Níl an t-ábhar seo ar fáil i nGaeilge.
Marco Gross
- 17 March 2023
- WORKING PAPER SERIES - No. 2795Details
- Abstract
- This paper evaluates the resilience benefits of borrower-based macroprudential policies—such as LTV, DSTI, or DTI caps—for households and banks in the EU. To that end, we employ a further developed variant of the integrated micro-macro simulation model of Gross and Población (2017). Besides various methodological advances, joint policy caps are now also considered, and the resilience benefits are decomposed across income and wealth categories of borrowing households. Our findings suggest that (1) the resilience of households improves notably as a result of implementing individual and joint policy limits, with joint limits being more than additively effective; (2) borrower-based measures can visibly enhance the quality of bank mortgage portfolios over time, supporting bank solvency ratios; and (3) the policies’ resilience benefits are more pronounced for households located at the lower end of the income and wealth distributions.
- JEL Code
- C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
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
- 2 October 2018
- WORKING PAPER SERIES - No. 2181Details
- Abstract
- We develop a structural model for valuing bank balance sheet components such as the equity and debt value, the value for the government when the bank is operated by private shareholders including the present value of a possible future bailout, the bailout value incurred by the government following the abandonment of the private shareholders, and, moreover, some price and risk parameters, including the funding cost spread and the banks’ probability of default. The structural model implies an abandonment threshold, at which if total income drops below this threshold, private shareholders abandon the bank. In this case, the shareholders lose part (or all) of the capital that they hold in the bank, the creditors lose part or all of their debt, and the government receives a portion (or all) of the capital and all of the debt that is not recovered by creditors. Hence, we assume that part of the capital can be lost due to financial distress or to cover bankruptcy costs. We use the model framework to assess the impact of capital-based macro-prudential policy measures and focus in particular on assessing the difference that an assumed bail-in as opposed to bail-out regime can make.
- 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
H81 : Public Economics→Miscellaneous Issues→Governmental Loans, Loan Guarantees, Credits, Grants, Bailouts
- 28 February 2018
- WORKING PAPER SERIES - No. 2134Details
- Abstract
- We bring together the spatial and global vector autoregressive (GVAR) classes of econometric models by providing a detailed methodological review of where they meet in terms of structure, interpretation, and estimation methods. We discuss the structure of cross-section connectivity (weight) matrices used by these models and its implications for estimation. Primarily motivated by the continuously expanding literature on spillovers, we define a broad and measurable concept of spillovers. We formalize it analytically through the indirect effects used in the spatial literature and impulse responses used in the GVAR literature. Finally, we propose a practical step-by-step approach for applied researchers who need to account for the existence and strength of cross-sectional dependence in the data. This approach aims to support the selection of the appropriate modeling and estimation method and of choices that represent empirical spillovers in a clear and interpretable form.
- JEL Code
- C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
C38 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Classification Methods, Cluster Analysis, Principal Components, Factor Models
C51 : Mathematical and Quantitative Methods→Econometric Modeling→Model Construction and Estimation
- 26 July 2017
- WORKING PAPER SERIES - No. 2088Details
- Abstract
- Nominal and real interest rates in advanced economies have been decreasing since the mid-1980s and reached historical low levels in the aftermath of the global financial crisis. Understanding why interest rates have fallen is essential for both monetary policy and financial stability. This paper focuses on one of the factors that have been put forward in the literature within the secular stagnation view: adverse demographic developments. The main conclusion that we draw from our empirical, panel equation system-based assessment is that these developments have exerted downward pressures on real short- and long-term interest rates in the euro area over the past decade. Moreover, building on the European Commission projections for dependency ratios until 2025, we illustrate that the foreseen structural change in terms of age structure of the population may dampen economic growth and continue exerting downward pressure on real interest rates also in the future.
