Prospective Evaluation of Health Communication Effects on Market Outcomes

Partial equilibrium models have been used extensively by policy makers to prospectively determine the consequences of government programs that affect consumer incomes or the prices consumers pay. However, these models have not previously been used to analyze government programs that inform consumers...

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Bibliographic Details
Published in:Journal of benefit-cost analysis 2022-01, Vol.13 (1), p.34-56
Main Authors: Summers, Rosemarie L., Wood, Dallas W., Lew, Nellie, Karns, Shawn A., Muth, Mary K., Nardinelli, Clark, Peckham, Janet G., Wolff, Carolyn
Format: Article
Language:English
Subjects:
Bayesian analysis
Consumer behavior
Consumers
Coronaviruses
COVID-19
Disease control
Folic acid
Government programs
Machine learning
Mathematical models
Risk communication
Womens health
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Summary:Partial equilibrium models have been used extensively by policy makers to prospectively determine the consequences of government programs that affect consumer incomes or the prices consumers pay. However, these models have not previously been used to analyze government programs that inform consumers. In this paper, we develop a model that policy makers can use to quantitatively predict how consumers will respond to risk communications that contain new health information. The model combines Bayesian learning with the utility-maximization of consumer choice. We discuss how this model can be used to evaluate information policies; we then test the model by simulating the impacts of the North Dakota Folic Acid Educational Campaign as a validation exercise.
ISSN:2194-5888
2152-2812
DOI:10.1017/bca.2022.1