Abstract
In the existing housing literature, there has been no academic consensus on how to combine the spatial dependence and the temporal dependence between housing transactions together. The combination is much dependent on the researcher’s priori knowledge of a referent market. This paper attempts to combine them by utilizing an information entropy-based spatiotemporal approach. The validity of the proposed information entropy-based spatiotemporal approach is tested by spatiotemporal regressions in terms of prices estimation accuracy. The methodology is conducted by using data on dwelling transactions from the San Francisco Bay Area. The empirical results suggest that the proposed information entropy-based modeling technique is a reasonable and efficient way to combine the spatial dependence and the temporal dependence.
Published Version
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