NFT stands for “non-fungible token.” There is real money involved here: hundreds of millions of of NFTs are bought and sold each week. Back in March, an NFT for a work of art called “Everydays: The First 5000 Days” sold through the Christie’s auction house in New York for $69 million. Notice that the buyer did not receive a canvas-and-paint piece of art. Nor did the buyer get exclusive ownership over the digital image: you can go to the image at the link above, copy it, and put it on your own computer. So what is this “token” that was purchased and what does the “non-fungible” part of NFT mean? Steve Kaczynski and Scott Duke Kominers offer a primer in “How NFTs Create Value” (Harvard Business Review, November 10, 2021). They write:
As the name “non-fungible token” suggests, each NFT is a unique, one-of-a-kind digital item. They’re stored on public-facing digital ledgers called blockchains, which means it’s possible to prove who owns a given NFT at any moment in time and trace the history of prior ownership. Moreover, it’s easy to transfer NFTs from one person to another — just as a bank might move money across accounts — and it’s very hard to counterfeit them. Because NFT ownership is easy to certify and transfer, we can use them to create markets in a variety of different goods.
But NFTs don’t just provide a kind of digital “deed.” Because blockchains are programmable, it’s possible to endow NFTs with features that enable them to expand their purpose over time, or even to provide direct utility to their holders. In other words, NFTs can do things — or let their owners do things — in both digital spaces and the physical world.
In this sense, NFTs can function like membership cards or tickets, providing access to events, exclusive merchandise, and special discounts — as well as serving as digital keys to online spaces where holders can engage with each other. Moreover, because the blockchain is public, it’s even possible to send additional products directly to anyone who owns a given token. All of this gives NFT holders value over and above simple ownership — and provides creators with a vector to build a highly engaged community around their brands.
It’s not uncommon to see creators organize in-person meetups for their NFT holders, as many did at the recent NFT NYC conference. In other cases, having a specific NFT in your online wallet might be necessary in order to gain access to an online game, chat room, or merchandise store. … Thus owning an NFT effectively makes you an investor, a member of a club, a brand shareholder, and a participant in a loyalty program all at once. At the same time, NFTs’ programmability supports new business and profit models — for example, NFTs have enabled a new type of royaltycontract, whereby each time a work is resold, a share of the transaction goes back to the original creator. …
NFTs enable new markets by allowing people to create and build upon new forms of ownership. These projects succeed by leveraging a core dynamic of crypto: A token’s worth comes from users’ shared agreement — and this means that the community one builds around NFTs quite literally creates those NFTs’ underlying value. And the more these communities increase engagement and become part of people’s personal identities, the more that value is reinforced. Newer applications will take greater advantage of online-offline connections, and introduce increasingly complex token designs.
I confess that I’m not at all sure how membership in an online community made it worthwhile for someone to spend $69 million for a nonfungible token on “Everydays: The First 5000 Days.” But a lot of money has been made by getting people to join up with certain online communities, through social media, gaming, and direct purchases. NFTs seem to offer new possibilities for organizing such groups.
Even as other academic fields have made considerable progress to equality in the numbers of female and male professors, economics has lagged behind. For an overview, a useful starting point is the three-paper symposium in the Winter 2019 issue Journal of Economic Perspectives:
A common approach in this literature is to think about the “pipeline”–that is, what share of economics majors are women, what share of PhD students in economics are women, and then what share of assistant, associate, and full professors of economics are women. Donna Ginther has written “Gender, Race, and Academic Career Outcomes — Does Economics Mirror Other Disciplines?” which provides an overview of research in the area in the October 2021 NBER Reporter. Here’s a figure that focuses on one stage of the pipeline: promotion from assistant to associate professor.
Ginther writes (footnotes omitted):
With my long-time collaborator Shulamit Kahn, who has played a key role in this work, I have examined gender differences in career outcomes for economists and for other academic fields. We found that after controlling for research publications, women were significantly less likely to be promoted to tenure in economics. Our most recent study used Academic Analytics data to update the analysis of the economics profession compared with other science and social science fields. Figure 1 shows survival curves by gender and compares economics to the fields of mathematics and statistics, political science, biomedical science, physical science, and engineering. The only significant gender difference in promotion to associate professor is in economics, where women were 15 percent less likely to be promoted after controlling for publications, citations, and research grants.
Some of the previous studies were limited to the best research universities. We therefore separately estimated the hazard analysis for two samples: those who entered academia into very high research activity institutions and those who did not. … The majority of the observations were in the very high research activity universities (which is primarily informative about the clients interested in Academic Analytics services). We were frankly stunned by the results. The gender tenure gap was small and insignificant in very high research activity institutions. However, in less research-intensive universities, it was huge, with women’s rate of receiving tenure (with all controls) 46 percent lower than men’s (p = 0.055). … [T]he huge point estimate of the tenure penalty at these less research-based universities and colleges is remarkable.
