In a previous post, I described a simple mechanism by which the government can encourage private spending toward some goal, such as reducing the spread of COVID-19. That mechanism is detailed in my recently completed paper, currently under submission to law reviews, Random Selection for Scaling Standards, with Applications to Climate Change. I received excellent comments and will return in a later post to answer some of the questions and objections raised by commentators. But I now want to make the previous post more narrow, by focusing on a subset of the COVID-19 spending problem, specifically the challenge of ramping up the manufacturing of medical supplies. Tyler Cowen’s Emergent Venture Prizes generously announced $1 million for rewards to be given ex post for COVID-19 work. My suggestion here is that the government should spend far more than this to ramp up manufacturing, relying primarily on ex post evaluations rather than ex ante contracts.
It is now clear that there will be a massive shortage of certain medical products. Let’s just focus on one particularly important product category: ventilators. If we had enough ventilators, many more future critical patients could be saved than with current capacity. Along with many other improvements, this might increase the production capacity of the healthcare system, eventually reducing the extent to which the curve must be flattened. If we no longer needed to worry about “flattening” the curve, global economic activity could resume, reducing the devastation of the inevitable recession. Thus, increasing ventilator production ought to be one (of many) important public policy goals.
So, what is happening? Well, the U.K. (whose government has resisted the urge to flatten the curve on the theory that it is better to generate herd immunity by allowing the virus to spread rapidly in low-vulnerability populations) has urged industry to switch to making ventilators. The U.S. hasn’t done much of anything at all as a policy matter. According to Forbes, ventilator firms themselves seem to think that they could increase production within a few months, but hospitals may not place orders that far into the future, given the risk that the machines will not be necessary. One imagines that ventilator firms and hospitals will increase production and orders considerably, because they want to do the right thing and be perceived as doing the right thing, but the overall level of ramping up might be considerably less than the social optimum. Rules and norms against price gouging limit the incentive to expand new production.
Vox reports that if the situation were similar to the Spanish flu pandemic, approximately 750,000 people would need ventilation. Even under worst-case scenarios, they would not need them all at once. Suppose that we need one-third of that capacity at any given time and that we accept Vox’s estimate that we currently have about 160,000 altogether. That suggests that an order of 100,000 ventilators would greatly increase our ability to meet this challenge (though still possibly fall short, given non-COVID-19 patients needing ventilation). Hospital-grade ventilators typically cost around $25,000, so if we were willing to wait indefinitely for ventilators, the total bill for this country would be around $2.5 billion. But we need these ventilators to be made very quickly, and that would presumably be a lot more expensive. Not only would ventilator makers need to increase their production capacity dramatically, but so too would their parts makers (and the makers of parts for those parts, and so on to not-quite-infinite regress). Even if the government were to spend $25 billion on 100,000 ventilators, that would easily pass cost-benefit analysis if just 5,000 lives could be saved, with a valuation of life of $5,000,000. It seems plausible that the investment could save many more lives than that, especially if the private sector is able to produce a larger number of ventilators.
I don’t have the knowledge to speculate how much one would need to spend to persuade ventilator makers and parts makers to greatly increase their production capacity quickly. Perhaps industry or government could study the question, but that would involve a fair amount of guesswork, requiring speculation about which parts of the supply chain will turn out to be bottlenecks and how expensive it would be to develop alternatives. The Hayekian claim would be that no one has the relevant knowledge, some of which doesn’t exist yet and some of which is diffused through markets. In any event, while even preliminary estimates would help, we don’t have time for a detailed study.
The conventional approach to this problem would be for the government (presumably the federal government, though one could also imagine states acting independently) to engage in procurement, letting private firms bid on price and perhaps some other variables. A benefit of this approach is that our legal institutions for conducting such procurements are greatly developed. There are even rules that relax other rules for emergencies, including “when the President has made a declaration under the Robert T. Stafford Disaster Relief and Emergency Assistance Act,” as the President has now done. For example under FAR 18.125, “agency protest override procedures allow the head of the contracting activity to determine that the contracting process may continue after GAO has received a protest.”
Still, there are reasons to wonder about the government’s ability to execute effectively. The absence of any call for proposals even today is not encouraging. Consider also at the government’s procurement of surgical masks. There was a two-week solicitation period ending March 18—very fast by government standards, but still, a long time by the time scale of a pandemic where cases are doubling every few days. Perhaps of greater concern is that the solicitation asks for “a proposed schedule for items that can be delivered quickly without overwhelming the supply chain, with additional items delivered over a period not to exceed 18 months.” Presumably, proposals that offer a greater proportion of masks sooner will be favored, but the solicitation gives no indication of how much of a bonus earlier delivery would be, and there is no statement that the goal is to greatly expand maximum supply capacity. It seems unlikely that anyone will perform even a back-of-the-envelope estimate of how much more valuable a mask would be if that mask could be produced next month than six months from now, let alone include performance incentives based on such a calculation.
Similarly, with ventilators, the ultimate question is how many QALYs will be saved by the production of a particular new ventilator using a particular technology at a particular time. I am skeptical that the government has the foresight to assess this for all types of ventilators, free from political considerations, let alone the ability to modify the contracting process over time. Yet it seems plausible that a few years from now, the government might be able to produce reasonable retrospective estimates of the utility provided by different ventilators at different times, based on statistical evidence about when patients needed ventilators and when they performed best. A system that relies more on ex post governmental assessments than on ex ante governmental projections allows the market to respond more quickly and with greater agility, changing plans and making adjustments as necessary. This is especially important in an emergency, where uncertainty is great and time is critical, but it matters at other times too.
So, how might an ex post decisionmaking approach work? The government commits to allocating $25 billion for ventilators. (Perhaps that could be limited to increased production over previous capacity, but it also sets a good precedent to reward producers for the production capacity they offered as of the beginning of a crisis.) The reason for the government to commit to payment is that the government might otherwise have incentives to lowball after the fact. Given the Winstar case, the government probably could not easily escape a commitment of this sort. An alternative approach would be for the government to set a range (say $15 billion to $60 billion), with the total amount to be based on the total number of QALYs estimated to have been saved in the country, perhaps at $100,000 per QALY, but constrained to this range.
Place aside for now the challenges involved in the ex post adjudication of QALYs, and consider the incentives of ventilator companies and providers of capital on the assumption that even if the decisionmaking process is imperfect, one’s best guess of the government’s evaluation of the contribution of a particular ventilator produced will be roughly proportional to the number of QALYs that it saves. What would a governmental commitment of this sort achieve? Ventilator companies will seek to make production decisions that maximize QALYs saved per dollar spent. That may affect which models they invest in. For example, some might decide that it’s worth producing many simpler ventilators, on the assumption that many imperfect ventilators (perhaps even models similar to DIY designs, if they believe that regulations could be changed to allow their use) are better than a small number of perfect ones. Moreover, ventilator companies could adjust to changing information, about both the disease and parts supplier capabilities, in making decisions, without the need for cumbersome procurement change orders.
The most obvious objection to this approach is the claim that ventilator companies would not be able to handle the risk. But capital markets are vehicles for eliminating risk through diversification. Pharmaceutical companies and others take massive risks all the time. Moreover, ventilator companies could raise money specifically for this purpose. The rights to eventual governmental payments could be tradeable, so the ventilator companies could exchange some of these tradable rights for funders, or they could do the more conventional thing of creating subsidiaries and selling stock in the subsidiaries. Even if any particular ventilator investment is risky, these investments can be part of a diversified portfolio. With interest rates exceptionally low, the claim that ventilator companies would not invest is absurd. Sure, government contractors may be accustomed to greater certainty, but there is no reason that they cannot function in such an environment. The risk might be reduced by requirements that companies can only receive reimbursement for efforts that they disclose in advance or shortly after beginning, so that each company can assess what others are doing and gauge how much total investment is chasing the government’s reward money.
Another objection is that the focus solely on ventilators is arbitrary. If the government procures ventilators but not other necessary life-saving equipment, the ventilators might not be used. Moreover, just as the government may not be well positioned to determine in advance exactly what type of ventilators maximized QALYs per dollar, so too might the government not be so well positioned to choose how to distribute total available government funds among alternative life-saving investments. In my original proposal, I suggested that perhaps the government might spend a trillion dollars to reward all investments, including medical supplies like protective gear and R&D on new drugs. That would give the private sector to assess what type of investments are most appropriate.
One might object that some level of generality will be too much. After all, even those who applaud ex post decisionmaking for a specific application will likely not want a government fund to be used for private contributions of any sort, whether or not they relate to COVID-19. There is some value to political accountability. Perhaps a fund for “hospital equipment and supplies” is the right level of generality, or perhaps “ventilators” is. Yet few would say that political accountability demands that members of Congress or the President choose ventilator specifications. Thus, it seems reasonable to me to have a ventilator fund, as well as maybe other funds.
