Month: April 2020

In an unsettled and uncertain time, Joshua Gans and MIT Press are trying an intriguing experiment: A complete draft of a new book by Gans, Economics in the Age of COVID-19, is freely available on-line. The draft is going through the standard process of getting comments from outside experts, but up until May 15, you can also read the draft for free and send along your own comments if you wish. The plan seems to be that after May 15, an updated  version of the book taking the comments from outside experts into account will become available for sale, and at some point after that, a final, final version will become available that takes the broader array of public comments into account.

Even when completed, the book will clearly be a first draft of history. But for those of us looking to get up to speed on the considerable amount that has already been thought and written about the economics of the crisis,  Joshua has already collected, organized, pre-digested, and exposited a large share of what\’s out there. In the future, when people are looking back to see what was known and argued when the pandemic was hitting, this book will be a natural starting point.

Here, I\’ll perhaps do the book a mild disservice by focusing on how Gans uses a familiar tool from intro econ, the production possibilities frontier, to describe the difficulties of making choices curing a pandemic. I should emphasize that this section is not typical of the style of exposition for the book as a whole. Joshua calls it a \”Technical Interlude,\” and writes: \”Readers who do not enjoy graphs are free to skip directly to Chapter 2 without missing any crucial information. For economists and other graph lovers, this section will go into more detail of the hollowing out and drift effects so critical to the economic conclusion that health should come before wealth.\” But for econ teachers wanting a way to bring the pandemic into their classroom (so to speak …), this part of the discussion offers a way to do so.

Start with this figure showing a tradeoff between the economy and health. The outer line is a standard production possibilities frontier. This diagram should be interpreted as the tradeoff at a point in time. At a point in time, it would be possible to, say, shut down factories and thus to improve air quality, in a way that would reduce the size of the economy but improve health. The blue dot shows the poitn chosen by society. This diagram should be interpreted very broadly, so that \”economy\” means all of the benefits generated by the economy, not just a simple measure of GDP.
<img alt="

Figure 1-3: Pandemic Production Possibilities Sets

a (left) Previous Levels Possible

b (right) Dark Recession

\” height=\”178\” src=\”https://resize.pubpub.org/fit-in/800×0/rbl9fn2y/11586313979114.png\” width=\”400\” />
What happens when a pandemic hits? Focus on the left-hand side panel first. Gans argues that the pandemic will mean that the possibilities for both economic output and for health contract. The previous combination of economy and health chosen by society–the blue dot–is no longer feasible. Instead, we have to think about whether we want to absorb the negative impact of the pandemic more through a reduction in the economy, or more through a reduction in health, or with some combination of the two. On the left-hand side of the diagram, point E shows a choice of keeping the economy where it was before, and having all the costs of the pandemic happen via less health. Point H shows a choice of keeping health where it was before, and having all the costs of of the pandemic happen via a reduction in the economy.

The shape of the red line curves has an inward curve, what Gans calls a \”hollowing out.\” What does that shape represent?  Gans writes:

That arises out of the nature of a pandemic. To consider this, suppose that we started from our original level of the economy (at a point like E, the black dot). Then, if we want more health during a pandemic, we need to give up a lot of the economy to get it. This is the social distancing argument — we need a lot of social distancing in order to halt the spread of infectious disease and a little bit won’t have much effect. The same logic applies if we start from our original level of health (at a point like H, the green dot). In that situation, if we look to give up a little health for a better economy we find that we cannot do that. Even to achieve a level of health remotely close to what we previously had, we have to employ lots of social distancing which means that the only way to get a better economy is to give up a ton of health. (Notice that the less virulent is the infection, the smaller the bite is likely to be.) The point is that if we take the epidemiologists seriously then our usual marginal thinking about trade-offs does not work

To put it another way, the shape of the red line emphasizes that trying to muddle through a pandemic with a slightly lower level of health and a slightly reduced economy isn\’t going to work well. If a society decides that it will choose half-way job of social distancing, it will experience both a big drop in health (because half-way social distancing isn\’t all that effective) and also a big drop in the economy (because half-way social distancing is still quite costly). A pandemic thus present a kind of either/or choice: choose health or economy, protect one of them, and accept the corresponding costs.

What Gans calls the \”drift\” makes this lesson even more clear. Imagine that society chooses point E, to protect the economy. As the pandemic advances over time and the health costs become more severe, the economy is going to decline further (as shown by the lower level of point E in the right-hand side of the figure). Also, if society tried to defend the same level of the economy, and thus the pandemic keeps spreading, trying to keep the level of public health more-or-less the same is no longer a workable option. If society wants to protect public health in a pandemic, it needs to act briskly, because the option of protecting public health won\’t be possible after the pandemic spreads.

Gans presents a series of pandemic PPFs, showing that they are flexible tool for thinking about a range of issues, like how an increased availability of testing would improve the tradeoffs. Intro econ teachers take note!

