Robust Confidence Regions for Incomplete Models. Issue 5 (September 2016)

• Record Type: Journal Article
• Authors: Epstein, Larry G.; Kaido, Hiroaki; Seo, Kyoungwon
• Is Part Of: Econometrica. Volume 84:Issue 5(2016:Sep.)
• Page Start: 1799
• Page End: 1838
• Publication Date: 2016-09
• Subjects: Partial identification -- entry games -- incomplete models -- belief functions -- central limit theorem; Econometrics -- Periodicals; Economics, Mathematical -- Periodicals; Economics -- Periodicals; Économétrie -- Périodiques; Mathématiques économiques -- Périodiques; Économie politique -- Périodiques; 330.05
• DOI: 10.3982/ECTA13394
• Languages: English
• ISSNs: 0012-9682

Abstract

Abstract : Call an economic model incomplete if it does not generate a probabilistic prediction even given knowledge of all parameter values. We propose a method of inference about unknown parameters for such models that is robust to heterogeneity and dependence of unknown form. The key is a Central Limit Theorem for belief functions; robust confidence regions are then constructed in a fashion paralleling the classical approach. Monte Carlo simulations support tractability of the method and demonstrate its enhanced robustness relative to existing methods.