Estimating Price Indices for Residential Property: A Comparison of Repeat Sales and Assessed Value Methods

TLDR

Accurate estimation of price indices for residential property is essential for real estate research, especially amid recent efforts to forecast 1990s price trends. The study develops a simple method to correct measurement errors in assessed value. Price trends are estimated using sales price, assessed value, and sale date for all residential transactions, comparing the assessed value method to the repeat sales method and developing a correction for measurement errors in assessed value. The AV method’s large sample size reduces measurement error to negligible levels, and price trends from AV and RS are largely similar over seven years, yet RS remains inefficient due to its smaller data subset, even with richer repeat sales datasets.

Abstract

Abstract Accurate estimation of price indices for residential property is an essential feature of real estate research, especially in view of recent efforts to forecast price trends for the 1990s. In this article, price trends are estimated by using the sales price, assessed value and date of sale for every residential property transaction between independent parties. This assessed value (AV) methodology is compared to the repeat sales (RS) method. This article develops a simple method for correcting the effect of the measurement errors associated with assessed value. We demonstrate that the large samples available with the AV method allow the measurement error problem to be reduced to negligible proportions. Using data on the Hartford, Connecticut metropolitan area, we find that price trends estimated from the AV and RS methods are substantially similar over a seven-year period. But the RS method is inefficient because it uses a relatively small subset of the data. Our results indicate that it remains inefficient when the researcher has a dataset much richer in repeat sales than ours.