Since Covid-19 hit, much has been written about the stark choices governments face between preserving lives and preserving livelihoods. Much less has been said about the equally stark choices regular citizens face. Yet what regular people decide to do could be at least as important as what governments do in determining how, when, and at what cost we overcome the pandemic.
The choices are particularly difficult for households in developing countries whose incomes hover barely above the survival line. But the situation is also dire for the many workers in developed countries who do not have the privilege of working online. As governments begin to lift restrictions, these workers will have to choose between the risk of going out to work and the peril of staying home with the prospect of much-reduced incomes.
In deciding whether or not to work or to engage in risky behaviour, the incentives people face matter a great deal — and those incentives in turn depend on policies. So instead of just alleviating the social effects of disease, economic policies can change the severity of the pandemic itself. That simple yet overlooked fact has profound implications for the fight against Covid-19.
Economic and epidemiological theories
To understand the role of economic policy in this crisis it is necessary to develop an economic theory of the joint determination of health and economic outcomes. What dominates debates so far are epidemiological theories of pandemics. The difference is not just academic. Epidemiological theories are backward-looking: people´s past choices determine how many cases of infection there are today. By contrast, economic theories are forward-looking: people´s choices — including decisions about whether or not to engage in risky behaviour that could result in infection — depend crucially on what they expect the future will bring.
Theoretical attempts to marry economics and epidemiology are few but important. Motivated by the AIDS pandemic, Kremer (1996) provided an early example. Gersovitz and Hammer (2003, 2004) also attempted to integrate behavioural choice and epidemiological dynamics, with emphasis on the different externalities at work and the implications for policy.
Two recent papers, written in response to the ongoing pandemic, include a channel for policy to influence contagion dynamics though its impact on the decisions of individuals. Eichenbaum et al. (2020) and Jones et al. (2020)  develop dynamic models where contagion follows SIR-type dynamics, the parameters of which depend on the levels of aggregate consumption and production. The papers do not provide a microeconomic justification for that assumption, but simply take it as a reduced form. The risk is that as policy changes, these patterns of behaviour will change, in a new version of the classic Lucas critique.
Incentives effect the evolution of a pandemic
In a recent paper (Chang and Velasco 2020), we develop a minimal economic model of the equilibrium determination of virus transmission and economic outcomes. Unlike standard SIR models, the dynamics of contagion are affected by people’s choices about whether to work or stay home, today and in the future. In turn, individual choices depend on their environment, including current and expected economic policies.
A novelty of our model is that SIR-like equations are not specified in an ad hoc manner. Instead, they follow from the economy’s underlying fundamentals. This is necessary so that policy analysis will be robust to critiques of the Lucas type, allowing for a consistent accounting of how individual choices, and hence the dynamics and severity of contagion, adjust in response to policy changes.
The model is deliberately simple, yet it yields interesting and sometimes unexpected insights. In the absence of policy interventions, decentralised equilibria are inefficient, in terms of both health and economic outcomes. This is not surprising because an externality is at work: when deciding whether or not to stay at home, individuals do not take into account the impact of their choice on the relative numbers of healthy and infected people ‘out there’ in the workplace, and therefore on the overall speed of disease transmission.
In most other models, because of the (negative) externality, people choose ‘too much’ risk relative to the social optimum. Our model shows that, under certain conditions, the externality can also operate in the other direction, causing people to behave ‘too conservatively’ relative to the social optimum. This may be relevant now that governments are choosing gradually to lift lockdowns, but in some places people are reluctant to go back to work.
Expectations matter a great deal for the evolution of a pandemic. For instance, if more healthy people choose to go back to work, the share of workers who are infected falls, and therefore the individual risk of infection increases, causing even more healthy people to re-join the workforce. As a result, multiple self-fulfilling equilibria, with different speeds of contagion, can occur.
