Determinants of House Prices: A Quantile Regression Approach
OLS regression has typically been used in housing research to determine the relationship of a particular housing characteristic with selling price. Results differ across studies, not only in terms of size of OLS coefficients and statistical significance, but sometimes in direction of effect. This study suggests that some of the observed variation in the estimated prices of housing characteristics may reflect the fact that characteristics are not priced the same across a given distribution of house prices. To examine this issue, this study uses quantile regression, with and without accounting for spatial autocorrecation, to identify the coefficients of a large set of diverse variables across different quantiles. The results show that purchasers of higher-priced homes value certain housing characteristics such as square footage and the number of bathrooms differently from buyers of lower-priced homes. Other variables such as age are also shown to vary across the distribution of house prices.
(This abstract was borrowed from another version of this item.)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Alan P. Kirman, 1992. "Whom or What Does the Representative Individual Represent?," Journal of Economic Perspectives, American Economic Association, vol. 6(2), pages 117-136, Spring.
- Tae-Hwan Kim & Christophe Muller, 2004.
"Two-stage quantile regression when the first stage is based on quantile regression,"
Royal Economic Society, vol. 7(1), pages 218-231, 06.
- Christophe Muller & Tae-Hwan Kim, 2004. "Two-Stage Quantile Regression When The First Stage Is Based On Quantile Regression," Working Papers. Serie AD 2004-03, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
- Heckman, James, 2013.
"Sample selection bias as a specification error,"
Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
- Epple, Dennis, 1987. "Hedonic Prices and Implicit Markets: Estimating Demand and Supply Functions for Differentiated Products," Journal of Political Economy, University of Chicago Press, vol. 95(1), pages 59-80, February.
- Bartik, Timothy J, 1987. "The Estimation of Demand Parameters in Hedonic Price Models," Journal of Political Economy, University of Chicago Press, vol. 95(1), pages 81-88, February.
- Roger Koenker & Kevin F. Hallock, 2001.
Journal of Economic Perspectives,
American Economic Association, vol. 15(4), pages 143-156, Fall.
- Stephen Malpezzi, . "Hedonic Pricing Models: A Selective and Applied Review," Wisconsin-Madison CULER working papers 02-05, University of Wisconsin Center for Urban Land Economic Research.
- William Gould, 1998. "Interquartile and simultaneous-quantile regression," Stata Technical Bulletin, StataCorp LP, vol. 7(38).
- Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
- Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
- Joachim Zietz & Bobby Newsome, 2002. "Agency Representation and the Sale Price of Houses," Journal of Real Estate Research, American Real Estate Society, vol. 24(2), pages 165-192.
- William Gould, 1993. "Quantile regression with bootstrapped standard errors," Stata Technical Bulletin, StataCorp LP, vol. 2(9).
When requesting a correction, please mention this item's handle: RePEc:kap:jrefec:v:37:y:2008:i:4:p:317-333. 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: (Sonal Shukla)or (Rebekah McClure)
If references are entirely missing, you can add them using this form.