Square-root nuclear norm penalized estimator for panel data models with approximately low-rank unobserved Heterogeneity

Beyhum, Jad and Gautier, Eric (2019) Square-root nuclear norm penalized estimator for panel data models with approximately low-rank unobserved Heterogeneity. TSE Working Paper, n. 19-1008, Toulouse

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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.

Item Type: Monograph (Working Paper)
Language: English
Date: April 2019
Place of Publication: Toulouse
Subjects: B- ECONOMIE ET FINANCE
Divisions: TSE-R (Toulouse)
Institution: Université Toulouse 1 Capitole
Site: UT1
Date Deposited: 23 Apr 2019 09:45
Last Modified: 25 Apr 2019 07:23
OAI ID: oai:tse-fr.eu:122931
URI: http://publications.ut-capitole.fr/id/eprint/32360

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