A Neural Network Analysis of the Effect of Age on Housing Values
AbstractEmpirical studies using multiple regression find the value of a residential property declines with its age. Because these results confirm the fact of physical deterioration of a house over time, little attention is paid to the statistical technique's inherent shortcomings. Accordingly, this paper uses a neural network, which is able to overcome multiple regression's methodological problems, to re-examine the effect of age on a house's value. We find that a negative relationship of value to age holds only for the first sixteen to twenty years of the life of a house. Then, not only does the decline in value stop, but a house actually starts to experience appreciation related, in part, to its lot size.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by American Real Estate Society in its journal Journal of Real Estate Research.
Volume (Year): 8 (1993)
Issue (Month): 2 ()
Contact details of provider:
Postal: American Real Estate Society Clemson University School of Business & Behavioral Science Department of Finance 401 Sirrine Hall Clemson, SC 29634-1323
Web page: http://www.aresnet.org/
Postal: Diane Quarles American Real Estate Society Manager of Member Services Clemson University Box 341323 Clemson, SC 29634-1323
Find related papers by JEL classification:
- L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Plakandaras, Vasilios & Gupta, Rangan & Papadimitriou, Theophilos & Gogas, Periklis, 2014.
"Forecasting the U.S. Real House Price Index,"
DUTH Research Papers in Economics
10-2014, Democritus University of Thrace, Department of Economics.
- Vasilios Plakandaras & Rangan Gupta & Periklis Gogas & Theophilos Papadimitriou, 2014. "Forecasting the U.S. Real House Price Index," Working Papers 2014-473, Department of Research, Ipag Business School.
- Vasilios Plakandaras & Rangan Gupta & Periklis Gogas & Theophilos Papadimitriou, 2014. "Forecasting the U.S. Real House Price Index," Working Papers 201418, University of Pretoria, Department of Economics.
- Nghiep Nguyen & Al Cripps, 2001. "Predicting Housing Value: A Comparison of Multiple Regression Analysis and Artificial Neural Networks," Journal of Real Estate Research, American Real Estate Society, vol. 22(3), pages 313-336.
- Steven Peterson & Albert B. Flanagan, 2009. "Neural Network Hedonic Pricing Models in Mass Real Estate Appraisal," Journal of Real Estate Research, American Real Estate Society, vol. 31(2), pages 147-164.
- Manuel Landajo & Celia Bilbao & Amelia Bilbao, 2012. "Nonparametric neural network modeling of hedonic prices in the housing market," Empirical Economics, Springer, vol. 42(3), pages 987-1009, June.
- R. Kelley Pace, 1998. "Appraisal Using Generalized Additive Models," Journal of Real Estate Research, American Real Estate Society, vol. 15(1), pages 77-100.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (JRER Graduate Assistant/Webmaster).
If references are entirely missing, you can add them using this form.