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Identification and Estimation of Large Network Games with Private Link Information

Hülya Eraslan & Xun Tang

International Economic Review2026https://doi.org/10.1111/iere.70050preprint
AJG 4ABDC A*
Weight
0.46

What the paper says

We study the identification and estimation of large network games in which individuals choose continuous actions while holding private information about their links and payoffs. Extending the framework of Galeotti et al., we build a tractable empirical model of such network games and show that the parameters in individual payoffs are identified under large‐market asymptotics in which the number of individuals increases to infinity on a single large network. We then propose a semiparametric two‐step M‐estimator for these individual payoffs and demonstrate its good finite‐sample performance in simulations.

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https://doi.org/https://doi.org/10.1111/iere.70050

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@article{hülya2026,
  title        = {{Identification and Estimation of Large Network Games with Private Link Information}},
  author       = {Hülya Eraslan & Xun Tang},
  journal      = {International Economic Review},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/iere.70050},
}

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Identification and Estimation of Large Network Games with Private Link Information

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Evidence weight

0.46

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.41 × 0.4 = 0.16
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.