Make the Difference! computationally Trivial Estimators for Grouped Fixed Effects Models

Martin Mugnier ()
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Martin Mugnier: Department of Economics, CREST, ENSAE, Institut Polytechnique de Paris, France

No 2022-07, Working Papers from Center for Research in Economics and Statistics

Abstract: Novel estimators are proposed for linear grouped fixed effects models. Rather than predicting a single grouping of units, they deliver a collection of groupings with the same flavor as the so-called LASSO regularization path. Mild conditions are found that ensure their asymptotic guarantees are the same as the so-called grouped fixed effects and post-spectral estimators (Bonhomme and Manresa, 2015; Chetverikov and Manresa, 2021). In contrast, the new estimators are computationally straigthforward and do not require prior knowledge of the number of groups. Monte Carlo simulations suggest good finite sample performance. Applying the approach to real data provides new insights on the potential network structure of the unobserved heterogeneity.

Keywords: panel data; grouped fixed effects; time-varying unobserved heterogeneity; k-means clustering (search for similar items in EconPapers)
JEL-codes: C14 C23 C25 (search for similar items in EconPapers)
Pages: 48 pages
Date: 2022-03-14
New Economics Papers: this item is included in nep-dcm, nep-ecm and nep-net
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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