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Lessons from the Economic-Epidemiological Frontier

Although the COVID-19 pandemic has forced economists to adjust their models and update their assumptions, it has not depleted their arsenals. By absorbing key insights from epidemiology, economics can still offer valuable lessons for how to navigate the current crisis.

LONDON/TURIN/OSLO – COVID-19 has led economists to turn to the models used by epidemiologists as they struggle to understand the dynamics of the pandemic and its likely costs. The original epidemic model, commonly known as SIR, was introduced by William Ogilvy Kermack and Anderson Gray McKendrick almost a century ago. It divides the population into those susceptible to the disease (S), those infected with it (I), and those who have either recovered or died from it (R).

In this standard model, an epidemic dies out when those exiting from the I cohort exceed the number of those entering it, owing to a declining stock of susceptible individuals. One key feature of the literature is “herd immunity,” which allows for the number of infected people to fall to zero before the number of susceptible people does (meaning that there are some individuals who will avoid the disease altogether).

Economists have studied unemployment dynamics using similar transitions from one state to another, though this work came much later and was developed independently of the epidemiologists’ models. A typical contribution is the Diamond-Mortensen-Pissarides matching model, wherein contacts between unemployed workers and firms lead to productive job matches, and thus to a transition from unemployment to employment.

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