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Martin Eiglsperger
- 24 June 2024
- STATISTICS PAPER SERIES - No. 47Details
- Abstract
- The Harmonised Index of Consumer Prices (HICP) currently only includes rentals for housing (paid by tenants) and auxiliary housing expenditures (paid by both tenants and owners). The inclusion of an item for owner-occupied housing (OOH) would be desirable for both representativeness and cross-country comparability. This paper reviews the potential options for including OOH in the HICP to derive a new inflation index. We discuss the conceptual and measurement issues involved. Additionally, we present our analytical calculations on the impact and economic properties of this index as compared to the HICP. We show that since 2011 the estimated impact of including OOH in HICP annual inflation, based on either the “net acquisition” approach or the “rental equivalence” approach, would have been within a band of between -1.2 and +0.4 percentage points. The net acquisition approach could result in bigger differences in future, should the fluctuations in the housing market cycles in the euro area be more pronounced and synchronised. The results should be interpreted keeping in mind that the period of observation is relatively short in relation to housing market cycles. In general, the empirical evidence suggests that including OOH based on the rental equivalence approach decreases the cyclicality of the new inflation index, while the net acquisition approach implies a small amplification of its cyclical properties compared to the HICP.
- JEL Code
- 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
E51 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Money Supply, Credit, Money Multipliers
- 17 July 2023
- OCCASIONAL PAPER SERIES - No. 323Details
- Abstract
- This paper provides an extensive literature review and analyses some open issues in the measurement of inflation that can only be explored in depth using micro price data. It builds on the analysis done in the context of the ECB’s strategy review, which pointed at directions for improvement of the Harmonised Index of Consumer Prices (HICP), including better quantification of potential biases. Two such biases are the substitution bias and the quality adjustment bias. Most analyses of substitution bias rest on the concept of the cost of living, positing that preferences are stable, homogeneous and homothetic. Consumer behaviour is characterised by preference shifts and heterogeneity, which influence the measurement of the cost of living and substitution bias. Climate change may make the impact of preference shifts particularly relevant as it causes the introduction of new varieties of “green” goods and services (zero-kilometre food, sustainable tourism) and a shift from “brown” to “green” products. Furthermore, PRISMA data show that consumption baskets and thus inflation vary across income classes (e.g. higher-income households tend to buy more expensive goods), pointing to non-homotheticity of preferences. When preferences are heterogeneous and/or non-homothetic, it is important to monitor different experiences of inflation across classes of consumers/citizens. This is particularly important when very large relative price changes affect items that enter the consumption baskets of the rich and the poor, the young and the old, in very different proportions. Another open area of analysis concerns the impact of quality adjustment on measured inflation. Evidence based on web-scraped prices shows that the various implicit quality adjustment methods can produce widely varying inflation trends when product churn is fast. In the euro area specifically, using different quality adjustment methods can be an overlooked source of divergent inflation trends in sub-categories, and, if pervasive, shows up in overall measured inflation divergence across countries.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
- 16 February 2022
- ECONOMIC BULLETIN - ARTICLEEconomic Bulletin Issue 1, 2022Details
- Abstract
- The ECB’s monetary policy strategy review confirmed that the Harmonised Index of Consumer Prices (HICP) remains the appropriate price measure for assessing the achievement of the medium-term price stability objective. However, the Governing Council recognised that the inclusion of costs related to owner-occupied housing in the HICP would better represent the inflation rate that is relevant for households. This article elaborates on the topic of owner-occupied housing and its proposed inclusion in the HICP. It showcases the two options considered by the Governing Council, focusing on their statistical and conceptual properties. For the net acquisition approach recommended by the Governing Council, the article presents analytical indices based on ECB approximations that serve as a blueprint for the quarterly internal measure to be monitored. Finally, the article looks ahead to the incorporation of the costs of owner-occupied housing into the HICP and the associated challenges, noting that the current HICP will remain the main reference index for monetary policy during the transition period.
- JEL Code
- 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
E51 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Money Supply, Credit, Money Multipliers
- 21 September 2021
- OCCASIONAL PAPER SERIES - No. 265Details
- Abstract
- This paper – which takes into consideration overall experience with the Harmonised Index of Consumer Prices (HICP) as well as the improvements made to this measure of inflation since 2003 – finds that the HICP continues to fulfil the prerequisites for the index underlying the ECB’s definition of price stability. Nonetheless, there is scope for enhancing the HICP, especially by including owner-occupied housing (OOH) using the net acquisitions approach. Filling this long-standing gap is of utmost importance to increase the coverage and cross-country comparability of the HICP. In addition to integrating OOH into the HICP, further improvements would be welcome in harmonisation, especially regarding the treatment of product replacement and quality adjustment. Such measures may also help reduce the measurement bias that still exists in the HICP. Overall, a knowledge gap concerning the exact size of the measurement bias of the HICP remains, which calls for further research. More generally, the paper also finds that auxiliary inflation measures can play an important role in the ECB’s economic and monetary analyses. This applies not only to analytical series including OOH, but also to measures of underlying inflation or a cost of living index.
- JEL Code
- C43 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→Index Numbers and Aggregation
C52 : Mathematical and Quantitative Methods→Econometric Modeling→Model Evaluation, Validation, and Selection
C82 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Macroeconomic Data, Data Access
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
- 3 February 2021
- STATISTICS PAPER SERIES - No. 40Details
- Abstract
- Consumer price inflation, as measured by the year-on-year increase in the Harmonised Index of Consumer Prices (HICP), is used by the European Central Bank (ECB) for assessing its monetary policy. The European Statistical System regularly introduces methodological improvements into this chain-linked price index in the linking month (December). If the outcome of such changes is a new series with a very different profile in December – either due to changed seasonality or one-off (sampling) effects – significant statistical distortions may arise when the new index series is chain-linked to the existing series. This paper explains the mechanism behind statistical distortions due to chain linking and provides some recent examples from European price statistics. Several alternative chain-linking practices, as well as recommendations for data users on how to deal with such statistical breaks in the HICP, are presented.
- JEL Code
- 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
- 10 November 2020
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 7, 2020Details
- Abstract
- The coronavirus (COVID-19) pandemic has triggered large shifts in household consumption as well as issues related to price collection. We construct a monthly-reweighted consumer price index for the euro area which is able to capture part of the changes in household consumption since the beginning of the pandemic. In this way, we quantify the gap between published HICP inflation and the inflation rate of the items actually purchased by final consumers. Furthermore, we discuss the issue of price imputation and its impact on published statistics.
- JEL Code
- E2 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy
E3 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles
E4 : Macroeconomics and Monetary Economics→Money and Interest Rates
- 21 March 2019
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 2, 2019Details
- Abstract
- Harmonised indices of consumer prices (HICPs) are regularly updated for changes in consumption weights and the items included, and on occasion also for methodological improvements. One such improvement is a change in the way the price index for package holidays is calculated in the HICP for Germany, which was implemented with the HICP release for January 2019. This has led to revisions of annual rates of change not only for Germany, but also for the euro area as a whole.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
- 19 March 2019
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 2, 2019Details
- Abstract
- Harmonised consumer price indices (HICPs) for food, industrial goods, services and energy are measures the ECB uses for its more detailed analysis of inflation in the euro area. With the release of HICPs for January 2019, these analytical groups – special aggregates – have been improved. They are now calculated from a more detailed classification of products. Another recent enhancement is the extended use of price data collected in form of supermarket scanner data and via web-scraping.
- JEL Code
- C82 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Macroeconomic Data, Data Access
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation