovan, R., Sanchez… (2022) Identifying causal effects in experiments with social interactions and non-compliance self | 0.928 | 10 | 5 | 80% |
| 3 | Ferrali, R., Grossman, G., Platas, M. R., Rodden, J (2020) It takes a village: Peer effects and externalities in technology adoption | 0.874 | 5 | 2 | 100% |
| 4 | Auerbach, E., Tabord-Meehan, M (2021) The local approach to causal inference under network interference | 0.843 | 3 | 3 | 100% |
| 5 | Bramoullé, Y., Djebbari, H., Fortin, B (2009) Identification of peer effects through social networks | 0.843 | 3 | 3 | 100% |
| 6 | Leung, M. P (2019) a | 0.843 | 3 | 3 | 100% |
| 7 | Leung, M. P (2022) Causal inference under approximate neighborhood interference | 0.843 | 3 | 3 | 100% |
| 8 | Rosenbaum, P. R., Rubin, D. B (1983) The central role of the propensity score in observational studies for causal effects | 0.843 | 3 | 3 | 100% |
| 9 | Tchetgen, E. J. T., Fulcher, I., Shpitser, I (2017) Auto-g-computation of causal effects on a network | 0.843 | 3 | 3 | 100% |
| 10 | Zeleneev, A (2020) Identification and estimation of network models with nonparametric unobserved heterogeneity | 0.843 | 3 | 3 | 100% |
Showing the top 10 of 70 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Spillovers of Program Benefits with Missing Network Links | 0.405 | 1 | 1 |