Mario Porqueddu
Economics
- Division
Prices & Costs
- Current Position
-
Principal Economist
- Fields of interest
-
Mathematical and Quantitative Methods,Macroeconomics and Monetary Economics,Labour Economics
- Education
- 2004-2009
PhD in Economics, Bocconi University, Milan, Italy
- 2003-2004
MA in Economics and Statistics, Universite Libre de Bruxelles, Belgium
- 1998-2003
BA in Economics, Bocconi University, Milan, Italy
- Professional experience
- 2015-2024
Economist, Senior and Principal Economist - Prices and Costs Division, Directorate General Economics, European Central Bank
- 2008-2015
Economist - Economic Outlook and Prices Division, Directorate General Economics, Statistics and Research, Banca d'Italia
- 12 June 2025
- WORKING PAPER SERIES - No. 3062Details
- Abstract
- Energy inflation is a major source of headline inflation volatility and forecast errors, therefore it is critical to model it accurately. This paper introduces a novel suite of Bayesian VAR models for euro area HICP energy inflation, which adopts a granular, bottom-up approach – disaggregating energy into subcomponents, such as fuels, gas, and electricity. The suite incorporates key features for energy prices: stochastic volatility, outlier correction, high-frequency indicators, and pre-tax price modelling. These characteristics enhance both in-sample explanatory power and forecast accuracy. Compared to standard benchmarks and official projections, our BVARs achieve better forecasting performance, particularly beyond the very short term. The suite also captures a sizable variation in the impact of commodity price shocks, pointing to higher elasticities at higher levels of commodity prices. Beyond forecasting, our framework is also useful for scenario and sensitivity analysis as an effective tool to gauge risks, which is especially relevant amid ongoing energy market transformations.
- 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
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
- 20 March 2025
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 2, 2025Details
- Abstract
- Historically, stronger dynamics in services prices than in non-energy industrial goods (NEIG) prices have led to a persistent positive gap between services and NEIG inflation rates. However, the relative price of goods versus services rose rapidly in 2021-2022 before subsequently falling back. This box reviews this episode and examines whether the pre-pandemic trend in this relative price development provides a good benchmark for future developments, also taking into account the potential impact of structural factors related to deglobalisation, digitalisation, demographic trends and climate change.
- JEL Code
- 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
- 27 July 2022
- RESEARCH BULLETIN - No. 98Details
- Abstract
- Labour market developments are important drivers of the business cycle and are therefore closely watched by monetary policymakers. One process with significant macroeconomic ramifications are wage negotiations, where workers and employers bargain over the surplus income generated by an employment relationship. Bargaining power determines how this surplus is split between negotiating parties. However, it is unobserved, and can be driven by a number of factors. We exploit information about key events in Germany that are relevant for wage negotiations, such as labour strikes and the introduction of a minimum wage, to pinpoint changes in bargaining power. We find that such wage bargaining “shocks” are important drivers of unemployment and inflation, that their effect on wages is almost fully reflected in prices, and that they reduce the vacancy rate and increase firms' profits and the labour share of income in the short run, but not in the long run.
- JEL Code
- J2 : Labor and Demographic Economics→Demand and Supply of Labor
J3 : Labor and Demographic Economics→Wages, Compensation, and Labor Costs
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
- 8 October 2021
- WORKING PAPER SERIES - No. 2602Details
- Abstract
- We quantify the effects of wage bargaining shocks on macroeconomic aggregates using a structural vector auto-regression model for Germany. We identify exogenous variation in bargaining power from episodes of minimum wage introduction and industrial disputes. This narrative information disciplines the impulse responses to a wage bargaining shock of un-employment and output, and sharpens inference on the behaviour of other variables. The implied transmission mechanism is in line with the theoretical predictions of a large class of search and matching models. We also find that wage bargaining shocks explain a sizeable share of aggregate fluctuations in unemployment and inflation, that their pass-through to prices is very close to being full, and that they imply plausible dynamics for the vacancy rate, firms’ profits, and the labour share.
- JEL Code
- J2 : Labor and Demographic Economics→Demand and Supply of Labor
J3 : Labor and Demographic Economics→Wages, Compensation, and Labor Costs
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
- 21 September 2021
- OCCASIONAL PAPER SERIES - No. 279Details
- Abstract
- The existence of nominal rigidities and inflation differentials between countries offers two of the main rationales for an inflation buffer in a monetary union where monetary policy is oriented towards an area-wide inflation objective. Evidence accumulated since 2003 suggests that nominal rigidities remain a prevalent feature of the euro area, with some differences as regards prices and wages. Price setting may have become more flexible and there is no evidence for any especially strong downward rigidities in price setting. At the same time, persistent downward nominal wage rigidity (DWR) provides a strong argument for a positive inflation buffer to “grease the wheels” of the euro area economy – also in order to avoid the risk of macroeconomic adjustments being managed in terms of quantities (unemployment) rather than prices when DWR is binding and particularly when productivity growth is low. Inflation differentials across euro area countries have tended to be small but persistent. For inflation dispersion in the euro area, the across countries has been more important than across regions, confirming that an inflation buffer might be especially important in a monetary union of different countries. Overall, inflation differentials were due to the rise of economic and financial imbalances in the first decade of the euro and the subsequent need for adjustment. Balassa-Samuelson effects which were highlighted in the 2003 strategy review were only a minor factor. By and large, the ECB’s inflation objective seems to have provided a sufficient margin to prevent countries from having to live with prolonged periods of excessively low inflation rates in the period 1999-2019. There were some exceptions in the second decade of the euro (from 2009-2019), when inflation in the euro area was, overall, substantially lower than during the first decade.
- JEL Code
- 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
E24 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Employment, Unemployment, Wages, Intergenerational Income Distribution, Aggregate Human Capital
- 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
- 25 March 2021
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 2, 2021Details
- Abstract
- The coronavirus (COVID-19) pandemic triggered significant changes in household spending in 2020. These shifts are reflected in the 2021 HICP weights, and consequently, also in measured annual inflation. The impact of these new HICP weights on annual inflation is not insignificant and is also heterogenous across countries. Looking ahead, the full impact will most likely only materialise over the course of the year as the relative prices gradually change.
- JEL Code
- 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
- 14 December 2020
- WORKING PAPER SERIES - No. 2501Details
- Abstract
- We compare direct forecasts of HICP and HICP excluding energy and food in the euro area and five member countries to aggregated forecasts of their main components from large Bayesian VARs with a shared set of predictors. We focus on conditional point and density forecasts, in line with forecasting practices at many policy institutions. Our main findings are that point forecasts perform similarly using both approaches, whereas directly forecasting aggregate indices tends to yield better density forecasts. In the aftermath of the Great Financial Crisis, relative forecasting performance was typically only affected temporarily. Inflation forecasts made by Eurosystem/ECB staff perform similarly or slightly better than those from our models for the euro area.
- JEL Code
- C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: 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
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
- 3 September 2019
- OCCASIONAL PAPER SERIES - No. 232Details
- Abstract
- Despite notable improvements in the labour market since 2013, wage growth in the euro area was subdued and substantially overpredicted in 2013-17. This paper summarises the findings of an ESCB expert group on the reasons for low wage growth and provides comparable analyses on wage developments in the euro area as a whole and in individual EU countries. The paper finds that cyclical drivers, as captured by a standard Phillips curve, seem to explain much of the weakness in wage growth during this period, but not all of it. Going beyond the drivers included in standard Phillips curves, other factors are also found to have played a role, such as compositional effects, the possible non-linear reaction of wage growth to cyclical improvements, and structural and institutional factors. In order to increase the robustness of wage forecasts, the paper also proposes ready-to-use tools for cross-checking euro area wage growth forecasts based on wage Phillips curves. These are derived based on a comprehensive real-time forecast evaluation exercise
- JEL Code
- J30 : Labor and Demographic Economics→Wages, Compensation, and Labor Costs→General
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
- 7 February 2019
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 1, 2019Details
- Abstract
- Inflation projections are based on models, assumptions and expert judgement. These include assumptions regarding the future evolution of oil prices, which mainly affect energy prices. Oil prices and oil futures have moved down significantly since autumn 2018, below the assumptions of the December 2018 Eurosystem staff projections. This box documents the mechanical implications of this shift for the projections of the energy component of HICP inflation.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
- 22 March 2018
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 2, 2018Details
- Abstract
- This box assesses to what extent changes in seasonality and idiosyncratic price changes (defined as outliers) can explain recent short-term volatility in the profile of euro area HICP inflation excluding food and energy.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
- 25 January 2017
- WORKING PAPER SERIES - No. 2002Details
- Abstract
- This paper examines the process of adjustment of prices in Italy to determine whether nominal flexibility, measured by the frequency of price changes, has increased in the recent years of protracted stagnation and double-dip recession. The analysis is based on a large micro-level dataset of individual prices collected monthly by Istat from 2006 to 2013 for the Consumer Price Index. We find that both the percentage of prices adjusted monthly and the average size of the adjustment have risen significantly since the 1996-2001 period, in particular for downward changes. This greater flexibility is related in part to the spread of modern distribution structures. Our estimates further indicate that the recession has affected the price adjustment mechanism: for manufactures, price cuts have become larger and more frequent, while increases are more moderate; for services, both the frequency and the size of price increases have diminished.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
D21 : Microeconomics→Production and Organizations→Firm Behavior: Theory
D40 : Microeconomics→Market Structure and Pricing→General
L11 : Industrial Organization→Market Structure, Firm Strategy, and Market Performance→Production, Pricing, and Market Structure, Size Distribution of Firms - Network
- Task force on low inflation (LIFT)
- 2016
- Journal of Business & Economic StatisticsShort-Term GDP Forecasting With a Mixed-Frequency Dynamic Factor Model With Stochastic Volatility
- 2014
- Studies in Nonlinear Dynamics & Econometrics