This paper investigates the importance of the age composition for pandemic policy design. To do so, it introduces an economic framework with age heterogeneity, individual choice, and incomplete information, emphasizing the value of testing. Calibrating the model to the US Covid-19 pandemic reveals an 80% reduction in death toll due to voluntary actions and the lockdown implemented in the US. The optimal lockdown, however, is more stringent than what was implemented in the US. Moreover, the social planner follows an asymmetric approach by locking down the young relatively more than the old. We underscore the importance of testing, showing its impact on reduced deaths, lower economic costs and laxer lockdown. We use the framework to provide systematic insights into pandemics caused by different viruses (among others the Spanish flu), and underline the influence of economic conditions on optimal policies.
Authors
Luiz Brotherhood, Philipp Kircher, Cezar Santos, Michèle Tertilt
- Acknowledgements & Disclosure
- All funding sources are named in the acknowledgements of the paper. In particular: Financial support from the German Research Foundation (through CRC-TR-224 (project A3) and the Gottfried Wilhelm Leibniz-Prize), the European Research Council (through ERC grant 818859), the Spanish Government (PID2021-126549NB-I00 and PID2020-114040RB-I00), and the Generalitat of Catalonia (AGAUR-2020PANDE00036 and 2021-SGR-00862) is gratefully acknowledged. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
- DOI
- https://doi.org/10.3386/w32558
- Published in
- United States of America
Table of Contents
- Introduction 3
- Literature Review 5
- Model 8
- Calibration and Model Fit 16
- Calibration 16
- Non-targeted Moments: Mortality and Behavior over Time 21
- The Importance of Behavioral Changes 24
- Optimal Lockdown 27
- Optimal Policy for Other Pandemics 31
- Spanish Flu Compared to Covid 31
- Covid in Developing Countries 37
- Future Pandemics 38
- Summary of Lessons Learned 43
- The Importance of Testing 43
- Conclusions 47
- Laws of Motion and Aggregation 54
- Extra Tables and Figures 58
- Calibration: Spanish Flu 70
- Computational Appendix 72
- A model with two-period uncertainty 74
- Value Functions in the model with two periods of uncertainty 74
- Susceptible 74
- Infected 74
- f1 fever people 75
- f2 fever people in period t: 76
- nf2 no fever people in period t: 78
- Type Distributions in the model with two periods of uncertainty 78
- Aggregation in the model with two periods of uncertainty 82
