Question

Discuss how you would ensure that an Ordinary Least Squares regression meet the BLUE requirement. (17marks)

Answer 1

Ordinary Least Square (OLS) Assumptions:

OLS Assumption 1: The linear regression model is “linear in parameters.”

OLS Assumption 2: There is a random sampling of observations

OLS Assumption 3: The conditional mean should be zero.

OLS Assumption 4: There is no multi-collinearity (or perfect collinearity).

OLS Assumption 5: Spherical errors: There is homoscedasticity and no autocorrelation.

OLS assumptions are extremely important. If the OLS assumptions 1 to 5 hold, then according to Gauss-Markov Theorem, OLS estimator is Best Linear Unbiased Estimator (BLUE).

So on behalf of these estimations we can say that an Ordinary Least Square (OLS) regression meet the BLUE requirement.