Robust Two-Stage Least Squares: some Monte Carlo experiments

Sudhanshu Mishra (mishrasknehu@yahoo.com)

MPRA Paper from University Library of Munich, Germany

Abstract: The Two-Stage Least Squares (2-SLS) is a well known econometric technique used to estimate the parameters of a multi-equation (or simultaneous equations) econometric model when errors across the equations are not correlated and the equation(s) concerned is (are) over-identified or exactly identified. However, in presence of outliers in the data matrix, the classical 2-SLS has a very poor performance. In this study a method has been proposed to conveniently generalize the 2-SLS to the weighted 2-SLS (W2-SLS), which is robust to the effects of outliers and perturbations in the data matrix. Monte Carlo experiments have been conducted to demonstrate the performance of the proposed method. It has been found that robustness of the proposed method is not much destabilized by the magnitude of outliers, but it is sensitive to the number of outliers/perturbations in the data matrix. The breakdown point of the method is quite high, somewhere between 45 to 50 percent of the number of points in the data matrix.

Keywords: Two-Stage Least Squares; multi-equation econometric model; simultaneous equations; outliers; robust; weighted least squares; Monte Carlo experiments; unbiasedness; efficiency; breakdown point; perturbation; structural parameters; reduced form (search for similar items in EconPapers)
JEL-codes: C13 C14 C15 C30 C63 C87 (search for similar items in EconPapers)
Date: 2008-07-26
New Economics Papers: this item is included in nep-ecm and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/9737/1/MPRA_paper_9737.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:9737

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter (winter@lmu.de).