While natural disasters are known to have devastating immediate economic impacts, their long-run effect on economic growth is not yet well enough understood and some studies have even suggested positive impacts. For the natural hazard of earthquakes, no global empirical study has so far been conducted that applies a disaster measure that represents the physical hazard of earthquake ground shaking. In this paper I exploit the random within-country variation of shaking over years to identify the causal effect of earthquakes on economic growth. I create a new data set containing the universe of global relevant earthquake ground shaking from 1973 to 2015 and combine it with Worldbank country-level GDP data to construct a panel dataset of country-year observations. I find significant negative global long-term growth impacts of earthquakes that are comparable with previous findings in the literature on cyclones. In particular, the results suggest that 8 years later an average (non-zero) exposure reduces GDP per capita by 1.9%. Furthermore, I find evidence for ample heterogeneity in these effects. The results suggest that (i) the impacts on growth are primarily incurred by low and middle-income countries and that (ii) high-income countries are potentially even able to experience positive “building back better'” effects. Moreover, based on an analysis of different spatial aggregation approaches, I conclude that impacts are primarily driven by (local) high intensity events and not by spatially large exposure to lower intensity shaking.
An Approach to Visualizing Spatial Exposure Data for Comparing Earthquakes.
The comparison of different earthquakes with each other is a popular tool to highlight particular aspects of one or several events. The objective is often to demonstrate differences in the social conditions and how those affect the outcome of earthquake impacts. In this work I argue that for a comprehensive comparison of events it is necessary to first discuss the differences in the natural hazard of ground shaking itself. Unfortunately, whenever differences in shaking are discussed, these discussions usually provide technical details that describe why the shaking was different and neglect to present how the shaking was different. In this work I suggest and demonstrate an approach that utilizes two separate but complimentary steps of data visualizations which can facilitate an effective communication of earthquake shaking and population exposure data to non-experts. The suggested approach can be applied to any ground motion parameter. The first step is a geospatial comparison of shaking maps at the same spatial and color scale. The second step simplifies the interpretation of the shaking profiles by removing the spatial component and plotting shaking and population “exposure curves” which I define in this work. In some cases the exposure curves allow for a clear ranking of events in terms of shaking strength or population exposure.
The Relationship between Nightlight and Socioeconomic Variables at High Spatial Resolutions.
Lackner, S., Pennerstorfer D., Sinabell F., and C. Small
Gulf Coast Parents Speak: Children’s Health Outcomes in the Aftermath of the Deepwater Horizon Oil Spill.
Beedasy J., Petkova E., Lackner S., Sury J., Jeong Oh E., and W.-Y. Tsai