
Introductory Econometrics: A Modern Approach 6th Edition by Jeffrey M Wooldridge
Edition 6ISBN: 130527010X
Introductory Econometrics: A Modern Approach 6th Edition by Jeffrey M Wooldridge
Edition 6ISBN: 130527010XLet
be the OLS estimate from the regression of y on X. Let A be a (k + 1) × (k + 1) nonsingular matrix and define zt = xtA, t = 1,….,n. Therefore, zt is 1 × (k + 1) and is a nonsingular linear combination of xt. Let Z be the n × (k + 1) matrix with rows zt. Let
denote the OLS estimate from a regression of y on Z.
(i) Show that
=A-1
.
(ii) L et
be the fitted values from the original regression and let . y t be the fitted values from regressing y on Z. Show that
=
, for all t =- 1, 2,…., n. How do the residuals from the two regressions compare?
(iii) Show that the estimated variance matrix for
is
A1(X?X)1A1?, where
is the usual variance estimate from regressing y on X.
(iv) L et the
be the OLS estimates from regressing yt on 1, xt1,...,xtk, and let the
be the OLS estimates from the regression of yt on 1, a1xt1,…,ak xtk, where aj ? 0, j =1,…,k. Use the results from part (i) to find the relationship between the
and the
(v) Assuming the setup of part (iv), use part (iii) to show that se(
) = se(
)/aj.
(vi) Assuming the setup of part (iv), show that the absolute values of the t statistics for
and
are identical.
Step 1 of 7
Given:
1)
is the OLS estimate of regression of y on X
2) A is
nonsingular matrix
3)
and that it is
nonsingular linear combination of 
4) The Z be
matrix with rows 
5) The
is the OLS estimate from the regression of y on Z
(i)
The matrix notation for the OLS estimate of
is given by:

Given that 
Since,

That means

Hence, 
Step 2 of 7
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Step 7 of 7
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=A-1
.
be the fitted values from the original regression and let . y t be the fitted values from regressing y on Z. Show that
=
, for all t =- 1, 2,…., n. How do the residuals from the two regressions compare?
is
A1(X?X)1A1?, where
is the usual variance estimate from regressing y on X.
be the OLS estimates from regressing yt on 1, xt1,...,xtk, and let the
be the OLS estimates from the regression of yt on 1, a1xt1,…,ak xtk, where aj ? 0, j =1,…,k. Use the results from part (i) to find the relationship between the
and the 
) = se(
)/aj.
and
are identical.
