Consider the following Simple Linear Regression Model: Y = Bo + B₁X + u (a) Discuss what is meant by Heteroscedasticity. Why is it a problem for least squares regression? How can we address that problem? (10 marks) (b)What is the role of the stochastic error term u in regression analysis? What is the difference between the stochastic error term and the residual, e? (8 marks) (c) What is the difference between cross-sectional data, panel data and times series data? Use examples in support of your answer. (7 marks) (d) What are the classical linear regression model assumptions? Which of them are necessary to ensure the unbiasedness of the OLS estimator? (10 marks) 4

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