Econometrica: Sep 2007, Volume 75, Issue 5
Estimation and Confidence Regions for Parameter Sets in Econometric Models
Victor Chernozhukov, Han Hong, Elie Tamer
This paper develops a framework for performing estimation and inference in econometric models with partial identification, focusing particularly on models characterized by moment inequalities and equalities. Applications of this framework include the analysis of game‐theoretic models, revealed preference restrictions, regressions with missing and corrupted data, auction models, structural quantile regressions, and asset pricing models.
Log In To View Full Content
Supplementary Material for ?Estimation and Confidence Regions for Parameter Sets in Econometric Models?In the main text the true probability measure, P, is the nuisance parameter. In this supplementary material we examine which contiguous perturbations of the original fixed P preserve or do not preserve the estimation and coverage properties of the regions constructed in the main text. A useful feature of the local approach is that the conditions for the robustness of the estimation and coverage properties do not depend on the way the consistent critical values are generated (e.g. bootstrap or other means). The conditions are simple to check and apply to any consistent method of estimating a critical value.