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Heterogeneous Effects of Endogenous Treatments with Interference and Spillovers in a Large Network

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  • Lin Chen
  • Yuya Sasaki

Abstract

This paper studies the identification and estimation of heterogeneous effects of an endogenous treatment under interference and spillovers in a large single-network setting. We model endogenous treatment selection as an equilibrium outcome that explicitly accounts for spillovers and derive conditions guaranteeing the existence and uniqueness of this equilibrium. We then identify heterogeneous marginal exposure effects (MEEs), which may vary with both the treatment status of neighboring nodes and unobserved heterogeneity. We develop estimation strategies and establish their large-sample properties. Equipped with these tools, we analyze the heterogeneous effects of import competition on U.S. local labor markets in the presence of interference and spillovers. We find negative MEEs, consistent with the existing literature. However, these effects are amplified by spillovers in the presence of treated neighbors and among localities that tend to select into lower levels of import competition. These additional empirical findings are novel and would not be credibly obtainable without the econometric framework proposed in this paper.

Suggested Citation

  • Lin Chen & Yuya Sasaki, 2025. "Heterogeneous Effects of Endogenous Treatments with Interference and Spillovers in a Large Network," Papers 2512.14515, arXiv.org.
    • Handle: RePEc:arx:papers:2512.14515
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    References listed on IDEAS

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    1. Kuersteiner, Guido M. & Prucha, Ingmar R., 2013. "Limit theory for panel data models with cross sectional dependence and sequential exogeneity," Journal of Econometrics, Elsevier, vol. 174(2), pages 107-126.
    2. Lung-fei Lee & Ji Li & Xu Lin, 2014. "Binary Choice Models with Social Network under Heterogeneous Rational Expectations," The Review of Economics and Statistics, MIT Press, vol. 96(3), pages 402-417, July.
    3. Kojevnikov, Denis & Marmer, Vadim & Song, Kyungchul, 2021. "Limit theorems for network dependent random variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 882-908.
    4. Gao, Mengsi & Ding, Peng, 2025. "Causal inference in network experiments: Regression-based analysis and design-based properties," Journal of Econometrics, Elsevier, vol. 252(PA).
    5. Bajari, Patrick & Hong, Han & Krainer, John & Nekipelov, Denis, 2010. "Estimating Static Models of Strategic Interactions," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(4), pages 469-482.
    6. David H. Autor & David Dorn & Gordon H. Hanson, 2013. "The China Syndrome: Local Labor Market Effects of Import Competition in the United States," American Economic Review, American Economic Association, vol. 103(6), pages 2121-2168, October.
    7. Hoshino, Tadao & Yanagi, Takahide, 2023. "Treatment effect models with strategic interaction in treatment decisions," Journal of Econometrics, Elsevier, vol. 236(2).
    8. Jing Cai & Alain De Janvry & Elisabeth Sadoulet, 2015. "Social Networks and the Decision to Insure," American Economic Journal: Applied Economics, American Economic Association, vol. 7(2), pages 81-108, April.
    9. Haiqing Xu, 2018. "Social Interactions In Large Networks: A Game Theoretic Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(1), pages 257-284, February.
    10. Mengsi Gao & Peng Ding, 2023. "Causal inference in network experiments: regression-based analysis and design-based properties," Papers 2309.07476, arXiv.org, revised Jun 2025.
    11. Yuchen Hu & Shuangning Li & Stefan Wager, 2022. "Average direct and indirect causal effects under interference [Estimating average causal effects under general interference, with application to a social network experiment]," Biometrika, Biometrika Trust, vol. 109(4), pages 1165-1172.
    12. Michael P. Leung, 2022. "Causal Inference Under Approximate Neighborhood Interference," Econometrica, Econometric Society, vol. 90(1), pages 267-293, January.
    13. William A. Brock & Steven N. Durlauf, 2001. "Discrete Choice with Social Interactions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 68(2), pages 235-260.
    14. Yuchen Hu & Shuangning Li & Stefan Wager, 2021. "Average Direct and Indirect Causal Effects under Interference," Papers 2104.03802, arXiv.org, revised Jan 2022.
    15. Balat, Jorge F. & Han, Sukjin, 2023. "Multiple treatments with strategic substitutes," Journal of Econometrics, Elsevier, vol. 234(2), pages 732-757.
    16. Yuya Sasaki, 2025. "GMM and M Estimation under Network Dependence," Papers 2503.00290, arXiv.org, revised Mar 2026.
    17. Berry, Steven T, 1992. "Estimation of a Model of Entry in the Airline Industry," Econometrica, Econometric Society, vol. 60(4), pages 889-917, July.
    18. Donald W. K. Andrews, 2005. "Cross-Section Regression with Common Shocks," Econometrica, Econometric Society, vol. 73(5), pages 1551-1585, September.
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