An analysis of the indicator saturation estimator as a robust regression estimator
AbstractAn algorithm suggested by Hendry (1999) for estimation in a regression with more regressors than observations, is analyzed with the purpose of finding an estimator that is robust to outliers and structural breaks. This estimator is an example of a one-step M-estimator based on Huber’s 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.
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Bibliographic InfoPaper provided by Economics Group, Nuffield College, University of Oxford in its series Economics Papers with number 2008-W03.
Length: 35 pages
Date of creation: 01 2008
Date of revision:
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Web page: http://www.nuff.ox.ac.uk/economics/
Empirical processes; Huber’s skip; indicator saturation; M-estimator; outlier robustness; vector autoregressive process.;
Other versions of this item:
- Søren Johansen & Bent Nielsen, 2008. "An analysis of the indicator saturation estimator as a robust regression estimator," CREATES Research Papers 2008-09, School of Economics and Management, University of Aarhus.
- Bent Nielsen & Soren Johansen & Bent Nielsen, 2008. "An analysis of the indicator saturation estimator as a robust regression estimator," Economics Series Working Papers 2008-WO3, University of Oxford, Department of Economics.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-02-16 (All new papers)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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