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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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Bibliographic Info

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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Web page: http://www.springerlink.com/link.asp?id=102945

Related research

Keywords: Hedonic price function; Quantile regression; Spatial lag; R31; C21; C29;

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References

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  1. 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.
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Citations

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Cited by:
  1. Contreras, Víctor & Garay, Urbi & Santos, Miguel Angel & Betancourt, Cosme, 2014. "Expropriation risk and housing prices: Evidence from an emerging market," Journal of Business Research, Elsevier, vol. 67(5), pages 935-942.
  2. Vestal, Mallory K. & Lusk, Jayson L. & Cooper, Steven R. & Ward, Clement E., 2012. "What Are the Consequences of United States Government Slaughter Policies on Horse Prices?," 2012 Annual Meeting, February 4-7, 2012, Birmingham, Alabama 119766, Southern Agricultural Economics Association.
  3. Bernardo Furtado & Frank van Oort, 2011. "Neighborhood weight matrix in a spatial-quantile real estate modeling environment: Evidence from Brazil," ERSA conference papers ersa10p424, European Regional Science Association.
  4. Liao, Wen-Chi & Wang, Xizhu, 2012. "Hedonic house prices and spatial quantile regression," Journal of Housing Economics, Elsevier, vol. 21(1), pages 16-27.
  5. Drescher, Larissa S. & Goddard, Ellen W., 2011. "Heterogeneous Demand for Food Diversity: A Quantile Regression Analysis," 51st Annual Conference, Halle, Germany, September 28-30, 2011 114484, German Association of Agricultural Economists (GEWISOLA).
  6. Fuchs, Benjamin & Fitzenberger, Bernd, 2013. "Tenancy Law Reform Act and Length of Tenancy Discount: Heterogenous Effects in a West German Household Sample," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79723, Verein für Socialpolitik / German Economic Association.
  7. Teuber, Ramona & Herrmann, Roland, 2012. "Towards a differentiated modeling of origin effects in hedonic analysis: An application to auction prices of specialty coffee," Food Policy, Elsevier, vol. 37(6), pages 732-740.
  8. Ming-Chi Chen & Chi-Lu Peng & So-De Shyu & Jhih-Hong Zeng, 2012. "Market States and the Effect on Equity REIT Returns due to Changes in Monetary Policy Stance," The Journal of Real Estate Finance and Economics, Springer, vol. 45(2), pages 364-382, August.
  9. Nicodemo, Catia & Raya, Josep M., 2012. "Change in the Distribution of House Prices across Spanish Cities," IZA Discussion Papers 6503, Institute for the Study of Labor (IZA).
  10. Justin Ross & Michael Farmer & Clifford Lipscomb, 2011. "Inconsistency in Welfare Inferences from Distance Variables in Hedonic Regressions," The Journal of Real Estate Finance and Economics, Springer, vol. 43(3), pages 385-400, October.
  11. Rafael González-Val, 2014. "Cross-sectional growth in US cities from 1990 to 2000," Working Papers 2014/17, Institut d'Economia de Barcelona (IEB).
  12. Philip Kostov, 2013. "Empirical likelihood estimation of the spatial quantile regression," Journal of Geographical Systems, Springer, vol. 15(1), pages 51-69, January.
  13. Fesselmeyer, Eric & Le, Kien T. & Seah, Kiat Ying, 2013. "Changes in the white–black house value distribution gap from 1997 to 2005," Regional Science and Urban Economics, Elsevier, vol. 43(1), pages 132-141.
  14. Uematsu, Hiroki & Mishra, Ashok K., 2012. "The Impact of Natural Amenity on Farmland Values: A Quantile Regression Approach," 2012 Annual Meeting, February 4-7, 2012, Birmingham, Alabama 119804, Southern Agricultural Economics Association.
  15. Liu, Sezhu & Hite, Diane, 2013. "Measuring the Effect of Green Space on Property Value: An Application of the Hedonic Spatial Quantile Regression," 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida 143045, Southern Agricultural Economics Association.
  16. Gerdesmeier, Dieter & Lenarčič, Andreja & Roffia, Barbara, 2012. "An alternative method for identifying booms and busts in the euro area housing market," Working Paper Series 1493, European Central Bank.

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