11. Consider the linear regression modelYt = Bo + B1(x1)e + ..+ Bk(Xx)t + Ut, t 1,... T,where the regressors 1, x1,...,X and errors u satisfy the Gauss-Markov assumptions.Let R? be the (centered) R2 of the regression of xj on all other regressors including aconstant. Show that for the OLS estimators of B1,...Bk it holdsvar ß, =T. Sx(1-R)Remark: The factorRis called the variance inflation factor and is used as an indicator of multicollinearityHint. Use the Frisch-Waugh theorem to partial out all other regressors,

Gauss Markov assumptions are used to estimate α and β that are best linear unbaised estimators: Best…

Answered: Yt = Bo + B1(x1)t ++ Br(Xx)t + Ut, t…

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter4: Eigenvalues And Eigenvectors

Section4.6: Applications And The Perron-frobenius Theorem

Problem 70EQ

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Yt = Bo + B1(x1)t ++ Br(Xx)t + Ut, t 1,.,T, where the regressors 1, x1,...Xk and errors u satisfy the Gauss-Markov assumptions. Let R? be the (centered) R2 of the regression of x on all other regressors including a constant. Show that for the OLS estimators of B1,....Bk it holds var B T.SKM(1-R)