Local House Price Indexes: 1982–1991

Abstract

We begin with a description of three house price panel data sets for the period 1982 to 1991. Next, we estimate a model that assumes the three sources are derived from an underlying unobserved price series, and we construct composite indexes that report house prices for 135 locations. These series can be used either as explanatory variables in studies of household formation, housing demand, and migration or to test models of the determinants of spatial and intertemporal variations in house prices. Finally, we construct regional series (based, alternatively, on census and Salomon Brothers regions) and two national aggregates and describe their movements. Our series are compared to other local, regional, and national series. Copyright American Real Estate and Urban Economics Association.

How Well Do Australian Home‐Owners Know the Value of Their Home?

“…They focused on 752 households for which an owner's estimate was recorded in 1985, but who sold prior to the next survey in 1987 and so for whom a market price existed. They next used price indices that were constructed at a regionally disaggregated level by Haurin, Hendershott and Kim () to extrapolate the 1985 price estimates forward to the date of sale and then examined the errors. They detected an average upward bias of 8.3 per cent in owners' estimates.…”

The Conditional Probability of Foreclosure: An Empirical Analysis of Conventional Mortgage Loan Defaults

“…APPREC for a given SMSA is measured by the cumulative percentage change in the INDEX from the time of loan origination until termination. The housing price INDEX value (Haurin et al 1991) measures the average percentage change in nominal single family housing prices for each region (SMSA). INCGROWTH is measured by the percentage change in per capita income in the relevant SMSA over the life of each loan in the sample.…”

Marking Single–Family Property Values to Market

“…Clapp, Kim and Gelfand (2002) model the residuals of a semiparametric hedonic house price model using a Bayesian framework and conclude that these statistical techniques help measure spatial variation in house prices more accurately. For additional references on house price measurement, see Haurin, Hendershott and Kim (1991), Peek and Wilcox (1991), Thibodeau (1992), and the articles published in Volume 14, Numbers 1/2 (1997) of The Journal of Real Estate Finance and Economics.…”