LAURIER
Business & Economics
Wilfrid Laurier University
School of Business and Economics
EC655 (Econometrics)
Instructor: Jean Eid
Assignment # 1
1
Statistics
Question-1 Let X, Y, and Z be random variables with E X = X , E Y = Y , E Z = Z , and Var X =
2
LAURIER
Business & Economics
Wilfrid Laurier University
School of Business and Economics
(Econometrics)
Instructor: Jean Eid
Lecture Notes: Gauss-Markov Theorem
Assume that the following hold
MLR-1 Linearity in the parameter
MLR-2 Independence of the erro
Class Notes for Econometrics
Expectation of Ordinary Least Squares under the Gauss
Markov assumptions
Jean Eid
Assume that the following hold
MLR1 Linearity in the parameter
MLR2 Independence of the error term u and random sampling
MLR3 No perfect Colline
Class Notes for EC355
Ordinary Least Squares and Method of Moments
Derivation under the Gauss Markov assumptions
Jean Eid
Assume that the following hold
MLR1 Linearity in the parameter eg. suppose we have
y = 0 + 1 x1 + 2 x2 + 3 x3 + + k xk + u
MLR2 Indep
Probability Review
John Norstad
j.norstad@mac.com
http:/homepage.mac.com/j.norstad
September 11, 2002
Updated: February 10, 2005
Abstract
We dene and review the basic notions of variance, standard deviation, covariance, and correlation coecients for rando
Class Notes for Econometrics
Variance of Ordinary Least Squares under the Gauss
Markov assumptions
Jean Eid
Assume that the following hold
MLR-1 Linearity in the parameter
MLR-2 Independence of the error term u and random sampling
MLR-3 No perfect Colline
Econometrics, Fall 2015
Jean Eid
Wilfrid Laurier University
LAZARIDIS
Business & Economics
Variance of
1
1/20
First recall
yi = 0 + 1 xi + ui
LAZARIDIS
Business & Economics
Variance of
1
2/20
First recall
yi = 0 + 1 xi + ui
n
X
xi x yi
1 =
i=1
n
X
2
x