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Luca Onorante

Economics

Division

Business Cycle Analysis

Current Position

Senior Economist

Fields of interest

Macroeconomics and Monetary Economics,International Economics

Email

Luca.Onorante@ecb.int

4 August 2021
ECONOMIC BULLETIN - ARTICLE
Economic Bulletin Issue 5, 2021
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Abstract
This article reviews how policy institutions – international organisations and central banks – use big data and machine learning methods to analyse the business cycle. It provides different examples to show how big data and machine learning methods are particularly suitable for capturing large shocks and non-linearities in real time. The coronavirus crisis is a case in point, where big data have provided invaluable timely signals on the state of the economy, thus helping to track and assess economic activity, domestic demand and labour market developments in real time. Finally, the article discusses the main challenges faced by central banks when using non-standard data and methods and areas of further application to the work of central banks.
JEL Code
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?
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
11 January 2021
WORKING PAPER SERIES - No. 2510
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Abstract
This paper develops Bayesian econometric methods for posterior inference in non-parametric mixed frequency VARs using additive regression trees. We argue that regression tree models are ideally suited for macroeconomic nowcasting in the face of extreme observations, for instance those produced by the COVID-19 pandemic of 2020. This is due to their flexibility and ability to model outliers. In an application involving four major euro area countries, we find substantial improvements in nowcasting performance relative to a linear mixed frequency VAR.
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
25 November 2020
WORKING PAPER SERIES - No. 2494
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Abstract
We propose a granular framework that makes use of advanced statistical methods to approximate developments in economy-wide expected corporate earnings. In particular, we evaluate the dynamic network structure of stock returns in the United States as a proxy for the transmission of shocks through the economy and identify node positions (firms) whose connectedness provides a signal for economic growth. The nowcasting exercise, with both the in-sample and the out-of-sample consistent feature selection, highlights which firms are contemporaneously exposed to aggregate downturns and provides a more complete narrative than is usually provided by more aggregate data. The two-state model for predicting periods of negative growth can remarkably well predict future states by using information derived from the node-positions of manufacturing, transportation and financial (particularly insurance) firms. The three-states model, which identifies high, low and negative growth, successfully predicts economic regimes by making use of information from the financial, insurance, and retail sectors.
JEL Code
C45 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→Neural Networks and Related Topics
C51 : Mathematical and Quantitative Methods→Econometric Modeling→Model Construction and Estimation
D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
N1 : Economic History→Macroeconomics and Monetary Economics, Industrial Structure, Growth, Fluctuations
9 January 2020
WORKING PAPER SERIES - No. 2359
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Abstract
We model economic policy uncertainty (EPU) in the four largest euro area countries by applying machine learning techniques to news articles. The unsupervised machine learning algorithm used makes it possible to retrieve the individual components of overall EPU endogenously for a wide range of languages. The uncertainty indices computed from January 2000 to May 2019 capture episodes of regulatory change, trade tensions and financial stress. In an evaluation exercise, we use a structural vector autoregression model to study the relationship between different sources of uncertainty and investment in machinery and equipment as a proxy for business investment. We document strong heterogeneity and asymmetries in the relationship between investment and uncertainty across and within countries. For example, while investment in France, Italy and Spain reacts strongly to political uncertainty shocks, in Germany investment is more sensitive to trade uncertainty shocks.
JEL Code
C80 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→General
D80 : Microeconomics→Information, Knowledge, and Uncertainty→General
E22 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Capital, Investment, Capacity
E66 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→General Outlook and Conditions
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
G31 : Financial Economics→Corporate Finance and Governance→Capital Budgeting, Fixed Investment and Inventory Studies, Capacity
3 December 2019
WORKING PAPER SERIES - No. 2335
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Abstract
The post-crisis environment has posed important challenges to standard forecasting models. In this paper, we exploit several combinations of a large-scale DSGE structural model with standard reduced-form methods such as (B)VAR (i.e. DSGE-VAR and Augmented-(B)VARDSGE methods) and assess their use for forecasting the Spanish economy. Our empirical findings suggest that: (i) the DSGE model underestimates growth of real variables due to its mean reverting properties in the context of a sample that is difficult to deal with; (ii) in spite of this, reduced-form VARs benefit from the imposition of an economic prior from the structural model; and (iii) pooling information in the form of variables extracted from the structural model with (B)VAR methods does not give rise to any relevant gain in terms of forecasting accuracy.
JEL Code
C54 : Mathematical and Quantitative Methods→Econometric Modeling→Quantitative Policy Modeling
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
F3 : International Economics→International Finance
F41 : International Economics→Macroeconomic Aspects of International Trade and Finance→Open Economy Macroeconomics
4 November 2019
WORKING PAPER SERIES - No. 2325
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Abstract
