Archives For externalities

Policy discussions about the use of personal data often have “less is more” as a background assumption; that data is overconsumed relative to some hypothetical optimal baseline. This overriding skepticism has been the backdrop for sweeping new privacy regulations, such as the California Consumer Privacy Act (CCPA) and the EU’s General Data Protection Regulation (GDPR).

More recently, as part of the broad pushback against data collection by online firms, some have begun to call for creating property rights in consumers’ personal data or for data to be treated as labor. Prominent backers of the idea include New York City mayoral candidate Andrew Yang and computer scientist Jaron Lanier.

The discussion has escaped the halls of academia and made its way into popular media. During a recent discussion with Tesla founder Elon Musk, comedian and podcast host Joe Rogan argued that Facebook is “one gigantic information-gathering business that’s decided to take all of the data that people didn’t know was valuable and sell it and make f***ing billions of dollars.” Musk appeared to agree.

The animosity exhibited toward data collection might come as a surprise to anyone who has taken Econ 101. Goods ideally end up with those who value them most. A firm finding profitable ways to repurpose unwanted scraps is just the efficient reallocation of resources. This applies as much to personal data as to literal trash.

Unfortunately, in the policy sphere, few are willing to recognize the inherent trade-off between the value of privacy, on the one hand, and the value of various goods and services that rely on consumer data, on the other. Ideally, policymakers would look to markets to find the right balance, which they often can. When the transfer of data is hardwired into an underlying transaction, parties have ample room to bargain.

But this is not always possible. In some cases, transaction costs will prevent parties from bargaining over the use of data. The question is whether such situations are so widespread as to justify the creation of data property rights, with all of the allocative inefficiencies they entail. Critics wrongly assume the solution is both to create data property rights and to allocate them to consumers. But there is no evidence to suggest that, at the margin, heightened user privacy necessarily outweighs the social benefits that new data-reliant goods and services would generate. Recent experience in the worlds of personalized medicine and the fight against COVID-19 help to illustrate this point.

Data Property Rights and Personalized Medicine

The world is on the cusp of a revolution in personalized medicine. Advances such as the improved identification of biomarkers, CRISPR genome editing, and machine learning, could usher a new wave of treatments to markedly improve health outcomes.

Personalized medicine uses information about a person’s own genes or proteins to prevent, diagnose, or treat disease. Genetic-testing companies like 23andMe or Family Tree DNA, with the large troves of genetic information they collect, could play a significant role in helping the scientific community to further medical progress in this area.

However, despite the obvious potential of personalized medicine, many of its real-world applications are still very much hypothetical. While governments could act in any number of ways to accelerate the movement’s progress, recent policy debates have instead focused more on whether to create a system of property rights covering personal genetic data.

Some raise concerns that it is pharmaceutical companies, not consumers, who will reap the monetary benefits of the personalized medicine revolution, and that advances are achieved at the expense of consumers’ and patients’ privacy. They contend that data property rights would ensure that patients earn their “fair” share of personalized medicine’s future profits.

But it’s worth examining the other side of the coin. There are few things people value more than their health. U.S. governmental agencies place the value of a single life at somewhere between $1 million and $10 million. The commonly used quality-adjusted life year metric offers valuations that range from $50,000 to upward of $300,000 per incremental year of life.

It therefore follows that the trivial sums users of genetic-testing kits might derive from a system of data property rights would likely be dwarfed by the value they would enjoy from improved medical treatments. A strong case can be made that policymakers should prioritize advancing the emergence of new treatments, rather than attempting to ensure that consumers share in the profits generated by those potential advances.

These debates drew increased attention last year, when 23andMe signed a strategic agreement with the pharmaceutical company Almirall to license the rights related to an antibody Almirall had developed. Critics pointed out that 23andMe’s customers, whose data had presumably been used to discover the potential treatment, received no monetary benefits from the deal. Journalist Laura Spinney wrote in The Guardian newspaper:

23andMe, for example, asks its customers to waive all claims to a share of the profits arising from such research. But given those profits could be substantial—as evidenced by the interest of big pharma—shouldn’t the company be paying us for our data, rather than charging us to be tested?

In the deal’s wake, some argued that personal health data should be covered by property rights. A cardiologist quoted in Fortune magazine opined: “I strongly believe that everyone should own their medical data—and they have a right to that.” But this strong belief, however widely shared, ignores important lessons that law and economics has to teach about property rights and the role of contractual freedom.

Why Do We Have Property Rights?

Among the many important features of property rights is that they create “excludability,” the ability of economic agents to prevent third parties from using a given item. In the words of law professor Richard Epstein:

[P]roperty is not an individual conception, but is at root a social conception. The social conception is fairly and accurately portrayed, not by what it is I can do with the thing in question, but by who it is that I am entitled to exclude by virtue of my right. Possession becomes exclusive possession against the rest of the world…

Excludability helps to facilitate the trade of goods, offers incentives to create those goods in the first place, and promotes specialization throughout the economy. In short, property rights create a system of exclusion that supports creating and maintaining valuable goods, services, and ideas.

But property rights are not without drawbacks. Physical or intellectual property can lead to a suboptimal allocation of resources, namely market power (though this effect is often outweighed by increased ex ante incentives to create and innovate). Similarly, property rights can give rise to thickets that significantly increase the cost of amassing complementary pieces of property. Often cited are the historic (but contested) examples of tolling on the Rhine River or the airplane patent thicket of the early 20th century. Finally, strong property rights might also lead to holdout behavior, which can be addressed through top-down tools, like eminent domain, or private mechanisms, like contingent contracts.

In short, though property rights—whether they cover physical or information goods—can offer vast benefits, there are cases where they might be counterproductive. This is probably why, throughout history, property laws have evolved to achieve a reasonable balance between incentives to create goods and to ensure their efficient allocation and use.

Personal Health Data: What Are We Trying to Incentivize?

There are at least three critical questions we should ask about proposals to create property rights over personal health data.

  1. What goods or behaviors would these rights incentivize or disincentivize that are currently over- or undersupplied by the market?
  2. Are goods over- or undersupplied because of insufficient excludability?
  3. Could these rights undermine the efficient use of personal health data?

Much of the current debate centers on data obtained from direct-to-consumer genetic-testing kits. In this context, almost by definition, firms only obtain consumers’ genetic data with their consent. In western democracies, the rights to bodily integrity and to privacy generally make it illegal to administer genetic tests against a consumer or patient’s will. This makes genetic information naturally excludable, so consumers already benefit from what is effectively a property right.

When consumers decide to use a genetic-testing kit, the terms set by the testing firm generally stipulate how their personal data will be used. 23andMe has a detailed policy to this effect, as does Family Tree DNA. In the case of 23andMe, consumers can decide whether their personal information can be used for the purpose of scientific research:

You have the choice to participate in 23andMe Research by providing your consent. … 23andMe Research may study a specific group or population, identify potential areas or targets for therapeutics development, conduct or support the development of drugs, diagnostics or devices to diagnose, predict or treat medical or other health conditions, work with public, private and/or nonprofit entities on genetic research initiatives, or otherwise create, commercialize, and apply this new knowledge to improve health care.

Because this transfer of personal information is hardwired into the provision of genetic-testing services, there is space for contractual bargaining over the allocation of this information. The right to use personal health data will go toward the party that values it most, especially if information asymmetries are weeded out by existing regulations or business practices.

Regardless of data property rights, consumers have a choice: they can purchase genetic-testing services and agree to the provider’s data policy, or they can forgo the services. The service provider cannot obtain the data without entering into an agreement with the consumer. While competition between providers will affect parties’ bargaining positions, and thus the price and terms on which these services are provided, data property rights likely will not.

So, why do consumers transfer control over their genetic data? The main reason is that genetic information is inaccessible and worthless without the addition of genetic-testing services. Consumers must pass through the bottleneck of genetic testing for their genetic data to be revealed and transformed into usable information. It therefore makes sense to transfer the information to the service provider, who is in a much stronger position to draw insights from it. From the consumer’s perspective, the data is not even truly “transferred,” as the consumer had no access to it before the genetic-testing service revealed it. The value of this genetic information is then netted out in the price consumers pay for testing kits.

If personal health data were undersupplied by consumers and patients, testing firms could sweeten the deal and offer them more in return for their data. U.S. copyright law covers original compilations of data, while EU law gives 15 years of exclusive protection to the creators of original databases. Legal protections for trade secrets could also play some role. Thus, firms have some incentives to amass valuable health datasets.

But some critics argue that health data is, in fact, oversupplied. Generally, such arguments assert that agents do not account for the negative privacy externalities suffered by third-parties, such as adverse-selection problems in insurance markets. For example, Jay Pil Choi, Doh Shin Jeon, and Byung Cheol Kim argue:

Genetic tests are another example of privacy concerns due to informational externalities. Researchers have found that some subjects’ genetic information can be used to make predictions of others’ genetic disposition among the same racial or ethnic category.  … Because of practical concerns about privacy and/or invidious discrimination based on genetic information, the U.S. federal government has prohibited insurance companies and employers from any misuse of information from genetic tests under the Genetic Information Nondiscrimination Act (GINA).

But if these externalities exist (most of the examples cited by scholars are hypothetical), they are likely dwarfed by the tremendous benefits that could flow from the use of personal health data. Put differently, the assertion that “excessive” data collection may create privacy harms should be weighed against the possibility that the same collection may also lead to socially valuable goods and services that produce positive externalities.

In any case, data property rights would do little to limit these potential negative externalities. Consumers and patients are already free to agree to terms that allow or prevent their data from being resold to insurers. It is not clear how data property rights would alter the picture.

Proponents of data property rights often claim they should be associated with some form of collective bargaining. The idea is that consumers might otherwise fail to receive their “fair share” of genetic-testing firms’ revenue. But what critics portray as asymmetric bargaining power might simply be the market signaling that genetic-testing services are in high demand, with room for competitors to enter the market. Shifting rents from genetic-testing services to consumers would undermine this valuable price signal and, ultimately, diminish the quality of the services.

Perhaps more importantly, to the extent that they limit the supply of genetic information—for example, because firms are forced to pay higher prices for data and thus acquire less of it—data property rights might hinder the emergence of new treatments. If genetic data is a key input to develop personalized medicines, adopting policies that, in effect, ration the supply of that data is likely misguided.

Even if policymakers do not directly put their thumb on the scale, data property rights could still harm pharmaceutical innovation. If existing privacy regulations are any guide—notably, the previously mentioned GDPR and CCPA, as well as the federal Health Insurance Portability and Accountability Act (HIPAA)—such rights might increase red tape for pharmaceutical innovators. Privacy regulations routinely limit firms’ ability to put collected data to new and previously unforeseen uses. They also limit parties’ contractual freedom when it comes to gathering consumers’ consent.

At the margin, data property rights would make it more costly for firms to amass socially valuable datasets. This would effectively move the personalized medicine space further away from a world of permissionless innovation, thus slowing down medical progress.

In short, there is little reason to believe health-care data is misallocated. Proposals to reallocate rights to such data based on idiosyncratic distributional preferences threaten to stifle innovation in the name of privacy harms that remain mostly hypothetical.

Data Property Rights and COVID-19

The trade-off between users’ privacy and the efficient use of data also has important implications for the fight against COVID-19. Since the beginning of the pandemic, several promising initiatives have been thwarted by privacy regulations and concerns about the use of personal data. This has potentially prevented policymakers, firms, and consumers from putting information to its optimal social use. High-profile issues have included:

Each of these cases may involve genuine privacy risks. But to the extent that they do, those risks must be balanced against the potential benefits to society. If privacy concerns prevent us from deploying contact tracing or green passes at scale, we should question whether the privacy benefits are worth the cost. The same is true for rules that prohibit amassing more data than is strictly necessary, as is required by data-minimization obligations included in regulations such as the GDPR.

If our initial question was instead whether the benefits of a given data-collection scheme outweighed its potential costs to privacy, incentives could be set such that competition between firms would reduce the amount of data collected—at least, where minimized data collection is, indeed, valuable to users. Yet these considerations are almost completely absent in the COVID-19-related privacy debates, as they are in the broader privacy debate. Against this backdrop, the case for personal data property rights is dubious.


The key question is whether policymakers should make it easier or harder for firms and public bodies to amass large sets of personal data. This requires asking whether personal data is currently under- or over-provided, and whether the additional excludability that would be created by data property rights would offset their detrimental effect on innovation.

Swaths of personal data currently lie untapped. With the proper incentive mechanisms in place, this idle data could be mobilized to develop personalized medicines and to fight the COVID-19 outbreak, among many other valuable uses. By making such data more onerous to acquire, property rights in personal data might stifle the assembly of novel datasets that could be used to build innovative products and services.

On the other hand, when dealing with diffuse and complementary data sources, transaction costs become a real issue and the initial allocation of rights can matter a great deal. In such cases, unlike the genetic-testing kits example, it is not certain that users will be able to bargain with firms, especially where their personal information is exchanged by third parties.

If optimal reallocation is unlikely, should property rights go to the person covered by the data or to the collectors (potentially subject to user opt-outs)? Proponents of data property rights assume the first option is superior. But if the goal is to produce groundbreaking new goods and services, granting rights to data collectors might be a superior solution. Ultimately, this is an empirical question.

As Richard Epstein puts it, the goal is to “minimize the sum of errors that arise from expropriation and undercompensation, where the two are inversely related.” Rather than approach the problem with the preconceived notion that initial rights should go to users, policymakers should ensure that data flows to those economic agents who can best extract information and knowledge from it.

As things stand, there is little to suggest that the trade-offs favor creating data property rights. This is not an argument for requisitioning personal information or preventing parties from transferring data as they see fit, but simply for letting markets function, unfettered by misguided public policies.

[TOTM: The following is part of a digital symposium by TOTM guests and authors on the law, economics, and policy of the antitrust lawsuits against Google. The entire series of posts is available here.]

As one of the few economic theorists in this symposium, I believe my comparative advantage is in that: economic theory. In this post, I want to remind people of the basic economic theories that we have at our disposal, “off the shelf,” to make sense of the U.S. Department of Justice’s lawsuit against Google. I do not mean this to be a proclamation of “what economics has to say about X,” but merely just to help us frame the issue.

In particular, I’m going to focus on the economic concerns of Google paying phone manufacturers (Apple, in particular) to be the default search engine installed on phones. While there is not a large literature on the economic effects of default contracts, there is a large literature on something that I will argue is similar: trade promotions, such as slotting contracts, where a manufacturer pays a retailer for shelf space. Despite all the bells and whistles of the Google case, I will argue that, from an economic point of view, the contracts that Google signed are just trade promotions. No more, no less. And trade promotions are well-established as part of a competitive process that ultimately helps consumers. 

However, it is theoretically possible that such trade promotions hurt customers, so it is theoretically possible that Google’s contracts hurt consumers. Ultimately, the theoretical possibility of anticompetitive behavior that harms consumers does not seem plausible to me in this case.

Default Status

There are two reasons that Google paying Apple to be its default search engine is similar to a trade promotion. First, the deal brings awareness to the product, which nudges certain consumers/users to choose the product when they would not otherwise do so. Second, the deal does not prevent consumers from choosing the other product.

In the case of retail trade promotions, a promotional space given to Coca-Cola makes it marginally easier for consumers to pick Coke, and therefore some consumers will switch from Pepsi to Coke. But it does not reduce any consumer’s choice. The store will still have both items.

This is the same for a default search engine. The marginal searchers, who do not have a strong preference for either search engine, will stick with the default. But anyone can still install a new search engine, install a new browser, etc. It takes a few clicks, just as it takes a few steps to walk down the aisle to get the Pepsi; it is still an available choice.

If we were to stop the analysis there, we could conclude that consumers are worse off (if just a tiny bit). Some customers will have to change the default app. We also need to remember that this contract is part of a more general competitive process. The retail stores are also competing with one another, as are smartphone manufacturers.

Despite popular claims to the contrary, Apple cannot charge anything it wants for its phone. It is competing with Samsung, etc. Therefore, Apple has to pass through some of Google’s payments to customers in order to compete with Samsung. Prices are lower because of this payment. As I phrased it elsewhere, Google is effectively subsidizing the iPhone. This cross-subsidization is a part of the competitive process that ultimately benefits consumers through lower prices.

These contracts lower consumer prices, even if we assume that Apple has market power. Those who recall your Econ 101 know that a monopolist chooses a quantity where the marginal revenue equals marginal cost. With a payment from Google, the marginal cost of producing a phone is lower, therefore Apple will increase the quantity and lower price. This is shown below:

One of the surprising things about markets is that buyers’ and sellers’ incentives can be aligned, even though it seems like they must be adversarial. Companies can indirectly bargain for their consumers. Commenting on Standard Fashion Co. v. Magrane-Houston Co., where a retail store contracted to only carry Standard’s products, Robert Bork (1978, pp. 306–7) summarized this idea as follows:

The store’s decision, made entirely in its own interest, necessarily reflects the balance of competing considerations that determine consumer welfare. Put the matter another way. If no manufacturer used exclusive dealing contracts, and if a local retail monopolist decided unilaterally to carry only Standard’s patterns because the loss in product variety was more than made up in the cost saving, we would recognize that decision was in the consumer interest. We do not want a variety that costs more than it is worth … If Standard finds it worthwhile to purchase exclusivity … the reason is not the barring of entry, but some more sensible goal, such as obtaining the special selling effort of the outlet.

How trade promotions could harm customers

Since Bork’s writing, many theoretical papers have shown exceptions to Bork’s logic. There are times that the retailers’ incentives are not aligned with the customers. And we need to take those possibilities seriously.

The most common way to show the harm of these deals (or more commonly exclusivity deals) is to assume:

  1. There are large, fixed costs so that a firm must acquire a sufficient number of customers in order to enter the market; and
  2. An incumbent can lock in enough customers to prevent the entrant from reaching an efficient size.

Consumers can be locked-in because there is some fixed cost of changing suppliers or because of some coordination problems. If that’s true, customers can be made worse off, on net, because the Google contracts reduce consumer choice.

To understand the logic, let’s simplify the model to just search engines and searchers. Suppose there are two search engines (Google and Bing) and 10 searchers. However, to operate profitably, each search engine needs at least three searchers. If Google can entice eight searchers to use its product, Bing cannot operate profitably, even if Bing provides a better product. This holds even if everyone knows Bing would be a better product. The consumers are stuck in a coordination failure.

We should be skeptical of coordination failure models of inefficient outcomes. The problem with any story of coordination failures is that it is highly sensitive to the exact timing of the model. If Bing can preempt Google and offer customers an even better deal (the new entrant is better by assumption), then the coordination failure does not occur.

To argue that Bing could not execute a similar contract, the most common appeal is that the new entrant does not have the capital to pay upfront for these contracts, since it will only make money from its higher-quality search engine down the road. That makes sense until you remember that we are talking about Microsoft. I’m skeptical that capital is the real constraint. It seems much more likely that Google just has a more popular search engine.

