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Stephan Fahr

Macro Prud Policy&Financial Stability

Division

Macroprudential Policy

Current Position

Principal Financial Stability Expert

Email

stephan.fahr@ecb.europa.eu

Other current responsibilities

Economist, Monetary Policy Strategy Division

Education

Ph.D. European University Institute, Florence

Diplom Goethe University, Frankfurt

Professional experience

2009 - now, Monetary Policy Strategy Division, European Central Bank

2008-2009: Euro Area Macro Developments, European Central Bank

2007-2008: Monetary Policy Research Division, European Central Bank

2006-2007: Post-Doc at Institut d'Analisi Economico, Barcelona

3 March 2009
WORKING PAPER SERIES - No. 1016
Details
Abstract
We analyze the dynamic e¤ects of lumpy factor adjustments at the firm level onto the aggregate economy. We find that distinguishing between capital and labour as lumpy factors within the production function result in very dfferent dynamics for aggregate output, investment and labour in an otherwise standard real business cycle model. Lumpy capital leaves the RBC mainly unchanged, while lumpy labour allows for persistence and an inner propagation within the model in form of hump-shaped impulse repsonses. In addition, when modeling lumpy adjustments on both investment and labour, the aggregate effects are even stronger. We investigate the mechanisms underlying these results and identify the elasticity of factor supply as the most important element in accounting for these differences.
JEL Code
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E22 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Capital, Investment, Capacity
E24 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Employment, Unemployment, Wages, Intergenerational Income Distribution, Aggregate Human Capital
8 April 2011
WORKING PAPER SERIES - No. 1321
Details
Abstract
Growth of wages, unemployment, employment and vacancies exhibit strong asymmetries between expansionary and contractionary phases. In this paper we analyze to what degree downward wage rigidities in the bargaining process affect other variables of the economy. We introduce asymmetric wage adjustment costs in a New-Keynesian DSGE model with search and matching frictions in the labor market. We find that the presence of downward wage rigidities strongly improves the fit of the model to the skewness of variables and the relative length of expansionary and contractionary phases even when detrending the data. Due to the asymmetry, wages increase more easily in expansions, which limits vacancy posting and employment creation, similar to the flexible wage case. During contractions nominal wages decrease slowly, shifting the main burden of adjustment to employment and hours worked. The asymmetry also explains the differing transmission of positive and negative demand shocks from wages to inflation. Downward wage rigidities help explaining the asymmetric business cycle of many OECD countries where long and smooth expansions with low growth rates are followed by sharp but short recessions with large negative growth rates.
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
C61 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Optimization Techniques, Programming Models, Dynamic Analysis
2 May 2011
WORKING PAPER SERIES - No. 1336
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Abstract
We evaluate the ECB's monetary policy strategy against the underlying economic structure of the euro area economy, in normal times and in times of severe financial dislocations. We show that in the years preceding the financial crisis that started in 2007 the strategy was successful at ensuring macroeconomic stability and steady growth despite shocks to the supply side and to the transmission mechanism which complicated the policy process. Emphasis on monetary indicators in the ECB's monetary policy strategy
JEL Code
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E51 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Money Supply, Credit, Money Multipliers
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
28 May 2015
FINANCIAL STABILITY REVIEW - ARTICLE
Financial Stability Review Issue 1, 2015
Details
Abstract
Macro-prudential measures implemented in individual Member States may have cross-border or cross-sectoral repercussions. This special feature discusses cross-border spillover channels. To limit negative spillover effects, macro-prudential instruments should be applied consistently across countries, and reciprocity agreements must be applied transparently.
JEL Code
G00 : Financial Economics→General→General
24 May 2018
FINANCIAL STABILITY REVIEW - ARTICLE
Financial Stability Review Issue 1, 2018
Details
Abstract
This special feature presents a tractable, transparent and broad-based cyclical systemic risk indicator (CSRI) that captures risks stemming from domestic credit, real estate markets, asset prices, external imbalances and cross-country spillovers. The CSRI increases on average several years before the onset of systemic financial crises and its level is highly correlated with measures of crisis severity. Model estimates suggest that high values of the CSRI contain information about large declines in real GDP growth three to four years down the road, as it precedes shifts in the entire distribution of future real GDP growth and especially of its left tail. Given its timely signals, the CSRI is a useful analytical tool for macroprudential policymakers to complement other existing analytical tools.
JEL Code
G00 : Financial Economics→General→General
14 February 2019
OCCASIONAL PAPER SERIES - No. 219
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Abstract
This paper presents a tractable, transparent and broad-based domestic cyclical systemic risk indicator (d-SRI) that captures risks stemming from domestic credit, real estate markets, asset prices, and external imbalances. The d-SRI increases on average several years before the onset of systemic financial crises, and its early warning properties for euro area countries are superior to those of the total credit-to-GDP gap. In addition, the level of the d-SRI around the start of financial crises is highly correlated with measures of subsequent crisis severity, such as GDP declines. Model estimates suggest that the d-SRI has significant predictive power for large declines in real GDP growth three to four years down the line, as it precedes shifts in the entire distribution of future real GDP growth and especially of its left tail. The d-SRI therefore provides useful information about both the probability and the likely cost of systemic financial crises many years in advance. Given its timely signals, the d-SRI is a useful analytical tool for macroprudential policymakers.
