Final Exam 2006 key

Final Exam 2006 key - Dec. 14, 2006 ECON 240A-1 Final L....

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Dec. 14, 2006 ECON 240A- 1 L. Phillips Final Answer all five questions . They are weighted equally. 1. (30) For a regression using ordinary least squares, OLS, y = b 0 + b 1 x 1 + b 2 x 2 …+ b n x n + e, we make certain assumptions about the properties of the error term, e. a. List five assumptions about e i. _ E(e) = 0, expected value of error equals zero ___________________ ii. _ Cov(xe) = 0, error and explanatory variable independent ______ iii. _ Cov(e j e k ) =0, j ≠k, errors are independent ____________________ iv. _ Var(e j ) = σ 2 , all j, errors are homoskedastic __________________ v. _ e~N(0, σ 2 ), error is normally distributed _____________________ b. For one-way analysis of variance, using regression of a quantitative variable against binary dummy explanatory variables (zero/one) we used one of these assumptions to interpret the meaning of the regression coefficients, b 0 , b 1 etc. Which assumption did we use? __ E(e) = 0 _______________ c. Which assumption is frequently violated in time series regressions? ___ Cov(e j e k ) =0, j ≠k ________________ d. Explain the difference between homoskedasticity and heteroskedasticity. _ homeskedastic: errors have same variance; _ heteroskedastic : error variance varies across observations __________ e. One can obtain estimates of the OLS parameters by minimizing the sum of squared residuals with respect to each regression parameter without making any assumptions about the error term e. So why are these assumptions about the error term important? _ The properties of the parameter estimates such as _ maximum likelihood estimators depends on this assumption as well as hypothesis tests using Student’s t-distribution and the calculation of confidence intervals ____ 2. (30) The number of days spent recovering from a heart attack was studied for a random sample of 300 patients in the US. The duration of days recovering was used to calculate the Kaplan-Meier estimates of (1) the hazard function, (2) the cumulative hazard
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Dec. 14, 2006 ECON 240A- 2 L. Phillips Final function, and (3) the survivor function, as displayed in Table 2-1. These Kaplan-Meier estimates for the hazard rate and the cumulative hazard rate are plotted in Figures 2-1 and 2-2. Table 2-1: Kaplan-Meier Estimates of Days Recovering from a Heart Attack, US US days # ending # at risk interval hazard rate cumulative hazard rate ratio Survivor Function (# ending/# at risk) (# at risk - # ending)/# at risk 8 1 300 0.0033 0.0033 0.997 0.997 9 1 299 0.0033 0.0066 0.997 0.994 12 4 298 0.0134 0.0201 0.987 0.980 13 1 294 0.0034 0.0235 0.997 0.977 14 4 293 0.0137 0.0371 0.986 0.964 15 10 289 0.0346 0.0717 0.965 0.930 16 3 279 0.0108 0.0825 0.989 0.920 17 8 276 0.0290 0.1115 0.971 0.894 18 8 268 0.0299 0.1413 0.970 0.867 19 13 260 0.0500 0.1913 0.950 0.824 20 12 247 0.0486 0.2399 0.951 0.784 21 11 235 0.0468 0.2867 0.953 0.747 22 14 224 0.0625 0.3492 0.938 0.700 23 13 210 0.0619 0.4111 0.938 0.657 24 9 197 0.0457 0.4568 0.954 0.627 25 16
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This note was uploaded on 12/09/2010 for the course ECON 240a taught by Professor Staff during the Spring '08 term at UCSB.

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Final Exam 2006 key - Dec. 14, 2006 ECON 240A-1 Final L....

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