Hedonic versus repeat-sales housing price indexes for measuring the recent boom-bust cycle

• Published in: Journal of housing economics Vol. 19; no. 2; pp. 75 - 93
• Main Authors: Dorsey, Robert E., Hu, Haixin, Mayer, Walter J., Wang, Hui-chen
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01-06-2010; Elsevier
• Series: Journal of Housing Economics
• Subjects: California; Correlation; Data analysis; Hedonic housing price indexes; Hedonic housing price indexes Repeat-sales indexes; Housing market; Housing prices; Metropolitan areas; Price index; Regression analysis; Repeat-sales indexes; Transactional analysis; U.S.A; R21; C43; C21; Hedonic housing price indexes; Repeat-sales indexes
• ISSN: 1051-1377; 1096-0791
• DOI: 10.1016/j.jhe.2010.04.001

Standard housing price indexes rely on strong constant-quality assumptions and often conflict. Hedonic price indexes overcome limitations of median price and repeat-sales indexes but their implementation has been limited by a lack of data. This paper constructs hedonic indexes at the zip code level for the Los Angeles and San Diego metropolitan areas using considerably more detailed data than previously available. Our sample was collected by a mortgage technology firm, and consists of almost 1.1 million transactions during the boom-bust cycle since 2000. Our hedonic regressions include new spatial models that capture correlations within submarkets (using zip codes as proxies) and allow temporal asymmetry. Compared to a repeat-sales price index constructed from the same data, the hedonic indexes indicate that the market peaked about 11
months later in Los Angeles and about 2
months earlier in San Diego, show less pre-peak appreciation and post-peak depreciation in low-tier housing and more pre-peak appreciation in high-tier housing. We also find that the intensity of the cycle varies greatly across zip codes and price-tiers in a pattern consistent with foreclosure activity.