Inflation Measurement with High-Frequency Data
利用涵盖178个产品类别、八年快消品交易数据，系统比较了双边和多边指数方法在计算月度通胀中的表现，为统计机构选择更准确及时的通胀测量方法提供依据。
The availability of large transaction-level datasets, such as retail scanner data, provides a wealth of information on prices and quantities that national statistical institutes can use to produce more accurate and timely measures of inflation. However, there is no universally accepted method for calculating price indexes using such high-frequency data, reflecting a lack of systematic evidence on the performance of different approaches. We use a dataset covering 178 product categories, comprising all fast-moving consumer goods over eight years, to provide a systematic comparison of the leading bilateral and multilateral index number methods for computing month-to-month inflation.