Q1.  Are the “economic” and “mortality” costs comparable?

A1.  They are both measured in dollars.  They are both measured relative to a “normal situation” without a pandemic.  As such, their sum is informative about the value of innovation that can hasten the end of the pandemic, or avoid a future pandemic altogether.  Their sum serves this purpose regardless of whether the economic costs are “voluntary” or “mandated” by governments.  The two costs can also be ingredients, but not the sole ingredients, into answering other questions such as the desirability of social distancing mandates.


Q2.  What about future opportunity costs?

A2.  Although future opportunity costs are counted among the mortality costs (indeed, they are essentially all of the mortality costs), they are not counted among "economic costs." In other words, the pandemic creates expected future opportunity costs for the vast majority of the population that remains alive, but I do not count them until the opportunities are passed. This is an important reason why my economic costs can be less than the costs that might be inferred from the drop in stock prices, which reflect expected future costs incurred by corporations. The unifying chacteristics of both of my cost categories is that they are not recoverable. Those who died will not be brought back to life to realize the opportunities they would have had without the pandemic. As another example, students who did not learn this year cannot recover the missed learning opportunities; they might learn the same material later but that future learning effort itself has an opportunity cost. In contrast, expected future opportunity costs would not necessarily be costs if the pandemic were to suddenly end tomorrow.


Q3.  Aren’t the health professionals the only ones who can meaningfully contribute to medical innovation and thereby help avoid the costs of the pandemic?

A3.  No.  Business and civic organizations and even individuals can also innovate how they accomplish their traditional missions while mitigating harms from COVID-19.  To name an example, retailers such as Walmart and Whole Foods have implemented special shopping hours for senior citizens, who are more vulnerable to the virus, so that they do not have to mingle with nonelderly shoppers.  If history is any guide, many valuable innovations will have surprising origins, beyond the big names in science and business.


Q4.  Is a loss of GDP a cost?

A4.  Market production (GDP) is not synonymous with welfare because factors of production can move into the nonmarket sector (i.e., people who would have been at work can do things at home), which itself is economically important even in normal times. However, there are two reasons why the dollar amount of the reduction in GDP understates the welfare cost of the 2020 shutdowns. The first reason is that GDP measures only averages, whereas the direct effects of shutdown are unequally distributed. The inequality apparently has costs by itself, because governments attempt to mitigate those costs by implementing relief efforts that will further reduce GDP both during the shutdown and afterwards. The second reason is that shutting down non-essential businesses makes the nonmarket sector less productive too because the sector is starved of market inputs. Human capital accumulation is an important instance, with more than 70 million children and young adults normally enrolled in school and tens of millions more would be accumulating skills during the early phase of their careers.


Q5.  Why aren’t the opportunity costs of the pandemic being calculated by the government rather than one citizen working on his own?

A5.  The executive branch of the Federal government is, for good reason, required to calculate the opportunity costs of its regulations and guidance.  It is supposed to ensure that its regulations and guidance provide more net benefit than a “less-stringent” alternative that achieves the same goals.  It is also supposed to look toward “market-oriented approaches rather than direct controls.  Market-oriented approaches that use economic incentives should be explored. ... alternatives that rely on incentives and offer increased flexibility are often more cost-effective than more prescriptive approaches.”  For the same reasons, state regulators should also be considering opportunity costs.  But a well-kept secret is that, in health and many other areas, these requirements are perennially ignored.  If individual citizens do not calculate these costs, their magnitudes will remain unknown.


Q6.  Which costs are measured more accurately: mortality costs or “economic” costs?

A6.  Because the economic costs are experienced by a much larger segment of our population, they can be easier to measure.  We do not need a very big sample to estimate how many people are not working.  Death from the coronavirus (or anything else) is more rare and requires larger samples.  It is also difficult to know the age and morbidity characteristics of the people who died in recent days.  However, nonmarket opportunity costs are also difficult to measure and monetize because (almost by definition) nonmarket activities do not have prices associated with them.  The market costs also require some interpolation between the labor-market surveys that are occurring every 2-5 weeks and some extrapolation from the most recent survey until today.


Q7.  Where can I get a file with data contained in the charts shown at PandemicCosts.com?

A7.  It is available in Excel and json format.


Q8.  What VSL do you use?

A8.  $2.1 million per death from COVID-19. The point of VSL is to make comparisons the same way that individuals do in their personal lives. They do not treat all mortality risks equally, and therefore a VSL approach should not treat them equally. The VSL is proportional to income or consumption, which is lower now (May 2020) than it was just two months ago. Also, "people <65 years old had 34- to 73-fold lower risk than those >= 65 years old in the European countries and 13- to 15-fold lower risk in New York City, Louisiana and Michigan." (cite from here). Co-morbidities are disproportionate among those dying from or with COVID-19. These are reflected in my $2.1 million estimate.

A number of other economists are using about $4 million, which PandemicCosts.com did too until this Briggs paper became available with estimate of life expectancy and comorbidities of the people dying from COVID-19. Specifically, I begin with Kniesner and Viscusi's $10 million estimate for 2017. Following the convention in this field, I then adjust to 2019 according to the increase in nominal GDP per capita. Because I am comparing the mortality costs to costs incurred during the pandemic, I then adjust for the ratio of pandemic consumption to 2019 consumption among the affected population, which I take to be 0.9 (for the general population it would be more like 0.8). The result of these two adjustments is $9.8 million. The more important adjustment is for differences between the age and comorbidities of the general population and the population dying from COVID-19. The mid estimate from Briggs is that those who died from COVID-19 had a discounted average of 4.1 remaining quality-adjusted life years (QALYs), as compared to 19.1 for the general population (I estimated the 19.1 using his table and age weights for the general population). My $2.1 million VSL is 9.8*4.1/19.1. Somewhat lower VSL would be obtained by using Briggs' undiscounted QALY or undiscounted life expectancy.

Any visitor to PandemicCosts.com interested in an alternative VSL value merely has to proportionally rescale my mortality-cost estimates.


Q9.  What are your methods?

A9.  Cumulative mortality costs are the product of VSL and cumulative deaths as reported by Johns Hopkins. Economic costs are essentially $20 billion per day, which is a result detailed in my paper. Here I use less than $20 billion in the early days and somewhat more than $20 billion recently, due to the fact that the economic depression got worse over time to a degree that I measure with household labor force surveys, initial UI claims, and Google Trends. My estimates are adjusted for the weekly and seasonal cycle (failing to adjust for the weekly cycle would show less cost on weekends and more cost on weekdays; my paper discusses this further). Regarding measuring employment and hours between monthly surveys, see this blog post. Note that, unlike the headline BLS reports, I do not consider people employed but absent from work for "other reasons" to be employed. I do not consider the excess number of people employed but home sick to be employed either. As of mid April, 7.5 million and 1.1. million people, respectively, were in these categories.


Q10.  What epidemiology models do you use?

A10.  None. Epidemiology models may help to forecast the future or to consider hypothetical disease policies, but neither of those are done at PandemicCosts.com. I only estimate costs that have already been incurred, rather than costs that will be incurred.


Q11.  Do you use employment or hours worked for GDP?

A11.  Hours worked. This follows my longstanding practice of putting most of my attention to hours worked rather than labor force status. The latter has too many gray areas (does a person getting paid for a while to stay at home and do no work count as employed?) that change artifically as subsidies emerge for one status category but not another.


Q12.  Is the cure worse than the disease?

A12.  Because a large majority of the pandemic’s costs are not health costs, this is a reasonable (albeit, strangely, politically incorrect) question to ask.  But the ratio of the two costs featured at PandemicCosts.com is not enough by itself to answer the question.

  • Additional data is needed, for example, to determine how much (if at all) mortality would increase if there more of the work, trade, and engagement that people normally do. Some of the data noted in answer A5 (above) may be relevant: health regulators have a track record of pursuing health objectives with little regard for the opportunity costs of those who have to obey them.
  • Here is an example of how additional data might complement my data in evaluating the benefit of a lockdown. If “it really may not be until next year that we can safely lift these lockdowns” (this is not for me to determine), then "lockdown" will cost more than $7 trillion (my data) and I don't see how it could deliver commensurate mortality benefits:
    • At the VSL, more than 3.3 million COVID-19 deaths would have to be AVERTED (COVID-19 deaths delayed do not count here). If the costs were more than $7 trillion (this is a point estimate, not a worst-case scenario), then even more deaths would have to be averted to "break even."
    • With 60K dying already by the end of April -- with lockdown -- there would (in the "not safe until next year" scenario) be 300K or more deaths even with the lockdown.
    • That means that, without any lockdown, the disease would be killing more than 1% of the entire population (not just those infected), which strains credulity.
    • Whether policymakers can implement the corresponding recommendation is another story (e.g., they have not yet demonstrated that they could or would force people to live the way that they used to, or that they are capable of stopping people from living that way for an extended period).
    • Even in lockdown averts 3.3 million COVID-19 deaths, we still have the "false-dichotomy" question of whether a large portion of the 3.3 million deaths could be averted with far less cost.
  • There is a real possibility (but NOT, as of May 2020, a certainty) that blanket shutdown orders, and much of the guidance coming from CDC, may be increasing deaths from COVID-19. In this scenario, vaccines and effective treatments are a long time in coming (see Murphy, Topel and I on "the possible end games"), so that an (approximately) fixed number of people must eventually get infected. The shutdown orders, and CDC guidance, delay deaths but increase their total number by reducing the fraction of those infected who are young and can more easily survive the infection.
    • The State of New York has already proven that well-intentioned policies can make the death toll worse by increasing the fraction of infections occuring among the old and vulnerable.
    • A few months from now, Sweden's results will tell us a lot about the likelihood of this possibility, because Sweden has emphasized reducing the elderly share of infections rather than reducing the number of infections occuring early in the pandemic.