Robust Z-Estimators for Semiparametric Moment Condition Models

Entropy (Basel). 2023 Jun 30;25(7):1013. doi: 10.3390/e25071013.

Abstract

In the present paper, we introduce a class of robust Z-estimators for moment condition models. These new estimators can be seen as robust alternatives for the minimum empirical divergence estimators. By using the multidimensional Huber function, we first define robust estimators of the element that realizes the supremum in the dual form of the divergence. A linear relationship between the influence function of a minimum empirical divergence estimator and the influence function of the estimator of the element that realizes the supremum in the dual form of the divergence led to the idea of defining new Z-estimators for the parameter of the model, by using robust estimators in the dual form of the divergence. The asymptotic properties of the proposed estimators were proven, including here the consistency and their asymptotic normality. Then, the influence functions of the estimators were derived, and their robustness is demonstrated.

Keywords: divergences; moment condition models; robustness.

Grants and funding

This work was supported by a grant of the Ministry of Research, Innovation and Digitization, CNCS CCCDI—UEFISCDI, Project Number PN-III-P4-ID-PCE-2020-1112, within PNCDI III.