Contents

Individual vaccination decision under uncertainty and information asymmetry

LEE, Wonseog

DC Field Value Language
dc.contributor.advisorShin, Jaeun-
dc.contributor.authorLEE, Wonseog-
dc.date.accessioned2022-02-08T16:30:19Z-
dc.date.available2022-02-08T16:30:19Z-
dc.date.issued2021-
dc.identifier.urihttps://archives.kdischool.ac.kr/handle/11125/42929-
dc.descriptionThesis(Master) -- KDI School: Master of Public Policy, 2021-
dc.description.abstractTwo models for individual decisions on vaccination under incomplete information, which poses uncertainty and information asymmetry, have been presented in this thesis. In the state- preference model, the vaccine plays a role of insurance against the disease. It suggests that the interaction between actuarial fairness of the vaccine and risk aversion of the agent commands her vaccination decision. The more actuarially advantageous the vaccine is and the more risk-averse the agent’s personality is, the more likely the agent will purchase the vaccine. The signaling game model shows that an individual buyer of the vaccine builds up her belief of the vaccine’s quality by observing the signal sent by the producer, in this case, the type of technology. The producer’s pooling and separating strategies may result in perfect Bayesian equilibria with conditions that bound the buyer’s belief and the producer’s incentive to deviate from the initial strategy.-
dc.description.tableOfContentsI. INTRODUCTION  II. LITERATURE REVIEW  III. THEORETICAL FRAMEWORK  IV. DISCUSSIONS V. CONCLUDING REMARKS-
dc.format.extent45 p-
dc.publisherKDI School-
dc.subjectVaccination--Psychological aspects-
dc.subjectPublic health--Psychological aspects-
dc.titleIndividual vaccination decision under uncertainty and information asymmetry-
dc.typeThesis-
dc.contributor.departmentKDI School, Master of Public Policy-
dc.date.awarded2021-
dc.description.degreemaster-
dc.description.eprintVersionpublished-
dc.type.DSpacethesis-
dc.publisher.locationSejong-
dc.description.statementOfResponsibilityWonseog LEE-
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