- 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
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
J11 : Labor and Demographic Economics→Demographic Economics→Demographic Trends, Macroeconomic Effects, and Forecasts
- 21 June 2017
- WORKING PAPER SERIES - No. 2081Details
- 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
- 5 May 2017
- WORKING PAPER SERIES - No. 2054Details
- Abstract
- Stress tests have been increasingly used in recent years by regulators to foster confidence in the banking sector by not only increasing its resilience via mandatory capital increases but also by enhancing transparency to allow investors to better discriminate between banks. In this study, using an event study approach, we explore how market participants reacted to the 2014 Comprehensive Assessment and the 2016 EBA EU-wide stress test. The results show that stress test disclosures revealed new information that was priced by the markets. We also provide evidence that the publication of stress test results enhanced price discrimination as the impact on bank CDS spreads and equity prices tended to be stronger for the weaker performing banks in the stress test. Finally, we provide some evidence that also sovereign funding costs were affected in the aftermath of the stress test publications. The results provide insights into the effects and usefulness of stress test-related disclosures.
- JEL Code
- G14 : Financial Economics→General Financial Markets→Information and Market Efficiency, Event Studies, Insider Trading
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
- 25 January 2017
- WORKING PAPER SERIES - No. 2004Details
- Abstract
- We develop a theoretical model that features a business cycle-dependent relation between out- put, price inflation and inflation expectations, augmenting the model by Svensson (1997) with a nonlinear Phillips curve that reflects the rationale underlying the capacity constraint theory (Macklem (1997)). The theoretical model motivates our empirical assessment for the euro area, based on a regime-switching Phillips curve and a regime-switching monetary structural VAR, employing different filter-based, semi-structural model-based and Bayesian factor model-implied output gaps. The analysis confirms the presence of a pronounced convex relationship between inflation and the output gap, meaning that the coefficient in the Phillips curve on the output gap recurringly increases during times of expansion and abates during recessions. The regime switching VAR reveals the business cycle dependence of macroeconomic responses to monetary policy shocks: Expansionary monetary policy induces less pressure on inflation at times of weak as opposed to strong growth; thereby rationalizing relatively stronger expansionary policy, including unconventional volume-based policy such as the Expanded Asset Purchase Programme (EAPP) of the ECB, during times of deep recession.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E42 : Macroeconomics and Monetary Economics→Money and Interest Rates→Monetary Systems, Standards, Regimes, Government and the Monetary System, Payment Systems
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 - Network
- Task force on low inflation (LIFT)
- 12 July 2016
- WORKING PAPER SERIES - No. 1935Details
- Abstract
- We develop an integrated Early Warning Global Vector Autoregressive (EW-GVAR) model to quantify the costs and benefits of capital-based macroprudential policy measures. Our findings illustrate that capital-based measures are transmitted both via their impact on the banking system's resilience and via indirect macro-financial feedback effects. The feedback effects relate to dampened credit and asset price growth and, depending on how banks move to higher capital ratios, can account for up to a half of the overall effectiveness of capital- based measures. Moreover, we document significant cross-country spillover effects, especially for measures implemented in larger countries. Overall, our model helps to understand how and through which channels changes in capitalization affect bank lending and the wider economy and can inform policy makers on the optimal calibration and timing of capital-based macroprudential instruments.
