On Choosing Among House Price Index Methodologies

TLDR

The hedonic price model is prone to specification bias and inefficiency, the weighted repeat‑sales model suffers from even more serious bias, and a hybrid hedonic‑repeat‑sales model largely avoids these problems. This study compares housing‑price indices derived from three different models and evaluates their performance using a rich local housing‑market database. The authors estimate indices with hedonic, weighted repeat‑sales, and hybrid models across multiple transaction datasets and assess their performance. Results, though ambiguous, confirm repeat‑sales model problems and indicate that systematic differences between repeat‑transacting and single‑transacting properties bias both hedonic and hybrid models.

Abstract

This paper compares housing price indices estimated using three models with several sets of property transaction data. The commonly used hedonic price model suffers from potential specification bias and inefficiency, while the weighted repeat‐sales model presents potentially more serious bias and inefficiency problems. A hybrid model combining hedonic and repeat‐sales equations avoids most of these sources of bias and inefficiency. This paper evaluates the performance of each type of model using a particularly rich local housing market database. The results, though ambiguous, appear to confirm the problems with the repeat sales model but suggest that systematic differences between repeat‐transacting and single‐transacting properties lead to bias in the hedonic and hybrid models as well.