Hedonic price models and indices based on boosting applied to the Dutch housing market
We create a hedonic price model for house prices for six geographical submarkets in the Netherlands. Our model is based on a recent data mining technique called boosting. Boosting is an ensemble technique that combines multiple models, in our case decision trees, into a combined prediction. Boosting enables capturing of complex nonlinear relationships and interaction effects between input variables. We report mean relative errors and mean absolute error for all regions and compare our models with a standard linear regression approach. Our model improves prediction performance with up to 40% compared with Linear Regression. Next, we interpret the boosted models: we determine the most influential characteristics and graphically depict the relationship between the most important input variables and the house price. We find the size of the house to be the most important input for all but one region, and find some interesting nonlinear relationships between inputs and price. Finally, we construct hedonic price indices and compare these to the mean and median index and find that these indices differ notably in the urban regions of Amsterdam and Rotterdam.
|Date of creation:||05 Apr 2006|
|Contact details of provider:|| Postal: Postbus 1738, 3000 DR Rotterdam|
Phone: 31 10 4081111
Web page: http://www.eur.nl/ese
More information through EDIRC
References listed on IDEAS
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.:
- Anglin, Paul M & Gencay, Ramazan, 1996. "Semiparametric Estimation of a Hedonic Price Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 633-648, Nov.-Dec..
- Ariel Pakes, 2003.
"A Reconsideration of Hedonic Price Indexes with an Application to PC's,"
American Economic Review,
American Economic Association, vol. 93(5), pages 1578-1596, December.
- Ariel Pakes, 2002. "A Reconsideration of Hedonic Price Indices with an Application to PC's," NBER Working Papers 8715, National Bureau of Economic Research, Inc.
- Carlos Martins-Filho & Okmyung Bin, 2005.
"Estimation of hedonic price functions via additive nonparametric regression,"
Springer, vol. 30(1), pages 93-114, January.
- Okmyung Bin & Carlos Martins-Filho, "undated". "Estimation of Hedonic Price Functions via Additive Nonparametric Regression," Working Papers 0116, East Carolina University, Department of Economics.
- 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.
- Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74, pages 132-132.
- Helen X.H. Bao & Alan T.K. Wan, 2004. "On the Use of Spline Smoothing in Estimating Hedonic Housing Price Models: Empirical Evidence Using Hong Kong Data," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 32(3), pages 487-507, September.
- R. Kelley Pace, 1998. "Appraisal Using Generalized Additive Models," Journal of Real Estate Research, American Real Estate Society, vol. 15(1), pages 77-100.
- Friedman, Jerome H., 2002. "Stochastic gradient boosting," Computational Statistics & Data Analysis, Elsevier, vol. 38(4), pages 367-378, February.
- John M. Clapp, 2004. "A Semiparametric Method for Estimating Local House Price Indices," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 32(1), pages 127-160, March.
- Gencay, Ramazan & Xian, Yang, 1996. "A forecast comparison of residential housing prices by parametric versus semiparametric conditional mean estimators," Economics Letters, Elsevier, vol. 52(2), pages 129-135, August.
When requesting a correction, please mention this item's handle: RePEc:ems:eureir:7665. 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: (RePub)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.