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Optimal Vaccine Subsidies for Endemic and Epidemic Diseases / Matthew Goodkin-Gold, Michael Kremer, Christopher M. Snyder, Heidi L. Williams.

NBER Working papers Available online

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Format:
Book
Author/Creator:
Goodkin-Gold, Matthew.
Contributor:
National Bureau of Economic Research.
Kremer, Michael.
Snyder, Christopher M.
Williams, Heidi L.
Series:
Working Paper Series (National Bureau of Economic Research) no. w28085.
NBER working paper series no. w28085
Language:
English
Physical Description:
1 online resource: illustrations (black and white);
Place of Publication:
Cambridge, Mass. National Bureau of Economic Research 2020.
Summary:
Vaccines exert a positive externality, reducing spread of disease from the consumer to others, providing a rationale for subsidies. We study how optimal subsidies vary with disease characteristics by integrating a standard epidemiological model into a vaccine market with rational economic agents. In the steady-state equilibrium for an endemic disease, across market structures ranging from competition to monopoly, the marginal externality and optimal subsidy are non-monotonic in disease infectiousness, peaking for diseases that spread quickly but not so quickly as to drive all consumers to become vaccinated.
Motivated by the Covid-19 pandemic, we adapt the analysis to study a vaccine campaign introduced at a point in time against an emerging epidemic. While the nonmonotonic pattern of the optimal subsidy persists, new findings emerge. Universal vaccination with a perfectly effective vaccine becomes a viable firm strategy: the marginal consumer is still willing to pay since those infected before vaccine rollout remain a source of transmission. We derive a simple condition under which vaccination exhibits increasing social returns, providing an argument for concentrating a capacity-constrained campaign in few regions. We discuss a variety of extensions and calibrations of the results to vaccines and other mitigation measures targeting existing diseases.
Notes:
Print version record
November 2020.

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