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COVID-19 Benefit Cost Analysis

Resources for Benefit-Cost Analyses to Inform COVID-19 Policymaking

June 30, 2020 update

This resource page is intended to help analysts and decision makers keep up with the rapidly growing policy analysis literature about interventions to address the COVID-19 pandemic. Studies seem to be forthcoming at a rate that almost approaches the speed at which the virus is spreading. As a service to the field, we are listing those studies that have come to our attention. We also look to readers to let us know if there are additional studies we should include.

At this stage in the pandemic, policy analyses will be inherently preliminary and reflect a higher level of imprecision than analyses of diseases and interventions where we have more history. But, each generation of studies can learn from and build on those that went before. So, we are listing virtually all the studies we find while recognizing that the specific policy comparisons being made and the underlying assumptions and estimates used must be considered somewhat tentative.

The Society expresses its thanks to all the analysts who have made early contributions to this literature. Part of being relevant is being timely, even when a lot of important information is missing or must be approximates. We look forward to seeing these early studies give rise to more thorough analyses.

We have listed studies in two categories. The first contains methodological studies from the Journal of Benefit-Cost Analysis that can guide efforts to assess policy responses to COVID-19. The second is the list of specific COVID-19 policy studies we have found that use benefit-cost analysis. If you know of something that should be added, please send a citation to

Relevant Methodological Material:

How Much is A Human Life Worth?

While the Benefit-Cost Analysis field cannot answer this specific question, it can provide considerable guidance to decision makers who must weigh alternative ways of reducing the risk of death. The key concept here is the Value of a Statistical Life which indicates how much money people will pay to reduce their chance of dying or how much extra pay they demand to take on a job with a higher risk of death.

The policy debates over how to respond to COVID-19 have seen an explosion of interest in this concept. Here are three great resources to help get you up to speed:

  • Valuing Mortality Risk in the Time of COVID-19 by James K. Hammitt, June 2020. This paper examines whether the value per statistical life (VSL) for the United States, estimated as approximately $10 million, is too large. It lists several reasons for thinking so. First, VSL is a marginal rate of substitution and the potential risk reductions are non-marginal. The standard VSL model implies the rate of substitution of wealth for risk reduction decreases sharply once the value of risk reduction accounts for a substantial share of income. Second, mortality risk is concentrated among the elderly, for whom VSL may be smaller and who would benefit from a persistent risk reduction for a shorter period because of their shorter life expectancy. Third, the pandemic and responses to it have caused substantial losses in income that should decrease VSL. In contrast, VSL is plausibly larger for risks (like COVID-19) that are dreaded, uncertain, catastrophic, and ambiguous. 
  • Assessing Ways of Saving Lives During the COVID-19 Pandemic: A conversation with Kip Viscusi Kip Viscusi, June 30, 2020 This Society for Benefit-Cost Analysis webinar features an interview between two experts in the field of valuing mortality risk reductions, Kip Viscusi and Tom Kniesner.
  • Valuing COVID Mortality Risks, by Center for Health Decision Science, March 28, 2020
  • Resource Pack: Valuing Health and Longevity in BCA by Center for Health Decision Science, 2020
  • How Much is a Human Life Actually Worth? As the US economy reopens amid a deadly pandemic, a dire question looms. Lets weigh the risksand do the math, by Adam Rogers. This well-written article in Wired give a nice history of the concept of the value of a statistical life and how that concept has been used in policy making. It then looks at how this value can inform the debate over responses to the COVID-19 pandemic.

