利用大经济交易数据衡量经济对自然灾害的抵御能力
Measuring Economic Resilience to Natural Disasters with Big Economic Transaction Data
摘要：
这项研究探讨了分析银行卡支付和ATM取现的潜力，以绘制和量化人们如何受到自然灾害的影响并从中恢复。我们的方法将受灾社区的经济恢复时间定义为银行卡支付和ATM取现次数恢复到基线活动水平所需的时间。对于2014年9月15日至17日袭击墨西哥南下加利福尼亚州（BCS）的飓风奥迪尔，我们测量并绘制了不同地点社区的经济恢复时间，从2天到40天不等。我们发现，在拥有银行账户的个人中，收入水平越低，经济活动恢复正常水平所需的时间就越短。还检测并量化了恢复时间的性别差异。此外，我们的方法通过量化飓风袭击前食品或汽油的支出增长来评估社区如何为灾难做好准备。我们认为，这种方法在以高时空分辨率衡量灾害的经济影响以及了解人口如何反弹和适应方面开辟了一个新的领域。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
