Scanner Data and the Treatment of Quality Change in Nonrevisable Price Indexes
研究了在滚动年GEKS程序中，使用插补Törnqvist价格指数处理新商品和消失商品的质量变化，通过三种插补方法（显式享乐回归、时间虚拟享乐和时间产品虚拟回归）对八类新西兰消费者电子产品的扫描数据进行了实证分析。
The recently developed rolling year GEKS procedure makes maximum use of all matches in the data to construct nonrevisable price indexes that are approximately free from chain drift. A potential weakness is that unmatched items are ignored. In this article we use imputation Törnqvist price indexes as inputs into the rolling year GEKS procedure. These indexes account for quality changes by imputing the “missing prices” associated with new and disappearing items. Three imputation methods are discussed. The first method makes explicit imputations using a hedonic regression model which is estimated for each time period. The other two methods make implicit imputations; they are based on time dummy hedonic and time-product dummy regression models and are estimated on bilateral pooled data. We present empirical evidence for New Zealand from scanner data on eight consumer electronics products and find that accounting for quality change can make a substantial difference.