Q6. In the model specified in Q5, you decide to test the possibility that explanatory variable (s) is (are) irrelevant b

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Q6 In The Model Specified In Q5 You Decide To Test The Possibility That Explanatory Variable S Is Are Irrelevant B 1 (90.39 KiB) Viewed 91 times

Q6 In The Model Specified In Q5 You Decide To Test The Possibility That Explanatory Variable S Is Are Irrelevant B 2 (90.39 KiB) Viewed 91 times

Q6. In the model specified in Q5, you decide to test the possibility that explanatory variable (s) is (are) irrelevant by dropping one or more variables from model and rerunning the equation. Discuss the reason why the variable(s) should and or should not be included in your model. Specify a final regression model which includes all relevant variable(s) that you identified as relevant explanatory variable(s) (Hint: be sure to use our four specification criteria). Present the results in a table and discuss them. (15 marks) Q7. Explain a distinction between an equation that is linear in the coefficients and one that is linear in variables. Examine whether log transformation of dependent and independent variables provides better estimates compared to regression analysis conducted using level-level regression model estimated in Q6. Furthermore, can you compare R-squared estimated results of level-level model with the estimated regression results of the double log regression model? If not, explain the rationale behind it. Present your estimated results using adouble log model in a table and discuss your findings. (15 marks) Q8. (8a) Specify your final choice of estimated model following analysis conducted at Q6 and Q7. What do we mean by heteroskedasticity? Apply alternate methods of testing for heteroskedasticity in your model. Discuss the strengths and weaknesses of those alternate methods for heteroskedasticity. Present your estimated model results in a table 3 and discuss the heteroskedasticity implications for estimated coefficients in your model. (15 marks) (8b) What are the remedies for heteroskedasticity? Use an alternate test to correct for heteroskedasticity in the estimated model and reproduce the estimated results based on the heteroskedasticity corrected standard errors in a table. Compare this estimated model with your estimated model results obtained in 8(a) and discuss your findings. (15 marks)