2007
Abstract:
Despite well-documented shortcomings, hedonic and repeat sales estimators
remain the most widely used methods for constructing quality controlled house price
indexes and for assessing housing attribute capitalization into dwelling prices.
Nonparametric estimators overcome many of the problems associated with these
approaches by controlling for misspecified spatial effects while using highly flexible
forms. Despite these advantages, nonparametric procedures are still not used extensively
for data analysis due to perceived difficulties associated with estimation and hypothesis
testing. We demonstrate that nonparametric estimation is both feasible for large data sets
with many explanatory variables and offers significant advantages in terms of the
information content of the estimates. These features are demonstrated in an application
of valuing capitalization of access to a rapid transit line into surrounding dwelling prices.
