Robust Confidence Regions for Incomplete Models

Larry Epstein, Hiroaki Kaido and Kyoungwon Seo ()
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Kyoungwon Seo: Korea Advanced Institute of Science and Technology (KAIST)

No wp2015-008, Boston University - Department of Economics - Working Papers Series from Boston University - Department of Economics

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.

Pages: 33
Date: 2015-09-27
New Economics Papers: this item is included in nep-hrm and nep-mic
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Related works:
Journal Article: Robust Confidence Regions for Incomplete Models (2016)
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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