Estimation of group structures in panel models with individual fixed effects

Mammen, Enno ; Wilke, Ralf A. ; Zapp, Kristina Maria

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URN: urn:nbn:de:bsz:180-madoc-627372
Document Type: Working paper
Year of publication: 2022
The title of a journal, publication series: ZEW Discussion Papers
Volume: 22-023
Place of publication: Mannheim
Publication language: English
Institution: Sonstige Einrichtungen > ZEW - Leibniz-Zentrum für Europäische Wirtschaftsforschung
MADOC publication series: Veröffentlichungen des ZEW (Leibniz-Zentrum für Europäische Wirtschaftsforschung) > ZEW Discussion Papers
Subject: 330 Economics
Classification: JEL: C14 , C23 , C38,
Keywords (English): panel data , statistical learning , regularisation , endogeneity
Abstract: The fixed effects (FE) panel model is one of the main econometric tools in empirical economic research. A major practical limitation is that the parameters on time-constant covariates are not identifiable. This paper presents a new approach to grouping FE in the linear panel model to reduce their dimensionality and ensure identifiability. By using unsupervised nonparametric density based clustering, cluster patterns including their location and number are not restricted. The approach works with large data structures (units and groups) and only clusters units that are sufficiently similar, while leaving others as unclustered atoms. Asymptotic theory and rates of convergence are presented. With the help of simulations and an application to economic data it is shown that the suggested method performs well and gives more insightful and efficient results than conventional panel models.

Das Dokument wird vom Publikationsserver der Universitätsbibliothek Mannheim bereitgestellt.

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