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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, timely, measures of inflation. However, there is no universally agreed upon method for calculating price indexes with such high frequency data, reflecting a lack of systematic evidence on the performance of different approaches. We use a dataset that covers 178 product categories comprising all fast-moving consumer goods over 8 years to provide a systematic comparison of the leading bilateral and multilateral index number methods for computing month-to-month inflation.
Authors

Researcher UNSW Sydney

Deputy Research Director
Peter joined in 2009. He has published several papers on the microeconomics of household spending and labour supply decisions over the life-cycle.

Research Fellow University of Wisconsin
Martin, previously Deputy Research Director, is a Research Fellow at IFS and Professor of Economics at the University of Wisconsin.
Working Paper details
- DOI
- 10.1920/wp.ifs.2023.2923
- Publisher
- Institute for Fiscal Studies
Suggested citation
K, Fox and P, Levell and M, O'Connell. (2023). Inflation measurement with high frequency data. 23/29. London: Institute for Fiscal Studies. Available at: https://ifs.org.uk/publications/inflation-measurement-high-frequency-data (accessed: 21 May 2025).
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