In: Statistics and Probability
The Gauss-Markov theorem says that the OLS estimator is the best linear unbiased estimator. Explain which assumptions are needed in order to verify Gauss-Markov theorem?
Consider the Cobb-Douglas production function
When all the assumptions of classical linear regression holds then OLS is BLUE, this is ensured by Gauss Markov theorem.
The assumptions are:
The regression model is linear in the coefficients and the error term
The error term has a population mean of zero
All independent variables are uncorrelated with the error term
Observations of the error term are uncorrelated with each other
The error term has a constant variance (no heteroscedasticity)
No independent variable is a perfect linear function of other explanatory variables
The error term is normally distributed (this assumption is not required for For Gauss markov theorem and is only useful for testing of Hypothesis)
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