A mixed index approach to identifying hedonic price models

David Brasington and Diane Hite

Regional Science and Urban Economics, 2008, vol. 38, issue 3, 271-284

Abstract: Recent literature suggests identifying house price hedonic regressions by using instrumental variables, spatial statistics, the borders approach, panel data, and other techniques. We present an empirical application of a mixed index model, first proposed by Bowden [Bowden, R.J., 1992. Competitive selection and market data: the mixed-index problem. The Review of Economic Studies 59(3):625-633.] to identify hedonic price regressions. We compare the performance of the mixed index model to a traditional hedonic model and to a hedonic model that includes characteristics of the buyer of each house. We find the mixed index model outperforms the other models based on bootstrap distributions of predicted housing values, prediction variance, and predicted policy effects. The mixed index model distributions are less skewed and kurtotic than the other models, suggesting it more closely satisfies the classical linear regression assumption of normally distributed errors. Compared to the mixed index model, the traditional hedonic overstates the importance of lot size and school quality to house price and understates the importance of environmental quality.

Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0166-0462(08)00023-9
Full text for ScienceDirect subscribers only

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:eee:regeco:v:38:y:2008:i:3:p:271-284

Access Statistics for this article

Regional Science and Urban Economics is currently edited by D.P McMillen and Y. Zenou

More articles in Regional Science and Urban Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().