Zequn Jin, Gaoqian Xu, Zixin Yang, Zhengyu Zhang
arXiv 23 Aug 2026 · Econometrics
arXiv:2608.22286 · PDF · Extracted main text
This paper studies quantile treatment and spillover effects in network experiments. Average spillover effects reveal how treating a unit's neighbors affects its outcome on average, but mask the heterogeneity of these effects across the outcome distribution. We define structural quantile effects that compare outcome quantiles between exposure states, characterizing how own treatment and exposure to treated neighbors affect different parts of the outcome distribution. Building on \citet{leung2020treatment}, we first establish the weak convergence of the estimated quantile-effect process under conditions requiring the stabilization of the degree distribution and the network-dependent covariance structure. Our main contribution is to propose uniform confidence bands (UCBs) based on Gaussian approximations conditional on the realized network, avoiding these stabilization requirements. The proposed method is evaluated through extensive simulation studies and an empirical application to a randomized savings-account experiment in Nepal \citep{prina2015banking}.
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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 | Leung, Michael P (2020) Treatment and spillover effects under network interference | 1.000 | 14 | 5 | 100% |
| 2 | Prina, Silvia (2015) Banking the poor via savings accounts: Evidence from a field experiment | 0.928 | 4 | 4 | 100% |
| 3 | Chernozhukov, Victor and Chetverikov, Denis and Kato, Kengo (2014) GAUSSIAN APPROXIMATION OF SUPREMA OF EMPIRICAL PROCESSES | 0.843 | 4 | 3 | 75% |
| 4 | Chernozhukov, Victor and Chetverikov, Denis and Kato, Kengo (2013) Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensional random vectors | 0.843 | 5 | 3 | 60% |
| 5 | Chernozhukov, Victor and Hansen, Christian (2005) An IV model of quantile treatment effects | 0.811 | 4 | 2 | 100% |
| 6 | Leung, Michael P (2022) Causal inference under approximate neighborhood interference | 0.811 | 4 | 2 | 100% |
| 7 | Manski, Charles F (2013) Identification of treatment response with social interactions | 0.811 | 4 | 2 | 100% |
| 8 | Angrist, Joshua and Chernozhukov, Victor and Fernández-Val, Iván (2006) Quantile regression under misspecification, with an application to the US wage structure | 0.737 | 3 | 3 | 67% |
| 9 | Aronow, Peter M and Samii, Cyrus (2017) Estimating average causal effects under general interference, with application to a social network experiment | 0.737 | 3 | 2 | 100% |
| 10 | Carter, Michael and Laajaj, Rachid and Yang, Dean (2021) Subsidies and the African Green Revolution: direct effects and social network spillovers of randomized input subsidies in Mozamb… | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 62 scored citations.