Abstract
We explore how the political survival of leaders in different political regimes is affected by drought and flooding precipitation, which are the two major anticipated impacts of anthropogenic climate change. Using georeferenced climate data for the entire world and the Archigos dataset for the period of 1950–2010, we find that irregular political exits, such as coups or revolutions, are not significantly affected by climate impacts. Similarly, drought has a positive but insignificant effect on all types of political exits. On the other hand, we find that floods increase political turnover through the regular means such as elections or term limits. Democracies are better able to withstand the pressures arising from the economic and social disruptions associated with high precipitation than other institutional arrangements. Our results further suggest that, in the context of floods, political institutions play a more important role than economic development for the leaders’ political survival.
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Notes
Notably, however, Neumayer et al. do not distinguish between different political institutions, using GDP and per capita income as the two control variables.
Both Flores and Smith (2013) and Chang and Berdiev (2015) rely on the Emergency Events Database (EM-DAT), which reports population impacts based on information provided by UN agencies, non-governmental organization, insurance companies, research institutes and press agencies (D. Guha-Sapir et al. 2015). The accuracy of the impacts data – such as the number of people killed, displaced, or requiring emergency assistance – depends on the quality of global monitoring and reporting of the relevant disasters. In addition, Chang and Berdiev employ a conditional logit model that is problematic because it does not explicitly account for time dependencies in the data, and therefore might produce overly optimistic results (Beck et al. 1998).
By convention, “adaptation” refers to measures that deal with the consequences of climate change, whereas “mitigation” aims to curb or halt the process of climate change itself (IPCC 2014).
Some exceptions exist. For example, non-democratic leaders can exploit donor preferences for political stability to trade higher political risk for greater rent extraction (Steinwand 2014).
For grid cells that are not completely contained by a country’s boundaries, we use national identification of the largest territory within the grid cell to determine the national identification of the cell. For coastal areas, the grid cell has a national identification of a country as long as there is at least some (no matter how small) land area within the cell.
SPEI calculation uses the monthly difference between precipitation and potential evapotranspiration (PET). This difference between precipitation and PET describes the water balance of the soil (Thornthwaite 1948). Although other drought indices are also based on water balance—such as the Palmer drought severity index (PDSI) (Palmer 1965)—SPEI is more convenient to calculate and can represent different time scales. At longer timescales (e.g., 12 months), the SPEI has been shown to correlate with the self-calibrating PDSI for a set of observatories with different climate characteristics, located in different parts of the world (Vicente-Serrano et al. 2009).
For example, developed countries may have a higher rate of reporting (but not actual occurrence) of various disasters than developing countries.
One exception that we could find is a study of length of stay and hospital discharge by (Sá et al. 2007). We note, however, that the ratio of the number of patients (34,250) to the number of hospitals (78) is much larger than the ratio of the number of leaders (1495) to the number of countries (172): 439.1 and 8.7, respectively. Even for a large number of patients relative to the number of hospitals, the authors acknowledge possible limitations associated with the fixed-effects approach.
The CIF is the appropriate quantity of interest for competing risk models. Standard survival functions are not well defined because the event of interest depends on the covariates both directly and indirectly through the effect of the covariates on competing events (Fine and Gray 1999).
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This project is funded by the National Science Foundation award #0940822. An earlier version of the paper was presented at American Political Science Association 2015 annual meeting in San Francisco, CA.
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The authors are listed alphabetically. T.X., M.Z., and O.S. generated the climate data. O.S. and M.S. performed data analysis and wrote the paper.
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Smirnov, O., Steinwand, M.C., Xiao, T. et al. Climate Impacts, Political Institutions, and Leader Survival: Effects of Droughts and Flooding Precipitation. EconDisCliCha 2, 181–201 (2018). https://doi.org/10.1007/s41885-018-0024-7
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DOI: https://doi.org/10.1007/s41885-018-0024-7