An Analysis of the Indicator Saturation Estimator as a Robust Regression Estimator
نویسندگان
چکیده
An algorithm suggested by Hendry (1999) for estimation in a regression with more regressors than observations, is analyzed with the purpose of nding an estimator that is robust to outliers and structural breaks. This estimator is an example of a one-step M -estimator based on Hubers skip function. The asymptotic theory is derived in the situation where there are no outliers or structural breaks using empirical process techniques. Stationary processes, trend stationary autoregressions and unit root processes are considered. Keywords: Empirical processes, Hubers skip, indicator saturation,M -estimator, outlier robustness, vector autoregressive process. JEL Classi cation: C32 The rst author gratefully acknowledges support from Center for Research in Econometric Analysis of Time Series, CREATES, funded by the Danish National Research Foundation. The second author received nancial support from ESRC grant RES-000-27-0179. The gure was constructed using R (R Development Core Team, 2006). The authors would like to thank David Cox and Mette Ejrnæs for some useful comments on an earlier version of the paper.
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