Semiparametric Estimation of a Hedonic Price Function
Previous work on the preferred specification of hedonic price models usually recommended a Box-Cox model. In this paper we note that any parametric model involves implicit restrictions and they can be reduced by using a semiparametric model. We estimate a benchmark parametric model which passes several common specification tests, before showing that a semiparametric model outperforms it significantly. In addition to estimating the model, we compare the predictions of the models by deriving the distribution of the predicted log(price) and then calculating the associated prediction intervals. Our data show that the semiparametric model provides more accurate mean predictions than the benchmark parametric model. Copyright 1996 by John Wiley & Sons, Ltd.
Volume (Year): 11 (1996)
Issue (Month): 6 (Nov.-Dec.)
|Contact details of provider:|| Web page: http://www.interscience.wiley.com/jpages/0883-7252/|
|Order Information:|| Web: http://www3.interscience.wiley.com/jcatalog/subscribe.jsp?issn=0883-7252 Email: |
This item is featured on the following reading lists or Wikipedia pages:
- Semiparametric estimation of a hedonic price function (JAE 1996) in ReplicationWiki
When requesting a correction, please mention this item's handle: RePEc:jae:japmet:v:11:y:1996:i:6:p:633-48. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing)or (Christopher F. Baum)
If references are entirely missing, you can add them using this form.