Influence of Transportation Access and Market Dynamics on Property Values

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Abstract
This paper presents housing price models by using multilevel modeling techniques. The key motivation of using the multilevel modeling technique is that it clearly identifies and differentiates between-cluster heterogeneity (i.e., intrinsic differences across aggregated units) and heterogeneity between units of analysis that are nested within aggregated clusters. Two different specifications are tested: two-level spatial and mixed two-level spatiotemporal random effects models. Whereas the first specification assumes that dwelling units are nested within spatial clusters (i.e., neighborhoods), the second specification hypothesizes that dwelling units are nested within spatiotemporal clusters (neighborhoods in a given time period). The unique contribution of this paper is that it accounts for temporal heterogeneity simultaneously with spatial heterogeneity in the housing price models. The study uses an extensive sample of more than 250,000 housing property transactions in 1987–1995 in the Greater Toronto Area of Canada. The paper examines the functional form of the hedonic price model and chooses a semilogarithmic model for subsequent multilevel housing price modeling. The results suggest that the spatiotemporal model performs better in terms of explanatory power and parameter estimates.

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