Working Paper: NBER ID: w9262
Authors: Dennis R. Capozza; Patric H. Hendershott; Charlotte Mack; Christopher J. Mayer
Abstract: We explore the dynamics of real house prices by estimating serial correlation and mean reversion coefficients from a panel data set of 62 metro areas from 1979-1995. The serial correlation and reversion parameters are then shown to vary cross sectionally with city size, real income growth, population growth, and real construction costs. Serial correlation is higher in metro areas with higher real income, population growth and real construction costs. Mean reversion is greater in large metro areas and faster-growing cities with lower construction costs. Empirically, substantial overshooting of prices can occur in high real construction cost areas, which have high serial correlation and low mean reversion, such as the coastal cities of Boston, New York, San Francisco, Los Angeles and San Diego.
Keywords: real house prices; serial correlation; mean reversion; metro areas; construction costs
JEL Codes: G12; R31
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| real income growth (O49) | serial correlation (C29) |
| population growth (J11) | serial correlation (C29) |
| real construction costs (L74) | serial correlation (C29) |
| construction costs (L74) | mean reversion (C22) |
| larger metropolitan areas (R12) | mean reversion (C22) |
| faster growth (O49) | mean reversion (C22) |
| high construction costs (L74) | high serial correlation (C22) |
| high construction costs (L74) | low mean reversion (C22) |