- 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
- 8 March 2016
- WORKING PAPER SERIES - No. 1888Details
- Abstract
- We develop a Mixed-Cross-Section Global Vector Autoregressive (MCS-GVAR) model for the 28 EU economies and a sample of individual banking groups to study the propagation of bank capital shocks to the economy. We conduct various simulations with the model to assess how capital ratio shocks influence bank credit supply and aggregate demand. We distinguish between contractionary and expansionary deleveraging scenarios and confirm the intuitive result that only when banks choose to achieve higher capital ratios by shrinking their balance sheets would economic activity be at risk to contract. The model can be used to establish ranges of impact estimates for capital-related macroprudential policy measures, including counter-cyclical capital buffers, systemic risk buffers, G-SIB buffers, etc., also with a view to assessing the cross-country spillover effects of such policy measures. We highlight the importance for macroprudential policy makers to give clear guidance to banks as to how certain macroprudential policy measures should be implemented
- JEL Code
- C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
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
- 5 February 2016
- WORKING PAPER SERIES - No. 1881Details
- Abstract
- We develop an integrated micro-macro model framework that is based on household survey data for a subset of the EU countries that the Household Finance and Consumption Survey (HFCS) contains. The model can be used for conducting scenario and sensitivity analyses with regard to the factors that drive households' income and expenses as well as their asset values and hence the structure of their balance sheet. Moreover, we use it for the purpose of assessing the efficacy of borrower-based macroprudential instruments, namely loan-to-value (LTV) ratio and debt service to income (DSTI) ratio caps. The simulation results from the model can be attached to bank balance sheets and their risk parameters to derive the impact of the policy measures on their capital position. The model framework also allows quantifying the macroeconomic feedback effects that would result from the policy-induced reduction of demand for mortgage loans. The model allows answering the question as to which of the two measures
- JEL Code
- C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
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 - Network
- Household Finance and Consumption Network (HFCN)
- 7 September 2015
- WORKING PAPER SERIES - No. 1845Details
- Abstract
- The purpose of this paper is to promote the use of Bayesian model averaging for the design of satellite models that financial institutions employ for stress testing. Banks employing
- JEL Code
- C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
C51 : Mathematical and Quantitative Methods→Econometric Modeling→Model Construction and Estimation
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
- 11 October 2013
- OCCASIONAL PAPER SERIES - No. 152Details
- 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
- 2 August 2013
- WORKING PAPER SERIES - No. 1570Details
- Abstract
- This paper aims to illustrate how a Mixed-Cross-Section Global Vector Autoregressive (MCS-GVAR) model can be set up and solved for the purpose of forecasting and scenario simulation. The application involves two cross-sections: sovereigns and banks for which we model their credit default swap spreads. Our MCS-GVAR comprises 23 sovereigns and 41 international banks from Europe, the US and Japan. The model is used to conduct systematic shock simulations and thereby compute a measure of spill-over potential for within and across the group of sovereigns and banks. The results point to a number of salient facts: i) Spill-over potential in the CDS market was particularly pronounced in 2008 and more recently in 2011-12; ii) while in 2008 contagion primarily went from banks to sovereigns, the direction reversed in 2011-12 in the course of the sovereign debt crisis; iii) the index of spill-over potential suggests that the system of banks and sovereigns has become more densely connected over time. Should large shocks of size similar to those experienced in the early phase of the crisis hit the system in 2011/2012, considerably more pronounced and more synchronized adverse responses across banks and sovereigns would have to be expected.
- JEL Code
- C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
C61 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Optimization Techniques, Programming Models, Dynamic Analysis
E17 : Macroeconomics and Monetary Economics→General Aggregative Models→Forecasting and Simulation: Models and Applications
- 2 August 2013
- WORKING PAPER SERIES - No. 1569Details
- Abstract
- The purpose of the paper is to develop a Regime-Switching Global Vector Autoregressive (RS-GVAR) model. The RS-GVAR model allows for recurring or non-recurring structural changes in all or a subset of countries. It can be used to generate regime-dependent impulse response functions which are conditional upon a regime-constellation across countries. Coupling the RS and the GVAR methodology improves out-of-sample forecast accuracy significantly in an application to real GDP, price inflation, and stock prices.