Benefit-Cost Studies of COVID-19 Policy Options

  •  The Benefits and Costs of Flattening the Curve for COVID-19, by Linda Thunström, Stephen Newbold, David Finnoff, Madison Ashworth, and Jason Shogren, March 2020 This paper is one of the first analyses of the benefits and costs in the United States of social distancing relative to an uncontrolled scenario without distancing. It uses data from prior epidemics and from current press reports and analyses. The authors conclude that assuming that social distancing can substantially reduce contacts among individuals, we find net benefits of roughly $5 trillion in our benchmark scenario. Several sensitivity tests are included. 
  • Does Social Distancing Matter? by Michael Greenstone and Vishan Nigam, Working Paper No. 2020-26, March 2020 This paper estimates the net mortality benefits in the United States of moving between two scenarios modeled by Ferguson et al. (2020): a no policy alternative and a mitigation scenario that combines home isolation of suspect cases, home quarantine of those living in the same household as suspect cases, and social distancing of the elderly and others at most risk of severe disease. The authors estimate that the mortality benefits of social distancing are over $8 trillion.
  • "Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand." By Ferguson, Neil M., et al. March 16, 2020, London: Imperial College COVID-19 Response Team. This paper provides estimates of mortality rates under a variety of scenarios.
  • The Macroeconomics of Epidemics! by Martin S. Eichenbaumy, Sergio Rebeloz, and Mathias Trabandtx, March 23, 2020 This paper examines how decisions to cut back on consumption and work reduce the severity of an epidemic, as measured by total deaths, but also exacerbate the size of the recession caused by the epidemic. The authors find that the optimal containment policy increases the severity of the recession but saves roughly half a million lives in the U.S
  • The Loss from Pandemic Influenza Risk, by Victoria Y Fan, Dean T Jamison, and Lawrence H Summers. This paper looks at influenza pandemics in general to estimate loses relative to a no-epidemic scenario. Estimates are provided for countries at all income levels. 
  • Pandemics: Risks, Impacts, and Mitigation, by Nita Madhav, Ben Oppenheim, Mark Gallivan, Prime Mulembakani, Edward Rubin, and Nathan Wolfe This article provides a global perspective on the likelihood of pandemics, their effects, and policy steps to mitigate them.
  • This Time the Numbers Show We Cant Be Too Careful, by Cass Sunstein, Bloomberg Opinion, March 26, 2020, 12:30 PM EDT This brief policy piece summarizes some of the early COVID-19 benefit-cost studies and concludes that there is considerable danger in being overcautious in addressing the pandemic.
  • Confronting COVID-19: A Conversation with Columbia University Professor Scott Barrett, by Robert N. Stavins and Scott Barrett, Mar. 27, 2020 This 40-minute podcast interview starts with an overview of Professor Barretts career. At minute 17.5 it turns to his views on a wide range of issues related to international cooperation, pandemics, the role of science in society, and benefit-cost analysis (at minute 26.5).
  • Economic analysis of COVID-19 responses (part 1 and part 2) by Julian C. Jamison, Incidental Economist,April 1, 2020. These pieces highlight the importance of specifying both an intervention and counterfactual in public policy analyses; in this case a government lockdown policy compared with moderate social distancing (MSD). He goes on to summarize five studies that approximate that comparison and concludes most of the epidemiological gains come from MSD and in particular changing the behaviors of the most socially active individuals, the most at-risk individuals, and symptomatic individuals. These changes should occur early and be sustained throughout the crisis, but the marginal benefits of applying them to everybody else are relatively low.
  • Can masks help with reopening the economy? by Maria Polyakova, Jason Andrews, Stephen Luby and Jeremy Goldhaber-Fiebert. Stanford Institute for Economic Policy Research, April 2020 This blog post concludes that the available evidence about whether wearing masks will curtail the spread of infectious disease is weak but nevertheless supports encouraging wide spread mask use.
  • Macroeconomic Implications of COVID-19: Can Negative Supply Shocks Cause Demand Shortages? by Veronica Guerrieri, Guido Lorenzoni, Ludwig Straub, Iván Werning. April 2, 2020. This technical paper provides a detailed economic model of how a shock like the COVID-19 virus can affect the country. The authors use the model to assess the likely effectiveness of alternative macro policies being discussed. Werning provides a nice summary of the model on twitter.
  • Principles and Standards for Benefit-Cost Analysis of Public Health Preparedness and Pandemic Mitigation Programs, by Joseph Cook, Washington State University. This chapter illustrates issues that might arise in conducting economic analyses of public health preparedness or pandemic mitigation programs. Some of the issues raised have been debated extensively elsewhere, such as the choice of a social discount rate, the importance of sensitivity analyses, and the use of distributional weights. Other issues such as incorporating externalities or macroeconomic effects have received less attention in the economic evaluation literature. The chapter aims to begin a discussion of appropriate principles and standards on both types of issues
