Worst-case estimation for econometric models with unobservable components

descriptionPublicationkeyboard_double_arrow_right Article 01 Apr 2007 English Publisher:Elsevier BVJournal:Computational Statistics & Data Analysis, volume 51, pages 3,330-3,354 (issn: 0167-9473,

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Authors: Mercedes Esteban-Bravo; Jose M. Vidal-Sanz;

doi: 10.1016/j.csda.2006.09.023

handle: 10016/7342

Worst-case estimation for econometric models with unobservable components

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Abstract

A worst-case estimator for econometric models containing unobservable components, based on minimax principles for optimal selection of parameters, is proposed. Worst-case estimators are robust against the averse effects of unobservables. Computing worstcase estimators involves solving a minimax continuous problem, which is quite a challenging task. Large sample theory is considered, and a Monte Carlo study of finite-sample properties is conducted. A financial application is considered

Related Organizations

Carlos III University of Madrid
Spain

Keywords

Worst-case decision, Minimax procedures in statistical decision theory, Monte Carlo methods, worst-case decision, Robust modelling, minimax optimization, Minimax optimization, Applications of statistics to economics, robust modelling, Empresa

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