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Imhof Approximations to Econometric Estimators

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  • M. Arellano
  • J. D. Sargan

Abstract

The article develops new approximations to the distribution function of a general econometric estimator or test statistic from a linear model. The method relies heavily on the general arguments for the validity of Edgeworth approximations, and produces formulae of a similar type, except that, instead of using the cumulative normal distribution, an Imhof distribution is used derived from the exact distribution of a linear combination of the sample data second moments. On theoretical grounds this might be expected to give better approximations for some estimators. In practice comparisons were made between computed approximations of both types for several simple cases.

Suggested Citation

  • M. Arellano & J. D. Sargan, 1990. "Imhof Approximations to Econometric Estimators," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 57(4), pages 627-646.
    • Handle: RePEc:oup:restud:v:57:y:1990:i:4:p:627-646.
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    File URL: http://hdl.handle.net/10.2307/2298089
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    Cited by:

    1. Altonji, Joseph G & Segal, Lewis M, 1996. "Small-Sample Bias in GMM Estimation of Covariance Structures," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 353-366, July.

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