IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/0015.html
   My bibliography  Save this paper

A Comparison of FIML and Robust Estimates of a Nonlinear Macroeconomic Model

Author

Listed:
  • Ray C. Fair

Abstract

The prediction accuracy of six estimators of econometric models are compared. Two of rthe estimators are ordinary least squares (OLS) and full-information maximum likelihood. (FML). The other four estimators are robust estimators in the sense that they give less weight to large residuals. One of the four estimators is approximately equivalent to the least-absolute-residual (LAR) estimator, one is a combination of OLS for small residuals and LAR for large residuals, one is an estimator proposed by John W. Tukey, and one is a combination of FIML and LAR. All of the estimators account for the first-order serial correlation of the error terms. The main conclusion is that robust estimators appear quite promising for the estimation of econometric models. Of the robust estimators considered in the paper, the one based on minimizing the sum of the absolute values of the residuals performed the best. The FIML estimator and the combination of the FIML and LAR estimators also appear promising.

Suggested Citation

  • Ray C. Fair, 1973. "A Comparison of FIML and Robust Estimates of a Nonlinear Macroeconomic Model," NBER Working Papers 0015, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:0015
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w0015.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chow, Gregory C, 1973. "On the Computation of Full-Information Maximum Likelihood Estimates for Nonlinear Equation Systems," The Review of Economics and Statistics, MIT Press, vol. 55(1), pages 104-109, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. David A. Belsley & Kent D. Wall, 1976. "Estimation of Econometric Model Using Nonlinear Full Information Maximum Likelihood: Preliminary Computer Results," NBER Working Papers 0142, National Bureau of Economic Research, Inc.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ray C. Fair, 1974. "On the Robust Estimation of Econometric Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 667-677, National Bureau of Economic Research, Inc.
    2. Ernst R. Berndt & Bronwyn H. Hall & Robert E. Hall & Jerry A. Hausman, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 653-665, National Bureau of Economic Research, Inc.
    3. Amemiya, Takeshi, 1983. "Non-linear regression models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 6, pages 333-389, Elsevier.
    4. David A. Belsley & Kent D. Wall, 1976. "Estimation of Econometric Model Using Nonlinear Full Information Maximum Likelihood: Preliminary Computer Results," NBER Working Papers 0142, National Bureau of Economic Research, Inc.
    5. David A. Belsley, 1974. "Estimation of Systems of Simultaneous Equations, and Computational Specifications of GREMLIN," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 551-614, National Bureau of Economic Research, Inc.
    6. Marianna Belloc, 2007. "Protection for Sale in the EU," Working Papers in Public Economics 100, University of Rome La Sapienza, Department of Economics and Law.

    More about this item

    Statistics

    Access and download statistics

    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:nbr:nberwo:0015. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.