Abstract
The fate of a proposal to expand health insurance is influenced by predictions of the proposal's effects on the number of newly insured and the cost of new coverage. Estimates vary widely, for reasons that are often hard to discern and evaluate. This article describes and compares the frameworks and parameters used for insurance modeling. It examines conventions and controversies surrounding a series of modeling parameters: how individuals respond to a change in the price of coverage, the extent of participation in a new plan by those already privately insured, firms' behavior, and the value of public versus private coverage. The article also suggests ways of making models more transparent and proposes "reference case" guidelines for modelers so that consumers can compare modeling results.
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