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DC Field | Value | Language |
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dc.contributor.advisor | Wantchekon, Leonard | - |
dc.contributor.author | Puri, Sukrit | - |
dc.date.accessioned | 2017-07-18T15:18:34Z | - |
dc.date.available | 2017-07-18T15:18:34Z | - |
dc.date.created | 2017-04-12 | - |
dc.date.issued | 2017-4-12 | - |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/dsp01tm70mx782 | - |
dc.description.abstract | Though political theory may not have settled the debate on the ideal role of the state, there is consensus that, at least, the state ought to be a night watchman, protecting civilians from harm. But then what explains why states turn on their minimal promise, to violently repress their own citizens? Constructing a dataset that counts the number of episodes of state violence that occur in each sub-national administrative division, across 129 countries from 1989-2015, and using instrumental variable techniques from the Resource Curse literature, I find that positive shocks to mineral and fuel resource rents tend to increase the likelihood of government violence at a sub-national level. This paper further confirms the Resource Curse hypotheses that the relationship between economic shocks and state violence are more pronounced in resource-dependent countries, and countries with weak institutional strength. Finally, I use GIS mapping software to exploit sub-national variation in resource endowment, and find that the existence of non-lootable resources is not a sufficient and systematic predictor of sub-national violence, thus proposing a potential limit on the local validity of the Resource Curse scholarship. | en_US |
dc.language.iso | en_US | en_US |
dc.title | A Method to the Madness: How Economic Shocks Influence State Violence Against Civilians | en_US |
dc.type | Princeton University Senior Theses | - |
pu.date.classyear | 2017 | en_US |
pu.department | Economics | en_US |
pu.pdf.coverpage | SeniorThesisCoverPage | - |
pu.contributor.authorid | 960793600 | - |
pu.contributor.advisorid | 210106788 | - |
pu.certificate | Center for Statistics and Machine Learning | en_US |
Appears in Collections: | Economics, 1927-2020 |
Files in This Item:
File | Size | Format | |
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SukritPuri_Thesis.pdf | 1.13 MB | Adobe PDF | Request a copy |
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