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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 2008-WO3.
Date of creation: 01 Jan 2008
Date of revision:
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," Economics Papers 2008-W03, Economics Group, Nuffield College, University of Oxford.
- 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.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
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.:
- Bent Nielsen, 2003.
"Strong consistency results for least squares estimators in general vector autoregressions with deterministic terms,"
2003-W23, Economics Group, Nuffield College, University of Oxford.
- Nielsen, Bent, 2005. "Strong Consistency Results For Least Squares Estimators In General Vector Autoregressions With Deterministic Terms," Econometric Theory, Cambridge University Press, vol. 21(03), pages 534-561, June.
- Bent Nielsen, 2003. "Strong consistency results for least squares estimators in general vector autoregressions with deterministic terms," Economics Series Working Papers 2003-W23, University of Oxford, Department of Economics.
- J. James Reade & Ulrich Volz, 2011. "From the General to the Specific," Discussion Papers 11-18, Department of Economics, University of Birmingham.
- Neil R. Ericsson, 2008.
"The fragility of sensitivity analysis: an encompassing perspective,"
International Finance Discussion Papers
959, Board of Governors of the Federal Reserve System (U.S.).
- Neil R. Ericsson, 2008. "The Fragility of Sensitivity Analysis: An Encompassing Perspective," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 895-914, December.
- David Hendry & Carlos Santos, 2010. "An Automatic Test of Super Exogeneity," Economics Series Working Papers 476, University of Oxford, Department of Economics.
- Neil R. Ericsson & Steven B. Kamin, 2008. "Constructive data mining: modeling Argentine broad money demand," International Finance Discussion Papers 943, Board of Governors of the Federal Reserve System (U.S.).
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Caroline Wise).
If references are entirely missing, you can add them using this form.