Robust Confidence Regions for Incomplete Models

S-Tier
Journal: Econometrica
Year: 2016
Volume: 84
Pages: 1799-1838

Score contribution per author:

2.681 = (α=2.01 / 3 authors) × 4.0x S-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:wly:emetrp:v:84:y:2016:i::p:1799-1838
Journal Field
General
Author Count
3
Added to Database
2026-01-25