2 Let B be the (k + 1) × 1 vector of OLS estimates. (i) Show that for any (k + 1) × 1 vector b, we can write the sum of squared residuals as SSR(b) = û'û + (ß – b)'X'X(ß – b). {Hint: Write (y – Xb)'(y – Xb) = [û + X(ß – b)]'[û + X(ß – b)] and use the fact that X'û = 0.} %3D earning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). t any suppressed content does not materially affect the overall learming experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. ii) Explain how the expression for SSR(b) in part (i) proves that B uniquely minimizes SSR(b) over all possible values of b, assuming X has rank k + 1.

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