Convergence rate of estimators of clustered panel models with misclassification

Andreas Dzemski and Ryo Okui

Abstract: We study kmeans clustering estimation of panel data models with a latent group structure and $N$ units and $T$ time periods under long panel asymptotics. We show that the group-specific coefficients can be estimated at the parametric root $NT$ rate even if error variances diverge as $T \to \infty$ and some units are asymptotically misclassified. This limit case approximates empirically relevant settings and is not covered by existing asymptotic results.

Date: 2020-08
New Economics Papers: this item is included in nep-ecm
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Related works:
Journal Article: Convergence rate of estimators of clustered panel models with misclassification (2021)
Working Paper: Convergence rate of estimators of clustered panel models with misclassication (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2008.04708

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