Ginther and Kahn frankly admit that they do not have an obvious explanation for why the gender tenure gap in economics is so much larger at less research-intensive universities. But it seems a topic worth exploring further.
I’ll just add that my own sense is that the issues with attracting women to careers in economics may start early. Since about 2005, women have been about 30-35% of the economics majors, the economics PhD students, and the new assistant professors. While I’m sure that some useful steps might be taken to bolster the pipeline to becoming a tenured professor at these stages, it will be challenging to get to gender equity in the tenured professoriate if only one-third of undergraduate economics majors are women. A few years ago, when I looked at at who takes AP microeconomics and macroeconomics exams, I found that the number of males who get a 4 or 5 on these examples was much higher than the number of females. Thus, it seems plausible that even before college students reach campus, there are many more men than women who considering a college major in economics.
If you look at the US states by income level and mortality rates, you find a reasonably strong negative correlation: that is, states with higher income tend to have lower mortality. But here’s the puzzle. If you go back a few decades to 1980 or 1968 and look at the same pattern, you find only a much weaker correlation: that is, much less tendency for states with higher income to have lower mortality. Why?
Benjamin K. Couillard, Christopher L. Foote, Kavish Gandhi, Ellen Meara, and Jonathan Skinner tackle this question among others in “Rising Geographic Disparities in US Mortality” (Journal of Economic Perspectives, Fall 2021, 35:4, pp. 123-46). (Full disclosure: I’m the Managing Editor of this journal, and have been since 1986, so I am perhaps predisposed to find the articles of interest.) Here’s a figure from their paper. The points represent US states. As you can see, if one looks at the data for 1968 or 1980 (the top two panels), the negative correlation between income and mortality rates is relatively weak. However, if one looks at the same correlation for 2019 (bottom left panel), the negative correlation is much stronger.
The bottom right correlation is usefully thought-provoking. It looks at the correlation between state-level income in 1968 and state-level mortality in 2019–which looks a lot like the figure using only 2019 data. To put this another way, state-level income data from 1968 has less correlation with mortality rates in 1968 than it does with mortality rates in 2019. This seems peculiar.
What seems to be happening inside this data is that the ranking of states by per-capita income hasn’t changed all that much since 1968 or 1980: states that tended to be better-off or worse-off then are still better-off or worse-off now. However, mortality rates across states have changed substantially in the last few decades, and in a way that causes the mortality rates to line up more with state-level measures of income. As the authors write: “Instead, mortality changes have been most favorable in those states that have tended to have high relative levels of income over the past three decades.”
Why might health have improved more in the higher-income states? One possible explanation is related to what are sometimes called “deaths of despair,” which are deaths due to drug overdoses, alcohol poisoning, and suicide. The difficulty with this explanation is that there aren’t enough of these deaths to drive the changes noted above. When one looks at major causes of death, it turns out that deaths from malignant neoplasms, diseases of the heart, cerebrovascular diseases, and lower respiratory diseases all have a greater (negative) correlation with income at the state-level than they did a few decades ago.
Couillard, Foote, Gandhi, Meara, and Skinner suggest an alternative explanation rooted in what they call a “portmanteau of state-level factors.” This has two parts. One part is that if one goes back a half-century and more, one can make a case that living in lower-income states had some health benefits. Studies from the 1930s suggest that when people migrated from lower-income rural states to higher-income urban areas, their health often got worse as they were exposed to the big-city evils of alcohol, tobacco, and pollution. One quirky fact comes from the state of “Kansas, which imposed prohibition in 1880, not ending it until 1948. Perhaps not coincidentally, in 1959, Kansas was tied in first place for the state with the highest life expectancy.”
The other part of the explanation is that in the late 1980s and early 1990s, high-income states were much more likely to enact a portfolio of health-related policies including higher taxes on alcohol and tobacco and expansions of Medicaid coverage focused on pregnant women. These specific policies were part of a broader emphasis on public health policies in the higher-income states that manifested itself in different ways in different places. A few decades later, the states that enacted such policies are seeing the payoff in improved mortality rates.
States are sometimes called the “laboratories of democracy.” One reason for having the federal government set some minimum standards, and then letting states experiment, is to get some evidence on what works and what doesn’t. In that spirit, the authors write: “Although states with high income have shown the way, states with lower income capacity are not inexorably constrained to rates of midlife mortality that rank among the worst in developed countries.”
Everyone knows that lots of people have ended up working from home, either part-time or full-time, since the start of the pandemic. But I’m not sure many of us have appreciated how extraordinary that shift has been. In effect, an enormous amount of what economists would classify as “residential capital” was converted to commercial real estate almost overnight: that is, people used their places of residence along with capital that had often been installed at their place of residence mostly for other purposes (like entertainment) to do their work.
The size of the shift is remarkable. Janice C. Eberly, Jonathan Haskel and Paul Mizen discuss “Potential Capital: Working From Home, and Economic Resilience” (NBER Working Paper 29431, October 2021, subscription needed). They compare the drop in economic output from the workplace in the first two quarters of 2020 to the overall drop in economic output: in the US economy, for example, they find that output in the workplace fell by about 17%, but total economic output actually fell about 9%. Work done outside the conventional workplace made up the difference.
This built-in resilience of the economy may now seem pretty obvious, but it wasn’t obvious (at least to me) before the pandemic hit. The magnitudes here are enormous. According the US Bureau of Economic Analysis, the value of residential real estate in 2020 was almost $25 trillion. Privately owned nonresidential structures were worth almost $16 trillion, while the equipment in those structures was another $7 trillion. In short, trillions of dollars of residential capital replaced trillions of dollars of nonresidential capital in a very short time. The transition was far from seamless or painless, of course, but the fact that it happened at all is worth a gasp.
The Eberly, Haskel and Mizen paper is academic research, so if you are not already initiated into the world of growth accounting frameworks and decompositions, it won’t be an easy read. But their broad arguments about the “potential capital” embedded in residences and the resilience of economies that can use that capital make me think about the shifting nature of work and jobs.
The nature of work for most people, at least going back to the industrial revolution, is that (as the authors write) “the point of going to the workplace is that workers have capital with which to work.” After all, that’s why manufacturing workers headed off to assembly lines. It’s also why so many people in service industries like finance and real estate needed to go to the office: it’s where the capital was to carry out their jobs. But now, when we talk about why it might be important or useful for workers to return to in-person work, it’s become clear that for many modern jobs in the services-and-information economy, going to the workplace to use the capital at the workplace is less important, or even not important at all. Instead, for a number of workers, the arguments for going to the workplace are more about communication between workers, training new workers, monitoring how much work is getting done, and the ways in which in-person communication may solve problems or spur innovation.
An obvious question is whether the shift to work from home will continue. It (now) seems obvious that working from home will remain higher after the pandemic than before, but how much higher seems uncertain to me. After all, we are only a very short time into this social and economic experiment. One can imagine a future evolution of the economy in which firms with mostly at-home workers compete with firms that have mostly in-the-office workers. It may turn out that the two types of firms have different strengths and weaknesses. For example, one possibility is that in-the-office firms are better at hiring, training, and certain kinds of innovation, but at-home firms offer greater flexibility and specialized skills. It may also be that workers have varying preferences over the context in which they would like to work. Young adult singles might like an in-person work experience, while middle-aged marrieds might see greater advantages in working from home. During the pandemic, many workers were able to do their basic tasks from home, but just because a working arrangement functions OK as a forced expedient under the stress of a pandemic doesn’t mean it’s also a long-run answer.
Here, I’ll focus on the economic side of the issues and set aside the direct costs and reduced quality of life for the person with dementia, although the personal side affects my own extended family, along with so many others. The core of the economic problem is that people with dementia need care. The NAS report notes (again, citations omitted):
The primary economic costs of dementia to persons living with dementia and their families are (1) medical and long-term care costs, and (2) the value of unpaid caregiving provided by family (most commonly) and friends. Most estimates of these costs in the literature draw on such nationally representative data sources as the Health and Retirement Study, the Medicare Current Beneficiary Survey, and Medicare claims data. An estimate of annual per-person costs for 2019, which includes health care and the value of unpaid care provided to persons with Alzheimer’s disease, is approximately $81,000 ($31,000 is the value of the unpaid care). This estimate is about four times higher than the costs of the same care provided to similarly aged persons without the disease. …
Residential care is very expensive. Estimates of the typical costs of long-term care range from $52,624 per year for a home health aide to $90,000 for a semiprivate room in a nursing home and up to $102,000 for a private room. Medicaid, which covers long-term care for low-income individuals and those who become poor as a result of paying for health care and long-term care, is the largest public payer for long-term care, covering 62 percent of nursing home residents, and one-quarter of adults with dementia who live in the community are covered by Medicaid over the course of a year.
When aggregated to the U.S. population, the costs are estimated to have exceeded $500 billion in 2019 and are projected to increase to about $1.5 trillion by 2050. Unaccounted for in these estimates are other economic costs, such as the impact on caregivers’ wages and future employability; when included, these costs increase estimates of unpaid caregiver costs by as much as 20 percent . Moreover, these costs may be underestimated because the physical and mental strain associated with unpaid caregiving likely translates to other costs, such as for caregivers’ own health care. … Other costs unaccounted for include financial harm to persons living with dementia and their families. Cognitive impairment may lead to financial decision-making errors, including payment delinquency and susceptibility to financial exploitation, starting years before diagnosis. Financial harm to individuals living with dementia may also have long-term implications for the surviving spouse.
