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changes in price. However, for the purpose of designing federal and state policy to improve

access to these services and still manage cost, it is essential to understand more clearly how

consumers might respond to differences in coverage. Studies to address this gap would require

the analysis of claims data (for each service type) to compare the use of care, and detailed

knowledge about the differences in insurance benefit designs for a common scope of coverage.

C. APPLICATION OF DEMAND ELASTICITIES

How researchers incorporate demand elasticities in modeling policy change can dramatically

affect their results. The application of elasticities derived from the literature may inadvertently

introduce error in estimates of policy effects or infer a degree of certainty that may be

misleading. Two specific changes, in research reporting and modeling conventions respectively,

could help to reduce the confusion that often results from these problems:

1.

Clear Reporting of Definitions

The price and income elasticities estimated in the literature may be defined very differently

(see Chapter II), and researchers often do not offer adequate documentation of the definitions

they have used. As a result, alternative elasticities taken from the literature can mean very

different things and have very different policy implications, but users are unaware of the

differences or how to compare them. Clear and full documentation of the precise formulas used

to calculate elasticities should be a universal standard in the published literature.

2.

Conventions for Conducting Sensitivity Analyses

Because every elasticity reported in the literature is based on estimation, they all involve

error. By convention, error in an estimate is measured as a confidence interval, which indicates

the magnitude of uncertainty around the estimate and provides the upper and lower bounds of

plausible estimates from the same analysis. Policy simulations based on this range will be more

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