[arXiv] BigDataFr recommends: Measuring Economic Resilience to Natural Disasters with Big Economic Transaction Data

transaction data

BigDataFr recommends: Measuring Economic Resilience to Natural Disasters with Big Economic Transaction Data

Subjects: Databases (cs.DB)

[…] This research explores the potential to analyze bank card payments and ATM cash withdrawals in order to map and quantify how people are impacted by and recover from natural disasters. Our approach defines a disaster-affected community’s economic recovery time as the time needed to return to baseline activity levels in terms of number of bank card payments and ATM cash withdrawals. For Hurricane Odile, which hit the state of Baja California Sur (BCS) in Mexico between 15 and 17 September 2014, we measured and mapped communities’ economic recovery time, which ranged from 2 to 40 days in different locations. We found that — among individuals with a bank account — the lower the income level, the shorter the time needed for economic activity to return to normal levels. Gender differences in recovery times were also detected and quantified.  […]

Read paper
By Elena Alfaro Martinez (BBVA Data & Analytics), Maria Hernandez Rubio (BBVA Data & Analytics), Roberto Maestre Martinez (BBVA Data & Analytics), Juan Murillo Arias (BBVA Data & Analytics), Dario Patane (BBVA Data & Analytics), Amanda Zerbe (United Nations Global Pulse), Robert Kirkpatrick (United Nations Global Pulse), Miguel Luengo-Oroz (United Nations Global Pulse), Amanda Zerbe (United Nations Global Pulse)
Source: arxiv.org

Laisser un commentaire

Votre adresse de messagerie ne sera pas publiée. Les champs obligatoires sont indiqués avec *