 Affiliated faculty Working papers Research notes Conference External links |
||
 |
||
The
Spatial Proximity of within Metropolitan Area Housing Submarkets
Allen C. Goodman and Thomas G. Thibodeau
Understanding how metropolitan areas are partitioned into housing submarkets is important for several reasons. First, assigning properties to housing submarkets will likely increase the prediction accuracy of the models that are used to measure house prices. Second, identifying within metropolitan area housing submarket boundaries will enable researchers to better model spatial and temporal variation in those prices. Third, an accurate assignment of properties to submarkets will improve lenders and investors ability to price the risk associated with financing homeownership. Finally, providing submarket information to housing consumers will reduce search costs.
Analysts have examined numerous techniques for constructing housing submarkets. Some analysts have used statistical clustering techniques to group small geographic areas (e.g. census block groups, census tracts, zip code districts, etc.) into housing submarkets while others have developed procedures that explicitly model submarket boundaries. Goodman and Thibodeau (1998, 2002), for example, identify housing submarket boundaries by applying the hierarchical modeling technique to housing markets. This technique, first used by Byrk and Radenbush to study education, assigns elementary school zones to housing submarkets depending on whether neighborhood public school quality is capitalized into area house prices.
An important question related to housing submarket construction is whether geographic areas need to be spatially adjacent in order to be considered the same submarket. Housing consumers do not necessarily limit their search to spatially concentrated areas and may search similarly priced neighborhoods located throughout a metropolitan area when making housing consumption decisions. This paper examines two alternative procedures for assigning census block groups to submarkets: one that combines adjacent census block groups into areas with enough transactions to estimate the parameters of a hedonic house price equation and a second that permits spatial discontinuities in submarkets. The criterion used to evaluate the alternative techniques is the accuracy of hedonic house price predictions. In addition, this paper examines the stability of housing submarket boundaries over time.
The empirical research is conducted using data obtained from the Dallas Central Appraisal District (DCAD). The DCAD provided information for every parcel of real property in Dallas County. In addition, since 1983 the DCAD has retained information on prior sales prices and sales dates for every property in the DCAD area. As of January 1, 2003, there were approximately 500,000 single-family homes in the DCAD area and approximately 300,000 transactions during the 1983-2002 period.