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Natural disasters and countries' exports: New insights from a new (and an old) database
Author(s) -
El Hadri Hajare,
Mirza Daniel,
Rabaud Isabelle
Publication year - 2019
Publication title -
the world economy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.594
H-Index - 68
eISSN - 1467-9701
pISSN - 0378-5920
DOI - 10.1111/twec.12833
Subject(s) - natural disaster , flood myth , pooling , raw data , storm , shock (circulatory) , econometrics , geography , database , economics , meteorology , statistics , mathematics , computer science , medicine , archaeology , artificial intelligence
This paper is the first to uncover in details the impact of different families of disasters on exports from 1979 to 2000 (storms, floods, earthquakes and changes in temperatures). Besides, our paper is the first to compare in a quasi‐systematic way the results across the two data sets at hand, the standard EM‐DAT data and GeoMet data, a newly available data set based on geophysical and meteorological data ( European Economic Review , 2013, 58, 18; Journal of Development Economics , 2014, 111, 92). We run series of regressions while accounting progressively for the characteristics of products (all traded goods v/s agriculture ones), the characteristics of the country (size, level of development) and the intensity of the catastrophes. When pooling all countries, and all types of disasters, we do not find any statistical impact on exports. But when focusing on each of them separately and on agricultural goods, the occurrence of an earthquake appears to reduce exports of about 3%, regardless of its location. A windstorm shock, even when it happens to be very severe, has hardly any impact. A flood, on its side, is estimated to reduce export flows of a small country by nearly 3%. The effect of changes in temperatures is ambiguous. All in all, except for temperature‐related disasters, the results are consistent across both data sets, EM‐DAT and GeoMet, although they appear to be slightly more in line with our expectations in the case of GeoMet.