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American Housing Survey III. Get Stata Data Set. Http://research.umbc.edu/~coates/ec611/owners_stata.zip extract owners_stata.dta this is a Stata 6 format data file Open Stata set mem 40m set matsize 600. Get Stata Data Set. Open the data set You can do this by using the pull down menu
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Get Stata Data Set • Http://research.umbc.edu/~coates/ec611/owners_stata.zip • extract owners_stata.dta • this is a Stata 6 format data file • Open Stata • set mem 40m • set matsize 600
Get Stata Data Set • Open the data set • You can do this by using the pull down menu • You should have 2082 observations, 103 variables • no duplicate controls • no negative lprice, unitsf, lot
Logging your work • log using “your log file name” • This will keep track of everything you do and store results • set more off • this will cause results to not pause every few lines - with a log file recording everything you can always view results there
House values • Different value of a bedroom (bathroom, dining room, etc.) by city (region)? • Yes: estimate separate model for each CMSA • No: • everything is the same: one model • average value higher, contribution of a room the same: different intercepts
Everything is different • Sort cmsa • tabu cmsa • what do you learn? • By cmsa: reg lprice explanatory variables • test for equality of coefficients
Intercept is different • yit = xitb + vt + eit • i is household i, t is CMSA t • Is vt correlated with xit? • Yes, then fixed effects estimation. • Xtreg lprice …, i(cmsa) fe • No, then random effects estimation. • Xtreg lprice …, i(cmsa) • Unsure, do random effects, test using xthaus
Model specification • Functional form • logs • non-parametric • Correct variables • age • commute time • neighborhood