ecm06-hw3-solutions

ecm06-hw3-solutions - ECN 140/Winter 06 Econometrics...

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ECN 140/Winter 06 1 Econometrics ASSIGNMENT 3 100 POINTS TOTAL DUE: by Tuesday, March 14 , 3:20 p.m. **IMPORTANT REMINDER: LATE ASSIGNMENTS CANNOT BE ACCEPTED – NO EXCEPTIONS** Note : Apart from Questions 4, the rest of the questions are computer-assisted assignments. Partial answers for the estimation part of these later questions are provided below. However, do make an effort to answer the problems without referring to the solution keys initially. All output printouts from the computer-assisted assignments must be attached to the final answers that you plan to hand in for credit. Please refer to the Division of Social Sciences Computer Lab’s website at http://dsslab.ucdavis.edu/ for the free time periods available for you to do your computer assignments. 1. [15] Use: WAGE1.RAW a) Use OLS to estimate the equation 2 log( ) 01 2 3 wage educ exper exper u ββ β = ++ + + and report the result using the usual format. b) Is exper 2 statistically significant at the 1% level? c) Using the approximation n m m % 100( 2 ) , 23 wage exper exper ∆= + find the approximate return to the fifth year of experience. What is the approximate return to the twentieth year of experience? d) At what value of exper does the additional experience actually lower predicted log (wage)? How many people have more experience in this sample?

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ECN 140/Winter 06 2 Solutions: a) The estimated equation is n log( ) wage = 0.128 + 0.0904 educ + 0.0410 exper – 0.000714 exper 2 (0.106) (0.0075) (0.0052) (0.000116) n = 526, R 2 = 0.300, 2 R = 0.296. b) The t statistic on exper 2 is about –6.16 , which has a p -value of essentially zero. So exper is significant at the 1% level(and much smaller significance levels). c) To estimate the return to the fifth year of experience, we start at exper = 4 and increase exper by one, so exper = 1: n % 100[.0410 2(.000714)4] 3.53%. wage ∆≈ Similarly, for the 20 th year of experience, n % 100[.0410 2(.000714)19] 1.39% wage d) The turnaround point is about 0.041 /[ 2 ( 0.000714 )] 28.7 years of experience. In the sample, there are 121 people with at least 29 years of experience. This is a fairly sizeable fraction of the sample. 2. [15] Use: WAGE2.RAW a) Estimate the model log( ) 01 2 3 4 5 6 7 wage educ exper tenure married black south urban u β ββ =+ + + + + + + + and report the results in the usual from. Holding other factors fixed, what is the approximate difference in the monthly salary between blacks and non-blacks? Is this difference statistically significant? b) Add the variable exper 2 and tenure 2 to the equation and show that they are jointly insignificant at even the 20% level. c) Extend the original model to allow the return to education to depend on race and test whether the return on education does depend on race. d) Again, start with the original model, but now allow wages to differ across four groups of people: married and black, married and non-black, single and black, and single and non-black. What is the estimated wage differential between married blacks and married non-blacks?
ECN 140/Winter 06 3 Solutions: a) The estimated equation is n log( ) wage = 5.40 +0.0654 educ + 0.0140 exper + 0.0117 tenure (0.11) (0.0063) (0.0032) (0.0025) +0.199 married 0.188 black 0.091 south + 0.184 urban (0.039) (0.038) (0.026) (0.027) n = 935, R 2 = 0.253.

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This note was uploaded on 08/27/2011 for the course ECON 7043 taught by Professor Projim during the Three '11 term at University of Adelaide.

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ecm06-hw3-solutions - ECN 140/Winter 06 Econometrics...

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