Another argument for a relatively narrow level of generality in construction of a fund is that it may make it easier to create an ex post decisionmaking process. It seems more plausible that a group of experts could compare the success of different ventilator producers than that they could compare ventilators against many other products, let alone make apples-to-oranges comparisons across many different types of responses to the COVID-19 epidemic. It might seem that a decisive argument against ex post decisionmaking, especially if the fund is at a relatively high level of generality, is that there will be a large number of complicated decisions to make. This can lead to one of two results. First, enormous sums might be spent on the adjudication process, and these anticipated transactions costs are moneys that otherwise could be spent on medical equipment. Second, decisionmakers might make relatively superficial decisions. Anticipation of that might distort private decisionmaking. Why make a slight improvement to a ventilator if one does not think that the eventual decisionmakers will notice it?
These concerns help explain the most unusual aspect of my proposal, the use of random selection. This aspect is not necessary if the level of generality is ventilator production, however, because there may be a relatively small number of claimants on the fund. At a broad level, my goal is to argue for distribution of government funds based on ex post evaluations, particularly in circumstances of emergency, and this argument suffices for my proposal here to spur production of ventilators (and perhaps a few other key products). It should not be difficult to craft legislation accomplishing this proposal, especially since the details of ex post adjudication can be worked out by an administrative agency later. It requires much less governmental advance planning than traditional approaches to government spending, including congressional authorizations and procurement. The government can do this, and it seems much more valuable than most of what the government is doing instead.
I recognize that the idea of using random selection may be too new to be considered for any legislation to be passed in the short term. Still, it’s worth explaining when random selection would be useful in an ex post decisionmaking system, as well as how and why it would work. The case for random selection increases in importance, the greater the level of generality and the greater the number of heterogeneous claims that might be filed. The beauty of random selection is that we could use ex post decisionmaking even if the government expected literally millions of different claims for many different types of contributions. That would be more likely for the climate change applications that I address in my paper, but could apply as well to a COVID-19 fund at a level of generality considerably higher than ventilator production.
How does random selection work? The government chooses only a small number of claims, say 100, and it distributes the entire fund to the owners of these claims in proportion to the measurement of social value (whether QALYs or broader). Everyone else gets nothing. (If the fund is variable in size, instead of fixed at a number like $25 billion, the total size of the fund would be extrapolated based on social value estimates extrapolated from the cases randomly adjudicated.) The advantage of this approach is pretty simple: Many fewer cases can be adjudicated, and so there will be sufficient resources to adjudicate each case with some care.
The disadvantage is that the proposal seems like a lottery. The project of my article is to argue that this is not a problem, that capital markets can absorb the risk. I will not repeat all of the relevant points here, but I will sketch out the general argument: Intermediary companies would be expected to buy up diversified portfolios of claims based on their assessments of how the government might value them if randomly selected. All producers need concern themselves with is how much these intermediaries will pay. (Some large producers might not need intermediaries, relying instead on other capital market tools.) Assuming there is sufficient competition among intermediaries, the amount the intermediaries pay should be equal to the amount they expect to receive minus the costs incurred by the intermediaries themselves. The intermediaries provide a socially useful service of evaluating producers’ plans (if the purchase is before production) and achievements (if the purchase is after production), as well as in prosecuting the few claims randomly selected for ex post evaluation.
To an intermediary or other diversified firm, it doesn’t matter that 1/n claims will be worth n times socially assessed value, because the expected value of a claim remains the same. Moreover, diversification does not need to be perfect. Random selection of claims by the government is a risk that can be precisely mathematically evaluated, and thus it is insurable. Indeed, the government itself could and should offer insurance at actuarially fair rates. Thus, an intermediary should be able to largely eliminate the risk attributable to uncertainty about which claims will be randomly selected. The intermediary will still face risk associated with randomness or arbitrariness by governmental decisionmakers in their evaluations. But because relatively few claims are adjudicated, these adjudications can be performed with care by multi-member panels, using expert testimony where necessary, thus reducing this form of uncertainty as well. The knowledge that any eventual adjudication will be careful will have ex ante benefits, as intermediaries will expect that the decisionmakers will notice subtle advantages of their products.
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