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Unformatted text preview: ECONOMETRICS I Take Home Final Examination Fall 2010 Professor William Greene Phone: 212.998.0876 Office: KMC 790 Home page:ww.stern.nyu.edu/~wgreene email: wgreene@stern.nyu.edu URL for course web page: www.stern.nyu.edu/~wgreene/Econometrics/Econometrics.htm Today is Thursday, December 9, 2010. This exam is due by 3PM, Monday, December 20, 2010. You may submit your answers to me electronically as an attachment to an email if you wish. Please do not include a copy of the exam questions with your submission; submit only your answers to the questions. Your submission for this examination is to be a single authored project you are assumed to be working alone. NOTE: In the empirical results below, a number of the form .nnnnnnE+aa means multiply the number .nnnnnn by 10 to the aa power. Eaa implies multiply 10 to the minus aa power. Thus, .123456E04 is 0.0000123456. This test comprises 150 points in two parts. Part I contains 10 questions, allocated 10 points per part, based on general econometric methods and theory as discussed in class. Part II asks you to dissect a recently published article that was documented in the popular press. This course is governed by the Stern honor code: I will not lie, cheat or steal to gain an academic advantage, or tolerate those who do. Signature ___________________________________________ 1 Department of Economics Part I. Applied Econometrics 1. Properties of the least squares estimator a. Show (algebraically) how the ordinary least squares coefficient estimator, b , and the estimated asymptotic covariance matrix are computed. b. What are the finite sample properties of this estimator? Make your assumptions explicit. c. What are the asymptotic properties of the least squares estimator? Again, be explicit about all assumptions, and explain your answer carefully. d. How would you compare the properties of the least absolute deviations (LAD) estimator to those of the ordinary least squares (OLS) estimator? Which is a preferable estimator? 2. The paper Farsi, M, M. Filippini, W. Greene, Efficiency Measurement in Network Industries, Application to the Swiss Railroads, Journal of Regulatory Economics , 28, 1, 2005, pp. 6990 is an analysis of an unbalanced panel of data on 50 railroads for 13 years, 605 observations in total. The variables in the data set are ct = total cost q = total output, sum of freight, passenger and mail pe = price of electricity pk = price of capital pl = price of labor narrow = dummy for narrow gauge track tunnel = dummy variable for long tunnels on routes rack = dummy variable for a certain track configuration I propose first to analyze the cost data with a loglinear model. My first model is lnc it = 1 + 2 lnq it + 3 lnpe it + 4 lnpl it + 5 lnpk it + 6 narrow i + 7 tunnel i + 8 rack i + it , it ~ N[0, 2 ]....
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 Fall '11
 WilliamGreene

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