Time-varying parameter (TVP) models have the potential to be over-parameterized, particularly when the number of variables in the model is large. Global-local priors are increasingly used to induce shrinkage in such models. But the estimates produced by these priors can still have appreciable uncertainty. Sparsification has the potential to remove this uncertainty and improve forecasts. In this paper, we develop computationally simple methods which both shrink and sparsify TVP models. In a simulated data exercise we show the benefits of our shrink-then-sparsify approach in a variety of sparse and dense TVP regressions. In a macroeconomic forecast exercise, we find our approach to substantially improve forecast performance relative to shrinkage alone.
JEL Code
C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C30 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→General
E3 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles
D31 : Microeconomics→Distribution→Personal Income, Wealth, and Their Distributions
6 August 2019
ECONOMIC BULLETIN - BOX
Economic Bulletin Issue 5, 2019
Details
Abstract
This box presents a model-based economic policy uncertainty (EPU) index for the euro area by applying machine learning techniques to news articles from January 2000 to May 2019. The machine learning algorithm retrieves components of overall EPU, such as trade, fiscal, monetary or domestic regulations, for a wide range of languages. Recently, a steady and pronounced increase in the euro area EPU index has been observed, driven mainly by trade, domestic regulation and fiscal policy uncertainties.
JEL Code
C1 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General
C8 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs
E65 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→Studies of Particular Policy Episodes
31 July 2019
WORKING PAPER SERIES - No. 2302
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Abstract
This paper proposes a large-scale Bayesian vector autoregression with factor stochastic volatility to investigate the macroeconomic consequences of international uncertainty shocks in G7 countries. The curse of dimensionality is addressed by means of a global-local shrinkage prior that mimics certain features of the well-known Minnesota prior, yet provides additional flexibility in terms of achieving shrinkage. The factor structure enables us to identify an international uncertainty shock by assuming that it is the joint volatility process that determines the dynamics of the variance-covariance matrix of the common factors. To allow for first and second moment shocks we, moreover, assume that the uncertainty factor enters the VAR equation as an additional regressor. Our findings suggest that the estimated uncertainty measure is strongly connected to global equity price volatility, closely tracking other prominent measures commonly adopted to assess uncertainty. The dynamic responses of a set of macroeconomic and financial variables show that an international uncertainty shock exerts large effects on all economies and variables under consideration.
JEL Code
C30 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→General
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
F41 : International Economics→Macroeconomic Aspects of International Trade and Finance→Open Economy Macroeconomics
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
17 July 2019
WORKING PAPER SERIES - No. 2295
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Abstract
We perform a robust estimation of the Phillips curve in the euro area using a battery of 630 theory-driven models. We extend the existing literature by adding model specifications, taking into account the uncertainty in the measurement of variables and testing for potential non-linearities and structural changes. Using Dynamic Model Averaging, we identify the most important determinants of inflation over the sample. We then forecast core inflation 12 quarters ahead and present its probability distribution. We compare the distribution of forecasts performed in recent years, and we assess, in a probabilistic manner, the convergence towards a sustainable path of inflation.
JEL Code
C30 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→General
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
F41 : International Economics→Macroeconomic Aspects of International Trade and Finance→Open Economy Macroeconomics
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
18 April 2018
WORKING PAPER SERIES - No. 2144
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Abstract
We examine, conditional on structural shocks, the macroeconomic performance of different countercyclical capital buffer (CCyB) rules in small open economy estimated medium scale DSGE. We find that rules based on the credit gap create a trade-off between the stabilization of fluctuations originating in the housing market and fluctuations caused by foreign demand shocks. The trade-off disappears if the regulator targets house prices instead. As a result, the optimal simple CCyB rule depends only on the house price but not the credit gap. Moreover, the optimal simple rule leads to significant welfare gains compared to the no CCyB case.
JEL Code
F41 : International Economics→Macroeconomic Aspects of International Trade and Finance→Open Economy Macroeconomics
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
10 July 2014
WORKING PAPER SERIES - No. 1688
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Abstract
This paper documents macroeconomic forecasting during the global financial crisis by two key central banks: the European Central Bank and the Federal Reserve Bank of New York. The paper is the result of a collaborative effort between staff at the two institutions, allowing us to study the time-stamped forecasts as they were made throughout the crisis. The analysis does not exclusively focuses on point forecast performance. It also examines methodological contributions, including how financial market data could have been incorporated into the forecasting process.
JEL Code
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 February 2012
WORKING PAPER SERIES - No. 1422
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Abstract
