Using gret l for Principles of Econometrics, 4th Edition
. Estimating a Regression
The regression is also based on the University town real estate data. The regression is:
price = ві + 61utown + P2sqft + 7(sqft x utown)
+вз age + 62pool + 63fpla. ce + e
The estimated model is
 |
 |
OLS, using observations 1-1000
Dependent variable: price
|
Coefficient |
Std. Error |
t-ratio |
p-value |
|
|
const |
24.5000 |
6.19172 |
3.9569 |
0.0001 |
|
utown |
27.4530 |
8.42258 |
3.2594 |
0.0012 |
|
sqft |
7.61218 |
0.245176 |
31.0477 |
0.0000 |
|
sqft_utown |
1.29940 |
0.332048 |
3.9133 |
0.0001 |
|
age |
-0.190086 |
0.0512046 |
-3.7123 |
0.0002 |
|
pool |
4.37716 |
1.19669 |
3.6577 |
0.0003 |
|
fplace |
1.64918 |
0.971957 |
1.6968 |
0.0901 |
The coefficient on the slope indicator variable sqft x utown is significantly different from zero at the 5% level. This means that size of a home near the university has a different impact on average home price. Based on the estimated model, the following conclusions are drawn:
• The location premium for lots near the university is $27,453
• The change in expected price per additional square foot is $89.12 near the university and $76.12 elsewhere
• Homes depreciate $190.10/year
• A pool is worth $4,377.30
• A fireplace is worth $1649.20
The script that generates these is:
1 scalar premium = $coeff(utown)*1000
2 scalar sq_u = 10*($coeff(sqft)+$coeff(sqft_utown))
3 scalar sq_other = 10*$coeff(sqft)
4 scalar depr = 1000*$coeff(age)
5 scalar sp = 1000*$coeff(pool)
6 scalar firep = 1000*$coeff(fplace)
7 printf "n University Premium = $%8.7gn
8 Marginal effect of sqft near University = $%7.6gn
9 Marginal effect of sqft elsewhere = $%7.6gn
10 Depreciation Rate = $%7.2fn
11 Pool = $%7.2fn
12 Fireplace = $%7.2fn",premium, sq_u, sq_other, depr, sp, firep
Notice that most of the coefficients was multiplied by 1000 since home prices are measured in $1000 increments. Square feet are measured in increments of 100, therefore its marginal effect is multiplied by 1000/100 = 10. It is very important to know the units in which the variables are recorded. This is the only way you can make ecnomic sense from your results.
