Willingness to pay for morbidity and mortality risk reductions during an epidemic. Theory and preliminary evidence from COVID-19
| Autor: | Luciana Echazu, Diego Nocetti |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Economics and Econometrics
Health-care capacity constraints Psychological intervention Vulnerability COVID-19 pandemic 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Willingness to pay Economic cost Accounting 0502 economics and business Pandemic Economics Risk management Public economics business.industry Social distance Value of statistical injury 05 social sciences Business Management and Accounting (miscellaneous) Original Article 050202 agricultural economics & policy Redistribution of income and wealth business Finance |
| Zdroj: | The Geneva Risk and Insurance Review |
| ISSN: | 1554-9658 1554-964X |
| Popis: | The COVID-19 pandemic and the strong social distancing measures adopted by governments around the world provide an ideal scenario to evaluate the trade-off between lives saved and morbidity avoided on the one hand and reduced economic resources on the other. We adapt the standard model of willingness to pay (WTP) for mortality/morbidity risk reductions by incorporating a number of aspects that are highly relevant during an epidemic; namely, health-care capacity constraints, dynamic aspects of prevention (i.e., interventions aimed at flattening the epidemic curve), and distributional issues due to high heterogeneity in the underlying risks. The calibration of the model generates a WTP of the order of 24% of GDP. We conclude that the benefits in terms of lives saved and morbidity avoided can well justify the enormous economic costs generated by social distancing interventions. There is, however, significant that heterogeneity in WTP estimates depending on the degree of vulnerability to infection risk (e.g., by age), implying a large redistribution of income and well-being. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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