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Boosting the accuracy of hedonic pricing models

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  • van Wezel, M.C.
  • Kagie, M.
  • Potharst, R.

Abstract

Hedonic pricing models attempt to model a relationship between object attributes and the object's price. Traditional hedonic pricing models are often parametric models that suffer from misspecification. In this paper we create these models by means of boosted CART models. The method is explained in detail and applied to various datasets. Empirically, we find substantial reduction of errors on out-of-sample data for two out of three datasets compared with a stepwise linear regression model. We interpret the boosted models by partial dependence plots and relative importance plots. This reveals some interesting nonlinearities and differences in attribute importance across the model types.

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File URL: http://repub.eur.nl/pub/7145/ei2005-50.pdf
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Bibliographic Info

Paper provided by Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute in its series Econometric Institute Research Papers with number EI 2005-50.

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Date of creation: 02 Dec 2005
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Handle: RePEc:ems:eureir:7145

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Related research

Keywords: conjoint analysis; data mining; ensemble learning; gradient boosting; hedonic pricing; marketing; pricing;

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  1. R. Kelley Pace, 1998. "Appraisal Using Generalized Additive Models," Journal of Real Estate Research, American Real Estate Society, American Real Estate Society, vol. 15(1), pages 77-100.
  2. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
  3. Harrison, David Jr. & Rubinfeld, Daniel L., 1978. "Hedonic housing prices and the demand for clean air," Journal of Environmental Economics and Management, Elsevier, vol. 5(1), pages 81-102, March.
  4. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 74, pages 132.
  5. Gilley, Otis W & Pace, R Kelley, 1995. "Improving Hedonic Estimation with an Inequality Restricted Estimator," The Review of Economics and Statistics, MIT Press, vol. 77(4), pages 609-21, November.
  6. Elie Ofek & V. Srinivasan, 2002. "How Much Does the Market Value an Improvement in a Product Attribute?," Marketing Science, INFORMS, INFORMS, vol. 21(4), pages 398-411, June.
  7. Anglin, Paul M & Gencay, Ramazan, 1996. "Semiparametric Estimation of a Hedonic Price Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 11(6), pages 633-48, Nov.-Dec..
  8. Gencay, Ramazan & Xian, Yang, 1996. "A forecast comparison of residential housing prices by parametric versus semiparametric conditional mean estimators," Economics Letters, Elsevier, Elsevier, vol. 52(2), pages 129-135, August.
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