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Inflation measurement with high frequency data

Author

Listed:
  • Fox, Kevin J.
  • Levell, Peter
  • O'Connell, Martin

Abstract

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.

Suggested Citation

  • Fox, Kevin J. & Levell, Peter & O'Connell, Martin, 2023. "Inflation measurement with high frequency data," CEPR Discussion Papers 18539, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:18539
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    Cited by:

    1. is not listed on IDEAS
    2. Robert J. Hill & Norbert Pfeifer & Miriam Steurer, 2025. "Spatial Rent Indices for Cities Around the World: A Comparison of Airbnb and Long-Term Rentals," Graz Economics Papers 2025-01, University of Graz, Department of Economics.

    More about this item

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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