The estimated amount of people affected by natural hazards stands at a staggering number of about 243 million people per year. While not all of the affected move across borders, international migration potentially provides an adaptation mechanism to natural hazards. The aim of this paper is to assess whether natural hazards induce international migration from a macro perspective. We construct a stylized theoretical gravity model of migration that includes hazards as random shocks. To estimate this model, we deploy exogenous data on geological and meteorological hazards from 1980 to 2010. We combine this data with the World Bank's Global Bilateral Migration Database. Overall, our results suggest little evidence that natural hazards affect medium to long-run international migration. However, considering heterogeneity across income groups, we find that particularly middle-income countries experience significant push and pull effects on migration from natural hazards.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may AbstractThe Schengen agreement has guaranteed unchecked travel across internal EU borders since 1995. Has it also facilitated trade flows? Our econometric analysis suggests that Schengen has boosted trade by 3% on average (equivalent to a drop in tariffs by 0.7 percentage points). Goods trade is more robustly affected than services, and peripheral countries benefit more than central ones.

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Climate research suggests that global warming will lead to more frequent and more extreme natural disasters. Most disasters are local events with effects on local economic activity. Hence, assessing their economic impacts with the help of econometric country-level analysis may lead to biased results. Moreover, correct identification is further complicated by the possibility that local shocks shift production and consumption to neighboring locations. In this paper, annual night-time light emission data covering about 24,000 grid cells for the years 1992-2013 are matched to geocoded information on meteorological and geological events. Spatial econometric panel methods are applied to account for interdependencies between locations. Interpreting variation in light emissions as reflecting changes in economic activity, findings convey evidence for pronounced local average treatment effects and strong spatial spillovers, particularly for weather shocks. Moreover, substantial heterogeneity across income groups and regions is identified.