HOUSEHOLD INVENTORY, TEMPORARY SALES, PRICE INDICES
研究发现链式价格指数存在因消费者囤积导致的跨期替代偏差，提出利用零售商扫描数据计算库存和消费变化的方法，并构建模型准确预测偏差方向与大小，最终推荐一种消除该偏差的价格指数。
Abstract This study addresses the large bias in chained price indices that persists even at lower frequencies. The bias arises from intertemporal substitution caused by consumer hoarding, and is problematic for purchase‐based data. In order to resolve this issue, we propose a method for calculating changes in inventories and consumption using retailer scanner data. We construct a partial equilibrium model to estimate inventories and consumption and show that the model accurately predicts the sign and size of the bias. We also demonstrate that the bias is smaller for consumption‐based data and propose a particular type of price index that eliminates intertemporal substitution bias.