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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