So I am reviewing chapter 7's material on regression, and it has honestly been a

Thanks...

Edit: cleaned up a typo and wanted to add that of course the standard error should be unbiased, its just that point isn't readily jumping out at me in the math and I'd appreciate any clarification.

*long while*since I've done this deep of a dive into econometric material, and I couldn't help notice that on the face of it, it looks like the variance/standard error of the regression parameters are biased which makes zero sense to me as the OLS estimators are supposed to be BLUEs (per the Gauss-Markov theorem). In the derivation of 7.12-7.14 any time we use \[ \sigma_x^2 \], we divide the squared deviations of x only by*n*and not*n-2.*From chapter 5 we saw that the variance estimator which only divides by*n*is a biased estimator of the sample variance, which leads to my question. I would assume that if we mix biased (the sample variance of*x*) and unbiased (the sample variance of the residuals) estimators, the resulting estimator would therefore be biased.... Is there some nuance I'm just not seeing here in the GARP material (or in*Miller,*or in*Undergraduate Econometrics*by Hill/Griffith/Judge)?Thanks...

Edit: cleaned up a typo and wanted to add that of course the standard error should be unbiased, its just that point isn't readily jumping out at me in the math and I'd appreciate any clarification.

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