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Anastasia Allayioti

16 December 2024
OCCASIONAL PAPER SERIES - No. 364
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Abstract
This paper looks back on the 25-year history of the ECB Survey of Professional Forecasters (SPF). Since its launch in the first quarter of 1999, it has served as an important input for policymaking and analysis, especially over the past five years, where the euro area has, following a period of low inflation, navigated a global pandemic, Russia’s invasion of Ukraine and an unprecedented surge in inflation. The survey has evolved over time and provides not only a long time series of economic expectations and forecasts, but also valuable insights on key topical issues and on economic risks and uncertainties. We show that, for each of the three main macroeconomic variables forecast – HICP inflation, real GDP growth and the unemployment rate – the track record of the ECB SPF in forecasting has been broadly comparable to that of the Eurosystem. In addition, its combination of quantitative point forecasts and probability distributions with qualitative explanations has provided useful input for macroeconomic analysis. Beyond analyses of the forecasts for the main macroeconomic variables, there are also two further sections that examine the technical assumptions (oil prices, policy rates, exchange rates and wages) underlying SPF expectations and an analysis and assessment of measures of macroeconomic uncertainty. Technical assumptions are shown to account for the lion’s share of the variance in the inflation forecast errors, while uncertainty is shown to have increased considerably relative to that which prevailed during the early years of the SPF (1999-2008). Looking ahead, the SPF – with its long track record, its large and broad panel (spanning both financial and non-financial forecasters) and committed panellists – will undoubtedly continue to provide timely and useful insights for the ECB’s policymakers, macroeconomic experts, economic researchers and the wider public.
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
E66 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→General Outlook and Conditions
3 December 2024
WORKING PAPER SERIES - No. 3003
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Abstract
We document that about 33% of the core inflation basket in the euro area is sensitive to monetary policy shocks. We assess potential theoretical mechanisms driving the sensitivity. Our results suggest that items of a discretionary nature, as reflected in a higher share in the consumption baskets of richer households, and those with larger role of credit in financing their purchase, tend to be more sensitive.Non-sensitive items are more frequently subject to administered prices and include non-discretionary items such as rents and medical services. Energy intensity does not seem to drive our results and the sensitive items are not dominated by durable goods, but are relatively evenly split between goods and services. Estimations over different samples show that the impact of monetary policy shocks on sensitive core inflation has become larger recently.
JEL Code
E30 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→General
E50 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→General
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
1 August 2024
ECONOMIC BULLETIN - BOX
Economic Bulletin Issue 5, 2024
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Abstract
Euro area inflation differentials rose sharply during the pandemic and the energy crisis but have since largely returned to previous levels. Monitoring the evolution and nature of inflation differentials is informative when assessing the transmission of the single monetary policy. This box puts the recent developments in inflation dispersion into perspective. Headline inflation and its subcomponents have all experienced considerable divergences across countries, with energy and food inflation playing a significant role. However, with a few exceptions, these temporarily sizeable differentials did not result in substantial changes in relative price levels across countries.
JEL Code
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
E65 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→Studies of Particular Policy Episodes
1 February 2024
WORKING PAPER SERIES - No. 2901
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Abstract
Commodity prices co-move, but the strength of this co-movement changes over time due to structural factors, like changing energy intensity in production and consumption as well as changing composition of underlying shocks. This paper explores whether econometric models that exploit this co-movement and account for parameter instability provide more accurate point and density forecasts of ten major commodity indices viz-a-viz constant coefficient models. Improvements in point forecast accuracy are small, with predictability varying substantially across forecast horizons and commodity indices, but they are large and significant in terms of density forecasting. An economic evaluation reveals that allowing for parameter time variation and commonalities leads to higher portfolios returns, and to higher utility values for investors.
JEL Code
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
C52 : Mathematical and Quantitative Methods→Econometric Modeling→Model Evaluation, Validation, and Selection
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
C55 : Mathematical and Quantitative Methods→Econometric Modeling→Modeling with Large Data Sets?
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications