Question

In: Statistics and Probability

The Gauss-Markov theorem says that the OLS estimator is the best linear unbiased estimator.


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

Solutions

Expert Solution

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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