Patients, Premiums, and Public Policy: Modeling Health Insurance Markets using Agent Computing

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dc.contributor.advisorAxtell, Robert L
dc.contributor.authorComer, Kevin Thomas
dc.creatorComer, Kevin Thomas
dc.date.accessioned2018-10-22T01:19:45Z
dc.date.available2018-10-22T01:19:45Z
dc.date.issued2017
dc.description.abstractThis dissertation focuses on the assessment of adverse selection as a result of uncertainty and asymmetric information in a market of buyers and sellers. This dissertation seeks to provide two novel contributions to science – the development of a true-scale (one agent to one household) agent-based model of the individual health insurance market at the state level, and the assessment of the impacts of various policy implementations on the individual health insurance market. These impacts will cover not only the participation rates of individuals in the market, but also the price of coverage, the distribution of subscribers across simulated plans, and the expected net revenue of policy elements.
dc.format.extent128 pages
dc.identifier.urihttps://hdl.handle.net/1920/11234
dc.language.isoen
dc.rightsCopyright 2017 Kevin Thomas Comer
dc.subjectEconomics
dc.subjectPublic policy
dc.subjectOperations research
dc.subjectAdverse selection
dc.subjectAgent-based modeling
dc.subjectComplexity
dc.subjectHealthcare policy
dc.subjectHealth insurance market
dc.titlePatients, Premiums, and Public Policy: Modeling Health Insurance Markets using Agent Computing
dc.typeDissertation
thesis.degree.disciplineComputational Social Sciences
thesis.degree.grantorGeorge Mason University
thesis.degree.levelPh.D.

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