{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

Slides Econ140A Heteroskedasticity

Slides Econ140A Heteroskedasticity - Goals...

Info iconThis preview shows pages 1–2. Sign up to view the full content.

View Full Document Right Arrow Icon
9/9/2011 1 Heteroskedasticity Copyright Dick Startz 1 Goals Meaning of “heteroskedasticity” What happens to OLS? GLS as an alternative Robust standard errors ARCH (if time) Copyright Dick Startz 2 Assumptions 1. ? ? = ? 1 ? ?1 + ? 2 ? ?2 + ⋯ + ? ? ? ?? + 𝜀 ? , true model of DGP 2. 𝑋 nonrandom (or exogenous), 𝑋 not perfectly collinear 3. 𝐸 𝜀 ? = 0 ∀? 4. Homoskedasticity 𝐸 𝜀 ? 𝜀 ? = 𝜎 2 , ? = ? 0, ? ≠ ? 5. (sometimes) 𝜀~??𝑟?𝑎? Copyright Dick Startz 3 Terminology General: Homoskedasticity 𝐸 𝜀 ? 𝜀 ? = 𝜎 2 , ? = ? 0, ? ≠ ? Heteroskedasticity 𝐸 𝜀 ? 𝜀 ? 𝜎 2 , ? = ? 0, ? ≠ ? Specific: Homoskedasticity 𝐸 𝜀 ? 2 = 𝜎 2 , ∀? Heteroskedasticity 𝐸 𝜀 ? 2 = 𝜎 ? 2 Copyright Dick Startz 4 What facts about OLS are still true? Still best fit Still unbiased Which now fail, and is there a fix-up within OLS? Variance formula wrong. Alternative variance formula sometimes available Gauss-Markov fails Generalized Least Squares (GLS) is the alternative to OLS.
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Image of page 2
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}