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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Bibliographic Details
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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Summary: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.
ISSN:0165-1765
1873-7374
DOI:10.1016/j.econlet.2021.109844