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Determinants of House Prices: A Quantile Regression Approach

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  • Joachim Zietz
  • Emily Zietz
  • G. Sirmans

Abstract

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.
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Suggested Citation

  • Joachim Zietz & Emily Zietz & G. Sirmans, 2008. "Determinants of House Prices: A Quantile Regression Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 37(4), pages 317-333, November.
  • Handle: RePEc:kap:jrefec:v:37:y:2008:i:4:p:317-333
    DOI: 10.1007/s11146-007-9053-7
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    References listed on IDEAS

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    1. Stephen Malpezzi, "undated". "Hedonic Pricing Models: A Selective and Applied Review," Wisconsin-Madison CULER working papers 02-05, University of Wisconsin Center for Urban Land Economic Research.
    2. Badi H. Baltagi, 2011. "Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-642-20059-5, April.
    3. Tae-Hwan Kim & Christophe Muller, 2004. "Two-stage quantile regression when the first stage is based on quantile regression," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 218-231, June.
    4. 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.
    5. 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..
    6. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    7. William Rogers, 1993. "Quantile regression standard errors," Stata Technical Bulletin, StataCorp LP, vol. 2(9).
    8. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    9. William Gould, 1998. "Interquartile and simultaneous-quantile regression," Stata Technical Bulletin, StataCorp LP, vol. 7(38).
    10. William Gould, 1993. "Quantile regression with bootstrapped standard errors," Stata Technical Bulletin, StataCorp LP, vol. 2(9).
    11. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    12. 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.
    13. 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.
    14. 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.
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    More about this item

    Keywords

    Hedonic price function; Quantile regression; Spatial lag; R31; C21; C29;
    All these keywords.

    JEL classification:

    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C29 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Other

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