Working Paper: CEPR ID: DP18539
Authors: Kevin J Fox; Peter Levell; Martin O'Connell
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.
Keywords: Consumer Price Index; CPI; Chain Drift; Multilateral Indexes; Scanner Data
JEL Codes: C43; E31
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| fixed weights (C46) | substitution bias (D11) |
| chained bilateral indexes (C43) | chain drift bias (C22) |
| chaining methods (C69) | observed biases (D91) |
| multilateral methods (C30) | accurate representation of inflation (E31) |
| index method used (C43) | accuracy of inflation measurement (E31) |