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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.

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Article provided by American Real Estate Society in its journal Journal of Real Estate Research.

Volume (Year): 8 (1993)
Issue (Month): 2 ()
Pages: 253-264

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Handle: RePEc:jre:issued:v:8:n:2:1993:p:253-264
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
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Order Information: Postal: Diane Quarles American Real Estate Society Manager of Member Services Clemson University Box 341323 Clemson, SC 29634-1323
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