Cargando…
Tracking the COVID-19 crisis with high-resolution transaction data
Payments systems generate vast amounts of naturally occurring transaction data rarely used for constructing official statistics. We consider billions of transactions from card data from a large bank, Banco Bilbao Vizcaya Argentaria, as an alternative source of information for measuring consumption....
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8355671/ https://www.ncbi.nlm.nih.gov/pubmed/34401194 http://dx.doi.org/10.1098/rsos.210218 |
_version_ | 1783736807074037760 |
---|---|
author | Carvalho, Vasco M. Garcia, Juan R. Hansen, Stephen Ortiz, Álvaro Rodrigo, Tomasa Rodríguez Mora, José V. Ruiz, Pep |
author_facet | Carvalho, Vasco M. Garcia, Juan R. Hansen, Stephen Ortiz, Álvaro Rodrigo, Tomasa Rodríguez Mora, José V. Ruiz, Pep |
author_sort | Carvalho, Vasco M. |
collection | PubMed |
description | Payments systems generate vast amounts of naturally occurring transaction data rarely used for constructing official statistics. We consider billions of transactions from card data from a large bank, Banco Bilbao Vizcaya Argentaria, as an alternative source of information for measuring consumption. We show, via validation against official consumption measures, that transaction data complements national accounts and consumption surveys. We then analyse the impact of COVID-19 in Spain, and document: (i) strong consumption responses to business closures, but smaller effects for capacity restrictions; (ii) a steeper decline in spending in rich neighbourhoods; (iii) higher mobility for residents of lower-income neighbourhoods, correlating with increased disease incidence. |
format | Online Article Text |
id | pubmed-8355671 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-83556712021-08-15 Tracking the COVID-19 crisis with high-resolution transaction data Carvalho, Vasco M. Garcia, Juan R. Hansen, Stephen Ortiz, Álvaro Rodrigo, Tomasa Rodríguez Mora, José V. Ruiz, Pep R Soc Open Sci Computer Science and Artificial Intelligence Payments systems generate vast amounts of naturally occurring transaction data rarely used for constructing official statistics. We consider billions of transactions from card data from a large bank, Banco Bilbao Vizcaya Argentaria, as an alternative source of information for measuring consumption. We show, via validation against official consumption measures, that transaction data complements national accounts and consumption surveys. We then analyse the impact of COVID-19 in Spain, and document: (i) strong consumption responses to business closures, but smaller effects for capacity restrictions; (ii) a steeper decline in spending in rich neighbourhoods; (iii) higher mobility for residents of lower-income neighbourhoods, correlating with increased disease incidence. The Royal Society 2021-08-11 /pmc/articles/PMC8355671/ /pubmed/34401194 http://dx.doi.org/10.1098/rsos.210218 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Computer Science and Artificial Intelligence Carvalho, Vasco M. Garcia, Juan R. Hansen, Stephen Ortiz, Álvaro Rodrigo, Tomasa Rodríguez Mora, José V. Ruiz, Pep Tracking the COVID-19 crisis with high-resolution transaction data |
title | Tracking the COVID-19 crisis with high-resolution transaction data |
title_full | Tracking the COVID-19 crisis with high-resolution transaction data |
title_fullStr | Tracking the COVID-19 crisis with high-resolution transaction data |
title_full_unstemmed | Tracking the COVID-19 crisis with high-resolution transaction data |
title_short | Tracking the COVID-19 crisis with high-resolution transaction data |
title_sort | tracking the covid-19 crisis with high-resolution transaction data |
topic | Computer Science and Artificial Intelligence |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8355671/ https://www.ncbi.nlm.nih.gov/pubmed/34401194 http://dx.doi.org/10.1098/rsos.210218 |
work_keys_str_mv | AT carvalhovascom trackingthecovid19crisiswithhighresolutiontransactiondata AT garciajuanr trackingthecovid19crisiswithhighresolutiontransactiondata AT hansenstephen trackingthecovid19crisiswithhighresolutiontransactiondata AT ortizalvaro trackingthecovid19crisiswithhighresolutiontransactiondata AT rodrigotomasa trackingthecovid19crisiswithhighresolutiontransactiondata AT rodriguezmorajosev trackingthecovid19crisiswithhighresolutiontransactiondata AT ruizpep trackingthecovid19crisiswithhighresolutiontransactiondata |