Multicollinearity and Reduced‐Form Price Equations For Residential Markets: An Evaluation of Alternative Estimation Methods*

George W. Gau and Daniel B. Kohlhepp

Real Estate Economics, 1978, vol. 6, issue 1, 50-69

Abstract: One of the problems that has plagued researchers in their estimation of reduced‐form price equations for specific housing markets has been multicollinearity—the lack of statistical independence of the explanatory variables. This paper evaluates the suitability for structural analysis and prediction of stepwise regression and principal components regression as alternatives to the standard regression model in the estimation of equations with interdependent data. In general, the results of this study indicate that under conditions of multicollinearity principal components regression is the superior estimation technique.

Date: 1978
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://doi.org/10.1111/1540-6229.00168

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:bla:reesec:v:6:y:1978:i:1:p:50-69

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=1080-8620

Access Statistics for this article

Real Estate Economics is currently edited by Crocker Liu, N. Edward Coulson and Walter Torous

More articles in Real Estate Economics from American Real Estate and Urban Economics Association Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().