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Heteroscedasticity Diagnostics Based on "Corrected" Standard Errors

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Author Info
Edward E. Leamer

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Abstract

Weights are found for weighted least squares estimates such that a selected coefficient (a) changes by one standard deviation or (b) changes in sign. The length of the vector of weight changes is equal to the usual OLS standard error divided by the White-corrected standard errors. Thus the White-corrected standard errors can help decide if it is necessary to adjust the location of the confidence sets to correct for heteroscedasticity. The vector of weight changes is similar to the effect of omitting observations, one at a time. The sensitivity diagnostics of Belsley, Kuh and Welsch are therefore linked with heteroscedasticity issues.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0094.

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Date of creation: Jan 1991
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Handle: RePEc:nbr:nberte:0094

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  1. Leamer, Edward E & Leonard, Herman B, 1983. "Reporting the Fragility of Regression Estimates," The Review of Economics and Statistics, MIT Press, vol. 65(2), pages 306-17, May. [Downloadable!] (restricted)
  2. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May. [Downloadable!] (restricted)
  3. Edward E. Leamer, 1983. "Global Sensitivity Results for Generalized Least Squares Estimates," UCLA Economics Working Papers 006, UCLA Department of Economics. [Downloadable!]
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