Robust Confidence Regions for Incomplete Models
Larry G. Epstein, Hiroaki Kaido, Kyoungwon Seo
Econometrica · 2016 · Volume 84 · Issue 5
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.
Keywords
Partial identification, entry games, incomplete models, belief functions, central limit theorem
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