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.

中文翻译：

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家庭库存、临时销售、价格指数

这项研究解决了连锁价格指数即使在较低频率下也存在的巨大偏差。这种偏差是由消费者囤积造成的跨期替代引起的，对于基于购买的数据来说是有问题的。为了解决这个问题，我们提出了一种使用零售商扫描仪数据计算库存和消耗变化的方法。我们构建了一个部分均衡模型来估计库存和消耗，并表明该模型准确地预测了偏差的符号和大小。我们还证明，基于消费的数据的偏差较小，并提出了一种特定类型的价格指数，可以消除跨期替代偏差。