The data file stockton5_small contains observations on 1200 houses sold in Stockton, California, during 1996–1998.
In this Stata file, which is in Brightspace, you are given data on price = selling price of homes (thousands of dollars), and
livarea = living area (hundreds of square feet), which is an indicator of lot size. The homes are also classified as large and
small lots. In the data file, the variable lgelot=1 if the lot is large and 0 if small. Use Stata to answer the following
questions.
(a) Obtain and compare the average price of small and large lot sizes. (2 points)
(b) Estimate the regression model price = β1 + β2livarea + e separately for (i) large lots sizes only, (ii) small lot only, and
(iii) both small and large lots combined.
1. Present the three estimated equations along with sample size. You need to write the equations by hand. (4 points)
2. Interpret the estimate of livarea coefficient in each case. What does a comparison of the three estimates suggest?
(3 points)
3. Predict the increase in house prices if living area were to increase by 1 thousand square feet. (2 points)
Note: In answering this question you could adopt the approach I showed in class for wage functions by sex; that is, using
the bysort command in Stata. Here the equivalent of the sex variable is the lot size variable.
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