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Elisabeth Wieland

17 June 2022
WORKING PAPER SERIES - No. 2669
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Abstract
Using CPI micro data for 11 euro area countries covering about 60% of the euro area consumption basket over the period 2010-2019, we document new findings on consumer price rigidity in the euro area: (i) each month on average 12.3% of prices change, which compares with 19.3% in the United States; when we exclude price changes due to sales, however, the proportion of prices adjusted each month is 8.5% in the euro area versus 10% in the United States; (ii) differences in price rigidity are rather limited across euro area countries but much larger across sectors; (iii) the median price increase (resp. decrease) is 9.6% (13%) when including sales and 6.7% (8.7%) when excluding sales; cross-country heterogeneity is more pronounced for the size than for the frequency of price changes; (iv) the distribution of price changes is highly dispersed: 14% of price changes in absolute values are lower than 2% whereas 10% are above 20%; (v) the overall frequency of price changes does not change much with inflation and does not react much to aggregate shocks; (vi) changes in inflation are mostly driven by movements in the overall size; when decomposing the overall size, changes in the share of price increases among all changes matter more than movements in the size of price increases or the size of price decreases. These findings are consistent with the predictions of a menu cost model in a low inflation environment where idiosyncratic shocks are a more relevant driver of price adjustment than aggregate shocks.
JEL Code
D40 : Microeconomics→Market Structure and Pricing→General
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
Network
Price Micro Setting Analysis Network (PRISMA)
21 September 2021
OCCASIONAL PAPER SERIES - No. 266
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Abstract
The digitalisation workstream report analyses the degree of digital adoption across the euro area and EU countries and the implications of digitalisation for measurement, productivity, labour markets and inflation, as well as more recent developments during the coronavirus (COVID-19) pandemic and their implications. Analysis of these key issues and variables is aimed at improving our understanding of the implications of digitalisation for monetary policy and its transmission. The degree of digital adoption differs across the euro area/EU, implying heterogeneous impacts, with most EU economies currently lagging behind the United States and Japan. Rising digitalisation has rendered price measurement more challenging, owing to, among other things, faster changes in products and product quality, but also new ways of price setting, e.g. dynamic or customised pricing, and services that were previously payable but are now “free”. Despite the spread of digital technologies, aggregate productivity growth has decreased in most advanced economies since the 1970s. However, it is likely that without the spread of digital technologies the productivity slowdown would have been even more pronounced, and the recent acceleration in digitalisation is likely to boost future productivity gains from digitalisation. Digitalisation has spurred greater automation, with temporary labour market disruptions, albeit unevenly across sectors. The long-run employment effects of digitalisation can be benign, but its effects on wages and labour share depend on the structure of the economy and its labour market institutions. The pandemic has accelerated the use of teleworking: roughly every third job in the euro area/EU is teleworkable, although there are differences across countries. ...
JEL Code
E24 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Employment, Unemployment, Wages, Intergenerational Income Distribution, Aggregate Human Capital
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
O33 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights→Technological Change: Choices and Consequences, Diffusion Processes
O57 : Economic Development, Technological Change, and Growth→Economywide Country Studies→Comparative Studies of Countries
3 February 2021
STATISTICS PAPER SERIES - No. 40
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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
11 July 2016
STATISTICS PAPER SERIES - No. 14
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Abstract
Integrated quarterly sector accounts (QSA) provide an analytical tool to understand the generation, allocation and use of income for all institutional sectors in the economy. They also provide a tool to analyse production from a sectoral point of view instead of an industry point of view. However, since QSA are published in current prices only, sectoral volume and price measures are lacking as an important toolkit for economic analysis and forecasting, notably in the case of gross value added. This paper introduces a methodology to estimate sectoral price and volume measures for euro area value added at a quarterly frequency and provides a comparison of alternative estimation methods. It presents a benchmark method which yields robust estimates of sectoral volumes and prices in the euro area.
JEL Code
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
C82 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Macroeconomic Data, Data Access
E01 : Macroeconomics and Monetary Economics→General→Measurement and Data on National Income and Product Accounts and Wealth, Environmental Accounts
E30 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→General