M-Estimation of Scale Parameters in a Structural Time Series Model

Publication Type

Journal Article

Publication Date

1996

Abstract

We develop scale estimators of a structural time series model which are robust towards additive outliers. This is done by extending the application of the $M$-estimation technique to the scale estimation problem in time series data. A Monte Carlo experiment is carried out to study the robust properties of the proposed estimators. The simulation results indicate that the proposed $M$-estimators clearly outperform the maximum likelihood estimators produced by the Kalman filter when the observations are contaminated by outliers.

Discipline

Econometrics

Research Areas

Econometrics

Publication

Journal of Applied Statistical Science

Volume

3

Issue

1

First Page

93

Last Page

105

ISSN

1067-5817

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