# ps5 - Problem Set 5 ECON 837 Prof Simon Woodcock Spring...

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

Problem Set 5 ECON 837 Prof. Simon Woodcock, Spring 2006 Due: Monday Feb 27 1. Consider the least squares residual vector e from the regression of y on X with V ar [ y ] = 2 I n : (a) Let e j be any element of e : Show V ar [ e j ] 2 : (b) What is the rank of E [ ee 0 ]? 2. Suppose we have the linear regression model y = X + " with E [ " ] = 0 and E [ "" 0 ] = 2 I n : Suppose X = [ i X 2 ] where i is an n ± vector of ones and X 2 is n ² ( k ± 1) and measured in deviations from means. Show that the least squares estimator of the intercept (the parameter on i ) is uncorrelated with the least squares estimator of the slopes (the parameters on X 2 ). 3. Suppose you estimate the linear regression y = X 1 1 + X 2 2 + " R 2 to be satisfactory, you reject the null hypothesis that all slope coe¢ cients are zero (the F t -statistics on the slope coe¢ cients. (a) What do you think the problem is? Do you suspect any assumptions of the linear

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

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

## This note was uploaded on 10/08/2011 for the course PHYS 102 taught by Professor Thewalt during the Spring '09 term at Simon Fraser.

### Page1 / 2

ps5 - Problem Set 5 ECON 837 Prof Simon Woodcock Spring...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online