JEL Code
G01 : Financial Economics→General→Financial Crises
G17 : Financial Economics→General Financial Markets→Financial Forecasting and Simulation
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
C54 : Mathematical and Quantitative Methods→Econometric Modeling→Quantitative Policy Modeling
27 March 2019
MACROPRUDENTIAL BULLETIN - ARTICLE - No. 7
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Abstract
When living by the ocean, instead of trying to calm the waves and tides, building a levee or a breakwater is the safest option. This article reviews the country-specific strategic choices and decisions regarding timing and calibration of the countercyclical capital buffer (CCyB) in countries participating in the Single Supervisory Mechanism (SSM). It identifies commonalities across countries and country specificities that influence decisions by national designated authorities. In so doing, it summarises the limitations encountered with the credit-to-GDP gap and the role of other indicators and factors in calibrating the appropriate CCyB rate on the basis of “guided discretion”. Ultimately, assessing risks across euro area countries consistently, while taking into account country-specific factors, supports the effective use of the CCyB as a macroprudential instrument and ensures that similar risk exposures are subject to the same set of macroprudential requirements.
JEL Code
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
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
F42 : International Economics→Macroeconomic Aspects of International Trade and Finance→International Policy Coordination and Transmission
29 May 2019
FINANCIAL STABILITY REVIEW - ARTICLE
Financial Stability Review Issue 1, 2019
Details
Abstract
The countercyclical capital buffer (CCyB) is one of the centrepieces of the post-crisis reforms that introduced macroprudential policy instruments and aims to protect the resilience of the financial system. As only a few euro area countries have activated the CCyB, macroprudential authorities currently have limited policy space to release buffer requirements in adverse circumstances. This special feature provides insights into the relevant macroprudential policy response under different macroeconomic conditions and a gradual build-up of cyclically adjustable buffers could be considered to help create the necessary macroprudential space and to reduce the procyclicality of the financial system in an economic and financial downturn.
JEL Code
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
G28. : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
17 May 2021
FINANCIAL STABILITY REVIEW - ARTICLE
Financial Stability Review Issue 1, 2021
Details
Abstract
The ECB has been intensifying its quantitative work aimed at capturing climate-related risks to financial stability. This includes estimating financial system exposures to climate-related risks, upgrading banking sector scenario analysis and monitoring developments in the financing of the green transition. Considerable progress has been made on capturing banking sector exposures to firms that are subject to physical risks from climate change. While data and methodological challenges are still a focus of ongoing debates, our analyses suggest (i) somewhat concentrated bank exposures to physical and transition risk drivers, (ii) a prevalence of exposures amongst more vulnerable banks and in specific regions, (iii) risk-mitigating potential for interactions across financial institutions, and (iv) strong inter-temporal dependency conditioning the interaction of transition and physical risks. At the same time, investor interest in “green finance” continues to grow – but so-called greenwashing concerns need to be addressed to foster efficient market mechanisms. Both the assessment of risks and the allocation of finance to support the orderly transition to a more sustainable economy can benefit from enhanced disclosures, including of firms’ forward-looking emission targets, better data and strengthened risk assessment methodologies, among other things.
JEL Code
G10 : Financial Economics→General Financial Markets→General
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
G20 : Financial Economics→Financial Institutions and Services→General
Q54 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Climate, Natural Disasters, Global Warming
20 May 2021
WORKING PAPER SERIES - No. 2556
Details
Abstract
Macroprudential policymakers assess medium-term downside risks to the real economy arising from financial imbalances and implement policies aimed at managing those risks. In doing so, they face an inherent intertemporal trade-off between the expected growth and downside risks. This paper reviews the literature on Growth-at-Risk, embeds it in the wider literature on macroprudential policy, and proposes an empirical risk management framework that combines insights from the two literatures, by forecasting the entire real GDP growth distribution with a structural quantile vector autoregressive model. It accounts for direct and indirect interactions between financial vulnerabilities, financial stress and real GDP growth and allows for potential non-linear amplification effects. The framework provides policymakers with a macro-financial stress test to monitor downside risks to the economy and a macroprudential stance metric to quantify when interventions may be beneficial.
JEL Code
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
Network
Discussion papers
2 June 2021
WORKING PAPER SERIES - No. 2565
Details
Abstract
Macro-prudential authorities need to assess medium-term downside risks to the real economy, caused by severe financial shocks. Before activating policy measures, they also need to consider their short-term negative impact. This gives rise to a risk management problem, an inter-temporal trade-off between expected growth and downside risk. Predictive distributions are estimated with structural quantile vector autoregressive models that relate economic growth to measures of financial stress and the financial cycle. An empirical study with euro area and U.S. data shows how to construct indicators of macro-prudential policy stance and to assess when interventions may be beneficial.
JEL Code
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
Network
Research Task Force (RTF)
Approaches to monetary policy revisited – lessons from the crisis
  • Stephan Fahr, Roberto Motto, Massimo Rostagno, Frank Smets and Oreste Tristani
Scandinavian Journal of Economics 112(4)
  • Stephan Fahr and Frank Smets