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Natural Disasters, ‘Partisan Retrospection,’ and U.S. Presidential Elections
Research investigating whether natural disasters help or hurt politicians’ electoral fortunes has produced conflicting results. Some find that voters punish elected officials indiscriminately in the wake of a natural disaster (i.e. ‘blind retrospection’). Others find that voters instead incorporate...
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Published in: | Political behavior 2022-09, Vol.44 (3), p.1225-1246 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Research investigating whether natural disasters help or hurt politicians’ electoral fortunes has produced conflicting results. Some find that voters punish elected officials indiscriminately in the wake of a natural disaster (i.e. ‘blind retrospection’). Others find that voters instead incorporate elected officials’ subsequent relief efforts in their assessment (i.e. ‘attentive retrospection’). We argue that an additional consideration affects voters’ response to natural disasters: the elected official’s partisan affiliation. We contend that whether voters reward or punish incumbents following a disaster is influenced by whether or not the official is a co-partisan. We look for evidence of such ‘partisan retrospection’ by examining the effects of Hurricane Sandy on the 2012 presidential election, and find that voters’ reactions to disaster damage were strongly conditioned by pre-existing partisanship, with counties that previously supported Obama reacting far more positively to disaster damage than those that had earlier opposed him. We then use existing data to investigate the relationship between disasters and presidential elections between 1972 and 2004. We find that incumbent-party candidates performed no worse in disaster-affected co-partisan counties than in non-affected co-partisan counties, but that they underperformed in disaster-affected counties safely in the opposing party column. |
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ISSN: | 0190-9320 1573-6687 |
DOI: | 10.1007/s11109-020-09653-y |