IDEAS home Printed from https://ideas.repec.org/a/ush/jaessh/v3y2008i4(6)_winter200841.html
   My bibliography  Save this article

Robust Two�Stage Least Squares: Some Monte Carlo Experiments

Author

Listed:
  • Sudhanshu Kumar MISHRA

Abstract

The Two�Stage Least Squares (2�SLS) is a well known econometric technique used to estimate the parameters of a multi�equation 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 generalize the 2�SLS to the Weighted Two�Stage Least Squares (W2�SLS), which is robust to the effects of outliers and perturbations. 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. The breakdown point of the method is quite high, somewhere between 45 to 50 percent of the number of points in the data matrix.

Suggested Citation

  • Sudhanshu Kumar MISHRA, 2008. "Robust Two�Stage Least Squares: Some Monte Carlo Experiments," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 3(4(6)_Wint).
  • Handle: RePEc:ush:jaessh:v:3:y:2008:i:4(6)_winter2008:41
    as

    Download full text from publisher

    File URL: http://www.jaes.reprograph.ro/articles/winter2008/RobustArticle10.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Sudhanshu Kumar MISHRA, 2008. "A New Method Of Robust Linear Regression Analysis: Some Monte Carlo Experiments," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 3(3(5)_Fall), pages 261-268.
    Full references (including those not matched with items on IDEAS)

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ush:jaessh:v:3:y:2008:i:4(6)_winter2008:41. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Laura Stefanescu). General contact details of provider: http://edirc.repec.org/data/fmuspro.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.