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Jérôme Henry

17 July 2019
OCCASIONAL PAPER SERIES - No. 227
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Abstract
This occasional paper describes how the financial stability and macroprudential policy functions are organised at the ECB. Financial stability has been a key policy function of the ECB since its inception. Macroprudential policy tasks were later conferred on the ECB by the Single Supervisory Mechanism (SSM) Regulation. The paper describes the ECB’s macroprudential governance framework in the new institutional set-up. After reviewing the concept and origins of systemic risk, it reflects on the emergence of macroprudential policy in the aftermath of the financial crisis, its objectives and instruments, as well as specific aspects of this policy area in a monetary union such as the euro area. The ECB’s responsibilities required new tools to be developed to measure systemic risk at financial institution, country and system-wide level. The paper discusses selected analytical tools supporting financial stability surveillance and assessment work, as well as macroprudential policy analysis at the ECB. The tools are grouped into three broad areas: (i) methods to gauge the state of financial instability or prospects of near-term systemic stress, (ii) measures to capture the build-up of systemic risk focused on country-level financial cycle measurement and early warning methods, and (iii) the ECB stress testing framework for macroprudential purposes.
JEL Code
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
F36 : International Economics→International Finance→Financial Aspects of Economic Integration
G20 : Financial Economics→Financial Institutions and Services→General
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
K23 : Law and Economics→Regulation and Business Law→Regulated Industries and Administrative Law
21 June 2017
WORKING PAPER SERIES - No. 2081
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Abstract
We investigate the consequences of overleveraging and the potential for destabilizing effects from financial- and real-sector interactions. In a theoretical framework, we model overleveraging and indicate how a highly leveraged banking system can lead to unstable dynamics and downward spirals. Inspired by Brunnermeier and Sannikov (2014) and Stein (2012), we empirically measure the deviation-from-optimal-leverage for 40 large EU banks. We then use this measure to condition the joint dynamics of credit flows and macroeconomic activity in a large-scale regime change model: A Threshold Mixed-Cross-Section Global Vector Autoregressive (T-MCS-GVAR) model. The regime-switching component of the model aims to make the relationship between credit and real activity dependent on the extent to which the banking system is overleveraged. We find significant nonlinearities as a function of overleverage. When leverage is standing above its equilibrium level, the effect of a deleveraging shocks on credit supply and economic activity are visibly more detrimental than at times of underleveraging.
JEL Code
E2 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy
E6 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook
C13 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Estimation: General
G6 : Financial Economics
11 October 2013
OCCASIONAL PAPER SERIES - No. 152
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Abstract
The use of macro stress tests to assess bank solvency has developed rapidly over the past few years. This development was reinforced by the financial crisis, which resulted in substantial losses for banks and created general uncertainty about the banking sector's loss-bearing capacity. Macro stress testing has proved a useful instrument to help identify potential vulnerabilities within the banking sector and to gauge its resilience to adverse developments. To support its contribution to safeguarding financial stability and its financial sector-related work in the context of EU/IMF Financial Assistance Programmes, and looking ahead to the establishment of the Single Supervisory Mechanism (SSM), the ECB has developed a top-down macro stress testing framework that is used regularly for forward-looking bank solvency assessments. This paper comprehensively presents the main features of this framework and illustrates how it can be employed for various policy analysis purposes.
JEL Code
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
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
G01 : Financial Economics→General→Financial Crises
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
19 January 2010
WORKING PAPER SERIES - No. 1145
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Abstract
This paper describes how we constructed a real-time database for the euro area covering more than 200 series regularly published in the European Central Bank Monthly Bulletin, as made available ahead of publication to the Governing Council members before their first meeting of the month. We describe the database in details and study the properties of the euro area real-time data flow and data revisions, also providing comparisons with the United States and Japan. We finally illustrate how such revisions can contribute to the uncertainty surrounding key macroeconomic ratios and the NAIRU.
JEL Code
C01 : Mathematical and Quantitative Methods→General→Econometrics
C82 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Macroeconomic Data, Data Access
E24 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Employment, Unemployment, Wages, Intergenerational Income Distribution, Aggregate Human Capital
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
22 August 2005
WORKING PAPER SERIES - No. 510
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Abstract
New-Keynesian models are characterized by the presence of expectations as explanatory variables. To use these models for policy evaluation, the econometrician must estimate the parameters of expectation terms. Standard estimation methods have several drawbacks, including possible lack of identification of the parameters, misspecification of the model due to omitted variables or parameter instability, and the common use of inefficient estimation methods. Several authors have raised concerns over the validity of commonly used instruments to achieve identification. In this paper we analyze the practical relevance of these problems and we propose remedies to weak identification based on recent developments in factor analysis for information extraction from large data sets. Using these techniques, we evaluate the robustness of recent findings on the importance of forward looking components in the equations of the New-Keynesian model.
JEL Code
E5 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit
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
25 October 2004
WORKING PAPER SERIES - No. 396
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Abstract
This paper reviews the existing empirical evidence on the short-term impact on prices of fiscal variables and assesses it against new results from harmonised simulations, conducted with six well-established econometric models used by the ECB and five national central banks (NCBs) of the Eurosystem. The outcome is also compared with results from the European Commission and the OECD models. Overall, a broad consensus appears on the impact on prices of changes in individual government budget items in the euro area. In all cases, changes in government demand and in direct taxes paid by households have a limited impact on prices in the first year while, in contrast, changes in indirect taxes and employers' social security contributions have a relatively large impact. The second year results show that the effects on prices usually take some time to materialise fully; in particular, they often become large for the public consumption shock.