The model helps identify individual decisions that, in turn, affect the severity of a pandemic. For example, a vast number of workers are currently being asked to stay at home rather than work in the market. Will they oblige? A worker who adheres to the directive will lose her wage minus any subsidies she may receive. Disobeying the directive, on the other hand, will cost her too: aside from penalties for disobedience, she will risk an increased probability of being infected with the virus, leading to the loss of future wages and increased medical and hospital costs, not to mention physical pain and possibly death.
Implications for policy evaluation and design
Economic policies can affect the evolution of a pandemic by changing incentives. Consider, for example, the debate over extended unemployment insurance benefits, which in the US accounted for a big share of the $2 trillion fiscal response. Critics griped that independent workers such as Uber drivers were not covered. But hardly anyone focused on one feature that may turn out to be essential: to collect unemployment benefits, workers must stay at home rather than going to factories or offices. Assuming that virus infection is much less prevalent at home, the incentives associated with unemployment insurance are the right ones to combat contagion.
Or consider any policy that causes people to expect higher wages in the future. Such a policy will benefit people later, but will also have an immediate beneficial effect: if people expect a high monetary reward from being healthy and being able to work in the future, then they will be more likely to stay home and reduce the chance of infection today.
So there is an additional reason to engage in expansionary macroeconomic policies in the recovery phase of the pandemic. But before we get too excited at the prospect of self-confirming cycles of optimism and infection abatement, one warning: promises of future expansion may be time-inconsistent, and therefore less than fully credible. Only governments with enough credibility, built via durable institutions or a history of honouring promises, can take advantage of this policy option and use it to diminish contagion and make progress against the pandemic.
Current and anticipated future economic policies can lower the individual costs of mandatory lockdowns or social distancing directives, prompting compliance and reducing the severity of the pandemic and its associated impact on the economy. Since the productivity and fiscal costs of generalised lockdowns are severe, there are potentially large gains from identifying and designing such policies.
The room for economic policy incentives to reduce the severity of the current pandemic is uncertain, but may be quite large. As an indication, look at the dramatic change in recent projections of Covid-19 deaths in the US. At the end of March, the Trump administration was publicly projecting virus-related deaths of between 100,000 and 240,000 by the end of the summer. On 10 April, the official estimate was lowered to 60,000.
What explained the astonishingly large and sudden change in the estimates? According to health officials and public health experts, the previous dire predictions had assumed low compliance rates with lockdown and social distancing measures. Compliance has turned out much better than expected, accounting for the bulk of the change in death estimates (LeBlanc 2020). If economic policy incentives are responsible for even a fraction of the unexpected rate of compliance, then the role of policy in the fight against Covid-19 could turn out to be much more important than has been recognised so far.
Chang, R and A Velasco (2020), “Economic Policy Incentives to Preserve Lives and Livelihoods”, CEPR Discussion Paper 14614, April. Also NBER Working Paper 27020.
Eichenbaum, M, S Rebelo and M Trabandt (2020), “The Macroeconomics of a Pandemic”, NBER Working Paper 26882, April.
Gersovitz, M and J Hammer (2003), “Infectious Diseases, Public Policy, and the Marriage of Economics and Epidemiology”, The World Bank Research Observer, 18(2), 129-157
Gersovitz, M and J Hammer (2004), “The Economical Control of Infectious Diseases”, Economic Journal 114 (492): 1-27
Jones, C, T Philippon and V Venkateswaran (2020), “Optimal Mitigation Policies in a Pandemic: Social Distancing and Working from Home”, Manuscript, NYU: 6 April.
Kaplan, G, B Moll and G Violante (2020), “Pandemics According to HANK”, PowerPoint presentation, LSE, 31 March.
Kremer, M (1996), “Integrating Behavioral Choice into Epidemiological Theories of AIDS”, Quarterly Journal of Economics 111 (2): 549-573.
LeBlanc, P (2020) “US coronavirus predictions are shifting. Here’s why”, CNN.com, April 9.
1 See also Kaplan, Moll, and Violante (2020).
2 The dominant model of virus transmission, due to Kermack and McKendrick (1927), features Susceptible, Infected, and Recovered populations, and therefore is known as SIR.