Flexible Spatial and Temporal Hedonic Price Indexes for Housing in the Presence of Missing Data

Iqbal Syed (), Robert Hill () and Daniel Melser

No 2008-14, Discussion Papers from School of Economics, The University of New South Wales

Abstract: We propose a flexible hedonic methodology for computing house price indexes that uses multiple imputation (MI) to account for missing data (a huge problem in housing data sets). Ours is the first study to use MI in this context. We also allow for spatial correlation, include interaction terms between characteristics, between regions and periods, and between regions and characteristics, and break the regressions up into overlapping blocks of five consecutive periods (quarters in our case). These features ensure that the shadow prices are flexible both across regions and time. This flexible structure makes the derivation of price indexes from the estimated regression equations far from straightforward. We develop innovative methods for resolving this problem and for splicing the overlapping blocks together to generate the overall panel results. We then use our methodology to construct temporal and spatial price indexes for 15 regions in Sydney, Australia on a quarterly basis from 2001 to 2006 and combine them to obtain an overall price index for Sydney. Our hedonic indexes differ quite significantly from the official index for Sydney published by the Australian Bureau of Statistics. We also find clear evidence of convergence in prices across regions from 2001-3 (while prices were rising), and divergence thereafter. We conclude by exploring some of the implications of these empirical findings.

Keywords: Real estate; House prices; Hedonic price index; Missing data; Multiple imputation; Spatial correlation (search for similar items in EconPapers)
JEL-codes: C43 E01 E31 R31 (search for similar items in EconPapers)
Pages: 64 pages
Date: 2008-10
New Economics Papers: this item is included in nep-geo, nep-mac and nep-ure
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Citations: View citations in EconPapers (7)

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