When using WLS to correct for heteroskedasticity,what weight should be used?
A)whatever weight scales all variables and creates a homoskedastic error variance
B)the inverse of the error variance at x̄
C)whatever weight is determined by the Goldfeld-Quandt test
D)the residuals from the initial regression model

Question

Quizplus · Accepted Answer

The correct weight for using Weighted Least Squares (WLS) to correct for heteroskedasticity is whatever weight scales all variables and creates a homoskedastic error variance. This approach aims to equalize the variance of the errors by applying appropriate weights to each observation.

When Using WLS to Correct for Heteroskedasticity,what Weight Should Be