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Data on cross-border exposures of 61 largest European banks

This article introduces a unique and hand-collected dataset on cross-border exposures of 61 European banks. Getting a complete overview of the cross-border positions of European banks is challenging, as there are no regular reporting standards for banks’ foreign exposures split by country. Most stud...

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Detalles Bibliográficos
Autores principales: Duijm, Patty, Schoenmaker, Dirk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7200766/
https://www.ncbi.nlm.nih.gov/pubmed/32382619
http://dx.doi.org/10.1016/j.dib.2020.105613
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author Duijm, Patty
Schoenmaker, Dirk
author_facet Duijm, Patty
Schoenmaker, Dirk
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description This article introduces a unique and hand-collected dataset on cross-border exposures of 61 European banks. Getting a complete overview of the cross-border positions of European banks is challenging, as there are no regular reporting standards for banks’ foreign exposures split by country. Most studies therefore rely on data on banks’ foreign subsidiaries. This however leads to a significant underestimation of banks’ cross-border positions. We collect data from annual reports and other public sources for the period 2010-2017 in order to construct a dataset covering the complete cross-border exposures by banks. The dataset is valuable to academic researchers in finance and economics as well as central banks interested in financial globalization. The data are collected at the individual bank-level, and this provides opportunities for researchers aiming to analyse the impact of banks’ strategic decisions [1]. Lastly, since the cross-border exposures are split by host country the data can be used in gravity models, since it provides a measure of connectedness between banks and/or countries.
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spelling pubmed-72007662020-05-07 Data on cross-border exposures of 61 largest European banks Duijm, Patty Schoenmaker, Dirk Data Brief Economics, Econometrics and Finance This article introduces a unique and hand-collected dataset on cross-border exposures of 61 European banks. Getting a complete overview of the cross-border positions of European banks is challenging, as there are no regular reporting standards for banks’ foreign exposures split by country. Most studies therefore rely on data on banks’ foreign subsidiaries. This however leads to a significant underestimation of banks’ cross-border positions. We collect data from annual reports and other public sources for the period 2010-2017 in order to construct a dataset covering the complete cross-border exposures by banks. The dataset is valuable to academic researchers in finance and economics as well as central banks interested in financial globalization. The data are collected at the individual bank-level, and this provides opportunities for researchers aiming to analyse the impact of banks’ strategic decisions [1]. Lastly, since the cross-border exposures are split by host country the data can be used in gravity models, since it provides a measure of connectedness between banks and/or countries. Elsevier 2020-04-23 /pmc/articles/PMC7200766/ /pubmed/32382619 http://dx.doi.org/10.1016/j.dib.2020.105613 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Economics, Econometrics and Finance
Duijm, Patty
Schoenmaker, Dirk
Data on cross-border exposures of 61 largest European banks
title Data on cross-border exposures of 61 largest European banks
title_full Data on cross-border exposures of 61 largest European banks
title_fullStr Data on cross-border exposures of 61 largest European banks
title_full_unstemmed Data on cross-border exposures of 61 largest European banks
title_short Data on cross-border exposures of 61 largest European banks
title_sort data on cross-border exposures of 61 largest european banks
topic Economics, Econometrics and Finance
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7200766/
https://www.ncbi.nlm.nih.gov/pubmed/32382619
http://dx.doi.org/10.1016/j.dib.2020.105613
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