Opções de pesquisa
Página inicial Sala de Imprensa Notas explicativas Estudos e publicações Estatísticas Política monetária O euro Pagamentos e mercados Carreiras
Sugestões
Ordenar por
Não disponível em português

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

17 May 2024
WORKING PAPER SERIES - No. 2942
Details
Abstract
While global supply chains have recently gained attention in the context of the Covid-related crisis as well as the war in Ukraine, their role in transmitting and amplifying climate-related physical risks across countries has received surprisingly little attention. To address this shortcoming, this paper for the first time combines country-level GDP losses due to climate-related physical risks with a global Input-Output model. More specifically, climate-related GDP-at-risk data are used to quantify the potential direct impact of physical risks on GDP at the country or regional level. This direct impact on GDP is then used to shock a global Input-Output (IO) model so that the propagation of the initial shock to country-sectors around the world becomes observable. The findings suggest that direct GDP loss estimates can severely underestimate the ultimate impact of physical risk because trade can lead to losses that are up to 30 times higher in the EA than what looking at the direct impacts would suggest. However, trade can also mitigate losses if substitutability across country-sectors is possible. Future research should (i) develop more granular, holistic, and forward-looking global physical risk data and (ii) examine more closely the role of both partially substitutable outputs, and critical outputs that are less substitutable or not substitutable at all, such as in the food sector.
JEL Code
E01 : Macroeconomics and Monetary Economics→General→Measurement and Data on National Income and Product Accounts and Wealth, Environmental Accounts
Q54 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Climate, Natural Disasters, Global Warming
Q56 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Environment and Development, Environment and Trade, Sustainability, Environmental Accounts and Accounting, Environmental Equity, Population Growth
F18 : International Economics→Trade→Trade and Environment
9 November 2023
WORKING PAPER SERIES - No. 2870
Details
Abstract
We empirically analyze the interaction of monetary policy with financial stability and the real economy in the euro area. For this, we apply a quantile vector autoregressive model and two alternative estimation approaches: simulation and local projections. Our specifications include monetary policy surprises, real GDP, inflation, financial vulnerabilities and systemic financial stress. We disentangle conventional and unconventional monetary policy by separating interest rate surprises into two factors that move the yield curve either at the short end or at the long end. Our results show that a build-up of financial vulnerabilities tends to be accompanied initially by subdued financial stress which resurges, however, over a medium-term horizon, harming economic growth. Tighter conventional monetary policy reduces inflationary pressures but increases the risk of financial stress. [...]
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
G01 : Financial Economics→General→Financial Crises
G10 : Financial Economics→General Financial Markets→General
31 May 2023
FINANCIAL STABILITY REVIEW - BOX
Financial Stability Review Issue 1, 2023
Details
Abstract
Following a strong post-pandemic recovery in profits, euro area non-financial corporations (NFCs) are now facing the risk of stagnating economic activity combined with tightening financial conditions. NFC vulnerabilities might increase as higher interest rates start to weigh on the ability of firms to cover their interest expenses, with highly indebted firms being particularly affected. This box shows that the share of vulnerable loans has been increasing since the second half of 2022 as financial conditions tighten, with those sectors of the economy that were impacted the most by the pandemic being significantly more affected than others. It also finds that higher interest rates could increase corporate vulnerabilities during periods of low or negative economic growth, while there is no statistically significant impact of higher rates on firms’ health during periods of economic expansion.
JEL Code
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G33 : Financial Economics→Corporate Finance and Governance→Bankruptcy, Liquidation
H32 : Public Economics→Fiscal Policies and Behavior of Economic Agents→Firm
31 May 2023
FINANCIAL STABILITY REVIEW - ARTICLE
Financial Stability Review Issue 1, 2023
Details
Abstract
Climate change can have a negative effect on sovereign balance sheets directly (when contingent liabilities materialise) and indirectly (when it has an impact on the real economy and the financial system). This special feature highlights the contingent sovereign risks that stem from an untimely or disorderly transition to a net-zero economy and from more frequent and severe natural catastrophes. It also looks at the positive role that governments can play in reducing climate-related financial risks and incentivising adaptation. If the recent trend of ever-lower emissions across the EU is to be sustained, further public sector investment is essential. In this context, the progress made to strengthen green capital markets has fostered government issuance of green and sustainable bonds to finance the transition. While putting significant resources into adaptation projects can increase countries’ resilience to climate change, the economic costs of extreme climate-related events are still set to rise materially in the EU. Only a quarter of disaster losses are currently insured and fiscal support has mitigated related macroeconomic and financial stability risks in the past. Looking ahead, vulnerabilities arising from contingent liabilities may increase in countries with high physical risk and a large insurance protection gap. If these risks rise alongside sovereign debt sustainability concerns, the impact on financial stability could be amplified by feedback loops that see sovereign credit conditions and ratings deteriorate.
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
G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill
Q51 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Valuation of Environmental Effects
Q54 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Climate, Natural Disasters, Global Warming
Q58 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Government Policy
22 September 2021
RESEARCH BULLETIN - No. 87.1
Details
Abstract
When considering the use of macroprudential instruments to manage financial imbalances, macroprudential policymakers face an intertemporal trade-off between facilitating short-term expected growth and containing medium-term downside risks to the economy. To assist policymakers in assessing this trade-off, in this article we propose a risk management framework which extends the well-known notion of growth-at-risk to consider the entire predictive real GDP growth distribution, with a view to quantifying the macroprudential policy stance. A novel empirical model fitted to euro area data allows us to study direct and indirect interactions between financial vulnerabilities, financial stress and real GDP growth, incorporating non-linear amplification effects among all variables. Our framework can support policymakers by facilitating model-based macro-financial stress tests and model-based assessments of when to adjust macroprudential instruments.
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)
21 September 2021
OCCASIONAL PAPER SERIES - No. 269
Details
Abstract
The ECB’s price stability mandate has been defined by the Treaty. But the Treaty has not spelled out what price stability precisely means. To make the mandate operational, the Governing Council has provided a quantitative definition in 1998 and a clarification in 2003. The landscape has changed notably compared to the time the strategy review was originally designed. At the time, the main concern of the Governing Council was to anchor inflation at low levels in face of the inflationary history of the previous decades. Over the last decade economic conditions have changed dramatically: the persistent low-inflation environment has created the concrete risk of de-anchoring of longer-term inflation expectations. Addressing low inflation is different from addressing high inflation. The ability of the ECB (and central banks globally) to provide the necessary accommodation to maintain price stability has been tested by the lower bound on nominal interest rates in the context of the secular decline in the equilibrium real interest rate. Against this backdrop, this report analyses: the ECB’s performance as measured against its formulation of price stability; whether it is possible to identify a preferred level of steady-state inflation on the basis of optimality considerations; advantages and disadvantages of formulating the objective in terms of a focal point or a range, or having both; whether the medium-term orientation of the ECB’s policy can serve as a mechanism to cater for other considerations; how to strengthen, in the presence of the lower bound, the ECB’s leverage on private-sector expectations for inflation and the ECB’s future policy actions so that expectations can act as ‘automatic stabilisers’ and work alongside the central bank.
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
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
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)
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
20 May 2021
DISCUSSION PAPER SERIES - No. 14
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
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
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
27 March 2019
MACROPRUDENTIAL BULLETIN - ARTICLE - No. 7
Details
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
14 February 2019
OCCASIONAL PAPER SERIES - No. 219
Details
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
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
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
2 May 2011
WORKING PAPER SERIES - No. 1336
Details
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
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
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
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