Robust Repeat Sales Indexes
利用肯塔基州路易斯维尔的独户住宅销售数据，展示了在重复销售背景下应用稳健方法降低异常交易影响的好处，并证明稳健方法能减少指数修正的幅度和波动性。
Using single‐family sales data for Louisville, Kentucky, we show the benefits of applying robust methods to down‐weight problematic transactions in a repeat sales context. Robust estimators reduce the influence of outliers in repeat sales price changes that are due to data entry errors, quality changes or nonmarket transactions. In addition to comparing conventional and robust indexes, we also use simulated data, where the correct index is known, to show that robust methods control for the impacts of contaminated data. Finally, we demonstrate that robust methods reduce the magnitude and volatility of index revisions.