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Unformatted text preview: Homework 3 Economics 120B Due December 5 th , 2008 at the beginning of the lecture All the files mentioned in this homework are available in our course Webct. Print the output (.log) file from your STATA work and staple it to your answer sheet. Some questions are theoretical and you will not need Stata to answer them. Try to use Stata as much as you can for all the other questions. Dont forget to set up your work by: a. Setting the central directory to C:\Econ120B (C:\Econ120B is just a suggestion: you can call your central directory whatever you want). b. Opening a log file. YOU NEED TO PRINT OUT YOUR LOG FILE SO DONT FORGET TO OPEN IT. You can do that by typing the command: log using hmw3.log, replace c. After opening each of the datasets you will need for each question, save your data as a new dataset (for example, you might call it filename _hmw3_out.dta). Now answer the following questions: 1) The dataset hprice1.dta was collected from the real estate pages of the Boston Globe during 1990. These were homes selling in the Boston, MA area. a. Use the dataset to estimate the model u bdrms qrft price + + + = 2 1 s * b. What is the estimated increase in price for a house with one more bedroom, holding square footage constant? c. What is the estimated increase in price for a house with an additional bedroom that is 140 square feet in size? Compare this to your answer to part b. d. What percentage of the variation in price is explained by square footage and number of bedrooms? e. The first house in the sample has sqrft = 2,438, and bdrms = 4. Find the predicted selling price for this house from the OLS regression line. f. The actual selling price for the first house in the sample was $300,000 (so price = 300). Find the residual for this house. Does it suggest that the buyer underpaid or overpaid for the house? g. We want to test the rationality of assessments of housing prices. To do that, we regress the following single regression: u assess price + + = 1 , where price is the house price and assess is the assessed housing value (before the house was sold). Report your estimated regression line....
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This note was uploaded on 02/01/2009 for the course ECON 23423 taught by Professor Staff during the Winter '08 term at UCSD.
- Winter '08