JEL Code
E17 : Macroeconomics and Monetary Economics→General Aggregative Models→Forecasting and Simulation: Models and Applications
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E62 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→Fiscal Policy
1 August 2003
WORKING PAPER SERIES - No. 252
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Abstract
Existing methods for data interpolation or backdating are either univariate or based on a very limited number of series, due to data and computing constraints that were binding until the recent past. Nowadays large datasets are readily available, and models with hundreds of parameters are fastly estimated. We model these large datasets with a factor model, and develop an interpolation method that exploits the estimated factors as an efficient summary of all the available information. The method is compared with existing standard approaches from a theoretical point of view, by means of Monte Carlo simulations, and also when applied to actual macroeconomic series. The results indicate that our method is more robust to model misspecification, although traditional multivariate methods also work well while univariate approaches are systematically outperformed. When interpolated series are subsequently used in econometric analyses, biases can emerge, depending on the type of interpolation but again be reduced with multivariate approaches, including factor-based ones.
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
C43 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→Index Numbers and Aggregation
C82 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Macroeconomic Data, Data Access
1 July 2002
WORKING PAPER SERIES - No. 160
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Abstract
On the basis of historical data aggregated over the period 1973 to 2000, we estimated four different equilibrium exchange rate models for the synthetic euro. Using the same data set, variable definitions and sample period offers the possibility to assess the uncertainty surrounding such equilibrium levels, both from a statistical and a theoretical perspective. We employed reduced form co-integration models, a structurla VAR, a Natrex model (estimated in structural form) and the ECB's small-sized euro area wide macro-economic model. In this order the approaches feature an increasing degree of 'structure', in the sense of the constraints based on economic theory embedded in the econometric models that were estimated. The results confirm the high leikelihood for the euro ahving been undervalued in Q4 2000, while stressing the significant empirical and theoretical uncertainty with respect to the equilibrium exchange rate level.
JEL Code
F31 : International Economics→International Finance→Foreign Exchange
F32 : International Economics→International Finance→Current Account Adjustment, Short-Term Capital Movements
1 April 2001
WORKING PAPER SERIES - No. 61
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Abstract
Diffusion indexes based on dynamic factors have recently been advocated by Stock and Watson (1998), and further used to perform forecasting tests by the same authors on US data. This technique is explored for the euro area using a multi-country data set and a broad array of variables, in order to test the inflation forecasting performance of extracted factors at the aggregate euro area level. First, a description of factors extracted from different data sets is performed using a number of different approaches. Conclusions reached are that nominal phenomena in the original variables might be well captured in-sample using the factor approach. Out-of-sample tests have more ambiguous interpretation, as factors seem to be good leading indicators of inflation, but the comparative advantage of the factors is less clear. Nevertheless, alternative indicators such as unemployment or money growth do not outperform them
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
1 April 2001
WORKING PAPER SERIES - No. 60
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Abstract
This paper applies the 'diffusion indices' approach proposed by Stock and Watson [1998] to the euro area. Following their methodology a set of factors are extracted from a balanced and unbalanced panel dataset comprising nominal variables for 11 countries of the euro area. The estimated factors appear to be fairly stable over time. It is also shown that the first factor is cointegrated with area wide HICP and private consumption deflator supporting the idea that it represents 'a common trend of inflation' for the euro area. The other factors, which are stationary instead, seem to capture dispersion of inflation across countries. There is moreover evidence of unilateral causality from the first factor with respect to HICP, suggesting that this factor could be valuably employed in forecasting euro area inflation
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
1 January 2001
WORKING PAPER SERIES - No. 42
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Abstract
This paper presents a quarterly estimated structural macroeconomic model for the euro area, denoted area-wide model (AWM). This model has been developed with four uses in mind: the assessment of economic conditions in the area, macroeconomic forecasting, policy analysis and deepening understanding of the functioning of euro area economy. Five key features of the model are highlighted. First, it treats the euro area as a single economy. Second, it is a medium sized model which, while detailed enough for most purposes, is nonetheless sufficiently small to be manageable in the context of forecasting and simulation exercises. Third, the model is designed to have a long run equilibrium consistent with classical economic theory, while its short run dynamics are demand driven. Fourth, the current version of the AWM is mostly backward-looking, i.e. expectations are reflected via the inclusion of lagged variables. Finally, the AWM uses quarterly data, allowing for a richer treatment of the dynamics, and is mostly estimated on the basis of historical data (rather than calibrated). The paper comprises the following elements. First, a general overview of the structure of the model and of its long-run and short-run properties is provided, with particular emphasis on how the model reaches its steady state. This is followed by a review of the key behavioural equations, showing e.g. the extent to which the standard behavioural equations are capable of fitting the historical euro area data which has been constructed. Finally results from two illustrative simulations are provided, i.e. a fiscal expenditure shock and a change in interest rates. Appended to the main text are the full list of econometric results, the detailed description of the database and the results of stochastic long run simulations. In addition, a companion file comprising all of the quarterly time series underlying the AWM is made available
JEL Code
C3 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables
C5 : Mathematical and Quantitative Methods→Econometric Modeling
E2 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy
Annexes
25 June 2009
ANNEX