 Testing for peer effects without specifying the network structureHyunseok Jung and Xiaodong Liu Journal of Econometrics, 2026, vol. 253, issue C Abstract: This paper proposes an Anderson–Rubin (AR) test for the presence of peer effects in panel data without the need to specify the network structure. The unrestricted model of our test is a linear panel data model of social interactions with dyad-specific peer effect coefficients for all potential peers. The proposed AR test evaluates if these peer effect coefficients are all zero. As the number of peer effect coefficients increases with the sample size, so does the number of instrumental variables (IVs) employed to test the restrictions under the null, rendering a many-IV environment of Bekker (1994). By extending existing many-IV asymptotic results to panel data, we establish the asymptotic validity of the proposed AR test. Our Monte Carlo simulations show the robustness and improved performance of the proposed test compared to some existing tests with misspecified networks. We provide two applications to demonstrate its empirical relevance. Keywords: Anderson–Rubin test; Many instruments; Testing with many restrictions; Social interactions; Unknown network structure (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:253:y:2026:i:c:s0304407625001782 DOI: 10.1016/j.jeconom.2025.106124 Access Statistics for this article Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson More articles in Journal of Econometrics from Elsevier |
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