Unit 11 ECONF16 (assignment)

Unit 11 ECONF16 (assignment) - Name Scott Ly JHUAdvanced...

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Name: Scott Ly __________________________________________ JHU—Advanced Academic Programs Graduate Program for Applied Economics Econometrics 440.606.82 FALL 2016 HW—UNIT #11 DUE SUN Dec 4th by 11:59PM (EST) Please read each question carefully and answer it completely. Please copy/paste software output to the end of the assignment, in an Appendix, and use the information from your output to answer these questions. Unless you are given a different value, please use α = 0.05 in your hypothesis tests. IMPORTANT: I have not “cleaned up” these data sets, although I have in some cases renamed them, which means that there are variables that you may not be using to answer these questions. #1. Chapter 13, C5 [p. 477] using the “rental data set,” [called RENTAL.RAW in the question]. Make sure you include all the necessary discussions, although your discussion may be brief. Please note that this questions is taken directly from the textbook meaning you should complete ALL PARTS of the question as written in your textbook in addition to any notes I have added specific to our course [see below]. Notes for working this question: (i) please report your estimated model (include R 2 and adjusted R 2 ) before you discuss the rest of the question; ^ log ( rent it ) = .848 + .3445 y 90 t + .054 log ( pop it ) + .407log ( avginc it ) + .005 pcstu it + u it (.579) (.037) (.022) (.060) (.001) n = 118, R 2 = 0.865 , ´ R 2 = 0.860 y90 is a positive and statistically significant at the 5% level and even so at the 1% level of significance. Ceteris Paribus, rent has increased 34.45% over the 10-year period of 1980 to 1990. From an economic perspective is a substantial increase in rent over a 10-year period. pcstu is positive and statistically significant at the 5% and even so at the 1% level of significance. Ceteris Paribus, if there is a 1% increase in the student population as a percentage of the city population during the school year rent would increase by 0.5%, which depending on what you are researching could be economically useful or not. (ii) (Hint: in your answer address the issue of a i and its possible presence in the underlying model); The equation to be estimated included the variable a i , however, this explanatory variable was not included in the Pooled OLS estimation. This could mean that a i was included in the error term u it , meaning that the error terms across the two time periods for each city exhibit positive correlation, because of this the standard errors of the intercept and other independent variables are invalid.
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