Marek Rusnák
- 19 April 2023
- WORKING PAPER SERIES - No. 2808Details
- Abstract
- Financial stability indicators can be grouped into financial stress indicators that reflect heightened spreads and market volatility, and financial vulnerability indicators that reflect credit and asset price imbalances. Based on a panel of euro area countries, we show that both types of indicators contain information about downside risks to real GDP growth (growth-at-risk) in the short-term (1-year ahead). However, only vulnerability indicators contain information about growth-at-risk in the medium-term (3-years ahead and beyond). Among various vulnerability indicators suggested in the literature, the Systemic Risk Indicator (SRI) proposed by Lang et al. (2019) outperforms in terms of in-sample explanatory power and out-of-sample predictive ability for medium-term growth-at-risk in euro area countries. Shocks to the SRI induce a rich ”term structure” for growth-at-risk: downside risks to real GDP growth are reduced in the short-term, but over the medium-term the effect reverses and downside risks to real GDP growth go up considerably. We also show that using cross-country information from the panel of euro area countries can improve the out-of-sample forecasting performance of growth-at-risk for the euro area aggregate.
- JEL Code
- 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
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
- 23 February 2023
- WORKING PAPER SERIES - No. 2789Details
- Abstract
- The acceleration of house price growth amidst falling interest rates to record-low levels across euro area countries between 2015 and 2021 has sparked renewed interest in the link between the two variables. Asset-pricing theory suggests that real house prices respond to changes in real interest rates in a non-linear fashion. This non-linearity should be especially pronounced at very low real interest rates. Most existing empirical studies estimate models with a con-stant semi-elasticity, thereby ruling out by design the potential non-linearities between house prices and interest rates. To address this issue, we estimate a panel model for the euro area countries with a constant interest rate elasticity (as opposed to a constant semi-elasticity), which is consistent with asset pricing theory. Our empirical results suggest that, in a low interest rate environment such as the period between 2015 and 2021, non-linearities in the house price response to interest rate changes are important: an increase of real interest rates from ultra-low levels could lead to downward pressure on real house prices three to eight times higher than the literature suggests.
- 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
R21 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Household Analysis→Housing Demand
R30 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Real Estate Markets, Spatial Production Analysis, and Firm Location→General
- 10 October 2022
- MACROPRUDENTIAL BULLETIN - FOCUSMacroprudential Bulletin Issue 19, 2022Details
- Abstract
- In recent years different macroprudential sectoral risk weight policies have been used in EU countries to address systemic risk in residential real estate markets. This focus shows that the impact of sectoral risk weight floors, add-ons and multipliers is similar to the impact of different sectoral capital and leverage ratio requirement policies.
- JEL Code
- G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G38 : Financial Economics→Corporate Finance and Governance→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
R38 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Real Estate Markets, Spatial Production Analysis, and Firm Location→Government Policy
- 10 October 2022
- MACROPRUDENTIAL BULLETIN - FOCUSMacroprudential Bulletin Issue 19, 2022Details
- Abstract
- For a comprehensive RRE risk assessment and to set macroprudential measures targeting RRE, it is important to understand the main drivers of RRE developments and the implications of the various scenarios for the RRE market outlook. In this focus, we propose a model framework based on Bayesian vector autoregressions to shed more light on these issues.
- JEL Code
- C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
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
R30 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Real Estate Markets, Spatial Production Analysis, and Firm Location→General
- 10 October 2022
- MACROPRUDENTIAL BULLETIN - ARTICLE - No. 19Details
- Abstract
- Understanding the drivers for residential real estate (RRE) price developments, measuring house price overvaluation, monitoring trends in bank lending and borrowers’ creditworthiness is important for assessing RRE risks and informing policy responses. The ECB uses a comprehensive monitoring framework for regularly assessing RRE vulnerabilities comprising a series of core risk indicators complemented by a broad set of analytical tools. This article describes some of these tools to explain how they are employed in risk analysis.
- JEL Code
- R31 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Real Estate Markets, Spatial Production Analysis, and Firm Location→Housing Supply and Markets
G01 : Financial Economics→General→Financial Crises
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G51 : Financial Economics
- 25 May 2022
- FINANCIAL STABILITY REVIEW - BOXFinancial Stability Review Issue 1, 2022Details
- Abstract
- House prices increased substantially in advanced economies during the pandemic, fuelling concerns about possible price reversals and their implications for financial stability. Shifts in housing preferences, possibly reflecting a desire for more space coupled with less need for commuting due to teleworking modalities, and low interest rates have been important drivers of such recent strong house price growth across advanced economies. In the current low interest rate environment, increased sensitivity of house price growth to changes in real interest rates makes substantial house price reversals more likely. An abrupt repricing in the housing market – if the demand for housing were to go into reverse, for example, with a return to pre-pandemic work modalities, or real interest rates were to rise significantly – could produce spillovers to the wider financial system and economy.