- 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
E17 : Macroeconomics and Monetary Economics→General Aggregative Models→Forecasting and Simulation: Models and Applications
G20 : Financial Economics→Financial Institutions and Services→General
- 6 March 2013
- WORKING PAPER SERIES - No. 1523Details
- Abstract
- This paper aims to illustrate how weight matrices that are needed to construct foreign variable vectors in Global Vector Autoregressive (GVAR) models can be estimated jointly with the GVAR's parameters. An application to real GDP and consumption expenditure price inflation as well as a controlled Monte Carlo simulation serve to highlight that 1) In the application at hand, the estimated weights differ for some countries significantly from trade-based ones that are traditionally employed in that context; 2) misspecified weights might bias the GVAR estimate and therefore distort its dynamics; 3) using estimated GVAR weights instead of trade-based ones (to the extent that they differ and the latter bias the global model estimates) shall enhance the out-of-sample forecast performance of the GVAR. Devising a method for estimating GVAR weights is particularly useful for contexts in which it is not obvious how weights could otherwise be constructed from data.
- JEL Code
- C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
C61 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Optimization Techniques, Programming Models, Dynamic Analysis
E17 : Macroeconomics and Monetary Economics→General Aggregative Models→Forecasting and Simulation: Models and Applications
- 24 September 2012
- WORKING PAPER SERIES - No. 1475Details
- Abstract
- The aim of this study is to assess the extent to which the degree of heterogeneity of inflation expectations is driven by the flow of information related to current and future price developments. To that end, we follow three routes: i) We propose different measures of information flow that have either a sender or a receiver perspective; ii) We present empirical results for the US and selected EU countries that aim to corroborate the hypothesis that news have the ability to densify expectations, i.e. to reduce forecast heterogeneity; and iii) We augment some otherwise standard models of expectation formation by allowing the individual updating frequency to depend on the observed measure of information flow; since the updating frequency is higher at times of high inflation and decreasing thereafter, this mechanism can contribute to upward biases in inflation expectations over long periods of time.
- JEL Code
- D12 : Microeconomics→Household Behavior and Family Economics→Consumer Economics: Empirical Analysis
D84 : Microeconomics→Information, Knowledge, and Uncertainty→Expectations, Speculations
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
- 13 December 2011
- WORKING PAPER SERIES - No. 1407Details
- Abstract
- In this paper we discuss the role of the cross-sectional heterogeneity of beliefs in the context of understanding and assessing macroeconomic vulnerability. Emphasis lies on the potential of changing levels of disagreement in expectations to influence the propensity of the economy to switch between different regimes, a hypothesis that finds robust empirical support from a regime-switching model with endogenous transition probabilities for output growth and realized stock market volatility in the US.
- JEL Code
- C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
D8 : Microeconomics→Information, Knowledge, and Uncertainty
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
- 10 January 2011
- WORKING PAPER SERIES - No. 1286Details
- Abstract
- This paper aims at providing a detailed analysis of the leading indicator properties of corporate bond spreads for real economic activity in the euro area. In- and out-of-sample predictive content of corporate bond spreads are examined along three dimensions: the bonds
- JEL Code
- E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
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
G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill
- 2 December 2009
- WORKING PAPER SERIES - No. 1119Details
- Abstract
- This paper addresses the estimation of Phillips curve equations for the euro area while employing less stringent assumptions on the functional correspondence between price inflation, inflation expectations and marginal costs. Expectations are not assumed to be an unbiased predictor of actual inflation and instead derived from the European Commission
- JEL Code
- C14 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Semiparametric and Nonparametric Methods: General
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
- 9 September 2009
- WORKING PAPER SERIES - No. 1088Details
- Abstract
- The aim of this study is to assess empirically to what extent the degree of heterogeneity of consumers' inflation perceptions and expectations is driven by the flow of information related to current and future price developments in the euro area. We conduct the analysis both on an aggregate level for the euro area as well as for a set of countries using panel techniques. We find that the degree to which consumers' expectations are discordant is negatively related to news intensity. Moreover, the results suggest that the absolute bias in expectations decreases as news become more intense and this effect has become more pronounced since the introduction of the common currency.
- JEL Code
- D12 : Microeconomics→Household Behavior and Family Economics→Consumer Economics: Empirical Analysis
D84 : Microeconomics→Information, Knowledge, and Uncertainty→Expectations, Speculations
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation