Robust Efficient Method of Moments

40 Pages Posted: 16 Oct 2002  

Fabio Trojani

University of Geneva; Swiss Finance Institute

Claudio Ortelli

University of Lugano

Date Written: September 2002

Abstract

This paper focuses on the robust Efficient Method of Moments (EMM) estimation of a general parametric stationary process and proposes a broad framework for constructing robust EMM statistics in this context. This extends the application field of robust statistics to very general time series settings, including situations where the structural and the auxiliary models in the EMM estimating equations are different, models with latent non linear dynamics, and models where no closed form expressions for the robust pseudo score of the given EMM auxiliary model are available. We characterize the local robustness properties of EMM estimators for time series by computing the corresponding influence functions and propose two versions of a robust EMM (REMM) estimator with bounded IF. Two algorithms by which the two versions of a REMM estimator can be implemented are presented. We then show by Monte Carlo simulation that our REMM estimators are very successful in controlling for the asymptotic bias under model misspecification while maintaining a high efficiency under the ideal structural model.

Keywords: Efficient Method of Moments, Indirect Inference, Influence Function, Robust Estimation, Robust Statistics

JEL Classification: C1, C13, C14, C15, C22

Suggested Citation

Trojani, Fabio and Ortelli, Claudio, Robust Efficient Method of Moments (September 2002). Available at SSRN: https://ssrn.com/abstract=335700 or http://dx.doi.org/10.2139/ssrn.335700

Fabio Trojani (Contact Author)

University of Geneva ( email )

Geneva
Switzerland

Swiss Finance Institute ( email )

c/o University of Geneve
40, Bd du Pont-d'Arve
1211 Geneva, CH-6900
Switzerland

Claudio Ortelli

University of Lugano ( email )

via G. Buffi 13
Lugano, 6904
Switzerland

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