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Glejser test
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Glejser test for heteroscedasticity, developed in 1969 by Herbert Glejser, is a statistical test, which regresses the residuals on the explanatory variable that is thought to be related to the heteroscedastic variance.[1] After it was found not to be asymptotically valid under asymmetric disturbances,[2] similar improvements have been independently suggested by Im,[3] and Machado and Santos Silva.[4]
![]() | This article may be too technical for most readers to understand. (October 2014) |
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Steps for using the Glejser method
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Step 1: Estimate original regression with ordinary least squares and find the sample residuals ei.
Step 2: Regress the absolute value |ei| on the explanatory variable that is associated with the heteroscedasticity.
Step 3: Select the equation with the highest R2 and lowest standard errors to represent heteroscedasticity.
Step 4: Perform a t-test on the equation selected from step 3 on γ1. If γ1 is statistically significant, reject the null hypothesis of homoscedasticity.
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Software Implementation
Glejser's Test can be implemented in R software using the glejser
function of the skedastic
package.[5] It can also be implemented in SHAZAM econometrics software.[6]
See also
Breusch–Pagan test
Goldfeld–Quandt test
Park test
White test
References
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