What might be done? One can try to think about ways of providing the needed services less expensively, but without compromising quality. One can think about steps that might reduce the incidence of dementia. One can hope for a cure. All of these seem worth trying; none at present seems especially promising.
The idea of less expensive and higher quality care is of course enticing, and perhaps it can be delivered by some combination of facilities designed for dementia patients, which would try to free up the time of human staff to provide care by handing off other tasks like cleaning and cooking to lower-cost automation. But I’m not aware of any big success stories along these lines.
There is strong evidence that being in better health overall reduces one’s chance of dementia. As the report notes: “For example, robust evidence suggests that people who take such common-sense measures as eating a healthy diet, exercising regularly, maintaining a healthy weight, and reducing cardiovascular risk have a lower risk of dementia.” Of course, a step-increase in healthy behaviors would have many other benefits as well, but I’m unaware of any big success stories that would dramatically improve health in this way beyond current levels.
Will technology ride to the rescue? Maybe. The FDA has just approved aducanumab, the first drug for treating Alzheimer’s disease. With wider use, we’ll see how well it works, and perhaps develop something beter. But new technologies come at a cost, too. The NAS report describes the issue this way:
First, more than 130 innovative treatments for Alzheimer’s disease and related dementias are being investigated in clinical trials, and some may turn out to slow or halt disease progression and reduce costs. A simulation study found that a hypothetical treatment innovation that delayed the onset of Alzheimer’s disease by 5 years would reduce the population with the disease by 41 percent in 2050, which would reduce annual costs by $640 billion. However, novel treatments, which would likely have high prices, could exacerbate the overall economic impact of the disease. …
The recent approval by the U.S. Food and Drug Administration (FDA) of the first new drug in decades that is intended to treat Alzheimer’s disease, aducanumab, is likely to have substantial impact on the cost picture. … The manufacturer of aducanumab initially estimated that 1 to 2 million persons would currently be eligible to receive the medication, although that number may change depending on eligibility guidelines. Using the manufacturer’s estimated cost of $56,000 per patient per year, the total cost just for the drug could range from $56 billion to as much as $112 billion. Whatever number of people ultimately receive the drug, such estimates do not include the costs of infusion, monitoring and treating adverse effects, and additional pre-administration testing. The magnitude of ancillary costs is not yet established, but observers have suggested that they could add tens of thousands in costs per eligible patient. To put the cost of the drug alone into perspective, the total 2021 National Institutes of Health budget is $43 billion and the total 2021 Medicare budget is $688 billion.
It’s past time for an Operation Warp Speed aimed at dementia, which would guarantee that the government would purchase a certain quantity of the drug in exchange for meeting certain health and cost-per-patient targets. But barring salvation via technology, the question of how society will treat its dementia patients–especially those who do not have family caregivers or financial resources–is looming over our health care policy debates.
I have been the Managing Editor of the Journal of Economic Perspectives since the first issue in Summer 1987. The JEP is published by the American Economic Association, which decided about a decade ago–to my delight–that the journal would be freely available on-line, from the current issue all the way back to the first issue. You can download individual articles or entire issues, and it is available in various e-reader formats, too. Here, I’ll start with the Table of Contents for the just-released Fall 2021 issue, which in the Taylor household is known as issue #138. Below that are abstracts and direct links for all of the papers. I will probably blog more specifically about some of the papers in the few weeks, as well.
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Symposium on Criminal Justice
“The Economics of Policing and Public Safety,” by Emily Owens and Bocar Ba
The efficiency of any police action depends on the relative magnitude of its crime-reducing benefits and legitimacy costs. Policing strategies that are socially efficient at the city level may be harmful at the local level, because the distribution of direct costs and benefits of police actions that reduce victimization is not the same as the distribution of indirect benefits of feeling safe. In the United States, the local misallocation of police resources is disproportionately borne by Black and Hispanic individuals. Despite the complexity of this particular problem, the incentives facing both police departments and police officers tend to be structured as if the goals of policing were simple—to reduce crime by as much as possible. Formal data collection on the crime-reducing benefits of policing, and not the legitimacy costs, produces further incentives to provide more engagement than may be efficient in any specific encounter, at both the officer and departmental level. There is currently little evidence as to what screening, training, or monitoring strategies are most effective at encouraging individual officers to balance the crime. reducing benefits and legitimacy costs of their actions.
“Next-Generation Policing Research: Three Propositions,” by Monica C. Bell
The Black Lives Matter movement has operated alongside a growing recognition among social scientists that policing research has been limited in its scope and outmoded in its assumptions about the nature of public safety. This essay argues that social science research on policing should reorient its conception of the field of policing, along with how the study of crime rates and police departments fit into this field. New public safety research should broaden its outcomes of interest, its objects of inquiry, and its engagement with structural racism. In this way, next-generation research on policing and public safety can respond to the deficiencies of the past and remain relevant as debates over transforming American policing continue.
“The US Pretrial System: Balancing Individual Rights and Public Interests,” by Will Dobbie and Crystal S. Yang
In this article, we review a growing empirical literature on the effectiveness and fairness of the US pretrial system and discuss its policy implications. Despite the importance of this stage of the criminal legal process, researchers have only recently begun to explore how the pretrial system balances individual rights and public interests. We describe the empirical challenges that have prevented progress in this area and how recent work has made use of new data sources and quasi-experimental approaches to credibly estimate both the individual harms (such as loss of employment or government assistance) and public benefits (such as preventing non-appearance at court and new crimes) of cash bail and pretrial detention. These new data and approaches show that the current pretrial system imposes substantial short- and long-term economic harms on detained defendants in terms of lost earnings and government assistance, while providing little in the way of decreased criminal activity for the public interest. Non-appearances at court do significantly decrease for detained defendants, but the magnitudes cannot justify the economic harms to individuals observed in the data. A second set of studies shows that that the costs of cash bail and pretrial detention are disproportionately borne by Black and Hispanic individuals, giving rise to large and unfair racial differences in cash bail and detention that cannot be explained by underlying differences in pretrial misconduct risk. We then turn to policy implications and describe areas of future work that would enable a deeper understanding of what drives these undesirable outcomes.
“Fragile Algorithms and Fallible Decision-Makers: Lessons from the Justice System,” by Jens Ludwig and Sendhil Mullainathan
Algorithms (in some form) are already widely used in the criminal justice system. We draw lessons from this experience for what is to come for the rest of society as machine learning diffuses. We find economists and other social scientists have a key role to play in shaping the impact of algorithms, in part through improving the tools used to build them.
“Inside the Box: Safety, Health, and Isolation in Prison,” by Bruce Western
A large social science research literature examines the effects of prisons on crime and socioeconomic inequality, but the penal institution itself is often a black box overlooked in the analysis of its effects. This paper examines prisons and their role in rehabilitative programs and as venues for violence, health and healthcare, and extreme isolation through solitary confinement. Research shows that incarcerated people are participating less today than in the 1980s in prison programs, and they face high risks of violence, disease, and isolation. Prison conditions suggest the mechanisms that impair adjustment to community life after release provide a more complete account of the costs of incarceration and indicate the performance of prisons as moral institutions that bear a responsibility for humane and decent treatment.
“Rising Geographic Disparities in US Mortality,” by Benjamin K. Couillard, Christopher L. Foote, Kavish Gandhi, Ellen Meara and Jonathan Skinner
The twenty-first century has been a period of rising inequality in both income and health. In this paper, we find that geographic inequality in mortality for midlife Americans increased by about 70 percent between 1992 and 2016. This was not simply because states like New York or California benefited from having a high fraction of college-educated residents who enjoyed the largest health gains during the last several decades. Nor was higher dispersion in mortality caused entirely by the increasing importance of “deaths of despair,” or by rising spatial income inequality during the same period. Instead, over time, state-level mortality has become increasingly correlated with state-level income; in 1992, income explained only 3 percent of mortality inequality, but by 2016, state-level income explained 58 percent. These mortality patterns are consistent with the view that high-income states in 1992 were better able to enact public health strategies and adopt behaviors that, over the next quarter-century, resulted in pronounced relative declines in mortality. The substantial longevity gains in high-income states led to greater cross-state inequality in mortality.
“The Causal Effects of Place on Health and Longevity,” by Tatyana Deryugina and David Molitor
Life expectancy varies substantially across local regions within a country, raising conjectures that place of residence affects health. However, population sorting and other confounders make it difficult to disentangle the effects of place on health from other geographic differences in life expectancy. Recent studies have overcome such challenges to demonstrate that place of residence substantially influences health and mortality. Whether policies that encourage people to move to places that are better for their health or that improve areas that are detrimental to health are desirable depends on the mechanisms behind place effects, yet these mechanisms remain poorly understood.
“When Innovation Goes Wrong: Technological Regress and the Opioid Epidemic,” by David M. Cutler and Edward L. Glaeser
The fourfold increase in opioid deaths between 2000 and 2017 rivals even the COVID-19 pandemic as a health crisis for America. Why did it happen? Measures of demand for pain relief—physical pain and despair—are high and in many cases rising, but their increase was nowhere near as large as the increase in deaths. The primary shift is in supply, primarily of new forms of allegedly safer narcotics. These new pain relievers flowed in greater volume to areas with more physical pain and mental health impairment, but since their apparent safety was an illusion, opioid deaths followed. By the end of the 2000s, restrictions on legal opioids led to further supply-side innovations, which created the burgeoning illegal market that accounts for the bulk of opioid deaths today. Because opioid use is easier to start than end, America’s opioid epidemic is likely to persist for some time.
“Neighborhoods Matter: Assessing the Evidence for Place Effects,” by Eric Chyn and Lawrence F. Katz
How does one’s place of residence affect individual behavior and long-run outcomes? Understanding neighborhood and place effects has been a leading question for social scientists during the past half-century. Recent empirical studies using experimental and quasi-experimental research designs have generated new insights on the importance of residential neighborhoods in childhood and adulthood. This paper summarizes the recent neighborhood effects literature and interprets the findings. Childhood neighborhoods affect long-run economic and educational outcomes in a manner consistent with exposure models of neighborhood effects. For adults, neighborhood environments matter for their health and well-being but have more ambiguous impacts on labor market outcomes. We discuss the evidence on the mechanisms behind the observed patterns and conclude by highlighting directions for future research.
“College Majors, Occupations, and the Gender Wage Gap,” by Carolyn M. Sloane, Erik G. Hurst and Dan A. Black
The paper assesses gender differences in pre-labor market specialization among the college-educated and highlights how those differences have evolved over time. Women choose majors with lower potential earnings (based on male wages associated with those majors) and subsequently sort into occupations with lower potential earnings given their major choice. These differences have narrowed over time, but recent cohorts of women still choose majors and occupations with lower potential earnings. Differences in undergraduate major choice explain a substantive portion of gender wage gaps for the college-educated above and beyond simply controlling for occupation. Collectively, our results highlight the importance of understanding gender differences in the mapping between college major and occupational sorting when studying the evolution of gender differences in labor market outcomes over time.
The argument over taxing corporate profits may sound familiar, because claims that corporations aren’t paying their fair share of taxes have been going on for decades. But the circumstances of large corporations have changed considerably in at least two ways: 1) they have become much more likely to cross national boundaries in their inputs, production, customers, and owners; and 2) they depend more on intellectual property, which means that profits are coming from something that isn’t physical in nature.
Fifty years ago, the top five companies by market capitalization were IBM, General Motors, AT&T, Standard Oil of New Jersey (Esso, the predecessor of today’s ExxonMobil), and Eastman Kodak. … These were companies that “made things” in identifiable locations, to a large extent in the United States. If we shift to today, we see another five familiar names, all giant companies: Apple, Microsoft, Amazon, Alphabet (Google’s parent), and Facebook. These companies are worldwide multinationals, relying very heavily on the use of intellectual property in the goods and services they provide …
In the last half century, the share of intellectual property measured in US nonfinancial corporate assets more than doubled, according to the Fed’s Financial Accounts of the United States. That’s probably a conservative estimate, because the measurement of intellectual property is a fairly narrow one here. The share of before-tax US corporate profits coming from overseas operations nearly quintupled, according to data from the Bureau of Economic Analysis. US companies have become much more multinational in character, not just selling things abroad, but making them abroad as well. And the share of cross-border equity ownership has steadily increased, to the point that foreign individuals and companies account for a significant fraction of US companies’ share ownership.
When production, customers, and owners are distributed around the world, when the “product” can be a service supplied digitally, and when the ultimate source of profit is closely tied to intellectual property, taxing big global firms becomes complex. The idea of corporate profits itself is far from a crystal-clear idea in a world of high-powered accountants and finance, operating against a backdrop of differing national tax codes. Every country would prefer to draw up the rules so that it attracts companies that it can tax. Companies that are operating across national borders in multiple ways have the ability to shift between countries, and to claim that profits are actually being earned in one place rather than another. What might be done. Auerbach discussed the possibilities, which I summarize here.
Make corporate taxation rules that seek to block firms from avoiding taxes. This has been the main strategy for some years, and the whole point of the earlier discussion about the changing nature of large firms is that it can be hard to make this work in the modern economy.
“Patent boxes” are a way of encouraging firms with intellectual property to claim residence in your country, so that your country can tax the company. But to attract the company, the “patent box” approach often promises lower corporate taxes. As Auerbach writes: “One problem with patent boxes is that, in a sense, they deal with tax competition by simply giving up.”
Tax global companies based on their users, not their profits. For example, European countries where a company like Google or Facebook has essentially zero employees might seek to tax these companies because people in the country use services from these firms. The idea is that some of the profits of the company trace back to users from a certain country, so the country should be able to tax the firm’s profits. But of course, drawing a straight line from users to profits for these companies is an enormous oversimplification. Their profits are based on many factors, including advertising revenues, operating costs, intellectual property, and other factors. The US is typically not pleased if foreign countries try to tax US-based firms.
Use a “destination-based tax,” which means taxing firms in proportion to where their sales are. This approach requires some detailed analysis, and Auerbach runs through variations of a destination-based tax like the Residual Profit Allocation by Income (RPAI) and a Destination-Based Cash Flow Tax (DBCFT). Given international cooperation, this approach seems broadly workable. But notice that it is a fundamental shift from the idea of taxing corporate profits to an idea of taxing corporate sales: that is, two firms with equal sales would pay equal taxes, even if one earned positive profits and one lost money. When people argue over whether corporations pay their fair share, I’m not sure if this approach accords with their intuition.
Scramble all of these approaches together, don’t worry too much about the contradictions, and do a bit of each. As Auerbach points out, this was essentially the approach of the 2017 Tax Cuts and Jobs Act.
The current international negotiations over global corporate taxation basically have two “pillars,” as they are often called. One “pillar” would take a certain share of the profits of big digital services companies and let other countries split up that tax revenue. Given that these big companies are mostly American firms, the rest of the world likes this idea, but it’s not clear that the US Senate will approve. The other “pillar” would be a minimum 15% tax rate on profits of large companies. The problem with this approach is that it essentially ignores the underlying issues. As Auerbach writes:
But beyond the immediate hurdles facing adoption, there is also a more fundamental, longer-term challenge arising from the attempt to preserve a tax system based on concepts that don’t really work anymore, that are ill-defined and endogenous: corporate residence and the location of production and profits (something that tax authorities have taken to referring to as the location of value creation). Because it relies on these ill-defined concepts, the two-pillar system is not going to be sustainable unless countries adopt and adhere to similar rules that lessen incentives for companies to shift production, profits, and residence.
Auerbach is a supporter of a destination-based tax approach, and thinks that economic and political forces will tend to push in that direction over time. Maybe he’s right. But an alternative possibility is that the nature of corporations keeps evolving, the importance of intangibles like intellectual property keeps growing, and the long-term argument over what it means for corporations to pay their fair share keeps sounding much the same, even though the underlying conditions keep changing.
One of the complaints fairly levelled against President Donald Trump was that, in a pure numerical sense and setting policy disagreements aside, his administration did a poor job of appointments. There are about 4,000 jobs in the federal government that require presidential appointment, with about 1,200 of those jobs requiring Senate confirmation. The Trump administration was slow to fill these jobs. For example, the Economist magazine noticed the slow pace of Trump administration appointments back in July 2017 with an article titled, “Donald Trump’s missing government: Presidential lethargy, not Democratic obstinacy, is to blame.” By the end of the Trump administration, of the roughly 750 appointments requiring Senate confirmation, about one-third had no appointments at all.
How is the Biden administration doing? The nonprofit Partnership for Public Service together with the Washington Post maintain an ongoing tracker that keeps track of appointments to about 800 of the more prominent positions that need Senate confirmation. Here’s their figure showing confirmed appointments. So far, the Biden administration is quite similar to the Trump administration, both lagging well behind the two preceding administrations.
I’ll confess that this total number of required appointees seems crazy to me. My suspicion is that bill after bill specified a need for certain positions to be presidentially appointed, without anyone really keeping track of the general total. It would probably be sensible to cut back the number substantially. The only way this total number of appointments can possibly work is to have a president with an exceptionally deep bench of advisers, who in turn can draw on deep networks of their own. Thus, one might be unsurprised that political novice President Trump lacked the network to find a large number of nominees, while expecting that nominees would be easier to find for a Biden administration. But it hasn’t worked that way.
In the early 1980s during the Reagan administration, it was common to hear the slogan “personnel is policy.” Conversely, a lack of personnel will inhibit policy. When problems come along–from pandemics to trade, from supply chain shutdowns to foreign policy–and there is no political appointee in place, then the regular government workers in that department are left to muddle through as best they can, without a lot of direction and with strong incentives not to do anything innovative or creative that might either attract blame or end up contradicting whatever official policy line ultimately emerges A lack of personnel is a kind of policy, too.
A vivid illustration of America’s supply chain woes are the photographs of container ships lined up outside the ports of Los Angeles and Long Beach, waiting to unload. But this outcome shouldn’t have been a major surprise. The World Bank and IHS Markit published The Container Port Performance Index 2020 back in May 2021 (available with free registration here). It is the first effort to offer a systematic ranking of performance of 351 ports around the world. In general, US ports do very poorly. As the report notes:
The CCPI 2020 was constructed based on two different methodological approaches, or what have been termed the administrative approach: a pragmatic methodology reflecting expert knowledge and judgment, and the statistical approach, using factor analysis (FA). … The top ranked container ports in the CPPI 2020 are Yokohama port (Japan), in first place, followed by King Abdullah port (Saudi Arabia) in second place. These two ports occupy the same two positions irrespective of the methodology. The top 50 ranked ports are dominated by ports in East Asia, with ports in the Middle East and North Africa region, such as King Abdullah port, Salalah in Oman (ranked 6th and 9th respectively), Khalifa port in Abu Dhabi (ranked 26th and 22nd respectively), and Tanger Med (ranked at 27th and 15th respectively) as the notable exceptions. Algeciras is the highest ranked port in Europe (ranked 10th and 32nd respectively), followed by Aarhus (ranked 44th and 43rd respectively). Colombo is the top-ranked port in South Asia (ranked 17th and 33rd respectively). Lazaro Cardenas the highest ranked port in Latin America (ranked 25th and 23rd respectively), with Halifax the highest ranked port in North America (ranked 39th and 25th respectively).
The reader will notice that no US ports are named in the top 50, and the top-ranked North American port is located in Canada. Here, I’ll just give the factor analysis statistical ranking of some major US ports, which essentially comes down to a measure of how long it takes ships to unload–adjusting for the size and type of ship. However, the scores based on expert knowledge and judgement are similar. Out of the 351 ports ranked around the world, the main west coast US ports are Los Angeles (#328), Oakland (#332), Long Beach #333), and Tacoma (#335).The main US east coast ports are New York and New Jersey (#89), Savannah (#279), Virginia (#85), and Charleston (#95). The main US Gulf of Mexico port is Houston (#266).
Inefficient ports matter. As the report notes:
Maritime transport is the backbone of globalized trade and the manufacturing supply chain, with more than four-fifths of global merchandise trade (by volume) carried by sea. The maritime sector offers the most economical, energy efficient, and reliable mode of transportation over long distances. A significant and growing portion of that volume, accounting for approximately 35 percent of total volumes and over 60 percent of commercial value, are carried by containers. …
Unfortunately, ports and terminals, particularly for containers, can often be sources of shipment delays, supply chain disruption, additional costs, and reduced competitiveness. Poorly performing ports are characterized by limitations in spatial and operating efficiency, limitations in maritime and landside access, inadequate oversight, and poor coordination between the public agencies involved, resulting in a lack of predictability and reliability. Poor performance can also have an impact far beyond the hinterland of a port: Container shipping services are operated on fixed schedules with vessel turnaround at each of the ports of call on the route planned within the allocated time for port stay. Poor performance at one port on the route could disrupt the entire schedule. The result far too often is that instead of facilitating trade, the port increases the cost of imports and exports, reduces the competitiveness of its host country …
While much of the discussion of US ports focuses on international trade, it’s worth noting that the issues affect within-US trade as well. There are substantial US flows of goods that could be shipped up and down the east coast, the west coast, or in and out of the Gulf of Mexico. But much of that ocean-based shipping doesn’t happen because of costly and inefficient ports. The result is that those goods end up being shipped overland by truck and rail.
The World Bank/IHS Markit report just offers a ranking: it doesn’t make any effort to sort out underlying explanations for the poor performance of US ports. I haven’t made a deep study of this subject, but there are plausibly three main contributing factors.
First, the benefits of more efficient ports are spread across the logistics system, with lower costs for all the carriers hooked into ports and ultimately lower costs for producers and consumers. But those potential benefits are somewhat invisible. Those who run the port will capture only a small share of those benefits if they go to the time and trouble of updating the capacities of a port and running it as efficiently as possible, so they have only mild incentives to make such an effort.
Second, the Jones act is a century-old law which requires that water transportation of cargo between U.S. ports is limited to ships that are U.S.-owned, U.S.-crewed, U.S.-registered, and U.S.-built.” The goal of the law was to protect US shipbuilders from foreign competition. The result has been that it costs far more to make ships in the US than anywhere else, and the ships that are U.S.-owned, -crewed, and -registered have much higher shipping costs. In other words, it’s not just in its ports where the efficiency of US shipping has fallen far behind.
Finally, the International Longshore and Warehouse Union is the famously militant union representing port workers on the west coast. The union has done a fabulous job of negotiating high pay and benefits for its workers, and in that sense, I say more power to it. But the union has also been able to pass along these higher costs along the supply chain, while making it harder to update the efficiency of the west coast US ports in particular.
Most of the largest US ports have dramatic room for improvement. The pandemic-related supply crunch has brought the issue to the surface, but it was a largely ignored issue that existed before the pandemic and–unless some dramatic and permanent changes are made–it will exist as the pandemic wanes, too.
Here’s the split between food at home and food away from home over time. The sharp pandemic-related movements in 2020 are obvious. But I remember being surprised when the food away from home share began to exceed the food at home share in 2020.
Here’s the spending in terms of dollars. The drop in total food spending of 8% in 2020 shows that the rise in the dollar value of food at home was smaller than the dollar value of the drop in food away from home.
Of course, the food away from home category is actually a bundle of goods and service: that is, it’s combines food with shopping, preparation, service and clean-up. A shift to food at home is also a shift to providing many of those complementary services yourself.
For my own family, we became more likely during the worst of the pandemic to prepare meals at home that used more costly ingredients, like cooking the steak or making the cocktails at home, given that we weren’t going out to eat. We ate our share of spaghetti during the pandemic, but we have also have added to our repertoire of high-end meals that required unique ingredients, shopping, and prep time. Also, the pandemic strengthened our incentives to identify the local restaurants with especially good take-out options. I suspect that some of those changes will be persistent.
