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arXiv · 1609.09340

Measuring Economic Resilience to Natural Disasters with Big Economic Transaction Data

Elena Alfaro Martinez·Maria Hernandez Rubio·Roberto Maestre Martinez·Juan Murillo Arias·Dario Patane·Amanda Zerbe·Robert Kirkpatrick·Miguel Luengo-Oroz
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Abstract

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. In addition, our approach evaluated how communities prepared for the disaster by quantifying expenditure growth in food or gasoline before the hurricane struck. We believe this approach opens a new frontier in measuring the economic impact of disasters with high temporal and spatial resolution, and in understanding how populations bounce back and adapt.

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Elena Alfaro Martinez, Maria Hernandez Rubio, Roberto Maestre Martinez, Juan Murillo Arias, Dario Patane, Amanda Zerbe, Robert Kirkpatrick, Miguel Luengo-Oroz. 2016-09-28. Measuring Economic Resilience to Natural Disasters with Big Economic Transaction Data. https://arxiv.org/abs/1609.09340

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