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Kotlarski's lemma for dyadic models

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  • Grigory Franguridi
  • Hyungsik Roger Moon

Abstract

We show how to identify the distributions of the latent components in the two-way dyadic model for bipartite networks $y_{i,\ell}= \alpha_i+\eta_{\ell}+\varepsilon_{i,\ell}$. This is achieved by a repeated application of the extension of the classical lemma of Kotlarski (1967) in Evdokimov and White (2012). We provide two separate sets of assumptions under which all the latent distributions are identified. Both rely on some of the latent components being identically distributed.

Suggested Citation

  • Grigory Franguridi & Hyungsik Roger Moon, 2025. "Kotlarski's lemma for dyadic models," Papers 2502.02734, arXiv.org, revised Jan 2026.
    • Handle: RePEc:arx:papers:2502.02734
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    References listed on IDEAS

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    1. Botosaru, Irene & Sasaki, Yuya, 2018. "Nonparametric heteroskedasticity in persistent panel processes: An application to earnings dynamics," Journal of Econometrics, Elsevier, vol. 203(2), pages 283-296.
    2. Elena Krasnokutskaya, 2011. "Identification and Estimation of Auction Models with Unobserved Heterogeneity," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(1), pages 293-327.
    3. Li, Tong & Perrigne, Isabelle & Vuong, Quang, 2000. "Conditionally independent private information in OCS wildcat auctions," Journal of Econometrics, Elsevier, vol. 98(1), pages 129-161, September.
    4. Li, Siran & Zheng, Xunjie, 2020. "A generalization of Lemma 1 in Kotlarski (1967)," Statistics & Probability Letters, Elsevier, vol. 165(C).
    5. Li, Tong, 2002. "Robust and consistent estimation of nonlinear errors-in-variables models," Journal of Econometrics, Elsevier, vol. 110(1), pages 1-26, September.
    6. Kurisu, Daisuke & Otsu, Taisuke, 2022. "On The Uniform Convergence Of Deconvolution Estimators From Repeated Measurements," Econometric Theory, Cambridge University Press, vol. 38(1), pages 172-193, February.
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