On Choosing Among House Price Index Methodologies
比较了三种房价指数模型（特征价格模型、重复销售模型和混合模型）在多个数据集上的表现，发现重复销售模型偏差和效率问题更严重，混合模型虽能避免部分问题但仍有偏差。
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.