Consider the regression model with heterogeneous regression
Question and Solution
Consider the regression model with heterogeneous regression coefficients Yi = b0i + b1i Xi + vi , where (vi , Xi, b0i, b
71 % (867 Review)
Consider the regression model with heterogeneous regression coefficients Yi = b0i + b1i Xi + vi , where (vi , Xi, b0i, b1i) are i.i.d. random variables with b0 = E(b0i ) and b1 = E(b1i ). a. Show that the model can be written as Yi = b0 + b1Xi + ui, where ui = (b0i - b0) + (b1i - b1)Xi + vi. b. Suppose that E3b0i Xi4 = b0, E3b1i Xi4 = b1, and E3vi Xi4 = 0 Show that E3ui Xi4 = 0. c. Show that Assumption #1 and Assumption #2 of Key Concept 4.3 are satisfied. d. Suppose that outliers are rare so that (ui , Xi ) have finite fourth moments. Is it appropriate to use OLS and the methods of Chapters 4 and 5 to estimate and carry out inference about the average values of b0i and b1i ? e. Suppose that b1i and Xi are positively correlated so that observations with larger-than-average values of Xi tend to have larger-than-average values of b1i. Are the assumptions in Key Concept 4.3 satisfied? If not, which assumption(s) is (are) violated? Is it appropriate to use OLS and the methods of Chapters 4 and 5 to estimate and carry out inference about the average value of b0i and b1i?
Your answer will be ready within 2-4 hrs. Meanwhile, check out other millions of Q&As and Solutions Manual we have in our catalog.
Crazy for Study is a platform for the provision of academic help. It functions with the help of a team of ingenious subject matter experts and academic writers who provide textbook solutions to all your course-specific textbook problems, provide help with your assignments and solve all your academic queries in the minimum possible time.
Disclaimer: Crazy For Study provides academic assistance to students so that they can complete their college assignments and projects on time. We strictly do not deliver the reference papers. This is just to make you understand and used for the analysis and reference purposes only.