Empirical findings on upper-level aggregation issues in the HICP

We analyse potential mismeasurement of the Harmonised Index of Consumer Prices (HICP) at the upper level of aggregation, focusing on two sources of measurement error: the choice of index formula (representativity component) and the reliability of weights (data vintage component). The representativity component captures the fact that a Laspeyres-type index such as the HICP suffers from a systematic over-estimation of inflation due to the disregard of changes in more recent consumption patterns. The data vintage component comprises potential mismeasurement arising from the annual updating of HICP weights based on preliminary national accounts data. With national accounts vintage data, we calculate bias and inaccuracy metrics in order to analyse mismeasurement at the upper level of aggregation in the HICPs for Germany, France, Italy, Spain and the Netherlands, as well as for the country group, over the period from 2012 to 2021. For the representativity component, the data availability allows an additional analysis of the period until 2024. Measured in terms of annual HICP rates, the total upper-level aggregation bias falls short of one-tenth of a percentage point. The representativity and the data vintage component are both found to contribute to overall bias in quite similar shares. We also find that the representativity component experienced a substantial revival during the recent high inflation period.