Matteo Farnè
- 4 October 2021
- WORKING PAPER SERIES - No. 2595Details
- 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
- 27 July 2018
- WORKING PAPER SERIES - No. 2171Details
- Abstract
- Outlier detection in high-dimensional datasets poses new challenges that have not been investigated in the literature. In this paper, we present an integrated methodology for the identification of outliers which is suitable for datasets with higher number of variables than observations. Our method aims to utilise the entire relevant information present in a dataset to detect outliers in an automatized way, a feature that renders the method suitable for application in large dimensional datasets. Our proposed five-step procedure for regression outlier detection entails a robust selection stage of the most explicative variables, the estimation of a robust regression model based on the selected variables, and a criterion to identify outliers based on robust measures of the residuals' dispersion. The proposed procedure deals also with data redundancy and missing observations which may inhibit the statistical processing of the data due to the ill-conditioning of the covariance matrix. The method is validated in a simulation study and an application to actual supervisory data on banks’ total assets.
- JEL Code
- C18 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Methodological Issues: General
C81 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Microeconomic Data, Data Access
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
- 26 May 2017
- WORKING PAPER SERIES - No. 2070Details
- 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