Replication Data for: A Duration Estimator for a Continuous Time War of Attrition Game Article Swipe
Frederick J. Boehmke
,
Charles R. Shipan
,
Douglas Dion
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.7910/dvn/jjl5vp
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.7910/dvn/jjl5vp
We develop a maximum likelihood estimator corresponding to the predicted hazard rate that emerges from a continuous time game of incomplete information with a fixed time horizon (i.e., Kreps and Wilson 1982). Such games have been widely applied in economics and political science and involve two players engaged in a war of attrition contest over some prize that they both value. Each player can be either a strong or weak competitor. In the equilibrium of interest, strong players do not quit whereas weak players play a mixed strategy characterized by a hazard rate that increases up to an endogenous point in time, after which only strong players remain. The observed length of the contest can therefore be modeled as a mixture between two unobserved underlying durations: one that increases until it abruptly ends at an endogenous point in time and a second involving two strong players that continues indefinitely. We illustrate this estimator by studying the durations of Senate filibusters and international crises.
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https://openalex.org/W4398664745Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.7910/dvn/jjl5vpDigital Object Identifier
- Title
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Replication Data for: A Duration Estimator for a Continuous Time War of Attrition GameWork title
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datasetOpenAlex work type
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enPrimary language
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2020Year of publication
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2020-03-06Full publication date if available
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Frederick J. Boehmke, Charles R. Shipan, Douglas DionList of authors in order
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https://doi.org/10.7910/dvn/jjl5vpPublisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://doi.org/10.7910/dvn/jjl5vpDirect OA link when available
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Replication (statistics), Attrition, Duration (music), Estimator, Computer science, Statistics, Mathematics, Art, Medicine, Dentistry, LiteratureTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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