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Angelos Vouldis

4 October 2021
WORKING PAPER SERIES - No. 2595
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Abstract
We study the relationship between banks’ size and risk-taking in the context of supranational banking supervision. Consistently with theoretical work on banking unions and in contrast to analyses emphasising incentives underpinned by the too-big-to-fail effect, we find an inverse relationship between banks’ size and non-performing loan growth for a sample of European banks. Evidence is provided that the mechanism operates through the enhanced organisational efficiency of the supranational set-up rather than incentives alignment among the supervisors and the banks.
JEL Code
F33 : International Economics→International Finance→International Monetary Arrangements and Institutions
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
G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill
C20 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→General
26 May 2017
WORKING PAPER SERIES - No. 2070
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Abstract
The paper identifies the business models followed by banks in the euro area utilising a proprietary dataset collected in the context of the supervisory reporting of the Single Supervisory Mechanism. The concept of a ‘business model’ has been neglected by economic theory and is defined here with respect to the set of activities performed by banks. We adopt a clustering methodology to provide evidence for the existence of distinct business models. Clustering is combined with dimensionality reduction optimally, given the nature of our dataset which features a large number of dimensions for each bank (‘fat’ data). The method produces a level and a contrast factor which are intuitive in the economic sense. Four business models are identified alongside a set of ‘outlier’ banks that follow unique business models. The risk and performance indicators of each cluster are examined and evidence is provided that they follow distinct statistical distributions.
JEL Code
C63 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Computational Techniques, Simulation Modeling
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
L21 : Industrial Organization→Firm Objectives, Organization, and Behavior→Business Objectives of the Firm
L25 : Industrial Organization→Firm Objectives, Organization, and Behavior→Firm Performance: Size, Diversification, and Scope
12 June 2015
WORKING PAPER SERIES - No. 1805
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Abstract
Motivated by the linkage between credit and growth in the Greek economy, and the deceleration of credit since the financial crisis, this paper studies the evolution of credit demand and supply in Greece. A disequilibrium model of demand and supply is estimated spanning the period 2003M1-2011M3. The adopted specification allows for stochastic shocks on both supply and demand. A Bayesian estimation methodology with data augmentation for the latent variables is used. The analysis is carried out separately for each type of loan (short- and long-term business loans, consumer loans and mortgages) enabling the comparative study of the credit rationing and supply constraint effects among loan categories. The results indicate that, for all loan categories, excess demand characterized the boom period. After the intensification of the debt crisis, evidence is provided for the existence of excess demand due to binding constraints on supply. However, demand for short-term business loans has slowed down more than supply, reflecting businesses
JEL Code
D50 : Microeconomics→General Equilibrium and Disequilibrium→General
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E42 : Macroeconomics and Monetary Economics→Money and Interest Rates→Monetary Systems, Standards, Regimes, Government and the Monetary System, Payment Systems
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
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
P00 : Economic Systems→General→General
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
8 July 2013
WORKING PAPER SERIES - No. 1563
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Abstract
The paper develops a financial systemic stress index (FSSI) for Greece. We present a methodology for constructing and evaluating a systemic stress index which: i) adopts the suggestion of Hollo et al. (2012) [Hollo, Kremer, and Lo Duca (2012)
JEL Code
G01 : Financial Economics→General→Financial Crises
G10 : Financial Economics→General Financial Markets→General
G20 : Financial Economics→Financial Institutions and Services→General
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
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