Estimation of group structures in panel models with individual fixed effects

Enno Mammen, Ralf Wilke and Kristina Maria Zapp

No 22-023, ZEW Discussion Papers from ZEW - Leibniz Centre for European Economic Research

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.

Keywords: Panel Data; Statistical Learning; Regularisation; Endogeneity (search for similar items in EconPapers)
JEL-codes: C14 C23 C38 (search for similar items in EconPapers)
Date: 2022
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:zbw:zewdip:22023

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