Estimation, Interpretation, and Hypothesis Testing for Nonparametric Hedonic House Price Functions

Daniel McMillen () and Christopher Redfearn

No 8550, Working Paper from USC Lusk Center for Real Estate

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.

Keywords: Housing; Nonparametric Estimation; Hedonic Estimators (search for similar items in EconPapers)
Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://lusk.usc.edu/sites/default/files/working_papers/wp_2007-1007.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:luk:wpaper:8550

Access Statistics for this paper

More papers in Working Paper from USC Lusk Center for Real Estate Contact information at EDIRC.
Bibliographic data for series maintained by Chris Steins ().