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Unformatted text preview: Final Exam Econ 360  Spring 2009 Professor Mumford Thursday, May 7 2009 [email protected] KRAN G002 • 7:00 – 9:00pm YOUR NAME: Answer all questions clearly and legibly. Show all of your work in the space provided. Do not use additional sheets or write on the back of the page. Do not refer to your notes, the text book, or any other materials during the exam. There are 100 points possible. Maximum points for each question are noted in parentheses. You have two hours to complete the exam. Good luck! 1. (8 points) Define or explain the following terms: a. (2 points) heteroskedasticity b. (2 points) tstatistic c. (2 points) fixed effects estimation d. (2 points) linear probability model 2. (12 points) a. (3 points) State assumption E.1 (linear in parameters) and give an example where this assumption is violated. b. (3 points) State assumption E.2 (no perfect collinearity) and give an example where this assumption is violated. c. (6 points) In the multiple regression model, derive the variancecovariance matrix of the OLS estimator under E.1  E.4 3. (14 points) We are interested in estimating a wage regression to measure the return to education: ln( wage ) i = β + β 1 education i + u i a. (2 points) Is ˆ β 1 a good measure of the return to education? Explain. b. (6 points) Suppose that ability (which is unobserved) is correlated with both the wage and the level of education. Derive the bias in ˆ β 1 . c. (2 points) Suppose that we have a potential instrument for education, the distance that a student lives from the nearest university. What conditions must be satisfied for this variable, distance , to be a valid instrument? d. (4 points) Describe how to do IV or twostate least squares estimation using distance as an instrument for education . 4. (16 points) a. (4 points) What is the DurbinWatson Test designed to detect? Explain what this is and how its presence would affect the OLS estimates....
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 Regression Analysis, OLS, female athlete, hsize hsizesq hsperc, colgpa hsize hsizesq

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