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Determinants of House Prices: A Quantile Regression Approach

  • Joachim Zietz


  • Emily Zietz


  • G. Sirmans


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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Article provided by Springer in its journal The Journal of Real Estate Finance and Economics.

Volume (Year): 37 (2008)
Issue (Month): 4 (November)
Pages: 317-333

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Handle: RePEc:kap:jrefec:v:37:y:2008:i:4:p:317-333
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  1. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
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  6. 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).
  7. William Gould, 1998. "Interquartile and simultaneous-quantile regression," Stata Technical Bulletin, StataCorp LP, vol. 7(38).
  8. 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.
  9. William Gould, 1993. "Quantile regression with bootstrapped standard errors," Stata Technical Bulletin, StataCorp LP, vol. 2(9).
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