A Comparison of FIML and Robust Estimates of a Nonlinear Macroeconomic Model / Ray C. Fair.

Author
Fair, Ray C. [Browse]
Format
Book
Language
English
Published/​Created
  • Cambridge, Mass. National Bureau of Economic Research 1973.
  • Cambridge, Mass. : National Bureau of Economic Research, 1973.
Description
1 online resource: illustrations (black and white);

Details

Subject(s)
Series
  • Working Paper Series (National Bureau of Economic Research) no. w0015. [More in this series]
  • NBER working paper series no. w0015
Summary note
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.
Notes
October 1973.
Bibliographic references
Includes bibliographical references.
Source of description
Print version record
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