Robust confidence regions for incomplete models - Larry G. Epstein; Hiroaki Kaido; Kyoungwon Seo (Centre for Microdata Methods and Practice (cemmap), 2015)
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 con.dence 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.
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