  • Covid-19 Infection Externalities: Trading Off Lives vs. Livelihoodsby Zachary A. Bethune and Anton Korinek, NBER Working Paper No. 27009, April 2020. This paper analyzes the externalities that arise when social and economic interactions transmit infectious diseases such as COVID-19. The authors show that private agents perceive the cost an additional infection to be around $80k whereas the social cost including infection externalities is more than three times higher, around $286k. This misvaluation has stark implications for how society ultimately overcomes the disease. They conclude that if targeting the infected is impossible, the optimal policy is still to aggressively contain and eliminate the disease, and the social cost of an extra infection rises to $586k.
  • Economic Effects of Coronavirus Outbreak (COVID-19) on the World Economy, by Fernandes, Nuno, March 22, 2020. This report discusses the economic impact of the Coronavirus/COVID-19 crisis across industries, and countries. It also provides estimates of the potential global economic costs of COVID-19, and the GDP growth of different countries based on data from 30 countries, under different scenarios. The report shows the economic effects of outbreak are currently being underestimated, due to over-reliance on historical comparisons with SARS, or the 2008/2009 financial crisis. 
  • Some Basic Economics of COVID-19 Policy: A look at the trade-offs we face in regulating behavior during the pandemicby Casey Mulligan, Kevin Murphy, and Robert Topel, April 27, 2020. This paper lays out the trade-offs involved with regulating the behavior of the general population during the COVID-19 pandemic.  It draws on the authors well-known work about the value of health (Kevin M. Murphy and Robert H. Topel, The Value of Health and Longevity, Journal of Political Economy, October 2006) and provides a useful list of what we already know and highlights some key unknowns that remain. It then compares relative advantages and disadvantages of large-scale social distancing regulation to a policy of screen, test, trace and quarantine.  One important point is that the authors find that the optimal type and timing of strategies depends critically on whether we expect to contain the pandemic long-term or until a vaccine or cure arises or whether we focus on minimizing the long-run costs of a pandemic that will run its course. 
  • On the Economic Benefits and Costs of COVID-19 Mitigation Measures in Mexicoby  Irvin Rojas, May 4, 2020. This paper calculates the daily flows of COVID-19 cases under the current scenario of recommended social distance and restricted economic activity, and under a counterfactual uncontrolled scenario with no mitigation measures. The author finds that the net cost of the control in terms of aggregate output is twice as large as the estimated benefits. Details about the methods and sensitivity tests are provided to help readers assess the application of that finding.
  • Costs and Trade-Offs in the Fight Against the Covid-19 Pandemic: A Developing Country Perspective by Norman Loayza, May 15, 2020. This World Bank policy brief documents the global economic contraction and its potential impact on developing countries. It argues that the pandemic crisis may hurt low- and middle-income countries disproportionately because most of them lack the resources and capacity to deal with a systemic shock of this nature. Furthermore, the author argues that, having more limited resources and capabilities but also younger populations, developing countries face different trade-offs in their fight against COVID-19 than advanced countries do.
  • Covid-19, Stay-at-Home Orders and Employment: Evidence from CPS Data. By Louis-Philippe Béland, Abel Brodeur, and Taylor Wright, May 23. 2020. This paper reports that as of early May, stay-at-home orders and related policies had increased unemployment by nearly 4 percentage points, but reduced COVID-19 cases by 186,600 311,000, and deaths by 17,85123,325. It goes on to compute lost income ($18.6$21.4 billion), reduced government income tax revenues ($3.4$5.5 billion), increased unemployment insurance benefit payments ($5$5.8 billion) and reduced hospital costs ($0.7$1.2 billion). Despite the jobs lost, age adjusted value of statistical life suggests that stay-at-home orders are cost.
  • Trading Off Consumption and COVID-19 Deaths by Robert E. Hall, Charles I. Jones, Peter J. Klenow, June 2020. This note develops a framework for thinking about the following question: What is the maximum amount of consumption that a utilitarian welfare function would be willing to trade off to avoid the deaths associated with the pandemic? The answer depends crucially on the mortality rate associated with the coronavirus. If the mortality rate averages 0.81%, taken from the Imperial College London study, our answer is 41% of one year's consumption. If the mortality rate instead averages 0.44% across age groups, our answer is 28%..
  • More to come..

General COVID-19 Resources

  • The SSRN maintains a page highlighting the array of work published in its network on COVID-19.
  • The Johns Hopkins Universitys COVID-19 Dashboard provides very useful and widely circulated counts of the number of COVID-19 cases, deaths, and recoveries around the world
  • The New England Journal of Medicine is making all of its articles related to COVID-19 available for free through its website.
  • The Journal of the American Medical Association also has a website with articles that summarize COVID-19 related medical care
  • How the Virus Got Out, by Jin WuWeiyi CaiDerek Watkins and James GlanzMarch 22, 2020. The New York Times provides a great graphic showing how international travel patterns spread the virus across the world. (Note: this graphic has a lot of data any may take a while to load on your computer.)
  • What Policymakers Can Do to Defeat COVID-19, by Vivian Ho and Heidi Russell, blog of Rice Universitys Baker Institute for Public Policy, April 13, 2020. This widely circulated blog, which includes lots of links to other sources, lists a number of treatment and policy options for addressing the pandemic.
  • Policy Implications of Models of the Spread of Coronavirus: Perspectives and Opportunities for Economistsby Christopher Avery, William Bossert, Adam Clark Glenn Ellison, Sara Fisher Ellison, NBER Working Paper 27007, April 2020.This paper provides a critical review of models of the spread of the coronavirus (SARS-CoV-2) epidemic that have been influential in recent policy decisions. There is tremendous opportunity for social scientists to advance the relevant literature as new and better data becomes available to bolster economic outcomes and save lives
  • NBER Papers on Health Economics.Not surprisingly, researchers in the National Bureau of Economic Research have produces a flood of papers on topics related to COVID-19 policies. In addition to the NBER papers listed elsewhere, here is a selected list of relevant papers as of April 20:
    • Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem by Charles Manski and Francesca Molinari w27023
    • The Subways Seeded the Massive Coronavirus Epidemic in New York City, by Jeffrey Harris w27021
    • Lock-downs Loneliness and Life Satisfaction, by Daniel Hamermesh w27018
    • How Are Small Businesses Adjusting to COVID-19? Early Evidence from a Survey, by Alexander Bartik, Marianne Bertrand, Zoë B. Cullen, Edward Glaeser, Michael Luca, and Christopher Stanton  w26989

Covid Impact Survey

The Data Foundation is releasing data collected in the COVID Impact Survey. The survey is an effort to provide national and regional statistics about physical health, mental health, economic security, and social dynamics in the United States during the coronavirus pandemic. 

The results released provide reliable estimates at the national level as well as for 10 states and 8 metropolitan areas, including for California, Colorado, Florida, Louisiana, Minnesota, Missouri, Montana, New York, Oregon, Texas, Atlanta, Baltimore, Birmingham, Chicago, Cleveland, Columbus, Phoenix, and Pittsburgh.

Key findings include:

  • Regional variations in compliance and lack of participation for 18-22 year olds with social distancing and wearing face masks continue to suggest either mixed messaging or unwillingness to comply with CDC guidance. Policymakers and CDC could deploy additional efforts to reinforce guidance and potential benefits for the American people in taking appropriate precautions to avoid the spread of coronavirus. 

  • Slight reductions in behaviors such as avoiding crowds and visiting restaurants across the country suggest growing COVID fatigue with certain restrictions in place as well as variations in how such measures are implemented across the country. Officials could more consistently communicate expectations and policies within their jurisdictions, including those practices that may still be necessary even when existing restrictions or stay-at-home orders are lifted.

  • Shifting views on the willingness for COVID-19 testing and participation in app-based tracking, with considerable regional and demographic variation, suggest that once policymakers decide on how to apply testing programs, education of the population will likely be needed to encourage participation.

  • Economic effects and food insecurity affect some demographics and household structures more than others. Policymakers could consider those disproportionately affected in determining strategies, for example, that more effectively encourage symptomatic individuals to stay home from work or to provide support for those who may fear losing their jobs if missing work because of illness.

The COVID Impact Survey is unique in that its methodological approach relies on an address-based random sample and also includes a range of questions about physical health, mental health, and economic security on a single survey. 

The survey was administered by NORC at the University of Chicago and the project is supported by the David and Lucile Packard Foundation, Alfred P. Sloan Foundation, and the Federal Reserve Bank of Minneapolis. Additional details about the COVID Impact Survey, including a complete de-identified, open dataset are available at for ongoing research and analysis.

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Late Breaking News:

COVID Impact Survey Webinar: Week 3 Data Release

       Thursday, June 11, 2020

       3:00 PM to 4:00 PM

       ONLINE (map)

On Thursday, June 11 the Data Foundation will release the third week (June 1 - 7, 2020) of data collected in the COVID Impact Survey. Join us for a discussion on week 3 findings!