Robust Confidence Regions for Incomplete Models

Larry Epstein, Hiroaki Kaido and Kyoungwon Seo

Econometrica, 2016, vol. 84, 1799-1838

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.

Date: 2016
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Citations: View citations in EconPapers (13)

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Related works:
Working Paper: Robust confidence regions for incomplete models (2015)
Working Paper: Robust confidence regions for incomplete models (2015)
Working Paper: Robust Confidence Regions for Incomplete Models (2015)
Working Paper: Robust confidence regions for incomplete models (2015)
Working Paper: Robust confidence regions for incomplete models (2015)
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