Convergence rate of estimators of clustered panel models with misclassification

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 NT-rate even if error variances diverge as T→∞ and consequently some u...

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Published in:Economics letters 2021-06, Vol.203, p.109844, Article 109844
Main Authors: Dzemski, Andreas, Okui, Ryo
Format: Article
Language:English
Subjects:
Asymptotic methods
Business & Economics
Clustering
Convergence
Convergence rate
Economics and Business
Ekonomi och näringsliv
Estimating techniques
kmeans
Latent grouped structure
Misclassification
Panel data
rate
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description 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 NT-rate even if error variances diverge as T→∞ and consequently some units are asymptotically misclassified. This limit case approximates empirically relevant settings and is not covered by existing asymptotic results. •New theoretical results for a stylized grouped panel model estimated by kmeans.•Some units exhibit large error variances and are possibly misclassified in the limit.•Nonetheless, group-specific coefficients are estimated at the root-NT rate.
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source International Bibliography of the Social Sciences (IBSS); ScienceDirect Freedom Collection 2022-2024
subjects Asymptotic methods
Business & Economics
Clustering
Convergence
Convergence rate
Economics and Business
Ekonomi och näringsliv
Estimating techniques
kmeans
Latent grouped structure
Misclassification
Panel data
rate
title Convergence rate of estimators of clustered panel models with misclassification
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