European Central Bank - eurosystem
Search Options
Home Media Explainers Research & Publications Statistics Monetary Policy The €uro Payments & Markets Careers
Suggestions
Sort by

Benny Hartwig

21 September 2021
OCCASIONAL PAPER SERIES - No. 266
Details
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
21 September 2021
OCCASIONAL PAPER SERIES - No. 264
Details
Abstract
This paper summarises the findings of the Eurosystem’s Expert Group on Inflation Expectations (EGIE), which was one of the 13 work streams conducting analysis that fed into the ECB’s monetary policy strategy review. The EGIE was tasked with (i) reviewing the nature and behaviour of inflation expectations, with a focus on the degree of anchoring, and (ii) exploring the role that measures of expectations can play in forecasting inflation. While it is households’ and firms’ inflation expectations that ultimately matter in the expectations channel, data limitations have meant that in practice the focus of analysis has been on surveys of professional forecasters and on market-based indicators. Regarding the anchoring of inflation expectations, this paper considers a number of metrics: the level of inflation expectations, the responsiveness of longer-term inflation expectations to shorter-term developments, and the degree of uncertainty. Different metrics can provide conflicting signals about the scale and timing of potential unanchoring, which underscores the importance of considering all of them. Overall, however, these metrics suggest that in the period since the global financial and European debt crises, longer-term inflation expectations in the euro area have become less well anchored. Regarding the role measures of inflation expectations can play in forecasting inflation, this paper finds that they are indicative for future inflationary developments. When it comes to their predictive power, both market-based and survey-based measures are found to be more accurate than statistical benchmarks, but do not systematically outperform each other. Beyond their role as standalone forecasts, inflation expectations bring forecast gains when included in forecasting models and can also inform scenario and risk analysis in projection exercises performed using structural models. ...
JEL Code
D84 : Microeconomics→Information, Knowledge, and Uncertainty→Expectations, Speculations
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
26 May 2021
WORKING PAPER SERIES - No. 2558
Details
Abstract
We document the impact of COVID-19 on frequently employed time series models, with a focus on euro area inflation. We show that for both single equation models (Phillips curves) and Vector Autoregressions (VARs) estimated parameters change notably with the pandemic. In a VAR, allowing the errors to have a distribution with fatter tails than the Gaussian one equips the model to better deal with the COVID-19 shock. A standard Gaussian VAR can still be used for producing conditional forecasts when relevant off-model information is used. We illustrate this by conditioning on official projections for a set of variables, but also by tilting to expectations from the Survey of Professional Forecasters. For Phillips curves, averaging across many conditional forecasts in a thick modelling framework offers some hedge against parameter instability.
JEL Code
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications