Inte tillgängligt på svenska
Michele Lenza
Research
- Division
Monetary Policy Research
- Current Position
-
Head of Section
- Fields of interest
-
Mathematical and Quantitative Methods,Macroeconomics and Monetary Economics
- Other current responsibilities
- 2023-
International Association for Applied Econometrics (IAAE) Fellow
- 2021-
CEPR Research Fellow, Monetary Economics and Fluctuations
- 2017-
Leader of the research coordination group on "Macroeconomic Dynamics and Microfoundations" (formerly, Forecasting and Business Cycle Analysis)
- 2014-
Member of the Forecast Steering Committee, European Central Bank
- Education
- 2000-2007
PhD in Economics and Statistics, Université Libre de Bruxelles, Belgium
- 1999-2000
MA in Economics and Statistics, Université Libre de Bruxelles, Belgium
- 1993-1998
BA in Economics, Bocconi University, Italy
- Professional experience
- 2017-
Head of Section - Monetary Policy Research Division, Macroeconomics Section, Directorate General Research, European Central Bank
- 2013-2016
Principal Economist - Monetary Policy Research Division, Directorate General Research, European Central Bank
- 2011-2013
Senior Economist - Monetary Policy Research Division, Directorate General Research, European Central Bank
- 2004-2010
Economist - Econometric Modelling Division, Directorate General Research, European Central Bank
- 2004
Internship - EU countries Division, Directorate General Economics, European Central Bank
- 2003
Internship - Euro area Macroeconomic Developments Division, Directorate General Economics, European Central Bank
- Teaching experience
- 2017-2022
Professor of Macroeconomics - Monetary Policy, Joint Master in Political Economy Georgetown University (USA)/Université Libre de Bruxelles (Belgium)
- 2014-2016
Professor of Graduate Econometrics 3 - Université Libre de Bruxelles, Belgium
- 2011-2014
Professor of Graduate Macroeconomics 3 - Université Libre de Bruxelles, Belgium
- 2010-2011
Invited lectures, Graduate Econometrics 3; Université Libre de Bruxelles, Belgium
- 2009
Macroeconomic tools and techniques: reduced form and structural models (with A. D'Agostino, D. Giannone and G. Primiceri), Dublin, Central Bank of Ireland
- 2000-2004
Teaching Assistant - Graduate Macroeconomics, Graduate Econometrics, Seminaire d'Econometrie, Université Libre de Bruxelles, Belgium
- 17 October 2023
- RESEARCH BULLETIN - No. 112Details
- Abstract
- Inflation forecasts and their risks are key for monetary policy decisions. The strategy review concluded in 2021 highlighted how most Eurosystem models used to forecast inflation are linear. Linear models assume that changes in, for example, wages, always have the same fixed, proportional effect on inflation. A new machine learning model, recently developed at the ECB, captures very general forms of non-linearity, such as a changing sensitivity of inflation dynamics to prevailing economic circumstances. Forecasts from this machine learning model closely track Eurosystem staff inflation projections, suggesting that these projections capture mild non-linearity in inflation dynamics – likely owing to expert judgement – and are in line with state-of-the-art econometric methodologies.
- JEL Code
- 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
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
- 14 July 2023
- WORKING PAPER SERIES - No. 2830Details
- Abstract
- Density forecasts of euro area inflation are a fundamental input for a medium-term oriented central bank, such as the European Central Bank (ECB). We show that a quantile regression forest, capturing a general non-linear relationship between euro area (headline and core) inflation and a large set of determinants, is competitive with state-of-the-art linear benchmarks and judgemental survey forecasts. The median forecasts of the quantile regression forest are very collinear with the ECB point inflation forecasts, displaying similar deviations from “linearity”. Given that the ECB modelling toolbox is overwhelmingly linear, this finding suggests that the expert judgement embedded in the ECB forecast may be characterized by some mild non-linearity.
- JEL Code
- 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
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
- 27 April 2021
- WORKING PAPER SERIES - No. 2542Details
- Abstract
- We compare sparse and dense representations of predictive models in macroeconomics, microeconomics and finance. To deal with a large number of possible predictors, we specify a prior that allows for both variable selection and shrinkage. The posterior distribution does not typically concentrate on a single sparse model, but on a wide set of models that often include many predictors.
- JEL Code
- C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
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?
- 17 September 2020
- RESEARCH BULLETIN - No. 74Details
- Abstract
- The analysis of inflation dynamics and their possible changes over time is a key input in the design of monetary policy, particularly in the context of the strategy reviews recently undertaken by the Federal Reserve System and currently under way at the European Central Bank and other central banks. In this article, we study the causes of the stability of US inflation over the business cycle since the 1990s. We conclude that it is mainly due to a reduced sensitivity of firms’ pricing decisions to their cost pressures. Ignoring this observation could impair the ability of monetary policy to steer inflation toward its objective.
- 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
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 August 2020
- WORKING PAPER SERIES - No. 2461Details
- Abstract
- This paper illustrates how to handle a sequence of extreme observations—such as those recorded during the COVID-19 pandemic—when estimating a Vector Autoregression, which is the most popular time-series model in macroeconomics. Our results show that the ad-hoc strategy of dropping these observations may be acceptable for the purpose of parameter estimation. However, disregarding these recent data is inappropriate for forecasting the future evolution of the economy, because it vastly underestimates uncertainty.
- 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
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
- 12 August 2020
- WORKING PAPER SERIES - No. 2453Details
- Abstract
- Monitoring economic conditions in real time, or nowcasting, is among the key tasks routinely performed by economists. Nowcasting entails some key challenges, which also characterise modern Big Data analytics, often referred to as the three \Vs": the large number of time series continuously released (Volume), the complexity of the data covering various sectors of the economy, published in an asynchronous way and with different frequencies and precision (Variety), and the need to incorporate new information within minutes of their release (Velocity). In this paper, we explore alternative routes to bring Bayesian Vector Autoregressive (BVAR) models up to these challenges. We find that BVARs are able to effectively handle the three Vs and produce, in real time, accurate probabilistic predictions of US economic activity and, in addition, a meaningful narrative by means of scenario analysis.
- JEL Code
- E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
C01 : Mathematical and Quantitative Methods→General→Econometrics
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
- 2 July 2020
- WORKING PAPER SERIES - No. 2435Details
- Abstract
- The business cycle is alive and well, and real variables respond to it more or less as they always did. Witness the Great Recession. Inflation, in contrast, has gone quiescent. This paper studies the sources of this disconnect using VARs and an estimated DSGE model. It finds that the disconnect is due primarily to the muted reaction of inflation to cost pressures, regardless of how they are measured—a flat aggregate supply curve. A shift in policy towards more forceful inflation stabilization also appears to have played some role by reducing the impact of demand shocks on the real economy. The evidence rules out stories centered around changes in the structure of the labor market or in how we should measure its tightness.
- 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
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
- 23 August 2019
- WORKING PAPER SERIES - No. 2311Details
- Abstract
- This paper investigates the effects of interbank rate uncertainty on lending rates to euro area firms. We introduce a novel measure of interbank rate uncertainty, computed as the cross-sectional dispersion in interbank market rates on overnight unsecured loans. Using proprietary bank-level data, we find that interbank rate uncertainty significantly raises lending rates on loans to firms, with a peak effect of around 100 basis points during the 2007-2009 global financial crisis and the 2010-2012 European sovereign crisis. This effect is attenuated for banks with lower credit risk, sounder capital positions and greater access to central bank funding.
- JEL Code
- E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
D80 : Microeconomics→Information, Knowledge, and Uncertainty→General
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages - Network
- Research Task Force (RTF)
- 29 January 2019
- RESEARCH BULLETIN - No. 54Details
- Abstract
- “Quantitative easing” refers to central bank purchases of assets such as stocks and bonds to increase the money supply when interest rates are too low for conventional rate cuts to provide further policy accommodation. Quantitative easing in the euro area through the ECB’s asset purchase programme (APP) has stimulated economic activity and asset prices, affecting income and wealth inequality among households. It has decreased income inequality, mostly by reducing the unemployment rate for poorer households, but also, to a lesser extent, by increasing the wages of the employed. Quantitative easing has also helped to reduce net wealth inequality slightly through its positive impact on house prices.
- JEL Code
- D31 : Microeconomics→Distribution→Personal Income, Wealth, and Their Distributions
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies - Network
- Research Task Force (RTF)
- 28 January 2019
- WORKING PAPER SERIES - No. 2227Details
- Abstract
- The Eurosystem staff forecasts are conditional on the financial markets, the global economy and fiscal policy outlook, and include expert judgement. We develop a multi-country BVAR for the four largest countries of the euro area and we show that it provides accurate conditional forecasts of policy relevant variables such as, for example, consumer prices and GDP. The forecasting accuracy and the ability to mimic the path of the Eurosystem projections suggest that the model is a valid benchmark to assess the consistency of the projections with the conditional assumptions. As such, the BVAR can be used to identify possible sources of judgement, based on the gaps between the Eurosystem projections and the historical regularities captured by the model.
- JEL Code
- 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
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
- 25 January 2019
- WORKING PAPER SERIES - No. 2226Details
- Abstract
- This paper studies the relationship between the business cycle and financial intermediation in the euro area. We establish stylized facts and study their stability during the global financial crisis and the European sovereign debt crisis. Long-term interest rates have been exceptionally high and long-term loans and deposits exceptionally low since the Lehman collapse. Instead, short-term interest rates and short-term loans and deposits did not show abnormal dynamics in the course of the financial and sovereign debt crisis.
- JEL Code
- E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E51 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Money Supply, Credit, Money Multipliers
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
C51 : Mathematical and Quantitative Methods→Econometric Modeling→Model Construction and Estimation
- 30 October 2018
- WORKING PAPER SERIES - No. 2190Details
- Abstract
- This paper studies the effects of quantitative easing on income and wealth of individual euro area households. The aggregate effects of quantitative easing are estimated in a multi-country VAR model of the four largest euro area countries, in which key variables affecting household income and wealth are included, such as the unemployment rate, wages, interest rates, house prices and stock prices. The aggregate effects are distributed across the individual households by means of a reduced-form simulation on micro data from the Household Finance and Consumption Survey, capturing the income composition, the portfolio composition and the earnings heterogeneity channels of transmission. We find that the earnings heterogeneity channel plays a key role: quantitative easing compresses the income distribution since many households with lower incomes become employed. In contrast, monetary policy has only negligible effects on wealth inequality.
- JEL Code
- D14 : Microeconomics→Household Behavior and Family Economics→Household Saving; Personal Finance
D31 : Microeconomics→Distribution→Personal Income, Wealth, and Their Distributions
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies - Network
- Household Finance and Consumption Network (HFCN)
- 25 June 2018
- ECONOMIC BULLETIN - ARTICLEEconomic Bulletin Issue 4, 2018Details
- Abstract
- Headline inflation can be noisy, blurring the signal on the medium-term inflationary pressure relevant for monetary policy. To help distinguish signal from noise in the data, central banks monitor measures of underlying inflation. As there are many ways of measuring underlying inflation, it is important to understand the properties of the various indicators and what factors may account for any divergence between them. This article describes in detail the measures of underlying inflation typically used at the ECB and evaluates them against a set of empirical criteria. Our results suggest that no one measure of underlying inflation is superior in all situations as the performance of the indicators varies over time. In practice, each indicator comes with merits and shortcomings, which calls for monitoring the full range of measures of underlying inflation.
- JEL Code
- 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
- 27 February 2018
- WORKING PAPER SERIES - No. 2132Details
- Abstract
- We propose a class of prior distributions that discipline the long-run behavior of Vector Autoregressions (VARs). These priors can be naturally elicited using economic theory, which provides guidance on the joint dynamics of macroeconomic time series in the long run. Our priors for the long run are conjugate, and can thus be easily implemented using dummy observations and combined with other popular priors. In VARs with standard macroeconomic variables, a prior based on the long-run predictions of a wide class of theoretical models yields substantial improvements in the forecasting performance.
- 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
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
- 19 September 2016
- WORKING PAPER SERIES - No. 1966Details
- Abstract
- Using a small Bayesian dynamic factor model of the euro area we estimate the deviations of output from its trend that are consistent with the behavior of inflation. We label these deviations the output gap. In order to pin-down the features of the model, we evaluate the accuracy of real-time inflation forecasts from different model specifications. The version that forecasts inflation best implies that after the 2011 sovereign debt crisis the output gap in the euro area has been much larger than the official estimates. Versions featuring a secular-stagnation-like slowdown in trend growth, and hence a small output gap after 2011, do not adequately capture the inflation developments.
- 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
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
- 1 July 2016
- RESEARCH BULLETIN - No. 24Details
- Abstract
- The estimates of the output gap depend on the features of the models used to derive them. We discriminate among different estimates on the basis of their ability to forecast inflation. Our analysis suggests that output in the euro area was 6% lower than potential in 2014 and 2015, which is substantially below institutional estimates.
- 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
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
- 12 September 2014
- WORKING PAPER SERIES - No. 1733Details
- Abstract
- This paper describes an algorithm to compute the distribution of conditional forecasts, i.e. projections of a set of variables of interest on future paths of some other variables, in dynamic systems. The algorithm is based on Kalman filtering methods and is computationally viable for large models that can be cast in a linear state space representation. We build large vector autoregressions (VARs) and a large dynamic factor model (DFM) for a quarterly data set of 26 euro area macroeconomic and financial indicators. Both approaches deliver similar forecasts and scenario assessments. In addition, conditional forecasts shed light on the stability of the dynamic relationships in the euro area during the recent episodes of financial turmoil and indicate that only a small number of sources drive the bulk of the fluctuations in the euro area economy.
- JEL Code
- C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C13 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Estimation: General
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
- 5 August 2014
- WORKING PAPER SERIES - No. 1707Details
- Abstract
- This study evaluates the macroeconomic effects of Outright Monetary Transaction (OMT) announcements by the European Central Bank (ECB). Using high-frequency data, we find that OMT announcements decreased the Italian and Spanish 2-year government bond yields by about 2 percentage points, while leaving unchanged the bond yields of the same maturity in Germany and France. These results are used to calibrate a scenario in a multi-country model describing the macro-financial linkages in France, Germany, Italy, and Spain. The scenario analysis suggests that the reduction in bond yields due to OMT announcements is associated with a significant increase in real activity, credit, and prices in Italy and Spain with relatively muted spillovers in France and Germany.
- JEL Code
- E47 : Macroeconomics and Monetary Economics→Money and Interest Rates→Forecasting and Simulation: Models and Applications
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
C54 : Mathematical and Quantitative Methods→Econometric Modeling→Quantitative Policy Modeling
- 8 August 2013
- OCCASIONAL PAPER SERIES - No. 151Details
- Abstract
- This report analyses and reviews the corporate finance structure of non-financial corporations (NFCs) in the euro area, including how they interact with the macroeconomic environment. Special emphasis is placed on the crisis that began in 2007-08, thus underlining the relevance of financing and credit conditions to investment and economic activity in turbulent times. When approaching such a broad topic, a number of key questions arise. How did the corporate sector
- JEL Code
- E0 : Macroeconomics and Monetary Economics→General
E5 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit
- 21 November 2012
- WORKING PAPER SERIES - No. 1496Details
- Abstract
- We analyse the impact on the euro area economy of the ECB’s non-standard monetary policy measures by studying the effect of the expansion of intermediation of interbank transactions across the central bank balance sheet. We exploit data drawn from the aggregated Monetary and Financial Institutions (MFI) balance sheet, which allows us to construct a measure of the ‘policy shock’ represented by the ECB’s increasing role as a financial intermediary. We find small but significant effects both on loans and real economic activity.
- JEL Code
- E5 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
- 16 November 2012
- WORKING PAPER SERIES - No. 1494Details
- Abstract
- Vector autoregressions (VARs) are flexible time series models that can capture complex dynamic interrelationships among macroeconomic variables. However, their dense parameterization leads to unstable inference and inaccurate out-ofsample forecasts, particularly for models with many variables. A solution to this problem is to use informative priors, in order to shrink the richly parameterized unrestricted model towards a parsimonious na
- 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
- 14 January 2011
- WORKING PAPER SERIES - No. 1290Details
- Abstract
- Standard accounts of the Great Depression attribute an important causal role to monetary policy errors in accounting for the catastrophic collapse in economic activity observed in the early 1930s. While views vary on the relative importance of money versus credit contraction in the propagation of this policy error to the wider economy and ultimately price developments, a broad consensus exists in the economics profession around the view that the collapse in financial intermediation was a crucial intermediary step. What lessons have monetary policy makers taken from this episode? And how have they informed the conduct of monetary policy by leading central banks in recent times? This paper sets out to address these questions, in the context of the financial crisis of 2008-09 and with application to the euro area. It concludes that the Eurosystem’s non-standard monetary policy measures have supported monetary policy transmission and avoided the calamity of the 1930s.
- JEL Code
- E5 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit
E4 : Macroeconomics and Monetary Economics→Money and Interest Rates
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
- 1 October 2010
- WORKING PAPER SERIES - No. 1253Details
- Abstract
- This paper describes the response of three central banks to the 2007-09 financial crisis: the European Central Bank, the Federal Reserve and the Bank of England. In particular, the paper discusses the design, implementation and impact of so-called "non-standard" monetary policy measures focusing on those introduced in the euro area in the aftermath of the failure of Lehman Brothers in September 2008. Having established the impact of these measures on various observable money market spreads, we propose an empirical exercise intended to quantify the macroeconomic impact of non-standard monetary policy measures insofar as it has been transmitted via these spreads. The results suggest that non-standard measures have played a quantitatively significant role in stabilising the financial sector and economy after the collapse of Lehman Bros., even if insufficient to avoid a significant fall in economic and financial activity.
- JEL Code
- E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
- 19 February 2009
- WORKING PAPER SERIES - No. 1010Details
- Abstract
- This paper shows that the EMU has not affected historical characteristics of member countries' business cycles and their cross-correlations. Member countries which had similar levels of GDP per-capita in the seventies have also experienced similar business cycles since then and no significant change associated with the EMU can be detected. For the other countries, volatility has been historically higher and this has not changed in the last ten years. We also find that the aggregate euro area per-capita GDP growth since 1999 has been lower than what could have been predicted on the basis of historical experience and US observed developments. The gap between US and euro area GDP per capita level has been 30% on average since 1970 and there is no sign of catching up or of further widening.
- JEL Code
- E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E3 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles
C5 : Mathematical and Quantitative Methods→Econometric Modeling
F2 : International Economics→International Factor Movements and International Business
F43 : International Economics→Macroeconomic Aspects of International Trade and Finance→Economic Growth of Open Economies
- 23 February 2008
- WORKING PAPER SERIES - No. 873Details
- Abstract
- This paper shows that general equilibrium effects can partly rationalize the high correlation between saving and investment rates observed in OECD countries. We find that once controlling for general equilibrium effects the saving-retention coefficient remains high in the 70’s but decreases considerably since the 80’s, consistently with the increased capital mobility in OECD countries.
- JEL Code
- C23 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Panel Data Models, Spatio-temporal Models
F32 : International Economics→International Finance→Current Account Adjustment, Short-Term Capital Movements
F41 : International Economics→Macroeconomic Aspects of International Trade and Finance→Open Economy Macroeconomics
- 23 February 2008
- WORKING PAPER SERIES - No. 865Details
- Abstract
- This paper shows that the explanation of the decline in the volatility of GDP growth since the mid-eighties is not the decline in the volatility of exogenous shocks but rather a change in their propagation mechanism.
- JEL Code
- E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
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
- 17 December 2007
- WORKING PAPER SERIES - No. 837Details
- Abstract
- This paper studies optimal monetary policy responses in an economy featuring sectorial heterogeneity in the frequency of price adjustments. It shows that a central bank facing heterogeneous nominal rigidities is more likely to behave less aggressively than in a fully sticky economy. Hence, the supposedly excessive caution in the conduct of monetary policy shown by central banks could be partly explained by the existence of a relevant sectorial dispersion in the frequency of price adjustments.
- JEL Code
- E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
- 2024
- Handbook on Macroeconomic ForecastingForecasting inflation in the US and in the euro area
- 2024
- Journal of Applied EconometricsHow Does Monetary Policy Affect Income and Wealth Inequality? Evidence from Quantitative Easing in the Euro Area
- 2023
- European Economic ReviewInflation and wage growth since the pandemic: a comment
- 2022
- Journal of Applied EconometricsHow to estimate a vector autoregression after March 2020
- 2022
- Journal of EconometricsNowcasting with Large Bayesian Vector Autoregressions
- 2021
- EconometricaEconomic predictions with big data: the illusion of sparsity
- 2020
- Brookings Papers on Economic Activity
- 2019
- International Journal of ForecastingMind the gap: a multi-country BVAR benchmark for the Eurosystem projections
- 2019
- International Journal of Central BankingMoney, credit, monetary policy and the business cycle in the euro area: what has changed since the crisis?
- 2019
- Journal of the American Statistical AssociationPriors for the long run
- 2018
- Journal of Money, Credit and BankingAn inflation-predicting measure of the output gap in the euro area
- 2017
- Empirical EconomicsThe national segmentation of euro area bank balance sheets during the financial crisis
- 2016
- International Journal of Central BankingThe financial and macroeconomic effects of the OMT announcements
- 2015
- International Journal of ForecastingConditional forecasts and scenario analysis with vector autoregressions for large cross-sections
- 2015
- The Review of Economics and StatisticsPrior selection for vector autoregressions
- 2014
- International Journal of ForecastingShort-term inflation projections: a bayesian vector-autoregressive approach
- 2014
- Advances in EconometricsNowcasting business cycles: a bayesian approach to dynamic heterogeneous factor models
- 2012
- The Economic JournalThe ECB and the interbank market
- 2012
- Interest rates, prices and liquidityNon-standard monetary policy measures and monetary developments
- 2011
- IMF Economic ReviewMarket Freedom and the Great Recession
- 2011
- Journal of Economics and StatisticsA factor model for euro area short-term inflation analysis
- 2010
- Economic PolicyMonetary Policy in exceptional times
- 2010
- Europe and the EMUBusiness cycles in the euro area
- 2010
- NBER International Seminars On Macroeconomics 2009The Feldstein-Horioka Fact
- 2009
- Journal of International Money and FinanceMonetary analysis and monetary policy in the euro area 1999-2006
- 2009
- The euro. The first decadeThe ECB and the bond market. A discussion
- 2008
- Journal of European Economic AssociationExplaining the Great Moderation: it's not the shocks!