As Ars reported recently, evidence from the 1918 flu pandemic suggests that cities with more aggressive lockdown responses had stronger economic recoveries.
There’s more than one way to think about the economics of lockdowns, and a paper due to be published in the Journal of Benefit-Cost Analysis has an entirely different approach. It accepts that lockdowns will hurt the economy compared to business-as-usual but calculates whether that cost is outweighed by the lives that will be saved by social-distancing measures.
The answer is yes—by $5.2 trillion. That’s an estimate that changes based on a range of different assumptions, but it represents what the authors consider the most realistic scenario.
How much is a life worth?
Putting a dollar value on a life can feel icky, but people implicitly act as though lives have a high (although not infinite) value. For instance, throwing all the world’s resources at saving the life of one person is not a choice we’d be likely to make. Yet we’re clearly prepared to pay quite a high price for both life and health.
US federal agency guidelines have needed to put a price on life in order to set policy on things that sometimes kill people, like driving. To do this, they use a figure that estimates how much extra money people will pay to save an additional life. For instance, take the higher pay that comes with riskier jobs: when you look at how much extra a group of 10,000 workers gets paid when their job comes with a higher risk, it comes out to around $10 million for each additional probable death in the group.
That figure of $10 million, the so-called “value of a statistical life,” is the figure used by federal agencies, and it’s also the figure used by economist Linda Thunström and her colleagues when they calculate the cost and benefit of social distancing. They start out by gathering a bunch of other benchmark numbers that represent realistic or middle-of-the-road scenarios for the pandemic—like assuming that social distancing will reduce contact between people by an average 38 percent.
Using that and other benchmark numbers, the researchers calculate that social distancing will save about 1.24 million lives compared to a scenario with no distancing. This translates to a saving of $12.4 trillion, based on the $10 million value of a statistical life used in policy. To work out how much this benefit weighs against the cost to the economy, the researchers take the recent Goldman Sachs prediction that social distancing will cause US GDP to shrink by 6.2 percent, leading to losses of $13.7 trillion.
They next had to calculate the impact the pandemic would have on the economy if we rode it out without any social distancing. Estimates made by others ranged from a loss of 1.5 to 8.4 percent of the GDP, so the researchers used a conservative value: 2 percent. This produces a smaller (yet still massive) hit of $6.49 trillion. Combined with the $13.7 trillion saved by the lack of social distancing, this makes the cost of social distancing $7.21 trillion.
Subtracting this from their earlier $12.4 trillion figure leads to their headline estimate. “Under our benchmark assumptions,” write Thunström and colleagues, “social distancing generates net benefits of about $5.16 trillion.”
With new information rolling in all the time, all the numbers of the coronavirus pandemic are inherently slippery and subject to updates. Because of this, Thunström and her colleagues take their basic calculation and throw a range of different numbers at it, to see where its boundaries lie. This analysis works out where the “break-even” point is for a range of different parameters—the point at which the value of lives saved outweighs the cost of social distancing.
For instance, if social distancing wasn’t as effective at slowing disease spread, but came with the same economic cost, the results wouldn’t shake out the same way: the number of lives saved would be outweighed by economic damage. The researchers estimate that, holding everything else equal, social distancing would only need to cut out one in five interactions to be worth the cost—but that’s a result based on so many assumptions that it shouldn’t be read as a prescription for how much social distancing to aim for.
On the other hand, if the virus is more infectious than their initial assumptions, social distancing would need to be way more effective for the economic costs to pay off.
The estimate of 1.24 million lives saved seems pretty high. But it’s not necessarily outlandish—a model published by a team at Imperial College London estimated that if the pandemic were allowed to rampage through the US unmitigated, it would lead to around 2.2 million deaths. Current estimates suggest that the total death toll by August may be more in the region of 60,000 to 124,000 deaths—if (and it’s a huge if) social distancing measures stay in place. That’s a horrific number, but at its most optimistic, it means 2.14 million fewer deaths than that worst-case scenario. This means that the estimate of 1.24 million lives saved could be on the low side.
Importantly, the researchers don’t question their assumption that social distancing will lead to a greater decline in GDP, or a slower economic recovery, compared to business as usual. That assumption doesn’t tie in with other recent research suggesting that social distancing may in fact be the best thing for the economy itself. If the economy recovers faster with social distancing than without, this research would actually be underestimating the economic benefits of lockdown.
There are reams of questions still to be answered about the economic results of the pandemic, and models like these will need to be tweaked, repeated and refined as more information rolls in. But right now, a range of different economic analyses are questioning the knee-jerk assumption that social distancing is a worse economic outcome than business as usual. And a poll of economists at US universities saw a unanimous response: restarting the economy should only be on the cards with a huge increase in testing capacity and a well-formed plan to control new outbreaks.
Journal of Benefit-Cost Analysis, Forthcoming. DOI: 10.2139/ssrn.3561934 (About DOIs).