This paper uses forecasts from the European Central Bank’s Survey of Professional Forecasters to investigate the relationship between inflation and inflation expectations in the euro area. We use theoretical structures based on the New Keynesian and Neoclassical Phillips curves to inform our empirical work and dynamic model averaging in order to ensure an econometric specification capturing potential changes. We use both regression-based and VAR-based methods. The paper confirms that there have been shifts in the Phillips curve and identifies three sub-periods in the EMU: an initial period of price stability, a few years where inflation was driven mainly by external shocks, and the financial crisis, where the New Keynesian Phillips curve outperforms alternative formulations. This finding underlines the importance of introducing informed judgment in forecasting models and is also important for the conduct of monetary policy, as the crisis entails changes in the effect of expectations on inflation and a resurgence of the “sacrifice ratio”.
JEL Code
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
22 July 2010
WORKING PAPER SERIES - No. 1229
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Abstract
This paper estimates a time-varying AR-GARCH model of inflation producing measures of inflation uncertainty for the euro area, and investigates their linkages in a VAR framework, also allowing for the possible impact of the policy regime change associated with the start of EMU in 1999. The main findings are as follows. Steadystate inflation and inflation uncertainty have declined steadily since the inception of EMU, whilst short-run uncertainty has increased, mainly owing to exogenous shocks. A sequential dummy procedure provides further evidence of a structural break coinciding with the introduction of the euro and resulting in lower long-run uncertainty. It also appears that the direction of causality has been reversed, and that in the euro period the Friedman-Ball link is empirically supported, consistently with the idea that the ECB can achieve lower inflation uncertainty by lowering the inflation rate.
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
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
14 April 2010
WORKING PAPER SERIES - No. 1168
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Abstract
In this paper we analyse the pass-through of a commodity price shock along the food price chain in the euro area. Unlike the existing literature, which mainly focuses on food commodity prices quoted in international markets, we use a novel database that accounts for the role of the Common Agricultural Policy in the European Union. We model several departures from the linear pass-through benchmark and compare alternative specifications with aggregate and disaggregate food data. Overall, when the appropriate dataset and methodology are used, it is possible to identify a significant and longlasting food price pass-through. The results of our regressions are applied to the strong increase in food prices in the 2007-08 period; a simple decomposition exercise shows that commodity prices are the main determinant of the increase in producer and consumer prices, thus solving the pass-through puzzle highlighted in the existing literature for the euro area.
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
E3 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles
Q17 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Agriculture→Agriculture in International Trade
14 May 2008
WORKING PAPER SERIES - No. 901
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Abstract
Short-term fiscal indicators based on public accounts data are often used by European policy makers. They represent one of the main sources of publicly available intra-annual fiscal information. Nevertheless, these indicators have received limited attention from the academic literature analysing fiscal forecasting in Europe. Some recent literature suggests the validity of public accounts data to forecast government deficits in the euro area. We extend this literature on two fronts:(i) we shift the focus from indicators of government deficits to look at indicators for government total revenue and total expenditure; (ii) we use a mixed-frequency state-space model to integrate readily available monthly/quarterly cash-based fiscal data with annual general government series (National Accounts). By doing so, we are able to maintain the focus on forecasting and monitoring annual outcomes, while making use of infra-annual fiscal information, available within the current year. The paper makes a case for the use of monthly cash indicators for multi- lateral fiscal surveillance at the European level.
JEL Code
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E6 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook
H6 : Public Economics→National Budget, Deficit, and Debt
27 July 2006
WORKING PAPER SERIES - No. 664
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Abstract
The monetary integration of the acceding countries will proceed in several distinct steps, starting with membership in the European Union (EU), followed by participation in the so-called Exchange Rate Mechanism (ERM) II and ultimately entry into the euro area. This paper addresses the question of whether a reduction of public deficits, such as imposed by the Maastricht fiscal criteria, is a necessary or useful step on the road to the adoption of the euro. The question is addressed by examining the interaction of monetary, fiscal and wage policies and their effects on prices in a monetary union hit by economic shocks. The theoretical model shows that fiscal activism is related with both entry in monetary union and with structural differences in the national labour markets, and analyses in detail the effect of both factors. As for acceding countries, the conclusion is that the process of deficit reduction should be completed before entry, as suggested by the Maastricht criteria. The chapter also suggests that fiscal constraints on government deficits appear essential in a monetary union when the wage formation is taken into due consideration.
JEL Code
E61 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→Policy Objectives, Policy Designs and Consistency, Policy Coordination
E62 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→Fiscal Policy
H30 : Public Economics→Fiscal Policies and Behavior of Economic Agents→General
2015
European Economic Review
  • Onorante, Luca & Raftery, Adrian E
2014
International Journal of Forecasting
  • Giannone, Domenico & Lenza, Michele & Momferatou, Daphne & Onorante, Luca
2014
Journal of Business and Economic Statistics
  • Alessi, Lucia & Ghysels, Eric & Onorante, Luca & Peach, Richard & Potter, Simon M.
2012
International Journal of Central Banking
  • Gianluigi Ferrucci & Rebeca Jiménez-Rodríguez & Luca Onorante
2012
Empirical Economics
  • Guglielmo Caporale & Luca Onorante & Paolo Paesani
2010
Journal of Policy Modeling
  • Onorante, Luca & Pedregal, Diego J. & Pérez, Javier J. & Signorini, Sara