- JEL Code
- E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
R21 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Household Analysis→Housing Demand
R30 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Real Estate Markets, Spatial Production Analysis, and Firm Location→General
- 17 November 2021
- FINANCIAL STABILITY REVIEW - BOXFinancial Stability Review Issue 2, 2021Details
- Abstract
- In order to assess the strength of the current residential real estate expansion, we compare recent developments in euro area housing markets with the period ahead of the global financial crisis (GFC). We find that house price dynamics, overvaluation and the risk profile of new mortgage loans are at similar levels to those observed during the height of the pre-GFC cycle in 2007. However, vulnerabilities from mortgage lending developments and household balance sheets are currently below their pre-GFC levels. We conclude that the continued build-up of vulnerabilities in residential real estate markets calls for close monitoring and possible macroprudential measures.
- JEL Code
- R31 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Real Estate Markets, Spatial Production Analysis, and Firm Location→Housing Supply and Markets
G51 : Financial Economics
P34 : Economic Systems→Socialist Institutions and Their Transitions→Financial Economics
G01 : Financial Economics→General→Financial Crises
- 26 May 2020
- FINANCIAL STABILITY REVIEW - ARTICLEFinancial Stability Review Issue 1, 2020Details
- Abstract
- It is often maintained that the recent real estate booms in many euro area countries have been accompanied by a loosening in lending standards. However, data for a thorough cross-country assessment of lending standards have been missing. This special feature uses a novel euro area dataset from a dedicated data collection covering significant institutions supervised by ECB Banking Supervision to analyse trends in real estate lending standards and derive implications for financial stability. First, lending standards for residential real estate loans in the euro area, in particular loan-to-income ratios, eased between 2016 and 2018. Given the significant deterioration in the euro area economic outlook since the coronavirus outbreak, this vulnerability seems of particular relevance. Second, lending standards appear to be looser in countries that saw stronger real estate expansions, suggesting that real estate vulnerabilities may have been growing in some euro area countries. Third, lending standards deteriorated less in countries with borrower-based macroprudential policies in place, highlighting the importance of early macroprudential policy action to help prevent the build-up of real estate vulnerabilities.
- 27 March 2019
- MACROPRUDENTIAL BULLETIN - ARTICLE - No. 7Details
- Abstract
- This article presents the ECB framework for assessing financial stability risks stemming from residential real estate markets and for designing macroprudential policy responses. It reviews recent developments in residential real estate markets and policy initiatives to address risks.
- JEL Code
- 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
R30 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Real Estate Markets, Spatial Production Analysis, and Firm Location→General
- 16 June 2015
- WORKING PAPER SERIES - No. 1810Details
- Abstract
- We identify a set of
- JEL Code
- C14 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Semiparametric and Nonparametric Methods: General
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
F37 : International Economics→International Finance→International Finance Forecasting and Simulation: Models and Applications
F47 : International Economics→Macroeconomic Aspects of International Trade and Finance→Forecasting and Simulation: Models and Applications
G01 : Financial Economics→General→Financial Crises
- 22 October 2012
- WORKING PAPER SERIES - No. 1486Details
- Abstract
- We search for early warning indicators that could indicate important risks in developed economies. We therefore examine which indicators are most useful in explaining costly macroeconomic developments following the occurrence of economic crises in EU and OECD countries between 1970 and 2010. To define our dependent variable, we bring together a (continuous) measure of crisis incidence, which combines the output and employment loss and the fiscal deficit into an index of real costs, with a (discrete) database of crisis occurrence. In contrast to recent studies, we explicitly take into account model uncertainty in two steps. First, for each potential leading indicator, we select the relevant prediction horizon by using panel vector autoregression. Second, we identify the most useful leading indicators with Bayesian model averaging. Our results suggest that domestic housing prices, share prices, and credit growth, and some global variables, such as private credit, are risk factors worth monitoring in developed economies.
- JEL Code
- C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
F47 : International Economics→Macroeconomic Aspects of International Trade and Finance→Forecasting and Simulation: Models and Applications
G01 : Financial Economics→General→Financial Crises - Network
- Macroprudential Research Network
- 19 October 2012
- WORKING PAPER SERIES - No. 1485Details
- Abstract
- We construct and explore a new quarterly dataset covering crisis episodes in 40 developed countries over 1970
- JEL Code
- C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
F47 : International Economics→Macroeconomic Aspects of International Trade and Finance→Forecasting and Simulation: Models and Applications
G01 : Financial Economics→General→Financial Crises - Network
- Macroprudential Research Network
Annexes- 19 October 2012
- ANNEX