TABLE 2
Estimation results of hedonic price model
Variables |
COEFFICIENTS |
T- |
PROB. T-STAT |
STANDARDIZED |
CONSTANT |
11.4431 |
236.8905 |
0.0000 |
- |
SURFACE AREA |
0.0044 |
14.0600 |
0.0000 |
0.7237 |
(SURFACE AREA)2 |
-2.99E-06 |
-6.4759 |
0.0000 |
-0.3530 |
NUMBER OF ROOMS |
0.0235 |
2.5089 |
0.0122 |
0.0506 |
NUMBER OF BATHROOMS |
0.1720 |
5.8588 |
0.0000 |
0.2871 |
(NUMBER OF BATHROOMS)2 |
-0.0141 |
-2.1521 |
0.0315 |
-0.1265 |
AGE OF THE BUILDING |
-0.0025 |
-3.1471 |
0.0017 |
-0.0603 |
FLOORS |
-0.0103 |
-5.2621 |
0.0000 |
-0.0627 |
DISTRICT2 |
0.1430 |
4.6906 |
0.0000 |
0.0703 |
DISTRICT4 |
-0.0308 |
-2.1053 |
0.0354 |
-0.0221 |
DISTRICT5 |
-0.1581 |
-6.1784 |
0.0000 |
-0.0687 |
DISTRICT6 |
-0.0462 |
-3.2302 |
0.0013 |
-0.0372 |
DISTRICT7 |
-0.0338 |
-2.0636 |
0.0392 |
-0.0233 |
DISTRICT10 |
0.0334 |
1.6728 |
0.0945 |
0.0230 |
DISTANCE TO DOWNTOWN |
0.0699 |
4.6526 |
0.0000 |
0.0523 |
PROXIMITY TO THE SEASIDE |
0.1266 |
7.2538 |
0.0000 |
0.0931 |
APARTMENT/STUDIO |
-0.0858 |
-2.2651 |
0.0236 |
-0.0273 |
DETACHED HOUSE |
0.5215 |
3.0785 |
0.0021 |
0.0622 |
ATTIC FLAT |
0.0781 |
1.7948 |
0.0728 |
0.0198 |
NEW |
0.0406 |
2.5225 |
0.0117 |
0.0320 |
NEEDING REFURBISHING |
-0.0948 |
-6.4510 |
0.0000 |
-0.0587 |
CARETAKER |
0.0475 |
3.2322 |
0.0012 |
0.0301 |
ELEVATOR |
0.0469 |
3.5336 |
0.0004 |
0.0466 |
PRIVATE PARKING |
0.1016 |
7.0954 |
0.0000 |
0.0997 |
POOR NATURAL LIGHT |
-0.1777 |
-12.6367 |
0.0000 |
-0.1080 |
DOUBLE GLAZING |
0.0265 |
1.0787 |
0.2808 |
0.0120 |
BUILT-IN WARDROBES |
0.0463 |
4.7398 |
0.0000 |
0.0459 |
d1 |
-0.4898 |
-10.7411 |
0.0000 |
-0.1100 |
d2___________________________ |
___________0.4145 |
5.0281 |
0.0000 |
________0.0931 |
Dependent Variable R2-adjusted Regression Standard error Prob (F Statistic) Theil Coefficient |
Price (in log) 1996 0.8314 0.2034 12.2233 0.4953 352.2755 0.0000 ___________________0.0080 |
To evaluate the results, the calculation of the coefficients for the variables "surface area
squared" and "number of bathrooms squared", were based on the procedure carried out by
Lassibille (1994, p.115). On the other hand, the impact of dummy variables on housing prices
was calculated by applying the methodology of Halvorsen and Palmquist (1980). Once these
procedures were carried out, Table 3 shows the relevance of each variable for the estimated
More intriguing information
1. The open method of co-ordination: Some remarks regarding old-age security within an enlarged European Union2. An Empirical Analysis of the Curvature Factor of the Term Structure of Interest Rates
3. What Drives the Productive Efficiency of a Firm?: The Importance of Industry, Location, R&D, and Size
4. Evaluating the Impact of Health Programmes
5. INTERACTION EFFECTS OF PROMOTION, RESEARCH, AND PRICE SUPPORT PROGRAMS FOR U.S. COTTON
6. The name is absent
7. The name is absent
8. The name is absent
9. The name is absent
10. Financial Market Volatility and Primary Placements