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Gaia Barbic

3 May 2017
STATISTICS PAPER SERIES - No. 20
Details
Abstract
The Consolidated Banking Data CBD) are a key component of the ECB/ESCB statistical toolbox for financial stability analysis. This dataset, which contains all the relevant dimensions of systemic risk stemming from and affecting national banking systems, is compiled from firm-level supervisory returns. With the entry into force of the new set of European Banking Authority (EBA) Implementing Technical Standards on Supervisory Reporting in 2014, the whole CBD statistical framework had to be reshaped. In August 2015 the first data for the revised CBD were released. This paper deals with the main issues in the challenging endeavour of transposing firmlevel supervisory returns, often based on different accounting systems, into comprehensive aggregate statistics, while ensuring as far as possible continuity in the time series for indicators and aggregates calculated from different successive data models. At the same time, the new CBD has substantially enlarged the quantity and increased the quality of data, available to the users. This paper provides a description of the database, together with some examples drawn from it.
JEL Code
C82 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Macroeconomic Data, Data Access
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
3 May 2017
STATISTICS PAPER SERIES - No. 20
Details
Abstract
The Consolidated Banking Data CBD) are a key component of the ECB/ESCB statistical toolbox for financial stability analysis. This dataset, which contains all the relevant dimensions of systemic risk stemming from and affecting national banking systems, is compiled from firm-level supervisory returns. With the entry into force of the new set of European Banking Authority (EBA) Implementing Technical Standards on Supervisory Reporting in 2014, the whole CBD statistical framework had to be reshaped. In August 2015 the first data for the revised CBD were released. This paper deals with the main issues in the challenging endeavour of transposing firmlevel supervisory returns, often based on different accounting systems, into comprehensive aggregate statistics, while ensuring as far as possible continuity in the time series for indicators and aggregates calculated from different successive data models. At the same time, the new CBD has substantially enlarged the quantity and increased the quality of data, available to the users. This paper provides a description of the database, together with some examples drawn from it.
JEL Code
C82 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Macroeconomic Data, Data Access
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
12 April 2019
WORKING PAPER SERIES - No. 2261
Details
Abstract
The paper proposes a framework for assessing the impact of system-wide and bank-level capital buffers. The assessment rests on a factor-augmented vector autoregression (FAVAR) model that relates individual bank adjustments to macroeconomic dynamics. We estimate FAVAR models individually for eleven euro area economies and identify structural shocks, which allow us to diagnose key vulnerabilities of national banking systems and estimate short-run economic costs of increasing banks’ capitalisation. On this basis, we run a fully-fledged cost-benefit assessment of an increase in capital buffers. The benefits are related to an increase in bank resilience to adverse shocks. Higher capitalisation allows banks to withstand negative shocks and moderates the reduction of credit to the real economy that ensues in adverse circumstances. The costs relate to transitory credit and output losses that are assessed both on an aggregate and bank level. An increase in capital ratios is shown to have a sharply different impact on credit and economic activity depending on the way banks adjust, i.e. via changes in assets or equity.
JEL Code
E51 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Money Supply, Credit, Money Multipliers
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