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1 BUEC 333 Assignment #3 Summer 2011 Instructor: Pierre Nguimkeu Due Friday July 22 IN CLASS Question 1 (a) Briefly identify the following in words or equations as appropriate: i. The major consequence of including an irrelevant variable in a regression equation. ii. Four valid criteria for determining whether a given variable belongs in an equation. iii. The elasticity of Y with respect to X in: lnY = ß 0 +ß1 lnX + e iv. The sign of the bias on the coefficient of age caused by omitting experience in an equation explaining the salaries of various workers. (b) Carefully outline (be brief!) a description of the problem typically referred to as pure autocorrelation. i. What is it? ii. What are its consequences? iii. How do you diagnose it? iv. What do you do to get rid of it? Question 2 A model of the number of cars sold in the United States from 1980 through 2004 produced the following results (standard errors in parentheses): Ct = 3738 – 48.0Pt + 10.0Yt + 6.0At – 360.0Rt (12.0) (2.0) (2.0) (120.0) R2 = 0.85 DW = 1.86 N = 25 (annual) Where: Ct = thousands of cars sold in year t Pt = price index for domestic cars in year t Yt = disposable income (billions of dollars) in year t At = billions of dollars of auto industry advertising expenditures in year t Rt = the interest rate in year t (a) Hypothesize the expected signs of the coefficients and test the appropriate null hypotheses at the 1% level. (b) What econometric problems appear to be present in this equation? Why? (c) Suppose you were now told that the simple correlation coefficients between P, A, and Y were all between 0.88 and 0.94 and that a Park test with Y as Z produced a t-score of 0.50. Would your answer to part (b) above change? Why or why not? How would it change? (d) What suggestions would you have for another run of this regression?
2 Question 3: Eviews exercise For this assignment, use the data in the file japan.wf1 found on the course website. These data are yearly observations on 115 Japan firms…
1 BUEC 333 Assignment #3 Summer 2011 Instructor: Pierre Nguimkeu Due Friday July 22 IN CLASS Question 1 (a) Briefly identify the following in words or equations as appropriate: i. The major consequence of including an irrelevant variable in a regression equation. ii. Four valid criteria for determining whether a given variable belongs in an equation. iii. The elasticity of Y with respect to X in: lnY = ß 0 +ß1 lnX + e iv. The sign of the bias on the coefficient of age caused by omitting experience in an equation explaining the salaries of various workers. (b) Carefully outline (be brief!) a description of the problem typically referred to as pure autocorrelation. i. What is it? ii. What are its consequences? iii. How do you diagnose it? iv. What do you do to get rid of it? Question 2 A model of the number of cars sold in the United States from 1980 through 2004 produced the following results (standard errors in parentheses): Ct = 3738 – 48.0Pt + 10.0Yt + 6.0At – 360.0Rt (12.0) (2.0) (2.0) (120.0) R2 = 0.85 DW = 1.86 N = 25 (annual) Where: Ct = thousands of cars sold in year t Pt = price index for domestic cars in year t Yt = disposable income (billions of dollars) in year t At = billions of dollars of auto industry advertising expenditures in year t Rt = the interest rate in year t (a) Hypothesize the expected signs of the coefficients and test the appropriate null hypotheses at the 1% level. (b) What econometric problems appear to be present in this equation? Why? (c) Suppose you were now told that the simple correlation coefficients between P, A, and Y were all between 0.88 and 0.94 and that a Park test with Y as Z produced a t-score of 0.50. Would your answer to part (b) above change? Why or why not? How would it change? (d) What suggestions would you have for another run of this regression?
2 Question 3: Eviews exercise For this assignment, use the data in the file japan.wf1 found on the course website. These data are yearly observations on 115 Japan firms…
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