Gauss-Markov Theorem
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# Gauss-Markov Theorem ## 3.1 The BLUE Property **Gauss-Markov Theorem:** Under the classical assumptions (linearity, zero mean errors, homoscedasticity, uncorrelated errors), the OLS estimator $\hat{\boldsymbol{\beta}}$ is BLUE — Best Linear Unbiased Estimator. ### Assumptions 1.

Gauss-Markov Theorem
3.1 The BLUE Property
Gauss-Markov Theorem: Under the classical assumptions (linearity, zero mean errors, homoscedasticity, uncorrelated errors), the OLS estimator β^ is BLUE — Best Linear Unbiased Estimator.
Assumptions
- Linearity: y=Xβ+ε
- Zero mean: E[ε]=0
- Homoscedasticity: Var(εi)=σ2 (constant variance)
- Uncorrelated errors: Cov(εi,εj)=0 for i=j
- Full rank: X has full column rank