The other problem with coordination failure arguments is that they are almost non-falsifiable. There is no way to tell, in the model, whether Google is used because of a coordination failure or whether it is used because it is a better product. If Google is a better product, then the outcome is efficient. The two outcomes are “observationally equivalent.” Compare this to the standard theory of monopoly, where we can (in principle) establish an inefficiency if the price is greater than marginal cost. While it is difficult to measure marginal cost, it can be done.

There is a general economic idea in these models that we need to pay attention to. If Google takes an action that prevents Bing from reaching efficient size, that may be an externality, sometimes called a network effect, and so that action may hurt consumer welfare.

I’m not sure how seriously to take these network effects. If more searchers allow Bing to make a better product, then literally any action (competitive or not) by Google is an externality. Making a better product that takes away consumers from Bing lowers Bing’s quality. That is, strictly speaking, an externality. Surely, that is not worthy of antitrust scrutiny simply because we find an externality.

And Bing also “takes away” searchers from Google, thus lowering Google’s possible quality. With network effects, bigger is better and it may be efficient to have only one firm. Surely, that’s not an argument we want to put forward as a serious antitrust analysis.

Put more generally, it is not enough to scream “NETWORK EFFECT!” and then have the antitrust authority come in, lawsuits-a-blazing. Well, it shouldn’t be enough.

For me to take the network effect argument seriously from an economic point of view, compared to a legal perspective, I would need to see a real restriction on consumer choice, not just an externality. One needs to argue that:

  1. No competitor can cover their fixed costs to make a reasonable search engine; and
  2. These contracts are what prevent the competing search engines from reaching size.

That’s the challenge I would like to put forward to supporters of the lawsuit. I’m skeptical.

[TOTM: The following is part of a blog series by TOTM guests and authors on the law, economics, and policy of the ongoing COVID-19 pandemic. The entire series of posts is available here.

This post is authored by Dirk Auer, (Senior Fellow of Law & Economics, ICLE); Eric Fruits (Chief Economist, ICLE; Adjunct Professor of Economics, Portland State University); and Kristian Stout (Associate Director, ICLE

The COVID-19 pandemic is changing the way consumers shop and the way businesses sell. These shifts in behavior, designed to “flatten the curve” of infection through social distancing, are happening across many (if not all) markets. But in many cases, it’s impossible to know now whether these new habits are actually achieving the desired effect. 

Take a seemingly silly example from Oregon. The state is one of only two in the U.S. that prohibits self-serve gas. In response to COVID-19, the state fire marshall announced it would temporarily suspend its enforcement of the prohibition. Public opinion fell into two broad groups. Those who want the option to pump their own gas argue that self-serve reduces the interaction between station attendants and consumers, thereby potentially reducing the spread of coronavirus. On the other hand, those who support the prohibition on self-serve have blasted the fire marshall’s announcement, arguing that all those dirty fingers pressing keypads and all those grubby hands on fuel pumps will likely increase the spread of the virus. 

Both groups may be right, but no one yet knows the net effect. We can only speculate. This picture becomes even more complex when considering other, alternative policies. For instance, would it be more effective for the state of Oregon to curtail gas station visits by forcing the closure of stations? Probably not. Would it be more effective to reduce visits through some form of rationing? Maybe. Maybe not. 

Policymakers will certainly struggle to efficiently decide how firms and consumers should minimize the spread of COVID-19. That struggle is an extension of Hayek’s knowledge problem: policymakers don’t have adequate knowledge of alternatives, preferences, and the associated risks. 

A Hayekian approach — relying on bottom-up rather than top-down solutions to the problem — may be the most appropriate solution. Allowing firms to experiment and iteratively find solutions that work for their consumers and employees (potentially adjusting prices and wages in the process) may be the best that policymakers can do.

The case of online retail platforms

One area where these complex tradeoffs are particularly acute is that of online retail. In response to the pandemic, many firms have significantly boosted their online retail capacity. 

These initiatives have been met with a mix of enthusiasm and disapproval. On the one hand online retail enables consumers to purchase “essential” goods with a significantly reduced risk of COVID-19 contamination. It also allows “non-essential” goods to be sold, despite the closure of their brick and mortar stores. At first blush, this seems like a win-win situation for both consumers and retailers of all sizes, with large retailers ramping up their online operations and independent retailers switching to online platforms such as Amazon.

But there is a potential downside. Even contactless deliveries do present some danger, notably for warehouse workers who run the risk of being infected and subsequently passing the virus on to others. This risk is amplified by the fact that many major retailers, including Walmart, Kroger, CVS, and Albertsons, are hiring more warehouse and delivery workers to meet an increase in online orders. 

This has led some to question whether sales of “non-essential” goods (though the term is almost impossible to define) should be halted. The reasoning is that continuing to supply such goods needlessly puts lives at risk and reduces overall efforts to slow the virus.

Once again, these are incredibly complex questions. It is hard to gauge the overall risk of infection that is produced by the online retail industry’s warehousing and distribution infrastructure. In particular, it is not clear how effective social distancing policies, widely imposed within these workplaces, will be at achieving distancing and, in turn, reducing infections. 

More fundamentally, whatever this risk turns out to be, it is almost impossible to weigh it against an appropriate counterfactual. 

Online retail is not the only area where this complex tradeoff arises. An analogous reasoning could, for instance, also be applied to food delivery platforms. Ordering a meal on UberEats does carry some risk, but so does repeated trips to the grocery store. And there are legitimate concerns about the safety of food handlers working in close proximity to each other.  These considerations make it hard for policymakers to strike the appropriate balance. 

The good news: at least some COVID-related risks are being internalized

But there is also some good news. Firms, consumers and employees all have some incentive to mitigate these risks. 

Consumers want to purchase goods without getting contaminated; employees want to work in safe environments; and firms need to attract both consumers and employees, while minimizing potential liability. These (partially) aligned incentives will almost certainly cause these economic agents to take at least some steps that mitigate the spread of COVID-19. This might notably explain why many firms imposed social distancing measures well before governments started to take notice (here, here, and here). 

For example, one first-order effect of COVID-19 is that it has become more expensive for firms to hire warehouse workers. Not only have firms moved up along the supply curve (by hiring more workers), but the curve itself has likely shifted upwards reflecting the increased opportunity cost of warehouse work. Predictably, this has resulted in higher wages for workers. For example, Amazon and Walmart recently increased the wages they were paying warehouse workers, as have brick and mortar retailers, such as Kroger, who have implemented similar policies.

Along similar lines, firms and employees will predictably bargain — through various channels — over the appropriate level of protection for those workers who must continue to work in-person.

For example, some companies have found ways to reduce risk while continuing operations:

  • CNBC reports Tyson Foods is using walk-through infrared body temperature scanners to check employees’ temperatures as they enter three of the company’s meat processing plants. Other companies planning to use scanners include Goldman Sachs, UPS, Ford, and Carnival Cruise Lines.
  • Kroger’s Fred Meyer chain of supermarkets is limiting the number of customers in each of its stores to half the occupancy allowed under international building codes. Kroger will use infrared sensors and predictive analytics to monitor the new capacity limits. The company already uses the technology to estimate how many checkout lanes are needed at any given time.
  • Trader Joe’s limits occupancy in its store. Customers waiting to enter are asked to stand six feet apart using marked off Trader Joe’s logos on the sidewalk. Shopping carts are separated into groups of “sanitized” and “to be cleaned.” Each cart is thoroughly sprayed with disinfectant and wiped down with a clean cloth.

