Patients, Premiums, and Public Policy: Modeling Health Insurance Markets using Agent Computing
Date
2017
Authors
Comer, Kevin Thomas
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Abstract
This 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.
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Keywords
Economics, Public policy, Operations research, Adverse selection, Agent-based modeling, Complexity, Healthcare policy, Health insurance market