 CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed EffectsMichael Vogt, Christopher Walsh and Oliver Linton Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge Abstract: Interactive fixed effects are a popular means to model unobserved heterogeneity in panel data. Models with interactive fixed effects are well studied in the low-dimensional case where the number of parameters to be estimated is small. However, they are largely unexplored in the high-dimensional case where the number of parameters is large, potentially much larger than the sample size itself. In this paper, we develop new econometric methods for the estimation of high-dimensional panel data models with interactive fixed effects. Our estimator is based on similar ideas as the very popular common correlated effects (CCE) estimator which is frequently used in the low-dimensional case. We thus call our estimator a high-dimensional CCE estimator. We derive theory for the estimator both in the large-T-case, where the time series length T tends to infinity, and in the small-T-case, where T is a fixed natural number. The theoretical analysis of the paper is complemented by a simulation study which evaluates the finite sample performance of the estimator. Keywords: CCE estimator; high-dimensional model; interactive fixed effects; lasso; panel data (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:2242 Access Statistics for this paper More papers in Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge |
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