In other cases, bargaining over the right level of risk-mitigation has been pursued through more coercive channels, such as litigation and lobbying:

  • A recently filed lawsuit alleges that managers at an Illinois Walmart store failed to alert workers after several employees began showing symptoms of COVID-19. The suit claims Walmart “had a duty to exercise reasonable care in keeping the store in a safe and healthy environment and, in particular, to protect employees, customers and other individuals within the store from contracting COVID-19 when it knew or should have known that individuals at the store were at a very high risk of infection and exposure.” 
  • According to CNBC, a group of legislators, unions and Amazon employees in New York wrote a letter to CEO Jeff Bezos calling on him to enact greater protections for warehouse employees who continue to work during the coronavirus outbreak. The Financial Times reports worker protests at Amazon warehouse in the US, France, and Italy. Worker protests have been reported at a Barnes & Noble warehouse. Several McDonald’s locations have been hit with strikes.
  • In many cases, worker concerns about health and safety have been conflated with long-simmering issues of unionization, minimum wage, flexible scheduling, and paid time-off. For example, several McDonald’s strikes were reported to have been organized by “Fight for $15.”

Sometimes, there is simply no mutually-advantageous solution. And businesses are thus left with no other option than temporarily suspending their activities: 

  • For instance, McDonalds and Burger King have spontaneously closed their restaurants — including drive-thru and deliveries — in many European countries (here and here).
  • In Portland, Oregon, ChefStable a restaurant group behind some of the city’s best-known restaurants, closed all 20 of its bars and restaurants for at least four weeks. In what he called a “crisis of conscience,” owner Kurt Huffman concluded it would be impossible to maintain safe social distancing for customers and staff.

This is certainly not to say that all is perfect. Employers, employees and consumers may have very strong disagreements about what constitutes the appropriate level of risk mitigation.

Moreover, the questions of balancing worker health and safety with that of consumers become all the more complex when we recognize that consumers and businesses are operating in a dynamic environment, making sometimes fundamental changes to reduce risk at many levels of the supply chain.

Likewise, not all businesses will be able to implement measures that mitigate the risk of COVID-19. For instance, “Big Business” might be in a better position to reduce risks to its workforce than smaller businesses. 

Larger firms tend to have the resources and economies of scale to make capital investments in temperature scanners or sensors. They have larger workforces where employees can, say, shift from stocking shelves to sanitizing shopping carts. Several large employers, including Amazon, Kroger, and CVS have offered higher wages to employees who are more likely to be exposed to the coronavirus. Smaller firms are less likely to have the resources to offer such wage premiums.

For example, Amazon recently announced that it would implement mandatory temperature checks, that it would provide employees with protective equipment, and that it would increase the frequency and intensity of cleaning for all its sites. And, as already mentioned above, Tyson Foods announced that they would install temperature scanners at a number of sites. It is not clear whether smaller businesses are in a position to implement similar measures. 

That’s not to say that small businesses can’t adjust. It’s just more difficult. For example, a small paint-your-own ceramics shop, Mimosa Studios, had to stop offering painting parties because of government mandated social distancing. One way it’s mitigating the loss of business is with a paint-at-home package. Customers place an order online, and the studio delivers the ceramic piece, paints, and loaner brushes. When the customer is finished painting, Mimosa picks up the piece, fires it, and delivers the finished product. The approach doesn’t solve the problem, but it helps mitigate the losses.


In all likelihood, we can’t actually avoid all bad outcomes. There is, of course, some risk associated with even well-resourced large businesses continuing to operate, even though some of them play a crucial role in coronavirus-related lockdowns. 

Currently, market actors are working within the broad outlines of lockdowns deemed necessary by policymakers. Given the intensely complicated risk calculation necessary to determine if any given individual truly needs an “essential” (or even a “nonessential”) good or service, the best thing that lawmakers can do for now is let properly motivated private actors continue to seek optimal outcomes together within the imposed constraints. 

So far, most individuals and the firms serving them are at least partially internalizing Covid-related risks. The right approach for lawmakers would be to watch this process and determine where it breaks down. Measures targeted to fix those breaches will almost inevitably outperform interventionist planning to determine exactly what is essential, what is nonessential, and who should be allowed to serve consumers in their time of need.