Cargando…
Panel and geospatial data for U.S. FDIC insured banks fiduciary activities and annual performance analyses over the periods 2016 to 2018
Created in 1934, the Federal Deposit Insurance Corporation (FDIC) is the independent agency of the United States Government tasked to protect depositors of insured banks located in the U.S. against the loss of their deposits in case of bank failure. To achieve this objective, the FDIC collects data...
Autor principal: | |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6704373/ https://www.ncbi.nlm.nih.gov/pubmed/31453306 http://dx.doi.org/10.1016/j.dib.2019.104358 |
_version_ | 1783445494080471040 |
---|---|
author | Niankara, Ibrahim |
author_facet | Niankara, Ibrahim |
author_sort | Niankara, Ibrahim |
collection | PubMed |
description | Created in 1934, the Federal Deposit Insurance Corporation (FDIC) is the independent agency of the United States Government tasked to protect depositors of insured banks located in the U.S. against the loss of their deposits in case of bank failure. To achieve this objective, the FDIC collects data on banks condition and income through quarterly Financial Report calls, which are then publicly released as “Statistics on Depository Institutions (SDI)”. The present data article, as a follow up to Niankara and Ismail, 2019 that focuses on U.S. banks’ exposure to foreign counterparty risk, describes an extract from the quarterly SDIs that is compiled into a panel of 16209 observations on 5403 U.S. FDIC insured Banks, observed over the three-year periods of 2016, 2017 and 2018. Since our objective is to bring forth a useful data source for analyzing U.S. FDIC banks fiduciary activities and annual performance changes over the past recent years, our constructed sample contains all FDIC insured banks with end of year (4th quarter) financial reporting for each of the 3 fiscal years 2016-2018. We further supplement this data with U.S. county and state level geospatial data that allow analysts and business researchers to address questions with temporal significance, but also spatial relevance through appropriate modelling and mapping of the data. Finally, we demonstrate the usability of the data using R based descriptive analytics, with computer codes provided for prospective Analysts and business researchers. |
format | Online Article Text |
id | pubmed-6704373 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-67043732019-08-26 Panel and geospatial data for U.S. FDIC insured banks fiduciary activities and annual performance analyses over the periods 2016 to 2018 Niankara, Ibrahim Data Brief Economics, Econometrics and Finance Created in 1934, the Federal Deposit Insurance Corporation (FDIC) is the independent agency of the United States Government tasked to protect depositors of insured banks located in the U.S. against the loss of their deposits in case of bank failure. To achieve this objective, the FDIC collects data on banks condition and income through quarterly Financial Report calls, which are then publicly released as “Statistics on Depository Institutions (SDI)”. The present data article, as a follow up to Niankara and Ismail, 2019 that focuses on U.S. banks’ exposure to foreign counterparty risk, describes an extract from the quarterly SDIs that is compiled into a panel of 16209 observations on 5403 U.S. FDIC insured Banks, observed over the three-year periods of 2016, 2017 and 2018. Since our objective is to bring forth a useful data source for analyzing U.S. FDIC banks fiduciary activities and annual performance changes over the past recent years, our constructed sample contains all FDIC insured banks with end of year (4th quarter) financial reporting for each of the 3 fiscal years 2016-2018. We further supplement this data with U.S. county and state level geospatial data that allow analysts and business researchers to address questions with temporal significance, but also spatial relevance through appropriate modelling and mapping of the data. Finally, we demonstrate the usability of the data using R based descriptive analytics, with computer codes provided for prospective Analysts and business researchers. Elsevier 2019-08-06 /pmc/articles/PMC6704373/ /pubmed/31453306 http://dx.doi.org/10.1016/j.dib.2019.104358 Text en © 2019 The Author(s) 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 Niankara, Ibrahim Panel and geospatial data for U.S. FDIC insured banks fiduciary activities and annual performance analyses over the periods 2016 to 2018 |
title | Panel and geospatial data for U.S. FDIC insured banks fiduciary activities and annual performance analyses over the periods 2016 to 2018 |
title_full | Panel and geospatial data for U.S. FDIC insured banks fiduciary activities and annual performance analyses over the periods 2016 to 2018 |
title_fullStr | Panel and geospatial data for U.S. FDIC insured banks fiduciary activities and annual performance analyses over the periods 2016 to 2018 |
title_full_unstemmed | Panel and geospatial data for U.S. FDIC insured banks fiduciary activities and annual performance analyses over the periods 2016 to 2018 |
title_short | Panel and geospatial data for U.S. FDIC insured banks fiduciary activities and annual performance analyses over the periods 2016 to 2018 |
title_sort | panel and geospatial data for u.s. fdic insured banks fiduciary activities and annual performance analyses over the periods 2016 to 2018 |
topic | Economics, Econometrics and Finance |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6704373/ https://www.ncbi.nlm.nih.gov/pubmed/31453306 http://dx.doi.org/10.1016/j.dib.2019.104358 |
work_keys_str_mv | AT niankaraibrahim panelandgeospatialdataforusfdicinsuredbanksfiduciaryactivitiesandannualperformanceanalysesovertheperiods2016to2018 |