For the rest of us, this framework helps to explain issues like why the social distancing rules were put in place so abruptly, why trying to take a half-way approach to social distancing would have probably imposed lots of economic costs with few health gains, and why choosing to prioritize health helps to avoid the \”drift\” that would otherwise occur as the pandemic evolved.

Here\’s an odd fact: Even though the total assets of US investors abroad is smaller than the total assets of foreign investors in the US economy, the total returns earned by US investors abroad has historically been larger than what is earned by foreign investors in the US economy. How does that happen?

As a starting point, here\’s the data on \”International Investment Position\” from the Bureau of Economic Analysis. As you can see, US assets abroad are rising, reaching $29.3 trillion at the end of 2019. But US liabilities–that is, ownership of US assets by foreign investors–is substantially larger at $40.3 trillion at the end of 2019.

Alexander Monge-Naranjo, in \”The United States as a Global Financial Intermediary and Insurer\” (Economic Synopses: Federal Reserve Bank of St.  Louis, 2020, No. 2) delves into the return on these international investments.  He calculates that from 1952-2015, the average annual return on assets that US investors was 5.2%, while the average annual return on assets held by foreign investors in the US economy was 2.5%.

Why does this difference exist, and how can it persist? As Monge-Naranjo argues, the typical pattern is that US investors in other economies are relatively more likely to invest in higher-risk asset–like investments in companies. Conversely, foreign investors in the US economy are relatively more likely to put their money into a safer asset, like US Treasury debt. In this sense, the patterns of international investment in and out of the US economy look like an insurance arrangement for the rest of the world–that is, investors in the rest of the world are trading off lower returns when times are good for safer and steadier returns when times are bad.

Or to put it another way, the US economy from this perspective resembles an investment fund which raises funds by issuing lower-cost debt and then makes money by investing in higher-risk companies.
This situation is not especially troubling. The US economy is the world\’s main producer of internationally-recognized safe assets like US Treasury debt; indeed, in bad economic times investors around the world are more likely to stock up on safe assets. In addition, the US financial, legal, and regulatory infrastructure is a huge advantage for US investors, helping to give them the confidence to make higher-risk investments in other countries. Of course, if US Treasury debt stopped looking like a safe asset, and better alternatives bloomed around the rest of the world, the current arrangement would be unsustainable–but in that situation, the US economy would be experiencing a lot of other problems, too.

Bottom line: If you dig down into the \”International Transactions\” accounts from the Bureau of Economic Analysis, you find that in 2019, the \”Primary Income Receipts\” for the US economy on foreign investments abroad were $1,123 billion in 2019, while the \”Primary Income Payments\” flowing from the US economy to foreign investors was $866 billion.

Merle van den Akker has an \”Interview with Colin Camerer\” at her Money on the Mind website (April 6, 2020). Here are some of Camerer\’s answers. 

First, you need to know the “rules” of economics—the basic canon and methods—very well. (That was a big advantage for me at Chicago in graduate school, it is a crucible for learning to “think like an economist”.) To break the rules you need to know the rules.

Second, in my opinion, if you want to succeed in behavioral economics it is a big help to be very fluent in an adjacent social science. A lot of behavioral economics is in the business of importing ideas and translating them, redesigning and “selling” them inside economics. So you need to become bilingual and know what psychology, or neuroscience, media studies, or whatever, is solid, and has a long good empirical pedigree. Figuring that out can be difficult.

Third, nowadays you really should be able to do lab (and online) experiments, know about quasi-experimental designs (IV, diff-in-diff, regression discontinuity) and know some machine learning. It is often said that most of the methods you will use in your long research career are those you learned in graduate school. It is like packing for a long, long trip to a place where there are no stores in case you forgot to pack anything. Fill that backpack with methods.

What are some promising frontier areas for behavioral economics? 

Behavioral economics has been slow to embrace machine learning (for reasons discussed in the next section— it got on the BEAM reading list very late), which is unfortunate. As a result, a lot of the exciting work in behavioral science is being done in computational social science by sociologists, cognitive science, cultural anthropologists, etc. …

It would be good to see more behavioral insights using systematic work on emotion, attention, memory, design, haptics, social influence, etc. Personalization is also important because one-size-fits-all interventions are so wasteful; a chunk of people won’t budge, a chunk budge easily, and then there is a middle group who need just the right nudge. But personalization requires thinking about personality, character skills, etc.—an area that behavioral economics willfully neglected for a long time (because we were busy doing more foundational things). The general success of behavioral economics, in my historical accounting, came from importing basic concepts and methods from psychology and putting them in the right place … But doing this well requires really understanding the psychology on its own terms. In the early days that was not so challenging because Slovic, Lichtenstein, Fischhoff, Loewenstein, Kahneman and Tversky, Einhorn and Hogarth (and many others) basically did the careful filtering for those of us who were not as psychology-trained. But nowadays if you want to understand concepts like habits, salience, attention, emotion, evolution, and use them to do behavioral economics you better do a lot of reading or co-produce data and co-author with a collaborator who knows a ton.

Underinvestment in Neuroeconomics

Neuroeconomics is the opposite of the 5-10 year fad phenomenon. It is thriving but very few behavioral economists are involved. It is almost like a sports league that got together and voted that a certain type of ball or clothing material should be outlawed because it is not “cricket”. It is a special case of the plain fact that the elite economics departments do not care at all about whether the behavior that people are assumed in models to be capable of are biologically implemented.

I am a little surprised there have not been more talented economics students taking up neuroeconomics since the upside is so huge. It seems related to the fact that the economics profession, particularly in the US, is much, much more status- and ranking-obsessed than any other academic field I know, and there is a lot of tribalism. Ambitious students who care about status and future job placement are petrified of doing anything too risky like neuroeconomics because they wouldn’t get jobs in HRM top-tier US economics departments (which is probably true). Their advisors often explicitly warn them away from new ideas too, because they care about their students’ placements in a similar way. There is so much low-hanging fruit in neuroeconomics.

There\’s much more in the interview. In addition, if you want to gain a nodding acquaintance with many of the key players in behavioral economics in both  business, there are more than 30 other interviews at the website, including with Kelly Peters, Biju Dominic, Joshua Greene, Evelyn Gosnell, George Loewenstein, and others.

Like many readers of this blog, I suppose, I\’m spending chunks of time reading about aspects of the coronavirus pandemic. I post here about some of what I run across. Examples include: 

• \”Can the Economy Just Be Put On Hold For a Few Months?\” (March 20, 2020)
• \”The Spanish Flu of 1918-20: Health and Macroeconomic Effects\” (March 19, 2020)
• \”Some Coronavirus Economics\” (March 11, 2020)

However, many of the readings I find don\’t seem like useful fodder for the kinds of posts I try to do. Here are five examples that I tweeted about in the last few days: 

1) Although it\’s not a great comfort just now, it\’s perhaps worth remembering that dealing with pandemics has been a common human experience through the millennia. For an interview that moves back and forth from historical examples to our current experience, I recommend: \”“Pandemic! What Do and Don’t We Know? Robert P. George in Conversation with Nicholas A. Christakis” (this edited version of the interview was published April 7, the original one-hour interview from March 30 is available here). For example, Christakis notes: 

It is a very standard thing to implement social distancing. Thucydides describes it in the plague that afflicted Athens in 430 BC. It’s not rocket science. There are two kinds of ways that we can respond to pandemics. One is so-called pharmaceutical interventions, drugs and vaccines, for which we don’t have any for this condition, although we hope to have some in the future. The other is so- called non-pharmaceutical interventions, of which there are two types: individual stuff—like washing your hands, self-isolating, not touching your nose and face—and collective interventions—like school closures or the governor banning public gatherings. All of these have been around forever. You can look at medieval woodcuts of how the people in European cities coped with pandemics and see them spaced out in the public squares. This is a fundamental human experience that we’re having. It’s been described for long periods of time. It’s just we’re not used to having it.

2) A pandemic forces society to strike a balance between public health and economic factors. It seems to me that some period of sheltering-in-place is a reasonable way to strike that balance, but for how long and under what rules are topics on which reasonable opinions can differ. Sergio Correia, Stephan Luck, and Emil Verner provide a readable overview of their just-published working paper in \”Fight the Pandemic, Save the Economy: Lessons from the 1918 Flu\” (Liberty Street Economics website, Federal Reserve Bank of New York, March 27, 2020). They look at geographical patterns of the 1918 flu, along with geographical patterns of steps like \”closures of schools, theaters, and churches, bans on public gatherings and funerals, quarantines of suspected cases, and restrictions on business hours.\” Unsurprisingly, they find that steps which shut down public spaces and business were associated with drops in economic activity. But perhaps surprisingly, they also found \”that cities that intervened earlier and more aggressively experienced a relative increase in real economic activity after the pandemic subsided.\”

3) For a number of people, one \”lesson\” they seem to be taking away from the pandemic is that a competitive market economy doesn\’t do a good job in addressing events like a pandemic, and greater government intervention is needed. The first claim (about shortcomings of markets) is fair enough, but the second claim (about the merits of greater government intervention) is in this case an unproven article of faith. Here\’s an article from the New York Times on how the US government started planning 13 years ago to build up a stockpile of ventilators. As of late 2019, the government had succeeded in approving which ventilator the contractor would deliver–but none had actually been delivered yet. 

4) Will experimental patterns tried out during the shelter-in-place period become longer-term habits? For example, will online education see a lasting surge? (After all, if it\’s good enough to get academic credit for degrees at Harvard, Stanford, and everywhere else, why not make it as standard practice?)
Katherine Guyot and Isabel V. Sawhill make the prediction that \”Telecommuting will likely continue long after the pandemic\” (Brookings Institution, April 6, 2020).  They make a strong case, but I confess that I\’m skeptical. My sense is that telecommuting is a two-edged sword: workers like having the option when it\’s convenient for them, but they dislike the feeling that their work-life is bleeding into the rest of their life and that they are perpetually on call for their employers. 

5) Yes, many people went on an odd toilet-paper buying spree. But in talking about this market, there\’s more to the story. Toilet paper is really two markets–home and commercial–and substitution between them isn\’t easy. With people sheltering at home, they objectively were planning to use more toilet paper than if they were spending hours each day at office or school. The quantity demanded for home toilet paper is usually quite predictable and steady, and the supply chain was thus quite unprepared for a rise in demand. Will Oremus tells the story in \”What Everyone’s Getting Wrong About the Toilet Paper Shortage\” (Marker Medium, April 2, 2020).

When I think of my children–now young adults–getting a \”job,\” what I am hoping for is  an arrangement between an employer and an employee that pays a wage or a salary, has a reasonably predictable work schedule, and that often has an implicit or explicit contract for a continuing employment relationship.

In an \”alternative\” work arrangement, at least some of these conditions don\’t hold. For example, the work may be paid by the job, or based on revenue earned by the worker, not on a wage or salary basis. The work schedule may be unpredictable. There is no strong expectation on either side that the employment relationship will continue into the future, which then influences decisions made on both sides about issues like whether the employer finds it worthwhile to offer training or benefits, the likelihood of future raises, and so on.

Of course, jobs often don\’t fall neatly into just two boxes, one \”traditional\” and one \”alternative.\” But in thinking about these alternative job arrangements, a key question is whether workers choose these jobs, perhaps because they like the flexibility? Or do workers end up in alternative job arrangements when they would have preferred a more traditional ongoing job relationship, but were unable to find one?

 Alexandre Mas and Amanda Pallais dig into these issues in \”Alternative Work Arrangements\” (December 2019, Princeton University Industrial Relations Section, Working Paper #634). From a different angle, so do Tito Boeri, Giulia Giupponi, Alan B. Krueger, and Stephen Machin in \”Solo Self-Employment and Alternative Work Arrangements: A Cross-Country Perspective on the Changing Composition of Jobs\” (Winter 2020, Journal of Economic Perspectives, 34: 1, pp. 170-95).

Despite considerable public discussion about alternative jobs and the \”gig economy,\” we don\’t actually have good evidence on whether the number of alternative jobs is rising. For some background, \”Do We Even Know if the Gig Economy is Growing?\” (January 29, 2019).

In these more recent essays, Mas and Pallais point out that US data don\’t show that the prevalence of irregular or flexible scheduling, or working from home, has risen much in the last couple of decades. They write: \”The number of electronically-mediated gig jobs has grown substantially, but these jobs remain a very small share of overall employment, and independent contracting and self-employment have grown, at most, modestly. While our broad definition of alternative work arrangements represent a large share of the U.S. labor market, the traditional job is still very much a relevant feature of the labor market, and there is little evidence that it is on a substantial decline.\” Boeri, Giupponi, Krueger, and Machin look at data from a number of high-income countries to find that rates of self-employment don\’t seem to be rising; however, they also find that look if you divide up at self-employment into solo self-employed or self-employed with employees, the fraction of solo self-employed is a rising share. \”Moreover, solo self-employment is largely associated with underemployment: that is, these workers would like to work more hours, and they earn less on an hourly basis than their counterparts with employees. The solo self-employed are also more liquidity constrained and more vulnerable to idiosyncratic shocks than the self-employed with workers.\”

In my own mind, the key question about job \”flexibility\” is who controls it. If I\’m the worker, and I have flexibility to telecommute some days or to vary my hours in the context of an ongoing employment relationship, that sounds good to me. But if I\’m the worker, and the employer is telling me that my time schedule is shifting on a weekly or even a daily basis, or that I am required to work from home some days, that\’s much less attractive to me. The issue becomes especially messy because \”flexibility\” may start off as something where workers feel as if they have the power to vary their hours or to telecommute on some days, but it may then rapidly evolve into something where workers feel as if they are under implicit or explicit pressure to take on jobs at times or on days that would not otherwise be desirable.

In this spirit, Mas and Pallais write that most of the workers who have job \”flexibility\” experience it as involving less work-life balance:

While flexibility in work schedule and location have often been touted as a means of achieving work-life balance, we do not find evidence that these practices lead to reductions in job stress or family life interruptions. In fact, the opposite is generally true. Workers who report more flexibility tend to also have worse outcomes in these dimensions, as well as higher shares of long work days and late night work. Perhaps surprisingly given the emphasis of the benefits of flexible arrangements on work-life balance, there is no evidence that women are more likely to be in jobs with more scheduling or work location flexibility. The ability to work part-time appears to be one of the primary job characteristics that workers, especially women, use to achieve work-life balance.

There are really two kinds of \”flexible\” labor market arrangements. One is workers with relatively  high levels of education and skills, who in theory have lots of flexibility, but in practice often feel pressure to be on call for the job 24/7. Another kind of \”flexible\” applies to low-skill workers whose schedules are being toggled and joggled at what often feels like the whim of an employer. These are often solo self-employed workers who often would prefer more stability in their work lives.

It may seem obvious that flexible work should be rising: after all, the technology that makes it easier to work from remote locations or that lets a firm coordinate \”gig\” jobs is getting cheaper and better all the time. But other factors are pushing back against the spread of these alternative jobs.  Mas and Pallais write:

We highlight several factors constraining the growth in gig work, flexible scheduling, and telework. Gig work (including independent contracting and freelancing) as a primary form of employment is likely held back by widely held preferences against irregular schedules and uncertain earnings. The primary benefits of electronically-mediated gig work are its potential to smooth fluctuations in earnings and to enable moonlighting. Regulatory pressure to reclassify independent contractors as regular employees may also limit future growth in these types of alternative arrangements. Temporary staffing has not grown, possibly because it primarily serves to smooth employment around temporary vacancies or meet transitory demand shocks, needs that may not have changed much over time. Flexible work practices may also be constrained by high marginal costs of implementation for two reasons. First, implementing these practices is infeasible in many jobs. Second, team production and coordination may require workers to be in proximity to each other. … 

Worker preferences for alternative work arrangements may be driven, in part, by how these arrangements impact workers’ careers. Bloom et al. (2015) found that workers randomized to work from home had lower promotion rates conditional on performance. Teleworking employees may have less understanding of office dynamics and so be less prepared for promotions. Alternatively, being away from the office may negatively influence managers’ evaluation of worker performance. In experimental work in psychology, Elsbach et al. (2010) find that “observers interpret passive face time as an indicator of specific traits (e.g., responsibility, dependability, commitment, and dedication), and that the context of passive face time (i.e., whether it occurs during vs outside of normal work hours) is critical to the particular traits that judges assigned to those displaying passive face time.” Kossek and Van Dyne (2008) find possible deleterious effects on careers may be one reason workers do not value flexibility more.

A reasonable takeaway from this literature is that lots of workers would like to have jobs where the hours are more regular, where you know in advance what your hours will be and where you can truly unhook from the job in between those hours. For high-skill workers, the greater flexibility is bought at the price of never being truly off the clock. For lower-skill workers, having an employer pay low wages and then also jack around your hours feels like adding insult to injury.

Patents are a tradeoff: they let an inventor escape direct competition, but only for a limited time and for a specific product, and in this way provide an incentive for innovation and–one hopes–heightened future competition.

But of course, there are prominent cases where firms focused on the ability of patents to limit competition. For example, I wrote last fall about \”The Return of the Patent Thicket\” (November 22, 2019), describing the historical example of how Xerox  back in the 1960s and 1970s had taken out more than 1,000 patents on various aspects of the photocopy machine. By continually adding new patents as older patents expired, Xerox had made it essentially impossible for others to enter the market–until the antitrust authorities intervened,

I was recently reminded of another attempt to use patents to block competition by Jen Maffessanti in a short article about  \”Why the Movie Industry Is Fleeing California\” (Foundation for Economic Education website, February 13, 2020). The main focus of the article is about why, in 2017, only 10 of Hollywood\’s top 100 movies were actually made (mostly) in California, and now more movies from Hollywood studios are (mostly) shot in the state of Georgia or in Canada. But along the way, she offers a reminder of when Thomas Edison tried to use his patent on movie technology to lock up monopoly control over the industry. She writes:

Back at the end of the 19th century, motion pictures were a very new technology, and a handful of people held almost all of the patents related to the filming and screening of said films. Chief among them was Thomas Edison. … 

Films at the tail-end of the 19th and beginning of the 20th century in America were made almost exclusively on the East Coast—New Jersey, mostly. Films were short, silent, and lacked much of the subtlety and nuance that modern moviegoers have come to expect from cinema. At the time, though, they were cutting-edge and incredibly popular. One could make a very good living running a show house or nickelodeon in any big city. Right up until December 1908, that is.

That’s when Edison spearheaded the creation of the Motion Picture Patents Company (MPPC), generally referred to as the Edison Trust. It was comprised of the holders of all the significant patents related to the production and screening of motion pictures, including Biograph, Vitagraph, American Mutoscope, Kodak, and others.

Edison was widely known for having strong opinions about what kinds of movies should be made, how long they should be, who should be credited in them, and what it should cost to show them. With the control of the patents he himself owned combined with the collective clout of the other members, the MPPC ruled the movie-making industry with an iron fist. They sued those who didn’t comply with their dictates for patent infringement, refused to sell them equipment and film, and, occasionally, sent hired hooligans to wreck up movie sets or show houses.

As Matthew Lasar explained some years back in \”Thomas Edison’s plot to hijack the movie industry,\” Edison had previously engaged in lawfare to pressure others to sell patents related to movies to him.

But the old man wanted it all, so he assembled his rivals and proposed that they join his Motion Picture Patents Company. It would function as a holding operation for the participants\’ collective patents—sixteen all told, covering projectors, cameras, and film stock. MPPC would issue licenses and collect royalties from movie producers, distributors, and exhibitors.

To top it all off, MPPC convinced the Eastman Kodak company to refuse to sell raw film stock to anyone but Patent Company licensees, a move designed to shut French and German footage out of the country.

Antitrust authorities did move to block Edison after a time. But long story short, a primary reason that the US movie industry ended up in Hollywood was that would-be film-makers and theater-owners were getting as far away from Thomas Edison as they could. For an overview of this and later antitrust issues involve movies, a useful starting pint is \”Breaking the Studios: Antitrust and the Motion Picture Industry,\”  by Alexandra Gil (NYU Journal of Law and Liberty 2008).

The attempts by Thomas Edison and Xerox to use patents as a way of creating broad and lasting monopolies has a broader implication. The ultimate goal of patents is to not to benefits innovators, but to benefit consumers: the benefits to innovators are just a mechanism for encouraging the inventions that will benefit consumers. Indeed, it used to be a fairly standard antitrust practice from the 1940s up through the 1970s to require that firms  be required to offer a \”compulsory license\” soo that others could use key patents, often with no royalty payments at all, as a way of encouraging competition.

One of the most famous cases involved a 1956 consent decree signed by Bell Labs to put all of its patents in the public domain. A number of Silicon Valley old-timers were quick to say that the start of the semiconductor industry would not have been possible without those patents becoming available. For a recent discussion of this case, see \”How Antitrust Enforcement Can Spur Innovation: Bell Labs and the 1956 Consent Decree,\” by Martin Watzinger, Thomas A. Fackler, Markus Nagler, and Monika Schnitzer, which is forthcoming in the American Economic Journal: Economic Policy.

Medtronic, a leading maker of many kinds of medical equipment, offered another example yesterday. Medtronic makes ventilators, but yesterday it announced that it is making available the complete blueprints for one of its popular ventilator products, so that others can see if they are in a good position to start making ventilators. My suspicion is that it\’s not just a good public relations move. If one assumes that lots of ventilators are going to be made and sold in the next few months, and Medtronic knows that it doesn\’t have the capacity to fill the rising demand, it will be to Medtronic\’s long-term benefit if many of the new ventilators follow Medtronic designs–and can benefit from Medtronic training and maintenance. Nonetheless, it\’s a nice example in which a company was able to see beyond the role of intellectual property as just a way of blocking immediate competition.

New technologies are the beating heart of productivity growth and a rising standard of living. But Nicholas Bloom, Charles I. Jones, John Van Reenen, and Michael Webb ask \”Are Are Ideas Getting Harder to Find?\” (American Economic Review, April 2020, pp. 1104-44, not freely available online). The fact that the are asking you the question tells you that their answer is a pessimistic one. This economics research article will be tough sledding for the uninitiated, but the heart of their case is made with some graphs suitable for anyone to mull over.

For example, take an overall look at the US economy, considering the number of researchers and productivity growth. You find that the number of researchers grows by multiples, but productivity growth rises and falls by small amounts. The inference is that it\’s taking a lot more researchers just to keep productivity growth at the same level.

For a specific example, consider Moore\’s law, the notion that the density of semiconductors on a computer chip will double every two years or so. Moore\’s law turned 50 a few years ago, and as I noted at the time, it\’s been getting more and more expensive and difficult to keep doubling the density of chips. As Bloom, Jones, van Reenen and Webb write: \”In particular, the number of researchers required to double chip density today is more than 18 times larger than the number required in the early 1970s. At least as far as semiconductors are concerned, ideas are getting harder to find. Research productivity in this case is declining sharply, at a rate of 7 percent per year.\”

Or how about agricultural crop yields? The green lines show the number of researchers, rising; the blue line shows agricultural productivity growth, falling.

Or how about inventions of new drugs? The authors write:

New molecular entities (NMEs) are novel compounds that form the basis of new drugs. Historically, the number of NMEs approved by the Food and Drug Administration each year shows little or no trend, while the number of dollars spent on pharmaceutical research has grown dramatically … We reexamine this fact … The result is that research effort rises by a factor of 9, while research productivity falls by a factor of 11 by 2007 before rising in recent years so that the overall decline by 2014 is a factor of 5.

Or how about reductions in cancer? Yes, death rates for cancer are falling, but research into fighting cancer has been rising quite rapidly. As a result, it seems to be taking more and more research publications about cancer and more and more clinical trials to reduce cancer deaths by an equivalent amount.

Based on these and other examples, the authors write: \”[J]ust to sustain constant growth in GDP per person, the United States must double the amount of research effort every 13 years to offset the increased difficulty of finding new ideas.\”

In the fashion of honest academics, the authors note in a number of places and in a number of ways that examples like these don\’t prove conclusively that it\’s becoming more costly to find ideas and harder for research to boost productivity. For example:

• Perhaps the measured growth of GDP doesn\’t capture many of the gains that are happening, like free or zero-marginal-cost access to so many goods and services over the internet. 
• Perhaps  there are other examples measures of the gains from research would be rising, not falling. 
• Perhaps Moore\’s law is a bad example, because it involves running into physical  limits, and thus isn\’t representative of other research efforts. 
• Perhaps we are doing fine at discovering new ideas, but our economy is doing a poor job of turning these ideas into commercial products and at diffusing the ideas and products across a wide spectrum of industries and companies. 
• Perhaps the shift away from \”basic research\” funded by governments and toward applied research largely funded by companies has reduced the number of big new ideas. 
• Perhaps more firms are using intellectual property as a defensive technique for warding off competition rather than as a method of moving forward with productivity gains. 
• Overall US R&D spending has been pretty flat for several decades at about 2.5% of GDP, and maybe that\’s the measure of \”research\” on which we should be focusing.
• Perhaps there is some technology threshold for technologies like artificial intelligence, such that once that threshold is reached, very large productivity gains will then be possible, but we just haven\’t hit the threshold yet.   

You can probably add some possibilities to this list. But the weight of the argument from Bloom, Jones, van Reenen and Webb is that if we want technology and new ideas to ride to our rescue in a variety of areas–productivity growth, reducing pollution, improving health care and education, and many others–we need to step up our efforts considerably.

Phillip Swagel, Director of the Congressional Budget Office, blogs on \”Updating CBO’s Economic Forecast to Account for the Pandemic\” (April 2, 2020)

The following are CBO’s very preliminary estimates, which are based on information about the economy that was available through this morning and which include the effects of an economic boost from recently enacted legislation.

Gross domestic product is expected to decline by more than 7 percent during the second quarter. If that happened, the decline in the annualized growth rate reported by the Bureau of Economic Analysis would be about four times larger and would exceed 28 percent. Those declines could be much larger, however.

The unemployment rate is expected to exceed 10 percent during the second quarter, in part reflecting the 3.3 million new unemployment insurance claims reported on March 26 and the 6.6 million new claims reported this morning. (The number of new claims was about 10 times larger this morning than it had been in any single week during the recession from 2007 to 2009.)

Urban areas have traditionally been engines of prosperity and social mobility. But the technologies driving changes in urban structure and the ways in which government responds to these changes has evolved  over time. Edward L. Glaeser prepared the Presidential Address for the Eastern Economic Association on \”Urbanization and Its Discontents\” (Eastern Economic Journal, April 2020, 46:191–21). It\’s also available as NBER Working Paper # 26839. (Both links require a subscription, which most academic libraries will have.)

Glaeser offers a brief reminder of past urban patterns:

Urban fortunes are shaped by technological change. During some periods, technological shifts are largely centripetal, meaning that they pull people toward cities. During other eras, technological trends are centrifugal, meaning that they push people away from dense urban cores.

The nineteenth century was predominantly a centripetal century, marked by series of innovations, including steam engines, streetcars and skyscrapers, that abetted urban growth. The first 60 years of the twentieth century was largely a centrifugal era, largely because technological change reduced the tyranny of distance. Cheaper shipping costs, from highways, cheaper railroads and containerization,
allowed far-flung people to participate more fully in the global economy (Glaeser and Kolhase 2004). Radio and television enabled the rural population to enjoy previously entertainment.

These lower costs reduced the need to locate production near the urban ports and railroads that once anchored all of America’s cities. The mass-produced automobile enabled low density mobility and the rise of car-oriented suburbs (Baum-Snow 2007). These centrifugal technologies first slowed the rise of American cities and then enabled a mass exodus from urban America. The air conditioner made America’s warmer places far more appealing than they had been before World War II, and a move to sun accompanied the move to sprawl. Urban social problems, especially weak schools and crime, were exacerbated by suburbanization and then further encouraged the move to the suburbs and to lower density Sunbelt cities.

However, the last four decades or so have seen a resurgence of many urban areas, based in large part on a rise in the economic importance of proximity. Glaeser explains:

The industrial jobs that had once been the backbone of urban economies did not return. Instead, human capital-intensive business services became the new export industries for urban areas. Financial services expanded enormously in urban America from 1980 to 2007. At its height in 2007, finance and insurance generated over forty percent of the total payroll on the island of Manhattan. The urban edge in transferring knowledge is particularly valuable in finance, because a bit of extra information can make millions for a trader in minutes.

Face-to-face contact is often part of the delivery mechanism for urban services. Clients like to meet their accountants, bankers, lawyers and management consultants in person. Face-to-face contact is even more imperative for barbers and manicurists. Urban interactions enable young workers to become more skilled. … 

Why didn’t improvements in electronic communication make face-to-face contact obsolete? While e-mail is possible almost everywhere, face-to-face interactions generate a richer information flow that includes body language, intonation and facial expression. As the world became more complex, the value of intense communication also increases. Physical immersion in an informationally intense environment, such as trading floor or an academic seminar, generates a rush of information that is hard to duplicate online. Moreover, dense environments facilitate random personal interactions that can create serendipitous flows of knowledge and collaborative creativity. The knowledge-intensive nature of the urban resurgence helps to explain why educated cities have done much better than uneducated cities. ..

While highly educated workers moved into professional and business services, successful cities also generated employment for less skilled workers in other parts of the service economy. Many workers switched from manufacturing to wholesale and retail trade during the 1990s. Hospitality and food services also expanded dramatically after 1980. Employment in these service industries depends on the demand generated by the success of more export-oriented services, like finance. In areas that lack viable export industries, the dominant sector is typically healthcare and social assistance, where demand is maintained by Federal transfers.

Cities also came back as places of consumption as well as places of production (Glaeser et al. 2001), which partially reflects the rise in returns to skill. As Americans became better educated and as educated people came to earn more, they spent more on higher-end urban pleasures, such as fine dining, art galleries and expensive retail. Young people increasingly lived in cities, even as they worked in suburbs. Prices rose dramatically in urban cores and remained flat in the suburbs.

This description also helps to what is being lost by the pandemic-induced recession. Yes, some workers can do many basic parts of their jobs from home, and students can do some work with online courses. But the \”richer information flow\” of \”face-to-face interactions\” in both production and consumption is being lost for a time, and while the network of such interactions can certainly be rebuilt, it doesn\’t flip on and off like a light switch.

The resurgence of many cities has also brought with it a new group of problems, as Glaeser details.

One change is that cities do not seem to be functioning as ladders of opportunity. It may be that the extent of social and ethnic segregation–in terms of who you have significant interactions with on a typical day–can be higher in urban areas. Schools in urban core areas have often not recovered from their declines back in the 1970s. Glaeser writes: \”It is a great paradox that cities appear to be forges of human capital for adults, but places where children seem to learn less productive knowledge.\”

Cities are also places of growing income inequality. Skilled workers in a large city or a downtown typically earn more than workers of similar skill outside those locations, but unskilled workers often do not have a similar pay boost from working in a city or downtown area.

Part of the issue may be government regulation of lower-skilled entrepreneurs. As Glaeser trenchantly notes:

Somewhat oddly, much of America appears to regulate low human capital entrepreneurship much more tightly than it regulates high human capital entrepreneurs. When Mark Zuckerberg started Facebook in his Harvard College dormitory, he faced few regulatory hurdles. If he had been trying to start a bodega that sold milk products three miles away, he would have needed more than ten permits. One question is whether the inequality that persists in America’s system is exacerbated by the legal and regulatory system.

And of course, the extremely high cost of housing in a number of economically strong urban areas makes it very hard for the middle-class, let alone those with lower skill levels, to pay the rent. Glaeser says:

For much of the post-war period, many urbanites could find housing that cost substantially less than construction costs even in successful cities (Glaeser and Gyourko 2005a). Housing depreciates, like cars and clothing, and so poorer urbanites could find older apartments in less fashionable neighborhoods that cost less. Filtering models predict that neighborhoods go through transitions, and that the rich would live in a newer, nicer areas but the poor occupy older, more dilapidated areas. The rich vacate areas as they depreciate and then move to a new area that had been built with higher-quality housing. Apparently, this model appears to have broken down after 1970, probably because of regulation and increased neighborhood opposition to redevelopment.

There is a persistent theme in American culture of moving to the big city, finding a low-level job, and working your way up. But US cities have become places where it\’s more costly to move in because the rent looks unthinkably high, and harder to find that low-skilled job, and then harder to move up unless you develop a high skill level. Add traffic congestion, and concerns about poor schools and crime, and moving to the big city doesn\’t look so attractive.

Glaeser argues that today\’s urban problems often reflect poor performance by local governments, who when it comes to housing markets, labor issues, schools, and other areas, have in recent decades often focused on blocking change or supporting insider groups. He writes:

Why has urban success been accompanied by so much discontent? The most natural explanation is that the success of private enterprise in cities has not been accompanied by sufficient development of public capacity. The public sector has often focused on limiting urban change, rather than working to improve the urban experience. In many cases, this focus reflects the political priorities of empowered insiders. … There are many good things about citizen empowerment, but the most empowered citizens tend to be longer-term residents with more resources. Those citizens do not internalize the interests of people who live elsewhere and would want to come to the city. Consequently, their political actions are more likely to exclude than to embrace.