A Neural Network Analysis of the Effect of Age on Housing Values
Empirical 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.
Volume (Year): 8 (1993)
Issue (Month): 2 ()
|Contact details of provider:|| Postal: |
Web page: http://www.aresnet.org/
|Order Information:|| Postal: Diane Quarles American Real Estate Society Manager of Member Services Clemson University Box 341323 Clemson, SC 29634-1323|
Web: http://pages.jh.edu/jrer/about/get.htm Email:
When requesting a correction, please mention this item's handle: RePEc:jre:issued:v:8:n:2:1993:p:253-264. 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: (JRER Graduate Assistant/Webmaster)
If references are entirely missing, you can add them using this form.