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Mowing the grass

Bibliographic Data

ID6297877
AuthorsMichael Gibilisco (0000-0002-6484-1314, California Institute of Technology, corresponding author)
Year2023
Volume35
Issue3
Pages204-231
Publication date2023-07-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Theoretical Politics (JOURNAL)
Journal identifiersISSN: 0951-6298 • E-ISSN: 1460-3667
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/09516298231185113
OpenAlexW4383226612
LanguageEN
Citations received2
References cited42

Mowing the grass is a cyclical pattern in counterterrorism campaigns where governments attack to destroy terrorist capacity, thereby achieving a period of quiet as groups recover. If groups expect their capacity to be destroyed, why build their capabilities in the first place? I analyze an infinite-horizon dynamic game where a group endogenously builds capacity in the face of potential attacks and capacity is an evolving, persistent variable. The model highlights that terrorist groups and governments have incentives to create strategic uncertainty and thus explains attack cycles without punishment strategies, revenge preferences or imperfect/incomplete information. I calibrate the model to time-series data in the Israeli–Palestinian conflict describing rockets fired from Gaza. The results illustrate a peace-making dilemma: altering the government’s incentives will have comparatively minimal effects on long-term conflict dynamics, whereas changing the terrorists’ incentives to acquire capacity would either increase the frequency of high-capacity terrorism or government attacks

Dilemma · Economics · Game theory · Government (linguistics · Imperfect · Incentive · Microeconomics · Perfect information · Political science · Prisoner's dilemma · Punishment (psychology · Terrorism · Crime, Illicit Activities, and Governance · Political Conflict and Governance · Social Psychology · Terrorism, Counterterrorism, and Political Violence

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Unique citing works2
Citations per year1
Citation span2024 - 2025 (2)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 2

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