We Pay Plasma Donors, Don't We?

The quantity of blood plasma being used in medical therapies was already rising at 6-10% a year. Now there is some evidence that blood plasma products may be useful in treating COVID-19. Peter Jaworski writes (footnotes omitted: 

Transfusing the blood plasma of those who have recovered from Covid-19, called convalescent plasma, appears to help against the novel coronavirus. The very same treatment has been used successfully as early as the 1918 Spanish Flu epidemic, and more recently with more similar infections such as MERS and the first SARS. The UK’s National Health Service has already begun trials of transfusing blood plasma of recovered Covid-19 patients. Convalescent plasma may also soon find another use in the form of a hyperimmune globulin. Hyperimmunes are plasma-derived medicinal products, or plasma therapies, made from isolated specific antibodies, in this case against SARS-CoV-2.

But here's the economic problem. The only way that quantity supplied has been keeping up with the rise in demand for blood plasma is through the efforts of the few countries in the world--primarily the United States--that allow blood donors to be paid. Thus, Jaworski has written "Bloody Well Pay Them: The Case for Voluntary Remunerated Plasma Collections" (2020, published by the Adam Smith Institute and the Niskanen Center). Here's how he described the global supply of blood plasma: 

The United States is responsible for 70% of the global supply of plasma. Along with the other countries that permit a form of payment for plasma donations (including Germany, Austria, Hungary, and Czechia), they together account for nearly 90% of the total supply.... Countries that exclusively use non-remunerated plasma collections for domestic plasma collections rely increasingly on the United States. The United States currently supplies approximately 70% of the global need, including about two-fifths of Europe’s needs, nearly all of the UK’s, over four-fifths of Canada’s, over half of Australia’s, and around 12% of New Zealand’s needs for plasma therapies. To put this into perspective, at present, 5% of the world’s population is responsible for more than half of all the plasma collected in the world. ... 

The global plasma supply situation has resulted in a staggering volume of plasma and plasma therapy exports from the United States. According to an estimate by The Economist, exports of plasma and plasma therapies represented approximately 1.6% of total exports by GDP, or U.S.$26 billion, in 2018, up from US$23.6 billion in 2016. To put this figure into perspective, that is more than exports of steel and aluminum, or the 11th most valuable export by value. Current projections, meanwhile, suggest that this figure will rise to U.S.$44.3  billion by 2023.

When it comes to blood plasma, many nations of the world have ended up in a position where paying for plasma is viewed as a moral wrong within their own country, but purchasing plasma from paid donors in the US and elsewhere is an everyday acceptable medical practice. This situation was already on shaky ground before COVID-19; if it turns out that blood plasma and its products are a useful part of a treatment for the coronavirus, then the quantity demanded of plasma will far outstrip available supply.  Jaworski writes: 

It is no longer reasonable, given the evidence, to continue to insist that non-remunerated plasma collections are able to meet domestic needs, never mind the global needs. Non-remunerated plasma collections have failed everywhere to secure a sufficient supply. There is now not a single jurisdiction anywhere in the world that meets its needs exclusively based on non-remunerated plasma collections.

In the United States, blood itself is usually collected only from volunteers, while blood plasma is from paid contributors. If it seems important to maintain this distinction, medical technology allows one to do so. Plasma can be either be collected as part of regular blood donations (the blood is spun in a centrifuge to separate red and white blood cells from the plasma), but plasma can also be donated separately. As Jaworski describes it: 

“[S]ource plasma” ... separates the plasma from the other blood components while the donor is in her chair, allowing the centre to capture only plasma while returning the remaining blood components to the donor. This process, called “plasmapheresis,” permits a donor to not only donate much more frequently but also to donate a much higher volume of plasma as compared to the plasma contained in a whole blood donation.

The question of blood plasma is not the only way in which COVID-19 is going to challenge some of our social intuitions about markets and medical discoveries. For example, consider the problem of testing a new vaccine. You pick a sample group of, say, 10,000 people. Randomly vaccinate half of them, while others get a placebo. Then have those people go about their business, waiting for some of them to get infected. But an obvious problem arises. When researchers at Oxford talk about testing a vaccine in this way, they raise the concern that of those 10,000 original people, maybe only 50 will end up being randomly exposed, maybe less. It's possible that so few people in the study group will end up being exposed that the test of the vaccine will not be statistically valid. And all of this takes time. 

In a purely practical sense, the fastest and most effective way to test a potential COVID-19 vaccine is to take a group of healthy people, vaccinate half of them at random, and then infect the entire group with COVID-19. One could either call for unpaid volunteers for such a project, or one could offer payment to a group of relatively healthy people. The payment could of course include compensation for lost wages, health care costs, living expenses, even life insurance. Instead of hoping for 50 people to be randomly exposed, make the exposure happen. For an argument along these lines, Ilya Somin makes "The Moral Case for Testing Coronavirus Vaccines through `Challenge Trials' on Paid Healthy Volunteers" (Reason website, May 27, 2020). 

It's of course true that paying for blood plasma or paying for vaccine trial volunteers raises some genuine moral issues. I won't pretend otherwise. But conversely, not paying also raises some genuine moral issues for opponents of such payments. 

For some earlier posts on paying for plasma and blood, see: 

• "Blood Plasma: US Paid Donors Dominate Global Market" (June 12, 2018)
• "Volunteers for Blood, Paying for Plasma" (May 16, 2014)

Updating GDP: Human Capital, Nonmarket Work, Inequality, Health Care, and More

No one who knows anything about gross domestic product, including economists and government statisticians, thinks it is a broad measure of social well-being. Moreover, economists at the Bureau of Economic Analysis don't want the job of coming up with a broad measure, either.  In the June 2020 issue of the Survey of Current Business, J. Steven Landefeld, Shaunda Villones, and Alyssa Holdren provide an essay on "GDP and Beyond: Priorities and Plans." They write: "BEA economists use market prices and volumes to measure GDP and other economic aggregates and have no special expertise in deciding the appropriate weights to combine indicators such as education and life expectancy with gross national income per capita." 

It seems sensible to me to have the government focused on collecting a wide array of statistics across a full range of economic and social indicators, and then having outsiders debate the ultimate meaning of "better off." But as Landefeld, Villones and Holdren point point out, along with a set of outside commenters, there are plenty of challenges even when just sticking to what can be measure or at least estimated based on prices and quantities. Here are some comments and thoughts on what BEA lists as its top priorities moving forward. 

Human Capital

We have known for a long time that investments in education, skills, and experience lead to greater "human capital" which pays off for the economy as a whole. But when we discuss "investment" as a part of GDP, we remain focused on purchases by firms of plant, equipment, and software along with intangible investment from corporate R&D. Landefeld, Villones and Holdren mention one striking estimate that one estimate comparing the accumulated stock of human capital with the accumulated stock of physical capital, the stock of human capital may be worth 16 times as much. 

But there's a real challenge here in measuring human capital investment. It can be estimated in various ways, which don't agree. In addition, it seems  plausible me that human capital in the form of education is a mixture of a consumption good and an investment good, which complicates matters further. Here's one of the outside comments from Lisa Lynch:

There are three main approaches for measuring human capital investment for the purpose of national accounts: Kendrick’s (1976) Cost-based approach; the Lifetime income approach as developed by Jorgenson and Fraumeni (1989 and on); and the Indicators approach as detailed by the OECD 2011 (and updated every two years since), and Barro and Lee 2013. Measuring investment in human capital based on costs typically includes spending on schools, employee training costs, opportunity cost of time acquiring human capital, and a range of expenditures on others items such as libraries, radio, TV, books and other items having human capital value. The Jorgenson-Fraumeni (J-F) Lifetime income stream focuses on the present value of the return to formal education only. Finally, the Indicators approach pulls together a range of metrics such as adult literacy, school enrollments rate, average years of schooling, and the percentage of highly qualified workers to capture differences across countries and time in human capital investment.

In principal the Cost-based and Lifetime income approaches should produce values equal to each other. In practice they do not. The Lifetime-income approach produces estimates of investments in human capital 6 to almost 10 times greater than the Cost-Based approach. ... 

Household production

A standard concern about GDP is that it doesn't measure household production that is not sold on the market, and standard estimates are that including estimates of the value of household production would raise GDP by about one-quarter.  But unpaid economic output purely for household production is only the start of the issues here. What about tasks like elder care, volunteering, and pumping your own gas or bagging your own groceries? Here's another comment from Lisa Lynch: 

While there has been significant work done by the BEA to develop a satellite account for household production I would urge the BEA to add additional non-labor market activities that take place outside the home but meet the threshold of “Would someone pay another person (a “third person” from outside the home) to perform the activity?” The first such activity is elder care. We know from the American Time Use Survey (2014–15) that approximately 16.2% of the U.S. population provides eldercare—unpaid care for someone over the age of 65 with a condition related to aging. Almost all of this care takes place outside the home and on an “average” day, 26 percent of unpaid eldercare providers spend an average of 3 hours in eldercare activities. With an aging population this is a growing dimension of household production that should receive increasing attention in household satellite accounts.

A second area of non-labor market work that is not captured in our satellite accounts is volunteering. From the 2015 American Time Use Survey we learn that 9% of those over age 64 volunteer on an average day. For all those volunteers over age 25 they spent an average of 2.25 hours in this activity. Examples of volunteering include administrative and support activities, social service and care activities, and indoor and outdoor maintenance, building, and clean‐up activities. While not all aspects of volunteering may meet the standard of paying another person for this work, much of it would.

A third area of non-labor market work includes the “free labor” facilitated by IT. Examples of this include ATM bank transactions, self-service work of pumping gas and bagging groceries, online airline ticket purchase and check-in, “self-service” baggage tagging/drop, self-service keyless check-in and checkout at hotels, and ordering, paying and self-pickup of meals. None of these economic activities are captured in our national accounts today even though we still have employees who are paid to do this work.

Distribution of Income

When thinking about growth of the overall economy as measured by GDP, and evaluating its costs and benefits, it seems useful to know what distribution of income is happening as well. But measuring income distribution in a way that links up directly to GDP is harder than it may sound at first. It's common for measures of income distribution to focus on personal income, using either survey data or administrative data (like tax returns). But such measures are mostly limited to personal income, which is only about half of GDP. Could measures of distribution be linked to overall GDP? In his comment, Angus Deaton sounds a cautionary note about this agenda: 

Piketty, Saez and Zucman (PSZ) have done a great service by calculating a set of distributionally disaggregated national accounts for the United States. The basic idea is irresistible. Yet these first attempts have raised many serious difficulties that were not apparent at first. Most immediately, only about half of national income appears on individual tax returns. Allocating from tax returns is hard enough, because tax units are neither individuals nor households, but allocating the other half of national income is an immensely more difficult task, requiring assumptions that are rarely well supported by evidence, and often seem arbitrary. Because distribution is such a controversial topic, these assumptions leave plenty of scope for politically-biased challenges, in which each commentator can choose their own alternatives and get almost any result they choose, inequality is increasing, inequality is not increasing, and everything in between. It is surely not good practice for statistical offices, as opposed to researchers, to have to make such deeply controversial choices. My own preference would be to give up on the bigger task of measuring the distribution of national income, and to stick to the feasible, but still difficult, challenge of allocating personal income, both before and after taxes and benefits.

Health Care

The usual idea of measuring GDP is to look at a product, and then to measure the price times the quantity produced. For products like steel or oil or cars or pizzas or haircuts, this works pretty well. But health care is an ever-evolving mixture of inputs, and the specific output that is being purchases is hard to measure.  Thus, a standard way of measuring "output" in health care has been to look at total spending on healthcare--which is of course a measure of inputs, not of outputs like reducing cases or morbidity or deaths from diabetes or cancer. Health care expenditures are a huge and growing, headed for one-fifth of all GDP. But there is often some skepticism over whether the rise in health care spending as a share of GDP represents a rise in outputs--like improved health. In his comment, Angus Deaton puts the point with some force: 

The American healthcare system poses one of the most serious challenges to national income measurement, and plays into its well-known weaknesses. Like other services, it is measured, not by its output in terms of its contribution to health, but by its inputs, such as the number of procedures, doctor visits, or prescriptions sold. I do not know how to do better than this, but I do know that these numbers, currently about 18 percent of GDP, vastly overstate any imaginable output measure. Americans have lower life expectancy and higher morbidity than do other rich countries, who spend much less. To take a concrete example, Switzerland, which has the world’s second most expensive healthcare system, spends only 12 percent of its GDP. So one measure of the value of the output of American healthcare is 12 percent of American GDP, which would mean that the sector has negative value added of a trillion dollars a year; to balance the accounts, this trillion dollars would show up as poll tax on consumers, $8,700 per head, which is being transferred as a tribute, or ransom, from consumers to healthcare providers. Of course, I am not suggesting that the BEA adopt this calculation, but it illustrates the dangers of not having a measure of output and of accepting valuation at cost.

The paper and comments raise a variety of other issues.  Those who want still more detail might head for a "Symposium: Are Measures of Economic Growth Biased?" in the Spring 2017 issue of the Journal of Economic Perspectives (where I work as Managing Editor): 

• "Underestimating the Real Growth of GDP, Personal Income, and Productivity" by Martin Feldstein (pp. 145-64)
• "Challenges to Mismeasurement Explanations for the US Productivity Slowdown," by Chad Syverson (pp. 165-86)
• "How Government Statistics Adjust for Potential Biases from Quality Change and New Goods in an Age of Digital Technologies: A View from the Trenches," by Erica L. Groshen, Brian C. Moyer, Ana M. Aizcorbe, Ralph Bradley and David M. Friedman (pp. 187-210)

Young Adults Entering COVID-19 Workforce: A Global View

When the labor market is severely disrupted, two age groups suffer in distinctive ways. Those who are just a few years from retirement, but then lose their jobs, are more likely to end up retiring earlier than expected. They lose several years of market earning and have to draw on their retirement savings during those years, which combine to reduce their standard of living during what may be several decades of retirement. 

The other age group that especially suffers is young adults just entering the workforce for the first time. Those who already have well-established jobs may have ways to telecommute, or to be called back by previous employers, or at least to have a resume of past work when they are applying for a new job. Here's some US data showing that unemployment rates and labor force participation rates are consistently lower for those in the 20-24 age group than for the population as a whole. 

The International Labour Organization describes some of these problems for young adults in an edition of  ILO Monitor: COVID-19 and the world of work (May 27, 2020, Fourth edition).  The ILO report notes (some boldface type omitted): 

Young people constitute major victims of social and economic consequences of the pandemic, and there is a risk that they will be scarred throughout their working lives – leading to the emergence of a “lockdown generation”. ...

Both technical and vocational education and training (TVET) and on-the-job training are suffering massive disruption. In a recent ILO–UNESCO–World Bank joint survey, around 98 per cent of respondents reported a complete or partial closure of technical and vocational schools and training centres. Although over two-thirds of training is now being provided at distance, often online, few low-income countries have actually made that transition.

Another new global survey by the ILO and partners of the Global Initiative on Decent Jobs for Youth reveals that over one in six young people surveyed have stopped working since the onset of the COVID‑19 crisis. Among young people who have remained in employment, working hours have fallen by 23 per cent. Moreover, around half of young students report a likely delay in the completion of their current studies, while 10 per cent expect to be unable to complete them at all. On a standardized scale of mental well-being, more than half of the young people surveyed have become vulnerable to anxiety or depression since the start of the pandemic.

It's worth remembering that in much of the developing world including many nations of sub-Saharan Africa, the Middle East, south Asia, and Latin America, one of the biggest economic and social problems for the short-and the medium-term is how the economy can create sufficient jobs to absorb large numbers of young adults into the workforce. The pandemic and its economic aftershocks will make make it even harder to incorporate young adults into the labor force. 

Adam Smith as a Practical Development Economist

For modern economists, Adam Smith's classic The Wealth of Nations is a source of memorable concepts: the division of labor, the "invisible hand," relying on the self-interest of the butcher and baker to provide us with products we want, the insight that people of the same trade rarely get together without trying to come up with some contrivance for raising prices, the four canons of taxation, and many more. 

But those actually reading the book, rather than cherry-picking snippets and quotations, will find that it is not just a book of theories and hypothetical examples. Instead, it is chock-full of historical episodes, national episodes, and arguments based on the evidence of the time. William Easterly takes on the task of rethinking Smith in this way in his essay, "Progress by consent: Adam Smith as development economist" (Review of Austrian Economics, published online September 9, 2019). As Easterly writes:  

There is a curious notion in development economics that the field emerged out of nowhere right after World War II. I used to share that view ... Apparently we believe that economists for decades and centuries had remarkably little curiosity about the dramatic development differences evident around them.

It took me embarrassingly long to acknowledge some obvious ancient history of development thinking, and some other development economists are apparently taking even longer. As long ago as 1776, Adam Smith wrote a book called the Wealth of Nations. It turns out, after many hours of careful reading, that the book is indeed about the Wealth of Nations.

Far from ignoring the wider world, Smith cited 164 different historical or contemporary
place names or names of ethnic groups. ... The omissions ... are rare and reflect information availability. Only Australia and New Zealand are left out altogether. Specific place names in Africa are limited to some places on the coast, but there are very important discussions of the African continent as a whole. The rest of the world is well covered ... Smith has abundant coverage of future Third World places such as Peru, Mexico, Chile, Egypt, India, Africa, Central Asia, and China. Smith’s First World success stories are England, lowland Scotland, British North America, and Holland. The future Second
World is also covered in discussions of Russia and Eastern Europe. ...

Smith used his widespread examples to test his preferred hypothesis to explain development. The hypothesis is not a surprise – development happens based on free trade and free markets, making possible the division of labor and gains from specialization. Many of his examples use natural variation in trade based on access to waterways, or proximity to prosperous towns or rich neighbors. So for example, England, Scotland, and Holland benefit from access to waterways, towns, and rich neighbors. Inland Africa suffers from the lack of all three. The Incas and the Aztecs had not enough trade for a
different reason – they lacked money as a means of exchange. China and India were intermediate development examples because they had large domestic markets and good interior water transport, but had refused to participate in international trade. Free institutions and moral norms that support individual choice and trade also matter. ...

Adam Smith (and economists in general) are sometime caricatured as believing that "greed is good." And of course, Smith is famous in part for emphasizing the power of self-interest to produce beneficial social outcomes, as if led by an invisible hand. But as Easterly emphasizes, Smith's vision of self-interest involved all parties having the power and freedom to make choices. Thus, Smith was a notable opponent of colonialism and slavery in his time, because those under colonial rule or enslaved were denied the power to make their own choices. Easterly explains: 

One such idea that was widespread and influential for a couple centuries in Western intellectual history is that less developed people were unfit to have the same rights as more developed people. Underdevelopment equaled innate inferiority, which implied your inability to make wise choices for yourself. Advanced development equaled innate superiority, which included the ability to direct development for the inferior people. These ideas opened the door for the more developed, allegedly superior people to make choices for the less developed people. Europeans had the right to seize lands of American Indians because Europeans would make the wise choices that would develop the lands more. Slave-owners had the right to dictate to slaves unfit to make choices for themselves.Colonizers had the right to dictate to whole countries unfit to make choices for themselves.

 Many thinkers linked the idea that underdevelopment reflects innate inferiority to the right of the more developed to coerce the less developed. Adam Smith is notable in this debate because he argued more universally for individuals’ right to choose for themselves, and emphasized how these choices would serve both their own interests and those of society and the world as a whole. Smith shows how recognizing the right to choose and consent is essential for development to really be beneficial for all. The gains from trade can only occur if one party does not coerce the other, an idea that led Smith to fiercely criticize European conquest and colonization of non-Europeans. ...

Slaves did not consent to have their production seized by their owner. Slaves are also not free to move to higher wage employments. Slaves have no incentive to work hard, and so lands worked by slaves “produce as little as possible.”Likewise, slaves have no incentive to make laborsaving innovations on the job, these “have been the discoveries of freemen.” (He confirms this empirically with a comparison of high productivity Hungarian mines with free labor compared to low productivity Turkish mines using slave labor in the same neighborhood.) ... Smith’s view here on African slavery was sufficiently notorious that Virginian pamphleteer Arthur Lee in 1764 complained Smith had “debased” the American slaveowning colonists into “monsters.”"

In other words, Smith is not arguing that self-interest which takes from others is economically (or socially) beneficial. Instead, he is pointing out the benefits that arise when self-interest of buyers and sellers interact in a shared moral context where all parties are able to make independent individual choices. Of course, this argument needs to be spelled out in detail in many ways, but that's why Smith wrote his book and Easterly wrote his essay. 

To modern ears, Smith's formulation may seem obvious (even for those who disagree and see it as naive or misleading). But as Easterly  points out, in his own time, Smith's view was distinctive: 

Despite what seems like a natural synthesis in Smith of a pro-market argument with an
anti-colonial and anti-racist one, it is sad that this combination would rarely occur again
among economists or other intellectuals in the centuries and decades after Smith before
the modern era.

The Productivity Race: US vs. Germany vs. Japan

Over the long run of decades, essentially all of the gains in standard of living are due to higher levels of productivity. On average and over time, what the people of a society produce is going to be closely linked what they can consume. In addition, the many and manifest problems of society are much easier to address in a context of an economy with rising productivity and economic growth, because an economy with flat productivity and zero growth is a zero-sum game, where helping one group always means imposing costs on others. 

Martin Neil Baily, Barry P. Bosworth and Siddhi Doshi search for "Lessons from Productivity Comparisons of Germany, Japan, and the United States (International Productivity Monitor, Spring 2020, pp. 81=103). These are the three biggest high-income developed economies, and three of the four biggest economies in the world (of course, China is the other). However, they differ in their experiences in recent decades, as well as in their institutions and cross-industry patterns. 

As a starting point, here's a quick-and-basic measure of productivity: GDP per hour worked.  Starting back in 1970, the US economy was way ahead in this measure of productivity: "Germany's aggregate productivity level was 0.72 relative to the United States in 1970, and Japan's aggregate productivity level was 0.40 relative to the US level in 1970." But Germany and Japan had more rapid productivity growth than the US in the 1980s and 1980s, and in fact Germany caught up to US levels. However, since about 1995, the US has reasserted its lead with faster productivity growth than Germany and Japan. 

As the authors look more deeply into these patterns, what do they see? 

1) The figure measures output per hour worked, but in Germany the average worker worked 1363 hours in 2018, while the average US worker was on the job 1786 hours that year.  (Take moment to wrap your mind around that difference. The average German workers worked more than 400 hours less in 2018--more than 10 weeks less!). Indeed, Germany has been substantially reducing average number of hours worked in recent years: for example, some German union workers negotiated for those who preferred it to choose a 28-hour work week. If one instead did a comparison by output per worker, not output per hour worked, the gap would be larger: "However, Ger­many has greatly reduced the number of hours worked per worker and so output per worker was only 73. 7 per cent of the US level in 2017." 

Japan has also reduced hours worked. In 1990, for example, the average Japanese worker was on the job 2031 hours per year, compared with 1,833 hours for a US worker. But by 2018, the average Japanese worker was at 1680 hour per year, lower than the US level of 1786 hours. 

2) These differences in hours worked across countries may also imply something about levels of productivity.  For the sake of argument, let's hypothesize that the decline in hours in Germany and Japan tended to be larger for workers with lower skills. If that is true, then the comparison of GDP/hour worked is looking at a broader range of US workers compared with a group that lacks the same proportion of low-skilled workers in Germany and Japan. 

3) Of course, West and East Germany combined in the early 1990s, so what "Germany" means as an economy shifts at that time. But overall, the authors write: "The German economy caught up to the US level of productivity in the 1990s and has since remained close behind. Their economy lacks the innovative IT sector of the United States but has other ad­vantages, including strong worker training. German GDP per capita is well below the US level, but that is because German work­ers have many fewer annual hours of work, and more leisure."

4) Of course, Japan has an economic meltdown for the ages in the early 1990s, from which its economy has arguably never fully recovered. The authors write: "In the 1990s that relative progress [for Japan] stalled out and GDP per hour worked fell further be­hind the levels achieved in both Germany and the United States. Increasing the level of competitive intensity and driving out low productivity small and large firms would help complete Japan's convergence to the productivity frontier. The Japanese manu­facturing sector still has strong productiv­ity performance, setting the frontier level of productivity in some industries, but its rel­ative performance has declined. ... The lit­erature suggests Japan may have had dif­ficulty with software development and the application of IT." 

 

5) One can also do a breakdown of productivity by industry, and look for industries where productivity in one of these three countries seems especially low compared to the others. For the US, the construction and utilities are two industries where low productivity stands out.  They write: "Recent productivity growth in the United States has been very slow indeed. There are promising technologies on the horizon but so far the gains are not being realized. The results in this article point to problem industries such as construction and utilities where productivity growth is very low or negative. While it is likely that productivity measurement needs to be im­proved, there are also underlying problems associated with regulation and a lack of ef­fective competition." I would add my own hobby-horses here for US productivity growth, which include an insufficient commitment to worker training and to research and development efforts. 

US Transportation Infrastructure: Manage Supply or Demand?

Much of the public discussion over US transportation infrastructure proceeds from the belief that it faces a supply problem which needs to be fixed by updating the old and building more of the new. Thus, the prescription is for spending more on roads, bridges, and mass transit. One common claim is that US transportation is "crumbling" (to use a word that often arises in this context). Other claims are that  additional transportation spending will reduce traffic congestion and improve economic growth.   

All of these claims are highly disputable. Gilles Duranton, Geetika Nagpal, and Matthew A. Turner lay out the issues in their essay, "Transportation Infrastructure in the US." The essay was written for a conference held at the National Bureau of Economic Research last November. The conference proceedings are going to be published in a book, Economics of Infrastructure Investment, edited by Edward L. Glaeser and James M. Poterba. But for now, the working paper versions of the essays and in some cases the galley proofs for the conference volume are available online. The Duranton-Nagpal-Turner essay is currently available here, and also available as NBER Working Paper #27254 (revised June 2020). 

What about the claim that US highways are in declining condition?

There's something called the Highway Performance Monitoring System, in which the Federal Highway Administration collects annual data from various state highway authorities. There is something called the International Roughness Index, which basically drives a vehicle over the road and measures bumpiness. "As part of HPMS, state highway authorities measure IRI on every segment of the interstate highway system, more-or-less, every year." Looking at available data from the 1992 to 2007: "The improvement in the condition of interstate highways has been almost monotonic."

What about the claim that US bridges are in declining condition?

There's a National Bridge Inventory. Looking at the data from 1990-2017, "the condition of bridges remained about the same, the number of bridges increased slowly, and bridge traffic increased modestly."

What about the claim that US mass transit is in declining condition?

There is a National Transit Administration, which maintains a National Transit Database. It shows that mass transit is heavily concentrated in a few cities. "New York accounts for about 40% of all transit rides in the entire country. Chicago is second, with 6%, followed by DC, Los Angeles, Boston and
Philadelphia. In total, these six districts account for about 60% of all transit rides in the country. ...The New York subway system carries about 71% of all subway riders and about 31% of all public transit riders in the whole country. ... The stock of public transit motor buses is younger than it was a generation ago and about 30% larger, although ridership has been about constant. The mean age of a subway car stayed about the same from 1992 to 2017, but at more than 20 years old, this average car is quite old. Subways carry about twice as many riders as they did a generation ago."

In short, there's is of course an ongoing need to update transportation infrastructure. But overall, the quality of US transportation infrastructure is not in decline. The authors write: "Massive increases in infrastructure are not required reverse the decline of us transportation infrastructure. Not only is this infrastructure, for the most part, not deteriorating, much of it is in good condition or improving. ... On average, most US transportation infrastructure is not crumbling, except (probably) for our subways."

But of course, one might argue that even if US transportation infrastructure is not literally getting worse, there might be large social gains from additional spending. For example, one might claim that more transportation spending will lead to improved economic growth or less traffic congestion.

On the issue of improved economic growth, Duranton, Nagpal, and Turner cite an array of evidence that improved transportation benefits those in close proximity. But much evidence suggests that transportation improvements lead to a geographic rearrangement of economic activity, not to additional gains for the area a whole. There is a broader case based on big-picture historical data that long-run growth benefits when society has sufficient infrastructure investments in transportation, electricity, communication, and water/sewage. But investing in these areas doesn't offer a quick boost to economic growth rates.  

On the issue of transportation infrastructure and congestion, the authors refer to the evidence that it's very hard to build your way out of congestion. For example, the six cities which account for most of US mass transit--New York, Chicago, Los Angeles, Boston, Washington, DC, and Philadelphia--all have extensive systems of both roads and mass transit. They also experience heavy traffic congestion. 

Overall, the authors suggest that gloominess about transportation infrastructure may not be primarily about its physical condition, but about displeasure over congestion. They write: 

The condition of infrastructure has, for the most part, improved over the past generation.
However, highways and subways per person have decreased, even as travel per
person has increased. Thus, while the condition of the infrastructure has improved or
stayed constant, it is serving much more demand, and so the speed of travel has decreased
and the experience of drivers and riders is worse. We speculate that the sentiment that infrastructure is deteriorating derives from the fact that users’ experiences are deteriorating
with increased congestion, and that this deterioration is largely independent of physical
condition.

As economists have argued for some time, people make choices when they commute: specifically, choices about the time, the route, and the mode (like whether to take a car or mass transit). When you build additional transportation capacity, some of those who were taking other times, other routes, and other modes will shift over, and the additional capacity quickly becomes congested, too. Thus, it's quite difficult to build one's way out of congestion: it would mean building enough capacity so that everyone who might choose to travel at a peak time can do so without hindrance--even if all those highway lanes and mass transit vehicles are near-empty at other times. The public policy answer to traffic congestion is instead to focus on the demand side--for example, by charging higher tolls and prices during peak-load times.

_______________

Here's the full Table of Contents for the Economics of Transportation Infrastructure volume: 

Table of Contents
Introduction: Edward L. Glaeser, James M. Poterba (bibliographic info)

1. Transportation Infrastructure in the US: Gilles Duranton, Geetika Nagpal, Matthew A. Turner (bibliographic info) (download) version of March 3, 2020 (Working Paper version)
Comment: Stephen J. Redding (bibliographic info) (download)

2. Measuring Infrastructure in BEA's National Economic Accounts: Jennifer Bennett, Robert Kornfeld, Daniel Sichel, David Wasshausen (bibliographic info) (download) version of March 3, 2020
Comment: Peter Blair Henry (bibliographic info)

3. Can America Reduce Highway Construction Costs? Evidence from the States: Leah Brooks, Zachary Liscow (bibliographic info) (download) version of March 3, 2020
Comment: Clifford Winston

4. Procurement Choices and Infrastructure Costs: Dejan Makovšek, Adrian Bridge (bibliographic info) (download) version of March 5, 2020
Comment: Shoshana Vasserman (bibliographic info) (download)

5. Digital Infrastructure: Shane Greenstein (bibliographic info) (download) version of March 3, 2020
Comment: Catherine Tucker (bibliographic info) (download)

6. When and How to Use Public-Private Partnerships in Infrastructure: Lessons from the International Experience: Eduardo Engel, Ronald D. Fischer, Alexander Galetovic (bibliographic info) (download) version of March 3, 2020 (Working Paper version)
Comment: Keith Hennessey (bibliographic info) (download)

7. A Fair Value Approach to Valuing Public Infrastructure Projects and the Risk Transfer in Public Private Partnerships: Deborah Lucas, Jorge Jimenez Montesinos (bibliographic info) (download) version of March 3, 2020
Comment: Richard Geddes (bibliographic info)

8. The Macroeconomic Consequences of Infrastructure Investment: Valerie A. Ramey (bibliographic info) (download) version of June 16, 2020
Comment: Jason Furman (bibliographic info)

The Boy, the Wolf, and the Case for Solar Radiation Management in Response to Climate Change

Richard Zeckhauser delivered a keynote address at the meetings of the Southern Economic Association last November, and an early online version in advance of publication is now available at the website Southern Economic Journal: Three prongs for prudent climate policy," by Joseph E. Aldy and Richard Zeckhauser (first published April 29, 2020). 

Zeckhause offers this retelling of the boy and the wolf fable (footnotes omitted): 

An extremely analytic boy lives in a village high in the mountains. The village used to have a traditional crop‐based economy, with a few scraggly sheep on the side. However, outside technology produced hybrid sheep that yield ample wool and mutton, and thrive at high altitudes. The village turned to mainly raising sheep, and ever more sheep.

When sheep were few, they could graze nearby the village. But when they became abundant, they had to graze well beyond where the villagers lived, namely in the outlands. The village had been warned that sheep without humans living nearby bring wolves. The boy has seen wolves and noticed that sheep have disappeared in unusual numbers. The boy's pleas for a shift back toward a less‐profitable crop economy have been ignored. Moreover, the boy is warning that more wolves are likely to take up residence nearby, and those wolves may reproduce. Changing the mix in the economy significantly back toward crops (a mitigation measure), will lower the wolf threat. As the first prong of defense, he recommended a 50% cutback in sheep, thus significantly reducing their attracting smell and their presence in the outlands.

The villagers heard the boy's message, and they responded, albeit in a woefully insufficient fashion. Whereas previously they had raised 20 sheep per family, they cut back to 18 and raised some vegetables. But evidently wolf numbers were still below equilibrium, and the losses to them increased.

Given the pace of sheep loss, and the unwillingness of the villagers to cut back sharply, the boy recommended that another layer of protective fencing (an adaptation technology) be erected in the outlands, even where the terrain is steep. This would be a second prong of the defense strategy. The village made a half‐hearted effort; after all, fencing is expensive, particularly in rocky and hilly domains. Some new fences were built, but the wolves readily evaded most of them. After a minor dip, the losses continued to rise.

Finally, the boy in desperation recommended that the village raise a hunting posse to search out and kill or scare away the wolves (an amelioration strategy), a third prong of defense. The villagers are very reluctant. They are farmers turned shepherds, not hunters. There may be riding accidents or gun accidents; indeed, a wolf may even turn on the posse. The village council votes against raising a posse. A few more fences are built, and the council implores the villagers to cut their flocks, and return to agriculture, but few villagers follow that course. Raising large numbers of hybrid sheep, even with the current 20% annual loss rate, is more profitable than growing crops.

As the annual loss rate climbs to 25%, the boy cries: "Please, can't we move forward on all three fronts? Someday the wolves will come to snatch our children, and that will end the world as we know it."

And so it is with climate change. We've been told, correctly, that the world is running out of time to curb its emission‐profligate ways. The world did little mitigation and ran out of the urgent time it was given. And matters have gotten worse, much worse. Emissions cutting, drastic emissions cutting, are still the recommended primary prong of our defense. Experience suggests, and economics reveals, that the magnitude of needed cutting will be almost impossible to achieve in the time available. Moreover, even if the prescribed level of mitigation is met, it may already be too late. A second prong of defense, adaptation, has received some discussion, but very little actual implementation. Adaptation would consist of such measures as building barriers to the ocean, restoring absorptive marshes, repositioning sensitive equipment from cellars to roofs, and preventing new construction in threatened areas. This analysis considers a third prong, amelioration through SRM to complement mitigation and adaptation.

Zeckhauser's emphasizes several themes. The mitigation strategy for climate change has now been in the public eye at least since the 1992 "Earth Summit" in Rio de Janiero. As we approach the three-decade anniversary of that summit, we can look at the data to find out how well the mitigation strategy is working. The first figure shows global carbon emissions annually from fossil fuels: the second figure shows atmospheric concentrations of carbon. 

Zeckhauser is not expressing opposition to a mitigation policy. He is just pointing out a hard truth: mitigation is an arduous and difficult and costly path. Given the politics and economics of the world in which we live, it is not guaranteed to succeed. Given the risks involved from high and rising emissions of carbon and other greenhouse gases, it makes to think about combining mitigation with advance planning for adaptation and amelioration some other costly and even risky steps. As the authors note: 

Mitigation efforts, which will require immense efforts and vast expenditures, will likely take decades to even cut emissions in half. Large‐scale renewable power, for example, would likely require years of innovation and commercialization of large‐scale battery storage, and the hopeful development of nuclear fusion. ...

On the choices between amelioration and adaptation (citations and footnotes omitted): 

The academic literature as well as the media have dedicated significantly less attention to amelioration than to emission mitigation. The most promising amelioration technology to date, in terms of feasibility and cost, as mentioned, is SRM [solar radiation management]. It would inject aerosols, most likely sulfur particles delivered by airplane, into the upper atmosphere to reflect back incoming solar energy. This would lower the temperature for a given accumulation of atmospheric GHGs [greenhouse gases]. This technology draws on research about the cooling impacts of introducing sulfur dioxide (SO2) into the atmosphere—from volcanic eruptions as well as the combustion of sulfur‐intensive coal and petroleum products. An SRM strategy would have side effects, perhaps extremely costly side effects.

Implementation of SRM on a scale sufficient to cool the planet will take considerable time and money, though a slight fraction of the costs of climate change ... While scientists are quite confident of its efficacy, experiments are still needed to demonstrate the feasibility of implementation. To deliver the SO2 to the lower stratosphere will require a new type of plane, and planes take years to develop. Such change will require research on feasibility, safety, and governance, and it could take many years to achieve grudging acceptance of this technology and then move to actual implementation at any scale.

Adaptation, will require considerable time and money as well. For example, if physical barriers are to be built to protect against rising sea levels and more intense storms, it will take years to figure out the engineering requirements, develop the plans, and secure the political will to produce the required resources. For example, the U.S. Army Corps of Engineers (2019) has identified a six‐mile long sea barrier with storm surge gates as a potential investment to protect New York City from climate change. It estimates that the wall would take 25 years to construct. Moving human activity away from the coasts will require decades and trillions of dollars. In short, the monies expended on adaptation will vastly exceed those required for SRM. That is true even if political realities prevent many worthwhile protective projects from being undertaken.

Zeckhauser focuses most of his talk on the difficult issues of risk and implementation of a strategy to ameliorate the effects of carbon emissions with a strategy of solar radiation management. Here, I'll just mention that people in the modern world yearn for and even expect that there will be a techno-fix for difficult problems.  A new coronavirus? Whip up a vaccine. Climate change? Whip up some low-cost and environmentally friendly solar and wind power.  There's nothing wrong, of course, with investing in possible techno-fix solutions. But there is something wrong with not being willing to consider to consider the risks that such solutions may not arrive soon or at all, or may be only partial answers, or may bring problems of their own--and to also make supplementary plans.  

For a couple of previous posts on geoengineering, see: 

• "Geoengineering: The Governance Problem (March 26, 2019)
• "Geoengineering: Forced Upon Us" (May 11, 2015)

The Random Presence of Females for Discovering Discrimination

It can be difficult to prove the existence of discriminatory attitudes to the full satisfaction of a social scientist. Ideally, one would like a real-world random event or policy intervention to occur, so that you could compare the real-world behavior of those who either experienced the random event, or not. A couple of recent studies have found specific situations where this can be done. 

Here's one example, analyzed by Marco Battaglini, Jorgen M. Harris, Eleonora Patacchini in "Professional Interactions and Hiring Decisions: Evidence from the Federal Judiciary" (January 2020, NBER Working Paper 26726). They note that in US appellate courts, the usual pattern is that cases are heard by three judges randomly assigned from the overall group. They also note that judges have pretty much a free hand in deciding who to hire as clerks. An overview of their work reports: 

Using data from the Judicial Yellow Book and a database of federal court cases, the researchers find that judges who hear more cases alongside female colleagues are 4 percentage points more likely to hire at least one female law clerk in the following year. They also examine whether exposure differentially affects judges who vary in meaningful ways — by gender, age, experience level, political affiliation, status, quality, and current law clerk staff composition. The effects of exposure to female judicial colleagues are larger for men, for judges whose current roster of law clerks is majority male, and for less-experienced judges. For example, male judges who hear more cases alongside female judges are 4.3 percentage points more likely to hire a female law clerk subsequently, while female judges who hear more cases alongside female judges are 1.6 percentage points more likely to hire a female law clerk subsequently.

Here's another example from a few years ago, this one from the venture capital industry, from research by Paul A. Gompers and Sophie Q. Wang  “And the children shall lead: Gender diversity and performance in venture capital” (2017. Harvard Business School Working Paper 17-103). They look at whether senior partners in venture capital firms have sons or daughters, which for this group we can treat as a random event. Then they look at how likely the firm is to hire women. 

We find that the proportion of female hires increases by 1.93% if you replace a son with a daughter for the existing partners in a firm. Given that about 8.03% of the new hires are female, this suggests a 24% increase in the probability of hiring a senior female investor when a son is replaced with a daughter for the existing partners. ... [W]e also show that improved gender diversity, induced by parenting more daughters, improves deal and fund performances.

My guess is that not many judges or venture capitalists had previously been openly vowing not to hire women as clerks or as as part of venture capital firms; indeed, I'm sure many of had previous hired a few women. In addition, I doubt that these changes involved an  open and conscious change-of-heart epiphany about hiring more women. I doubt that a  lot of judges were muttering in their chamber: "Well, now that I've been on a panel with a female judge, I'll go ahead and hire more female law clerks." I doubt a lot of venture capitalists were muttering to themselves: "Well, now that I have a daughter, all of a sudden women job applicants seem more plausible to me." Instead, it seems to me that these kinds of studies both demonstrate the existence of an unconscious bias and a mechanism for attenuating that bias. 

The studies also demonstrate that increasing contact can be a meaningful tool for reducing discriminatory attitudes. Kevin Lang and Ariella Kahn-Lang Spitzer make this point in the context of racial discrimination in their essay "Race Discrimination: An Economic Perspective" (Spring 2020, Journal of Economic Perspectives). They point out that racial discrimination potentially affects many areas: residential location, credit access, educational opportunity, hiring, criminal justice, medical treatment, and so on. Pushing back against discrimination in each of these areas is of course worthwhile, but some ways of pushing back may have broader leverage than others across a range of areas. They write: 

[P]olicies to increase interracial contact—like limiting residential segregation—may offer a useful point of leverage. Residential and social segregation may lead to prejudice and taste-based discrimination. Pettigrew and Tropp (2006) provide a meta-analysis of 515 studies and conclude that there is strong support for “intergroup contact theory,” which proposes that contact tends to reduce prejudice. Some economists have contributed to our understanding of this topic. Carrell, Hoekstra, and West (2015), for example, found that having an additional black member in an Air Force squadron of roughly 35 people increased the probability of having a black roommate as a sophomore (usually not a freshman squadron member) by about one percentage point, or about 18 percent. Similarly, exposure to more black peers with high admissions scores increased the probability that whites reported that they had become more accepting of African Americans. Dahl, Kotsadam, and Rooth (2018) find similar positive effects on male attitudes towards female recruits from having been assigned to a squad with a woman member during boot camp in Norway. In particular, given the importance of networks in job search, social distance can directly increase racial disparities in employment (Loury 2000). These studies, together with the large literature outside economics, suggest a public interest in greater integration and reducing social distance across groups.

The (Semi-Official) End of the Longest US Economic Expansion

The longest economic expansion in US history (or at least back to 1854, before which time the data gets not just shaky but exceedingly shaky) ended in February at 128 months. It beat the record established during the 120-month expansion of the 1990s. Third place is the 106 month expansion of the 1960s, with the 92-month expansion of the 1980s in fourth place. These figures are from the Business Cycle Dating Committee of the National Bureau of Economic Research, which is to say it's from a group of academic economists who have an affiliation with a certain prestigious research institute. 

(Specifically, the economists involved in this decision were Robert Hall, Stanford University (chair); Robert Gordon, Northwestern University; James Poterba, MIT and NBER President; Valerie Ramey, University of California, San Diego; Christina Romer, University of California, Berkeley; David Romer, University of California, Berkeley; James Stock, Harvard University; and Mark Watson, Princeton University).

It sometimes comes as a surprise to non-economists, but although the US government publishes a wide array of economic data, it does not attempt to pronounce on when a recession has started or ended. Given the political implications of setting such dates, the choice of leaving this task to an outside group is probably a wise one.  In a press release earlier this week, the NBER committee of economists announced that they had chosen February 2020 as the month for the peak of the previous business cycle, and explained why. The committee focuses on monthly data about domestic production and employment.

For domestic employment, there is a Current Employment Statistics (CES) survey of employers. Each month, "CES surveys approximately 145,000 businesses and government agencies, representing approximately 697,000 individual worksites." It does not include, for example proprietors running their own firm, the self-employed, farm-workers, or those employed by households. But the Total Nonfarm Payroll that it does cover includes about 80% of all workers. As you can see, it peaks in February.

However, one problem with the CES data is that because it's collected from employers, it includes workers who are being paid--but are on furlough and thus might be thought of as "unemployed." So for confirmation, the NBER committee also looked at the the Current Population Survey, which surveys about 60,000 households each month. The advantage here is that the survey can ask whether you are on furlough. The downside is that data from payrolls is a pretty solid measure of how many people are getting paid, while surveys that ask people may be subject to more measurement error. But that said, the CPS data peaks in February, too. 

On the production side, estimates of total US economic output like gross domestic product are not available on a monthly basis, but only quarterly: moreover, GDP numbers are first released as an "advance" estimate with preliminary data at the end of a given quarter, updated several months later with second and third estimate as more data become available. For making a decision now about the month the recession started, reliable if less complete monthly data is needed. Thus, the NBER turns to measures of personal consumption expenditures and personal income. Personal consumption expenditures is part (about 70%) of total GDP; personal income is part of the gross national income calculation. 

The data on real personal consumption expenditures is compiled by the Bureau of Economic Analysis from a variety of sources,  including the Monthly Retail Trade Survey, but also other government agencies (like the Departments of Energy, Transportation, Health and Human Services) as well as private associations and trade groups).  

Instead of measuring production by expenditures, an alternative is to measure the income that people received for producing. However, the issue here is that one needs to look at transfers in a way that does not include transfer payments, using sources like the ongoing data collected for the Quarterly Census of Employment and Wages for income, and government data on payments for estimating transfers. The monthly data on income is thought of as being a little more subject to later revision than the data on expenditures, but it also shows a peak in February 2020. 

These four measures are not always so synchronized in their timing. But in this case, it's of course not a surprise that the various measures are neatly aligned, because the pandemic that brought on the recession hit the economy with full force in March.

All definitions of "recession" are unofficial, but a definition one sometimes hears is that a recession is two quarters of negative economic activity. Thus, it may seem odd to have the NBER declaring a recession in June, with only three months of data available since February 2020. In response to these issues, the NBER committee writes: 

[I]n deciding whether to identify a recession, the committee weighs the depth of the contraction, its duration, and whether economic activity declined broadly across the economy (the diffusion of the downturn). The committee recognizes that the pandemic and the public health response have resulted in a downturn with different characteristics and dynamics than prior recessions. Nonetheless, it concluded that the unprecedented magnitude of the decline in employment and production, and its broad reach across the entire economy, warrants the designation of this episode as a recession, even if it turns out to be briefer than earlier contractions.

Finally, I'll add as a mignardise that the four longest economic expansions have all happened since the 1960s and three of the four longest happened since the 1980s. It's not much comfort for the current economic problems, but one of my best friends, Casual Empiricism, suggests that the US economy has become less recession-prone over time.  

Some Economics of Tipping

Tipping is a puzzle for economists. The service has already been provided. In many cases, the restaurant diner or taxicab driver will never see the provider of the service again. So why would a rational consumer pay extra?It seems clear that customs of tipping are embedded in a psychology and social expectations. But given that tipping varies across times and countries, and that even  consumers at a certain time and place tip for some purchases but not others, the explanation is likely to be complex.  Ofer H. Azar explores these questions and the limited evidence that is available in "The Economics of Tipping" (Spring 2020, Journal of Economic Perspectives, pp. 215-236). 

I had not known this history of tipping: 

There is no agreement on just how the practice of tipping started. Hemenway (1993) suggests that tipping dates as far back as the Roman era and is probably even older. Segrave (1998) claims that tipping may have begun in the late Middle Ages when a master or lord of the manor could give a little extra money to a servant or laborer, whether from appreciation of a good deed or from compassion. Brenner (2001) attributes the tipping origins to 16th century England, where brass urns with the inscription “To Insure Promptitude” were placed first in coffeehouses and later in local pubs. People tipped in advance in order to get good service by putting money in these urns. Indeed, Schein, Jablonski, and Wohlfahrt (1984) and Brenner (2001) suggest that “tip” comes from the first three letters of “To Insure Promptitude,” but others suggest different stories. Hemenway (1993), for example, argues that “tip” may come from stipend, a version of the Latin “stips.”

I had also not known that the practice of tipping flowed from Europe to the United States, which is ironic, because the practice has faded in Europe while strengthening in the US--at least in certain industries. Azar writes:  

It seems that Europe exported the practice of tipping to the United States, when high-income Americans who traveled in Europe in the 19th century started tipping upon their return to the United States, to show that they had been abroad and were familiar with the European customs (Schein, Jablonski, and Wohlfahrt 1984). By 1895, the average tip in European restaurants was 5 percent of the bill, while in the United States a common tip was 10 percent. Segrave (1998) estimates that during the early 1910s, five million US workers—more than 10 percent of the labor force—had tip-taking occupations. The large extent of tipping gave some tipped employees relatively high income, and employers both in Europe and the United States sometimes tried to take these economic rents from the workers either by taking the tips, or by charging employees for the right to work and earn tips (Scott 1916; Segrave 1998; Azar 2004a).

By the early 20th century, even though the tipping custom had only just arrived in the United States, there were already attempts to abolish it. Some saw tipping as creating a servants’ class, part of a society where the tippers looked down upon the service providers. Gunton (1896) called tipping offensively un-American, because it was contrary to the spirit of American life of working for wages rather than fawning for favors. Some states passed laws against tipping, starting with Washington in 1909, but these laws were repealed after several years.

Over the years, the percentage tipped in the United States has gradually risen. The 10 percent tipping norm in restaurants in the late 19th century stayed for several decades (Hathaway 1928; Post 1937), but eventually increased to 15 percent (Post 1984). In her etiquette manual, Post (1997) writes, “It wasn’t long ago that 15 percent of the bill, excluding tax, was considered a generous tip in elegant restaurants. Now the figure is moving toward 20 percent for excellent service. In ordinary family-style restaurants 15 percent is still the norm.” Today, some travel guides refer to 15−25 percent as a tipping standard in restaurants (for example, https://www.lonelyplanet. com/news/2016/12/07/how-much-to-tip/). A similar pattern of increasing tip percentages is observed in taxi tipping, starting with 10 percent early in the 20th century (Hathaway 1928), rising in mid-century to 15 percent (Post 1984), and then by the end of the 20th century reaching 20 percent in large cities (Post 1997). Today, tipping norms differ around the globe. Tourist guidebooks often provide advice about the tipping norms in the country (for example, Star 1988). In Europe, where tipping originated and was common already hundreds of years ago, today tipping is generally less common and in much smaller magnitudes than in the United States. In many European restaurants, tipping takes the form of rounding up the restaurant bill a little, not adding 15−20 percent to the bill. Along with restaurant servers and taxicab drivers, some of the professions where tipping is at least relatively common include food delivery people, bartenders, and hair salon workers. ...

Why does tipping persist, at least in certain settings? For example, why don't more restaurants move to a fixed service charge, or just raise their prices? Azar offers a number of ways in which the different players in a restaurant have reasons to prefer tipping and to facilitate it--for example, by leaving a line on the bill for the tip and even suggesting a precalculated amount. 

From the customer's point of view, as Azar notes: "Many customers prefer the control of choosing a tip and have a positive feeling that they are showing generosity." 

From the server's point of view, tips are a form of variable compensation. A server probably works a lot harder on Friday and Saturday than on Tuesday and Wednesday, but the hourly pay from the restaurant may not distinguish much or at all between days. It also seems clear that servers often get higher pay as a result of tips--and their implicit deal with diners--than they would get with pure hourly pay. Azar writes: "Servers earn more as a result [of tipping] and find that busy shifts where they have to work harder are rewarded with higher income. Service quality seems modestly higher." 

For restaurant owners, in a setting where tipping is an established norm, attempts to move away from tipping run a risk of alienating those customers who like the feel of tipping and also of driving away their best servers, who will earn more at a restaurant with tips--especially if they can work Friday and Saturday nights. However, restaurant owners will also look at tips with a degree of longing. They will either try to find ways to share tips among all workers, including the kitchen workers, or to shift some of the tip money to their own pockets, or both. 

There's much more in the article itself. As Azar writes: "Perhaps the self-reinforcing social norm of tipping will be toppled eventually in the United States, but with more than a century of history,

it seems unlikely to go quickly."

[Full disclosure: I've worked as Managing Editor of the Journal of Economic Perspectives since 1986, so I am perhaps predisposed to find the articles of great interest. However, this blog is an unpaid labor of love, not part of my job.] 

Pregnancy-Related Mortality in the US

When it comes to maternal mortality during pregnancy, the United States not only lags behind other high-income countries, but has been getting worse. The National Academies of Sciences, Engineering, and Medicine tells the story in its report Birth Settings in America: Outcomes, Quality, Access, and Choice.  Here's the trendline of US maternal mortality over time: 

As part of putting this in (grim) perspective, the report notes (citations omitted):

In contrast, the rate of maternal mortality has consistently dropped in most high-resource countries over the past 25 years. Severe maternal morbidity has been increasing in the United States as well. It is estimated that for every woman who dies in childbirth, 70 more come close to dying . All told, more than 50,000 U.S. women each year suffer severe maternal morbidity or “near miss” mortality, and roughly 700 die, leaving partners and families to raise children while coping with a devastating loss. Like the rates of maternal mortality, U.S. rates of severe maternal morbidity are high relative to those in other high-resource countries. In this context, it is notable that some local efforts in the United States have shown progress in reducing rates of maternal mortality and morbidity. In California, for example, the California Maternal Quality Care Collaborative led an initiative that reduced rates of maternal mortality by 55 percent (from 2006 and 2013) ... 

The fundamental problem here doesn't seem to be an issue of too little overall spending, but more of misallocated spending. US overall healthcare spending is high, and costs of childbirth are a big part of that. The NAS report notes (citations omitted):  

Childbirth is the most common reason U.S. women are hospitalized, and one of every four persons discharged from U.S. hospitals is either a childbearing woman or a newborn . As a result, childbirth is the single largest category of hospital-based expenditures for public payers in the country, and among the highest investments by large employers in the well-being of their employees. Cumulatively, this spending accounts for 0.6 percent of the nation’s entire gross domestic product, roughly one-half of which is paid for by state Medicaid programs.

The discussion in the report suggests that there is too little spent on prenatal care, perhaps some overview of (costly) hospitals as a venue for births compared with other options, and an overuse of some costly care like C-sections. 

A natural concern is how this might relate to infant mortality. However, US infant mortality has been falling over time. The two main concerns in this area seem to be a rise in the share of children born with low birthweights, together with large discrepancies across groups. Here's a figure on low birthweights from a National Center for Health Statistics Data Brief in 2018: 

Here's the NAS report on infant mortality differences across groups (citations and references to figures omitted). 

In contrast to maternal mortality, infant mortality in the United States has been declining over the past 20 years, and there are expanded opportunities for survival at increasing levels of prematurity and illness complexity. However, large disparities persist among racial/ethnic groups and between rural and urban populations. In 2017, infant mortality rates per 1,000 live births by race and ethnicity were as follows: non-Hispanic Black, 10.97 per 1,000; American Indian/Alaska Native, 9.21 per 1,000; Native Hawaiian or Other Pacific Islander, 7.64 per 1,000; Hispanic, 5.1 per 1,000; non-Hispanic White, 4.67 per 1,000; and Asian, 3.78 per 1,000. ... Rates of preterm birth and low birthweight have increased since 2014, and as with other outcomes, show large disparities by race and ethnicity. Low-birthweight (less than 5.5 pounds at birth) and preterm babies are more at risk for many short and long-term health problems, such as infections, delayed motor and social development, and learning disabilities. About one-third of infant deaths in the United States are related to preterm birth ... 

The NAS report does not offer a lot of clear recommendations for what should be done. The discussion of steps that could be taken for quality improvement (QI) is full of statements like: "While many QI initiatives have shown promising results, many current QI initiatives are underfunded." Do tell. But the report does offer some possible models to follow, like the California Maternal Quality Care Collaborative mentioned earlier. 

Some Thoughts on Police Reform

Disputes over policing are of course not new. Andrea M. Headley and James E. Wright, II, look at "National Police Reform Commissions: Evidence-Based Practices or Unfulfilled Promises?" (Review of Black Political Economy, 2019, 46:4, pp. 277–305). As they point out, the 1931 National Commission on Law Observance and Enforcement “the Wickersham Commission” was focused on problems like excessive police use of force, how the police should focus more on prevention of crime, and improvement of personnel standards for policy hiring.

Headley and Wright look at later police commissions, including the Kerner Commission report in the aftermath of the 1968 riots, the 2015 President’s Task Force on 21st Century Policing, and the 2018 report from the U.S. Commission on Civil Rights released a detailed report entitled “Police Use of Force: An Examination of Modern Policing Practices.” As they note, later commissions often revisit the topics from the 1931 commission, while adding some additional concerns like improving police-community relations, accountability, transparency, and diversity. 

In short, the current controversies surrounding police departments are not new, which of course is part of what makes them frustrating. Headley and Wright call it a "wicked problem," and write: Wicked problems are characterized by their complex nature, changing circumstances, lasting impact as well as the incomplete information regarding the issue—all of which pose difficulties for solving such problems."  

Of course, commissions are often willing to write up a wish list of what the members think should be done. But does the existing research offer useful guidance about what might work? Lack of data has been a severe problem.  For example, as the 2018 report of the US Civil Rights Commission notes, starting on the first page of the "Executive Summary": 

While allegations that some police force is excessive, unjustified, and discriminatory continue and proliferate, current data regarding police use of force is insufficient to determine if instances are occurring more frequently. The public continues to hear competing narratives by law enforcement and community members, and the hard reality is that available national and local data is flawed and inadequate. A central contributing factor is the absence of mandatory federal reporting and standardized reporting guidelines. ... [M]oreoer, the data that are available is most frequently compiled by grassroots organizations, nonprofits, or media sources. Data are not only lacking regarding fatal police shootings, but data regarding all use of force are scant and incomplete.

The report then quotes Roland Fryer: "Data on lower level uses of force, which happen more frequently than officer-involved shootings, are virtually non-existent. This is due, in part, to the fact that most police precincts don’t explicitly collect data on use of force, and in part, to the fact that even when the data is hidden in plain view within police narrative accounts of interactions with civilians, it is exceedingly difficult to extract." 

In a similar vein, Headley and Wright note:

Despite the breadth of studies surrounding police use of force, there are still questions that merit more attention. First, scholarship would be enhanced if we could identify why disparities in use of force exist and for which type of officers? For instance, are disparities present due to biases and discrimination on part of the officer? Are they present due to institutionalized racism or biases that are implicitly embedded in department practices, policies, or protocols? Or, are they present due to differences in the quantity and quality of civilian interactions with, and treatment toward, officers? Second, the literature on police use of force tells us very little about when force is not used. Thus, to be able to understand police use of force decision making more broadly, we need to also assess the interactions where force could have been used but was not. Getting at these nuances is key to enhancing the knowledge base on police use of force. To aid in addressing these questions, a national and comprehensive database of police–civilian interactions is warranted.

Headley and Wright also cite an array of evidence about"community-oriented policing" (COP), a broad term that usually includes "the provision of victim services, counseling, community organizing, and education; and the establishment of foot patrols, neighborhood teams/offices, and precinct stations." They note: "The research has generally shown COP positively affects community perceptions and attitudes and thus builds relations, whereas such strategies have very limited, if any, effects on reducing crime." Given that improving police-community relations is a goal in itself, COP policies may be worth pursuing, but perhaps with limited expectations about how they will reduce crime.

They describe a knot of potential conflicts that can arise between goals of increasing diversity and the hiring standards that have in some cases limited hiring a more diverse workforce. Headley and Wright comment: 

Police departments across the country are realizing the need to expand their hiring pool while also acknowledging some of the harms that have been done to keep people of color and women out of policing (whether intentionally or not), which provides a fruitful area for future research to assess. For instance, Madison Police Department in Wisconsin has restructured its physical agility test and has increased the number of women police officers hired, whereas St. Paul Police Department (Minnesota) changed its written test requirements (which had disproportionately adverse impacts on applicants of color) to focus more on personal history and community engagement rather than situational testing. Going a step further, Colorado’s Peace Officer Standards and Training Board allows officers who have been arrested for criminal convictions to still be considered for law enforcement positions under certain criteria, whereas other police departments, such as the Burlington Police Department in Vermont, only require legal permanent residency or work authorizations instead of U.S. citizenship. These advances occurring in the police profession open a new door for researchers to conduct pre- and post-evaluations of recruitment and hiring initiatives particularly as it relates to long-term organizational culture and employee performance.

One of the go-to suggestions for any police reform is "better training." They pour a little chilled (if not quite cold) water on this suggestion: 

Training has been one of the most commonly used ways to respond to crises in the policing profession in hopes to affect police behavior. Unfortunately, with the lack of consistency in training across police departments, scholarship has not rigorously or systematically been able to examine the impacts of various types of trainings. This is a huge gap in the existing scholarship that needs to be filled to move the practice of policing forward and improve outcomes.

Headley and Wright are not trying to provide a full overview of the literature. As they point out, many of the problems of policing fall under the heading of "culture"--whatever explicit rules exist, they are filtered through the culture of police departments. They do not discuss the issue of police unions, which may in some cases be a substantial barrier to accountability, transparency, and shifts in culture. Katherine J. Bies makes this case in a 2017 essay in the Stanford Law and Policy Review, where she writes: "Let the Sunshine In: Illuminating the Powerful Role Police Unions Play in Shielding Office Misconduct.'' She writes: 

[D]uring the rise of police unions to political power in the 1970s, police unions lobbied for legislation that shrouded personnel files in secrecy and blocked public access to employee records of excessive force or other officer misconduct. Today, these officer misconduct confidentiality statutes continue to prohibit public disclosure of disciplinary records related to police shootings and other instances of excessive force. Moreover, as the failure of recent sunshine legislation demonstrates, police unions continue to challenge and deter today’s progressive reform efforts that would replace secrecy with accountability and transparency. This Note also argues that police unions are unparalleled in their ability to successfully advocate for policy proposals that conflict with traditional democratic values of accountability and transparency.

The problem of police reform of course involves a desire to minimize grievous abuses or excessive violence, but it's much more than that. The terrible cases in the headlines are the 10% of the iceberg that is showing above the waterline. The police need to be able to operate within their communities with some basic level of community support, but in many cities, police in their day-to-day interactions have already lost the trust of a substantial share of the public, and are in danger of losing the trust of many more.