Square-root nuclear norm penalized estimator for panel data models with approximately low-rank unobserved Heterogeneity
Jad Beyhum and
Eric Gautier
No 19-1008, TSE Working Papers from Toulouse School of Economics (TSE)
Abstract:
This paper considers a nuclear norm penalized estimator for panel data models with interactive effects. The low-rank interactive effects can be an approximate model and the rank of the best approximation unknown and grow with sample size. The estimator is solution of a well-structured convex optimization problem and can be solved in polynomial-time. We derive rates of convergence, study the low-rank properties of the estimator, estimation of the rank and of annihilator matrices when the number of time periods grows with the sample size. Two-stage estimators can be asymptotically normal. None of the procedures require knowledge of the variance of the errors.
Date: 2019-04
New Economics Papers: this item is included in nep-ecm
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Persistent link: https://EconPapers.repec.org/RePEc:tse:wpaper:122931
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