Tuesday, April 20, 2021

The US Net International Investment Position, aka "Debtor Nation"

US investors of all types--individual, corporate, government--purchase debt and equity issued in other countries. International investors of all types--individual, corporate, government--purchase debt and equity issued in the United State. The US Bureau of Economic Analysis estimates the total holdings of foreign assets by US investors, and the total holdings of US assets by foreign investors. Here's the tally from the BEA: 
Back in 2011,  US-owned assets abroad (blue line) were about $2.5 trillion less than the US liabilities owned by foreign investors (orange line). At the end of 2020, the gap had risen to $14 trillion. This is the US "net international investment position."

This gap can change for two main reasons. One reason is that, in a given year, the inflow and outflow of financial investments to and from the US economy don't need to balance. In fact, when the US economy runs trade deficits, with imports greater than exports, it necessarily means that the US economy is consuming (with imports included) more than it is producing (with exports included). As economists are quick to point out, the result of this situation is that foreign parties will take some of the US dollars they have earned, and invest them in US financial assets. 

The other reason the gap can change is that prices of financial assets can move around. For example, the S&P 500 stock market index has more than tripled in the last decade. Thus, the liabilities of the US economy to foreign investors who purchased US stocks a decade ago will be much larger as a result. Indeed, the BEA estimates that the value of foreign holdings of US portfolio assets--that is, holding debt or equity, but not with control of the US company--rose from $12 trillion a decade ago to more than $24 trillion at present, thus accounting for essentially all of the larger gap between US foreign assets and US foreign liabilities shown in the figure above. When comparing the size of foreign assets and liabilities over time, movements in exchange rates will also matter. 

Because the value of US foreign liabilities exceeds that of US foreign assets, the US is sometimes referred to as a "debtor nation." The name isn't quite right for several reasons. When you read about the "national debt," the reference is usually to the accumulated debt from US government borrowing. But while this measure included government debt that is involved international investment decisions, it also include private sector choices about international investments in debt and equity as well. 

How much should Americans be worried about the fact that the US net international investment position is negative $14 trillion. Gian Maria Milesi-Ferretti suggests that it shouldn't be cause for large concern (Brookings Institution, "The US is increasingly a net debtor nation. Should we worry?" (April 14, 2021).  He breaks down the US net international investment position into flows of debt and flows of equity. In addition, he breaks down debt and equity into "flows" and "position," where "flows" describes the amount flowing back and forth across the border, and "position" includes changes in the total value of debt and equity.
The figure shows that the common pattern for the US economy during the last quarter-century is that foreign investors hold much more in US-issued debt than US investors hold in foreign debt. One main reason for that is that US-dollar debt--especially the debt issued by the US government, is viewed around the world as a safe asset. The US dollar has been the world's dominant currency for a long time.

However, during the last 25 years, US investors have tended to hold more in international equity than foreign investors held in US equity. The dashed blue line shows that flows of equity investment back and forth across the border haven't changed a lot. But because of the sharp rise in US stock markets, and also the stronger value of the US dollar, the total value of foreign holdings of US equity have risen compared to US holdings of foreign equity--and the US net international investment position has fallen accordingly.  Milesi-Ferretti writes: 
Since 2010, ... the net international investment position has plunged by some 50 percent of GDP. This time the valuation effects have worked in reverse: the U.S. dollar has strengthened notably since 2010, and U.S. equity prices have risen much more than foreign equity prices. In other words, the value of foreigners’ investments in the U.S. has risen a lot relative to the value of Americans’ investments abroad.

Thus, one way to look at the fall in US net international investment position is that it's the result of good news--a rising US stock market. 

The other important pattern here is that, in general, if you have $100 in debt it will pay a lower return than $100 in equity, basically because the debt is safer than the equity. The US investment in foreign equity is often in the form of "foreign direct investment," where a US firm owns a large enough share of a foreign firm that the US firm has a say in managing the foreign firm (although the US firm may not have complete control over the foreign firm). This means that US investments abroad systematically earn more than foreign investments in the US. Here's a figure from Milesi-Ferretti:

Indeed, even though the rest of the world owns $14 trillion more in US assets than US investors own in foreign assets, it has been and continues to be true that the actual total returns paid on assets held in other countries is higher for US investors holding foreign assets than it is for foreign investors  holding US assets. 

I sometimes say that when it comes to international investment, the US economy is like a company that borrows money at a low interest rate and then invests that money in corporate stock and receives a higher rate of return. There are of course risks to this approach, but it's been this way for the US economy for a long time and there are clearly benefits, too. 

Sunday, April 18, 2021

A Hive of Authentic College Applicants

As someone with a couple of college-age children who have navigated the admissions process at selective colleges, I found myself nodding in agreement with Matt Feeney's essay in the Chronicle of Higher Education, "The Abiding Scandal of College Admissions: The process has become an intrusive and morally presumptuous inquisition of an applicant’s soul" (April 16, 2021). 

A basic fact is that applications at selective colleges are way up, and given a fixed number of slots of students, acceptance rates are way down. For example, the Washington Post just reported: "Columbia's applications were up a stunning 51 percent this year, and Harvard's were up 42 percent. There were also double-digit increases at Brown (27 percent), Dartmouth (33 percent), Princeton (15 percent), the University of Pennsylvania (33 percent) and Yale (33 percent)." Acceptance rates at places like Harvard, Stanford, and Princeton are in the range of 4-5%.

When a school is accepting only one applicant of every 20, or every 10, or every five, you might think that the school would want to be clear with applicants about their low odds--before those applicants invest time, sweat, soul, and money in writing the essays and doing the paperwork. But of course, that's incorrect. Lots of applicants and a low acceptance rate may mean wasted time and enormous disappointment for applicants, but it looks good for the school. 

So instead, selective schools encourage everyone to apply: we were on tours at multiple selective schools that started with hundreds of people in auditoriums where such encouragement was given. We were repeatedly not to worry too much about test scores or high school grades--although even the most casual acquaintance with the facts about who is actually admitted suggests that these measures are pretty important. Instead, the emphasis was, as Feeney points out, on "holistic admissions" and "authentic" application that demonstrates the real specialness of you. 

On one side, saying that it's all about "authenticity" is an encouragement to apply. On the other side, if not accepted based on your authentic self, while others are accepted based on their authentic selves, it will seem pretty clear to an overwhelming majority of applicants that either your authentic self was either presented poorly or judged and found wanting. It's all too reminiscent of what Groucho Marx said about "sincerity," "If you can fake that, you've got it made." 

Moreover, it's clear at selective colleges that the applicant all need to show their special personal authenticity in some very specific ways: grades/test scores, involvement in extracurriculars and the community, ability and willingness to diagnose and write about their own selves, and so on. 

As Feeney points out, as college admissions have become more selective in recent decades, what the admissions people say they are looking at and emphasizing has changed, too. There was a stretch in the 1980s and 1990s where the emphasis was on extracurricular activities and the "well-rounded" applicant After this (quite predictably).after this resulted in an epidemic of extreme resume-padding, "more recently they have come to favor the passionate specialist, otherwise known as the `well-lopsided' applicant." Apparently on the horizon is an admissions online platform that will let you start storing your essays and videos starting in ninth grade. 

(Bad news here for applicants to selective colleges: Multiply the number of applicants by, say, a generously estimated one or two hours to look over every application. The admissions personnel on average don't have much more time than that. The idea that they are going to spend many hours looking over video and text of the best science reports, short stories, choir/band concerns, sports team highlights, and community service projects for every applicant is delusional. At best, they could skim and skip through a few entries for specific applicants.) 

Here's Feeney in the Chronicle of Higher Education:  
The people who made applying to college an elaborate performance, a nervous and years-long exercise in self-construction have now decided that the end result of this elaborate performance must be “the real you.” The tacit directive in all this — “Be authentic for us or we won’t admit you” — puts kids in a tough position. It’s bad that kids have to suffer this torment. It’s also bad that admissions departments actually think that the anxiously curated renderings that appear in applications can in any way be called “authentic.” It’s like watching Meryl Streep portray Margaret Thatcher and thinking: Now that is the real Meryl Streep. ... 

What distinguishes an applicant here is not authenticity, but access to the best advice on how to create the right authenticity effect — cultured parents, costly admissions coaches, able and informed college counselors. ... This points to another dark aspect of all this personalizing, with its imposed subtleties of performance and discernment — the barely hidden class bias. Admissions personnel are generally eager to add their voices to the chorus bewailing the socioeconomic and racial bias in standardized testing, but they’re largely incurious about the class bias in their own softer measures. In practice, that is, what ends up resembling “authenticity” to admissions officers is an uncannily WASPy mix of dispensations better understood as discretion, or, perhaps, good taste. After all, what admissions readers really dislike are the braggarts, and isn’t bragging a vice of the classless, the parvenus and arrivistes? ...

Admissions bureaucrats faced with thousands more applicants than they can accept soon reach a level of arbitrariness. At that point, they launch an inquisition of their applicants’ souls. This makes little sense academically but allows them to stage a powerful, utterly undeserved disciplinary claim on the inner lives of teenagers — that is the abiding scandal of college admissions. ....

Admissions officers have come to see the process they oversee in therapeutic terms. They present the college application as a set of therapeutic prompts, gentle invitations for the applicant to free herself from repression and self-deceit and move toward authentic self-expression and self-knowledge. ...

Setting up a years-long, quasi-therapeutic process in which admissions goads young people into laying bare their vulnerable selves — a process that conceals a high-value transaction in which colleges use their massive leverage to mold those selves to their liking — is reprehensible. It is terrible thing to do. It renders the discovery of true underlying selves absurd. Sometimes, as we’ve seen, admissions people will admit they have this formative leverage over young people. But they fail to show the humility that should attend this admission, the clinician’s awareness that to use this power is to abuse it. Instead, they want even more power. They want to intrude even more deeply into the souls of their applicants. ...
I can easily understand some sensible reasons why colleges want their own admissions department. Sometimes there is a really good fit between the abilities and interests of student and the specific strengths of an institution. Pools of applicants will vary from year to year, and there's some logic in trying to make sure that you admit a class that has a degree of balance in terms of academic interests, nonacademic interests, and geographic and demographic characteristics. 

But with no deep disrespect meant to the admissions personnel at selective colleges and universities, who I think are mostly just doing the best they can, they aren't professors or therapists. So who died and made them the monarchs of defining what is the desirable kind of authenticity, and how a holistic view of that authenticity should be expressed?  Especially the authenticity of 17 year-olds? 

Friday, April 16, 2021

Interview with Esther Duflo: On Experimental Methods and Inequality

Douglas Clement provides an "Esther Duflo interview: Deciding how to share" (For All: Federal Reserve Bank of Minneapolis, Spring 2021).  

On the existence of a tradeoff between growth and inequality:
I think the whole notion of a trade-off is likely a fallacy, for various reasons. First of all, there is no clear link either on theoretical grounds or empirically between higher inequality and more growth. There is no reason why inequality is necessary for growth. And there is no law of economics that says that growth increases inequality either. So I think there is no causality necessarily going in either direction; therefore, there is not necessarily a trade-off. Just as a matter of accounting, growth is equality-enhancing if most of the benefits of growth are going toward the poor. And growth is inequality-enhancing if most of the advantages are going toward the rich. Both are possible. I don’t think there is a systematic pattern either way. ... 

In fact, we don’t seem to have much of a handle on what causes growth anyway, although we might have interesting theoretical narratives on growth. If there is a consensus among macroeconomists, it’s on what should be avoided at all costs, like hyperinflation. But there is not a set of recipes that guarantees growth, and it’s not that these recipes therefore lead to a trade-off. So, I think there is actually no trade-off.
On how evidence from randomized control trials is like a pointillist painting
The idea of the pointillist painting is, imagine a painting by Seurat. It’s literally made of dots, and each of these dots on its own is perfectly nice, but it doesn’t generalize to anything. But if you step back and accumulate all these dots, you see the entire painting of, say, a family on the bank of the Seine having a picnic.

Suppose you’re trying to assemble a jigsaw puzzle of that Seurat painting. Just by looking at the rest of the painting, you sort of know what goes next. You have a prediction about where a given piece fits. You might find that your piece doesn’t fit. It might be wrong. It’s not what you expected. But the frame, the painting, gives you good guidance for what you might expect.

That’s how progress happens. The caricature is that you try one small experiment in one place, and then you can take the result to the entire world. That’s not it. The way it actually works is: Do your small experiment; get some findings that are interesting. They might contradict or confirm the theory that you started from, but they give you fodder for the next experiment, and so on and so forth, until you have an understanding of what might be the entire shape or contour of that problem.
On using the superstar power of economists to save lives
My husband, Abhijit Banerjee, also a Nobel Prize laureate, was asked to be the chairman of the coronavirus response team in West Bengal. ... We knew from previous work ... that stars and celebrities are very influential in conveying these messages, so we were looking for stars to pass along very basic social distancing advice to households in India at a time when it was completely confusing. It finally dawned on us that the best star we had was right on our team! Abhijit Banerjee has been a bit of a household name in West Bengal—where he’s from—since he won the Nobel Prize. ...

Abhijit recorded messages that were sent in two rounds to subscribers with Airtel, a bigger subscriber network. One message was about asking people to be kind to coronavirus patients and not to shun them out of the village, and the other was about how travel during Durga Puja, where people normally come in droves to town and make pilgrimages to makeshift temples. So, potentially, a scene of millions of people crowded together, coming from everywhere and going back. It could have been a coronavirus disaster.

Abhijit worked with others in putting together something that was feasible. You cannot say, “Cancel the holiday.” That’s not really an option. So something that was feasible, but would improve things. And we sent one more round of messages urging people to stay home if they’re older, and if they do go out, visit just one location, and wear a mask.

And quickly after that, Durga Puja happened, and we saw that the attendance was down a significant amount from previous years. So it was much, much, much lower attendance. And we can now see whether there was an uptick of coronavirus and we don’t see that.

So, of course, it was not just his messages. There was also the chief minister went on television to relay the message. But this entire effort to convince people with clear messages about what to do seems to have been very effective. I’m convinced that that saved thousands and thousands of lives ultimately. You don’t get to do that every day.

For an earlier post on the award of the 2019 Nobel Prize in economics to Duflo, Banerjee, and Michael Kremer, see "A Nobel for the Experimental Approach to Global Poverty for Banerjee, Duflo, and Kremer" (October 18, 2019). 

Thursday, April 15, 2021

Pharma R&D: Vaccines and Other Drugs

Surely one of the key lessons of the pandemic is the value of research and development, which in turn means the value of making the investments over time in education and equipment so that researchers are tooled up and ready to go as needed. The Congressional Budget Office has published "Research and Development in the Pharmaceutical Industry" (April 2021), which offers a useful primer in getting up to speed on some of the key trends and issues. Here are five of the main themes as I see them. 

1) Research and development may play a bigger role in pharmaceuticals than in any other industry. 

This figure shows how much different industries spend on R&D as a share of their "net revenues"--that is, revenues minus expenses. A few years back, pharmaceuticals were similar in their "research intensity" to industries like semiconductors and software, but in the last decade or so, pharma has become even more research-intensive. 

Pharma R&D spending has gone way up. The CBO writes: 

In real terms, private investment in drug R&D among member firms of the Pharmaceutical Research and Manufacturers of America (PhRMA), an industry trade association, was about $83 billion in 2019, up from about $5 billion in 1980 and $38 billion in 2000. Although those spending totals do not include spending by many smaller drug companies that do not belong to PhRMA, the trend is broadly representative of R&D spending by the industry as a whole. A survey of all U.S. pharmaceutical R&D spending (including that of smaller firms) by the National Science Foundation (NSF) reveals similar trends.

Let's say that again: in real (that is, adjusted for inflation) dollars, pharma R&D is up by a factor of about 10 from the average in the 1980s and even before the pandemic had more than doubled since 2000. The CBO also points out that the cost of developing a successful new drug can commonly be in the range of $1-$2 billion, once the costs of the drugs that didn't work out are included, and the process of developing a drug so that it's ready to sell can take a decade or more. 

2) There's controversy over the direction of pharma R&D spending. 

Pharma companies will be attracted by producing expensive drugs for big markets. Conversely, the incentive for a drug company to spend $1 billion  and a decade addressing a smaller market or finding a lower-cost alternative to an existing money-maker will not be large. The CBO writes: 

The number of new drugs approved each year has also grown over the past decade. On average, the Food and Drug Administration (FDA) approved 38 new drugs per year from 2010 through 2019 (with a peak of 59 in 2018), which is 60 percent more than the yearly average over the previous decade. Many of the drugs that have been approved in recent years are “specialty drugs.” Specialty drugs generally treat chronic, complex, or rare conditions, and they may also require special handling or monitoring of patients. Many specialty drugs are biologics (large-molecule drugs based on living cell lines), which are costly to develop, hard to imitate, and frequently have high prices. Previously, most drugs were small-molecule drugs based on chemical compounds. Even while they were under patent, those drugs had lower prices than recent specialty drugs have. Information about the kinds of drugs in current clinical trials indicates that much of the industry’s innovative activity is focused on specialty drugs that would provide new cancer therapies and treatments for nervous-system disorders, such as Alzheimer’s disease and Parkinson’s disease.

Here's a figure showing the therapeutic areas where US drug spending has increased the most in the last decade. The big ones at the top are drugs to address cancer, diabetes, and autoimmune diseases. Because these are the big markets, this is also where pharma R&D for future drugs will tend to be focused. 

3) There's controversy over the role of larger and smaller pharma companies. 

The pharma industry has developed a partial division of labor, where smaller companies are more likely to be doing R&D, and larger companies are more likely to be leading the way on the clinical testing needed before the drugs come to market. Thus, a common dynamic is that if a small company has developed a promising drug, either the drug or the entire company may be bought by a larger firm. There's nothing necessarily wrong with this dynamic. It gives successful entrepreneurs a way to start small and then cash out when successful. But it does raise a danger that big pharm companies are buying out the very firms that could, in time, have grown into being their future competitors. There's evidence that in some cases, large pharma companies have bought smaller firms with a new drug that might have competed with existing drugs--and then halted development of the new drug. The CBO writes (footnotes and references to text boxes omitted): 

Although total R&D spending by all drug companies has trended upward, small and large firms generally focus on different R&D activities. Small companies not in PhRMA [the trade association of big pharma companies] devote a greater share of their research to developing and testing new drugs, many of which are ultimately sold to larger firms. By contrast, a greater portion of the R&D spending of larger drug companies (including those in PhRMA) is devoted to conducting clinical trials, developing incremental “line extension” improvements (such as new dosages or delivery systems, or new combinations of two or more existing drugs), and conducting post-approval testing for safety-monitoring or marketing purposes. ...

Small drug companies (those with annual revenues of less than $500 million) now account for more than 70 percent of the nearly 3,000 drugs in phase III clinical trials. They are also responsible for a growing share of drugs already on the market: Since 2009, about one-third of the new drugs approved by the Food and Drug Administration have been developed by pharmaceutical firms with annual revenues of less than $100 million. Large drug companies (those with annual revenues of $1 billion or more) still account for more than half of new drugs approved since 2009 and an even greater share of revenues, but they have only initiated about 20 percent of drugs currently in phase III clinical trials.

4) The government has always played an important role in vaccine markets, with its requirements for who needs to get vaccinated. And of course, the government played a substantial role in developing COVID-19 vaccines with the Warp Speed program. 

Here's the CBO summary of what companies got money for a COVID-19 vaccine, and for what purpose.  Given the costs of COVID-19, this $19 billion probably ranks with the most cost-effective money the US government has ever spent on anything.

5) Research expertise in vaccines, as in many other areas, often can shift from one disease to another, so that what looks like "failure" in producing a vaccine for one disease can build expertise in addressing a different disease. 

For example, it turns out that although the effort to produce an HIV vaccine has not so far been successful, many of of the technologies and skills developed in that search were useful in creating a ?COVID-19 vaccine (for discussions of this point, see here and here). 

Jeffrey E. Harris argues this case in some detail in "The Repeated Setbacks of HIV Vaccine Development Laid the Groundwork for SARS-COV-2 Vaccine" (March 2021, NBER Working Paper 28587). As he points out, before AIDS the common vaccines were "dead" or "live." A "dead" vaccine (like the polio vaccine) treated the infectious organism with heat or chemicals so that it was no longer infectious, but still helped the body to produce an immune response. A "live" vaccine (like the measles vaccine) ran the infectious organism through animals or other treatments to produce a version that produced only a very mild infection--but still caused the body to produce an immune response. 

But neither method worked in trying to produce a vaccine for the highly mutable AIDS virus. Instead, working on an AIDS vaccine forces researchers to think about how a vaccine might attack the molecular structure of AIDS. I won't embarrass myself by trying to summarize the progression of scientific research, but it turns out that a key "spike" protein that had been studies in the HIV research turned out to be the key protein for the mRNA vaccines that are being used against COVID-19. In addition, discussions in the trade press suggest that, in turn, the knowledge gained from the COVID-19 vaccine about mRNA technologies could help lead to a vaccine for malaria, hepatitis C, dengue--and even HIV.  

The broader point is that although private pharma firms clearly have strong incentives to do R&D aimed at large existing drug markets, there is a broad social benefit from having research into many areas of vaccines and other drugs, because you can't know in advance how scientific progress will lead to practical gains. 

Tuesday, April 13, 2021

What Do You Call a Bigger Wave of Debt?

Sometimes you work on a big and worthwhile project, and then find yourself to be overtaken by events. The project remains worthwhile, but it can suddenly feel outdated. Thus, I found myself wincing in sympathy at  Global Waves of Debt: Causes and Consequences, a World Bank report written by M. Ayhan Kose, Peter Nagle, Franziska Ohnsorge, and Naotaka Sugawara and published in March 2021. 

The problem is that the report focuses on four major waves of government debt up through 2018. Of course, when the authors launched into this project they had no way of knowing that the world was on the cusp of a COVID-related surge in government debt starting in 2020.  But the result is that the authors are warning of the potential dangers of a wave of government debt given the debt levels of 2018--but pandemic-related debt wave is now bigger than they would have anticipated. For example, they write: 

The global economy has experienced four waves of broad-based debt accumulation over the past 50 years. In the latest wave, underway since 2010, global debt has grown to an all-time high of 230 percent of gross domestic product (GDP) in 2018. The debt buildup was particularly fast in emerging market and developing economies (EMDEs). Since 2010, total debt in these economies has risen by 54 percentage points of GDP to a historic peak of about 170 percent of GDP in 2018. Following a steep fall during 2000-10, debt has also risen in low-income countries to 67 percent of GDP ($268 billion) in 2018, up from 48 percent of GDP (about $137 billion) in 2010. ...

Before the current wave, EMDEs [emerging market and developing economies] experienced three waves of broad-based debt accumulation. The first wave spanned the 1970s and 1980s, with borrowing primarily accounted for by governments in Latin America and the Caribbean region and in low-income countries, especially in Sub-Saharan Africa. The combination of low real interest rates in much of the 1970s and a rapidly growing syndicated loan market encouraged these governments to borrow heavily.

The first wave culminated in a series of crises in the early 1980s. Debt relief and restructuring were prolonged in the first wave, ending with the introduction of the Brady Plan in the late 1980s for mostly Latin American countries. The Plan provided debt relief through the conversion of syndicated loans into bonds, collateralized with U.S. Treasury securities. For low-income countries, substantial debt relief came in the mid-1990s and early 2000s with the Heavily Indebted Poor Countries initiative and the Multilateral Debt Relief Initiative, spearheaded by the World Bank and the International Monetary Fund.

The second wave ran from 1990 until the early 2000s as financial and capital market liberalization enabled banks and corporations in the East Asia and Pacific region and governments in the Europe and Central Asia region to borrow heavily, particularly in foreign currencies. It ended with a series of crises in these regions in 1997-2001 once investor sentiment turned unfavorable. The third wave was a run-up in private sector borrowing in Europe and Central Asia from European Union headquartered “mega-banks” after regulatory easing. This wave ended when the global financial crisis disrupted bank financing in 2007-09 and tipped several economies in Europe and Central Asia into recessions. ... 

The latest wave of debt accumulation began in 2010 and has already seen the largest, fastest, and most broad-based increase in debt in EMDEs in the past 50 years. The average annual increase in EMDE debt since 2010 of almost 7 percentage points of GDP has been larger by some margin than in each of the previous three waves. In addition, whereas previous waves were largely regional in nature, the fourth wave has been widespread with total debt rising in almost 80 percent of EMDEs and rising by at least 20 percentage points of GDP in just over one-third of these economies. ... 
Since 1970, there have been 519 national episodes of rapid debt accumulation in 100 EMDEs, during which government debt typically rose by 30 percentage points of GDP and private debt by 15 percentage points of GDP. The typical episode lasted about eight years. About half of these episodes were accompanied by financial crises, which were particularly common in the first and second global waves, with severe output losses compared to countries without crises. Crisis countries typically registered larger debt buildups, especially for government debt, and accumulated greater macroeconomic and financial
vulnerabilities than did noncrisis countries.
Although financial crises associated with national debt accumulation episodes were typically triggered by external shocks such as sudden increases in global interest rates, domestic vulnerabilities often amplified the adverse impact of these shocks. Crises were more likely, or the economic distress they caused was more severe, in countries with higher external debt—especially short-term—and lower international reserves.
Of course, pandemic-related debt has increased the previous debt projections. Here are some figures from the IMF Fiscal Monitor published in April 2021. The first panel shows debt/GDP ratios from 2007 to 2021. The yellow lines show interest payments, which so far have been able to remain fairly low thanks to the prevailing low interest rates. The rising debt/GDP ratios in emerging market and developing economies are clear.
The second set of panels shows how debt projections have changes since the pandemic for these three groups of countries. The bars show annual deficit/GDP predictions, pre- and post-pandemic, while the lines show the shift in accumulated debt, pre- and post-pandemic. 
As the authors of the World Bank report above point out in their discussion, rising debt does not automatically bring disaster. The sharp-eyed reader will note that the debt/GDP ratios for advanced economies are higher than those for emerging market and developing economies. There is a general pattern that as an economy develops, the financial sector of that economy also develops in ways that typically lead to a higher debt/GDP ratios. More broadly, the depth of the financial sector and the sophistication of financial regulation will make a big difference. 

On the other side, debt is often referred to as "leverage," because it magnifies the outcome of both positive and negative events for a national economy (or for a company or a household)  . With a higher level of debt, an adverse event can easily become two problems--the adverse event itself and also a debt crisis. It is concerning that this risk was viewed as high for many countries around the world, even before they increased their debt during the pandemic. 

Monday, April 12, 2021

The US Productivity Slowdown After 2005

In the long run, a rising standard of living is all about productivity growth. When the average person in a country produces more per hour worked, then it becomes possible for the average person to consume more per hour worked. Yes, there is a meaningful and necessary role for redistribution to the needy. But the main reason why societies get rich is by redistributing more: rather, societies are able to redistribute more because rising productivity expands the size of the overall pie. 

In the latest issue of the Monthly Labor Review from the US Bureau of Labor Statistics, Shawn Sprague provides an overview in "The U.S. productivity slowdown: an economy-wide and industry-level analysis" (April 2021). In particular, he is focused on the slowdown in US productivity growth since 2005, after a resurgence of productivity growth in the previous decade. Here's a figure showing the longer-run patterns, which have birthed roughly a jillion research papers. 
Notice that total productivity growth is robust in the decades after World War II, from 1948 to 1973. Then there is a productivity slowdown, especially severe in the stagflationary 1970s, but continuing through the 1980s and into the 1990s. There's a productivity surge from 1997 to 2005, commonly attributed to acceleration in the power and deployment of computing and information technology. But just when it seemed as if the economy might be moving back to a higher sustained rate of productivity growth, then starting around 2005, productivity sagged back to the levels of the slowdown in the 1970s and 1980s. 

The figure also shows how economists break down sources of economic growth. First look at how much the quality of the labor force has improved, as measured by education and experience. Then look at how much capital the average worker is using on the job. After calculating how much productivity growth can be explained by those two factors, what is left over is called "multifactor productivity growth." This is often interpreted as changes in technology--broadly understood to include not just new inventions but all the ways that production can be improved. But as the economist Moses Abramowitz said years ago, measuring multifactor productivity growth as what is left over, after accounting for other factors, means that productivity growth is "the measure of our ignorance."

As Sprague points out, variations in multifactor productivity growth are the biggest part of changes in productivity over time. 
The deceleration in MFP growth—the largest contributor to the slowdown—explains 65 percent of the slowdown relative to the speedup period; it also explains 79 percent of the sluggishness relative to the long-term historical average rate. The massive deceleration in MFP growth is also emblematic of a broader phenomenon shown in figure 2. We can see that throughout the historical period since WWII, the majority of the variation in labor productivity growth from one period to the next was from underlying variation in MFP growth, rather than from the other two components.
However, the most recent slowdown in productivity also seems to have something to do with capital investment. Sprague again: 
At the same time, in addition to the notable variation in MFP growth during the recent periods, something unprecedented about these recent periods was the additional contribution from variation in the contribution of capital intensity. The contribution of capital intensity had previously remained within a relatively small range (0.7 percent to 1.0 percent) during the first five decades of post-WWII periods, but then in the 1997–2005 period, the measure nearly doubled, from 0.7 percent up to 1.3 percent, followed by nearly halving to 0.7 percent in the 2005–18 period. ... The contribution of capital intensity accounts for 34 percent of the labor productivity slowdown relative to the speedup period and explains 25 percent of the sluggishness relative to the long-term historical average rate.
What are some possible explanations for the growth slowdown? As Sprague writes: [N]not only has the productivity slowdown been one of the most consequential economic phenomena of the last two decades, but it also represents the most profound economic mystery during this time ..." Sprague does a detailed breakdown of economy-wide factors that may have contributed to the productivity slowdown as well as industry-specific factors. Here, I'll just mention some of the main themes. 

A first set of explanations focus on the Great Recession, and the sluggish recovery afterwards. One can argue, for example, that when the financial sector is in turmoil and an economy is growing slowly, firms have less ability and less incentive to raise capital for productivity gains. This seems plausible, and surely has some truth in it, but it also has some weak spots. For example, the productivity slowdown in the data pretty clearly starts a few years before the Great Recession. Also, one might argue that in difficult times, firms might have more incentive to seek out productivity gains. Finally, it feels like a circular argument to ask "why aren't additional inputs producing output gains as large as before?" and then to answer "because the output gains were not as large as before." 

A second explanation is that productivity gains at the frontier have not actually slowed down: instead, what has slowed down is the rate at which these gains are diffusing to the rest of the economy. From this point of view, the real news is a wider dispersion in productivity growth within industries, as productivity laggards fall farther behind leaders (for discussion, see here and here). At a more detailed level, "not many of the firms that have been innovating have not similarly been able to scale up and hire more employees commensurate with their improved productivity." It could also be that there are certain characteristics of productivity growth leaders--like an ability to apply leading-edge information technology to business processes throughout the company--that are especially hard for productivity laggards to follow. This lack of reallocation in the economy toward high-productivity firms may be related to other prominent issues like a decrease in levels of competition in certain industries or rising inequality. 

A third explanation is that the productivity surge from 1997-2005 should be be viewed as a one-time anomalous event, and what's happening here is a long-term slowdown in the rate of productivity growth. Sprague writes: 
One underlying rationale for this potential story is provided by Joseph A. Tainter. This author offers that, in general, as complexity in a society increases following initial waves of innovation, further innovations become increasingly costly because of diminishing returns. As a result, productivity growth eventually succumbs and recedes below its once torrid pace: “As easier questions are resolved, science moves inevitably to more complex research areas and to larger, costlier organizations,” clarifying that “exponential growth in the size and costliness of science, in fact, is necessary simply to maintain a constant rate of progress.” Nicholas Bloom, Charles I. Jones, John Van Reenen, and Michael Webb offer supporting evidence for this view regarding the United States, asserting that given that the number of researchers has risen exponentially over the last century—increasing by 23 times since 1930—it is apparent that producing innovations has become substantially more costly during this period.
Again, this explanation has some plausibility. But it also feels as if the modern economy does have a substantial number of innovations,  and the puzzle is why they aren't showing up in the productivity statistics.

A fourth set of explanations digs down into which industries showed the biggest falls in productivity after 1995 and which ones showed the biggest rises. Here's an illustrative figure. The industries with the biggest losses are computers/electronics products, along with retail and wholesale trade. 
This selection of industries may feel counterintuitive, but remember that this is a comparison between two time periods. Thus, the figure isn't saying that productivity outright declined in these sectors--only that the gain after 2005 was slower than the gain in the pre-2005 decade. In computers, for example, rate of decline in  prices of microprocessors began to slow down in the mid-2000s. Similarly, retail and wholesale businesses underwent a huge change in the late 1990s and early 2000s that increased their productivity, but then the changes after that time were more modest.  In short, this is the detailed version industry-level version of the argument that the productivity rise from 1997-2005 was a one-time blip.

A final explanation, not really discussed by Sprague, is worth considering as well: Perhaps we are entering an economy where certain kinds of gains in output are not well-reflected in measured GDP gains. For example, imagine that the development of COVID-19 vaccines halts the virus. The social welfare gains from such vaccines are much larger than just the measured gains to GDP. Or imagine that a set of innovations makes it possible to reduce carbon emissions in a way that reduces the risk of climate change. From a social welfare perspective, this avoided risk would be a huge benefit, but it wouldn't necessarily show up in the form of a more rapidly expanding GDP. 

Or consider the range of online activities now available: entertainment, social, health, education, retail, working-away-from-the-office. Add in the services that are available at no direct financial cost, like email, software, shared websites, cloud storage, and so on. It seems plausible to me that the social benefits from this expanding set of options are much greater than how they are measured in GDP terms--for example, by how much I pay for my home internet service or how much ad revenue is taken in by companies like Google and Facebook. 

Again, this thesis has some plausibility. One never wants to fall into the trap of thinking that output as measured by GDP is also a measure of social welfare. It's well-known that GDP measures money spent on health care and money spent on environmental protection, but will have troubles measuring gains in actual health or the environment. GDP will often have a hard time measuring gains in variety and flexibility as well.  

But this set of explanations also raises issues of its own. It suggests that people may be experiencing gains in their standard of living that are not reflected in their paychecks. In contrast, when productivity gains in terms of output per worker slow down, we are talking about output as measured by what is bought and sold in the economy. In short, gains in measured productivity are what can help to produce pay raises. But if these other kinds of gains are meaningful, they can't be used to pay your rent or your taxes.  

Friday, April 9, 2021

Electrify Everything: Some Limitations of Solar and Wind

The "electrify everything" vision supports generating electricity in low-carbon or zero-carbon ways, and then also using electricity to replace other sources of energy like oil, coal, and natural gas--for example, by using cars powered by electricity rather than vehicles rather than by gasoline. It seems to me that some advocates of this vision are (implicitly) hoping that solar and wind power can meet most or all of future energy needs. That's not likely, as discussed in "Clean Firm Power is the Key to California’s Carbon-Free Energy Future" by Jane C.S. Long, Ejeong Baik, Jesse D. Jenkins, Clea Kolster, Kiran Chawla, Arne Olson, Armond Cohen, Michael Colvin, Sally M. Benson, Robert B. Jackson, David G. Victor, and Steven Hamburg (Issue in Science and Technology, March 24, 2021). 

Just to be clear, this group of authors can't be caricatured as naysayers on non-carbon energy. For example, two of the authors are scientists with the Environmental Defense Fund (Long and Hamburg). another is director of the Clean Air Task Force (Cohen), and another is co-director of the Deep Decarbonization Initiative (Victor). Others are researchers and scientists either in academia (including at Stanford and Princeton) or involved in green investment funds. The publication is published by the National Academies of Sciences, Engineering, and Medicine and Arizona State University.

They start with the fact that California has announced that it wants to have zero net emissions of carbon by 2045. This means not only having all electricity generated by non-carbon methods (rather than, say by natural gas or coal), but also following the "electrify everything" agenda so that electricity replaces fossils fuels for transportation, heating homes and buildings, and industrial uses. In short, total electricity output will need to double, and noncarbon energy sources will need to more than double. 

Can solar and wind handle this shift? The authors write: 

Groups from Princeton University, Stanford University, and Energy and Environmental Economics (E3), a San Francisco-based consulting firm, each ran separate models that sought to estimate not only how much electricity would cost under a variety of scenarios, but also the physical implications of building the decarbonized grid. How much new infrastructure would be needed? How fast would the state have to build it? How much land would that infrastructure require? ...  Despite distinct approaches to the calculations, all the models yielded very similar conclusions. The most important of these was that solar and wind can’t do the job alone. ...

Although the costs of solar and wind power are now fully competitive with other sources per kilowatt-hour, their inescapable variability creates reliability problems. Average daily output from today’s California solar and wind infrastructure in the winter declines to about a third of the summer peak. Periodic large-scale weather patterns extending over 1,000 kilometers or more, known as dunkelflaute (the German word for dark doldrums), can also drive wind and solar output to low levels across the region that can last days, or even several months. Average wind and solar outputs also vary from year to year, particularly for wind power.

What can be used to address this problem? One possibility is to store energy in batteries. But as the authors write: "Better batteries play a key role in a carbon-free grid; they provide flexibility on hourly and diurnal time scales, for instance by saving some solar-generated electricity from late afternoon into the evening. But economical batteries cannot provide energy for weeks at a time." They point out that "the largest battery storage facility in the world is being built at Morro Bay ... and will be able to provide power for 4 hours, or 2.4 gigawatt-hours, enough to power 80,000 homes for about a day." But relying on solar and wind, together with battery storage, would require that California alone build hundreds of Morro Bay-sized batter facilities. 

Another possible back-up plan is to build large amounts of extra capacity for solar and wind power. Imagine that during certain times weather prevents solar from working well, and a given solar panel can generate only (say) one-tenth as much power as usual. But 10 times as many solar panels operating at a small fraction of their top power could make up the difference. The issue here is that there would be a huge and costly overcapacity of solar panel installations much of the time. Not only would building thos overcapacity of solar/wind (along with the additional required transmission liness) drive electricity costs up, it may not be physically possible. The authors write that this approach "would require expanding solar capacity at a rate 10 times higher than has ever been done before. There may not be enough people, supplies, or land to do this." For example, investing in solar overcapacity in California means that "more than 6,250 square miles of land would be required—bigger than the combined size of Connecticut and Rhode Island."

Thus, the results of this modelling drive the authors to the need for what they call "clean firm power," by which they mean " carbon-free power sources that can be relied on whenever needed, for as long as they are needed." 

Like what? One theoretical option would be to keep using natural gas for generating electricity, but combined with future generations of carbon capture and storage technology.  Another option is nuclear power. Geothermal energy is option that would work at certain locations in California. In other states, hydroelectric power might play a role. The researchers also mention the possibility of producing hydrogen from noncarbon sources.  

The authors aren't wedded to any particular source of "clean firm power." But their calculations emphasize that even in a solar-friendly state like California, solar is only part of the answer to a low-carbon future and a willingness to rely on "clean firm power" will be needed, too.