There is no evidence that anyone in the EA movement was aware of the FTX fraud, and one of its founders, Will MacAskill, has strongly denounced Bankman-Fried’s actions. Still, the company’s collapse, and SBF’s November 2023 conviction for stealing billions of dollars from customer accounts, caused immense reputational damage to the movement.

The Baggage of Sam Bankman-Fried

It wasn’t just because FTX had funneled game-changing amounts of money in its direction. Until 2019, Bankman-Fried had also served on the Center for Effective Altruism board, which MacAskill co-founded. Mac-Askill served on the board of the FTX Future Fund—until resigning in November 2022. 

It was also a huge black eye for effective altruism’s “earn to give” philosophy, which encourages individuals to amass as much wealth as possible to give it away. MacAskill reportedly convinced Bankman-Fried to do just that by taking a high-paying job in finance when he was an undergraduate at MIT. SBF was later billed as the “world’s most generous billionaire” for his support of EA causes since then.

Intentionally or not, ‘‘earn to give’’ has concentrated decision-making power about who benefits from effective altruism around the globe in the hands of a small group of billionaires—the wealthiest of them in tech. Bankman-Fried was not even the movement’s largest funder. Open Philanthropy, set up by Facebook co-founder Dustin Moskovitz and his wife Cari Tuna, is by far the biggest donor to EA causes, and handed out over $650 million of grants in 2022 alone. 

Launching the Effective Altruism Movement

Effective altruism certainly didn’t begin this way in 2009, when MacAskill and fellow Oxford University postgraduate philosophy student Toby Ord founded Giving What We Can. The charity asks that normal people, not billionaires, pledge to give at least 10% of their income to “effective” charities, and to date it has received pledges from 8,703 people in 99 countries, totaling $3.8 billion.

Since then, the movement has spawned many other nonprofits in the U.K. and the U.S. that have collectively raised billions more from a large donor pool. GiveWell, a U.S. nonprofit that researches and funds charities that it estimates save or improve the most lives per dollar, raised over $600 million in 2022. 

How effective altruism expanded in a few short years was dramatic. Its key tenets—focusing on doing social good, making decisions informed by evidence and logic, and intentionally trying to do as much good as you can—were not new. So says Katherina Rosqueta, founding executive director of the Center for High Impact Philanthropy and faculty co-director at the University of Pennsylvania’s High Impact Philanthropy Academy.

However, increasing publicly available data about the nonprofit sector and the influence of Australian moral philosopher Peter Singer’s book The Life You Can Save, turned EA into a movement. “You had this set of young people who had access to data and information, and this philanthropic practice tied to this moral framework,” says Rosqueta. “That was a great package to engage a new generation of donors.”

Addressing Immediate Philanthropic Needs

Some effective altruism groups have had a real impact in saving and improving lives worldwide. GiveWell, for example, has donated over $120 million to New Incentives. The charity provides direct cash transfers to caregivers in Nigeria who take babies for routine childhood vaccinations. It has enrolled 2.6 million infants to date. 

GiveWell has also donated over $82 million to the Schistosomiasis Control Initiative and Evidence Action’s Deworm the World Initiative, two programs that treat children with parasitic worms. And over $176 million has gone to the Against Malaria Foundation, which has protected around 450 million people with mosquito nets. 

Once all its currently funded nets have been distributed, the Against Malaria Foundation estimates it will have prevented 185,000 million deaths. “When we first set up AMF there was a very simple aim: raise funds, purchase nets, distribute them so that they ended up over heads and beds, and make sure we had the data to prove it,” said Rob Mather, the Foundation’s CEO, during an AMA chat hosted by the Effective Altruism Forum in December. 

These early EA movement projects worked because they supported proven, cost-effective humanitarian solutions, says Brian Berkey, associate professor of legal studies and business ethics at the University of Pennsylvania Wharton School. “I think mosquito nets, deworming, and direct cash transfers are the cases where there is the clearest evidence of significant impacts,” he says. “They were all things where you could run randomized control trials and test the effects of the intervention.”

This focus on impact per dollar has been one of the EA movement’s most important influences on philanthropy. “It’s not the exclusive domain of effective altruism, but I hope that thinking about the relationship between impact and cost and philanthropy’s role in creating more public good persists,” says Rosqueta.

Shifting EA’s Focus to the Future

However, more recently, the movement’s focus, particularly among its wealthiest funders, has shifted towards advancing longer time horizons. The FTX Future Fund focused on “long-term improvements for humankind,” like pandemic preparedness and AI safety. Open Philanthropy has donated over $330 million to organizations—such as OpenMined, an AI audit software company—that are researching or tackling the potential risks of advanced artificial intelligence.

Longtermism, the tenet of EA that saving the lives of humans living in the future is as important as saving the lives of people living today, is a controversial philosophy. Interventions in longtermist causes are also based on educated guesses about their impact, not on proven, cost-effective solutions to current humanitarian needs, according to Berkey. “The core ethical commitment can be lost if you focus on cool tech and sci-fi stuff, as opposed to how we prevent more people from dying from malaria [and get] money to people who are suffering now,” he says. Still, it’s currently what excites EA’s powerful tech industry funders. “If longtermism dominates the resources and attention of prominent effective altruism organizations, bringing more people into the movement will become much more difficult,” Berkey says.

Measuring Effective Altruism’s Impact

Effective altruism needs to refocus on funding cost-effective solutions to current problems, according to Berkey. But cost effectiveness, while important, is only one way of measuring a charity’s impact. For example, Charity Navigator, the largest non-profit evaluator in the U.S., considers a charity’s impact and results alongside its accountability and finance, culture and community, and leadership and adaptability. 

“A key differentiator between Charity Navigator’s approach and effective altruism is that we’re also looking at the broader set of metrics that lead to high performance and a healthy organization,” says CEO Michael Thatcher. “Is this charity financially sound? Does it have good leadership and governance, with an independent board? Are its internal equity practices meaningful? Are they receiving input from their beneficiaries and using that input in a way that’s going to change how they deliver their programs?”

Input from beneficiaries is not a focus of effective altruism. “They determine the need and then fund the intervention that is supposed to address that need,” says Rosqueta. “If you believe that individuals should be able to determine their own lives, it should be the other way around. Philanthropists should be listening to what self-determined needs are.” This is the funding strategy of billionaire philanthropist MacKenzie Scott, who believes that people struggling against inequities, not large donors, should drive giving.

Rosqueta says that some effective altruism groups do consider the beneficiary perspective in their funding of direct cash transfers to those that need them most, but that’s the exception, rather than the rule. “There is a lot of evidence about how effective it is to give cash to individuals, but I have not yet heard effective altruists talk much about the philosophical underpinnings behind that evidence, which is the self determination of the individuals.”

Determining Altruism

EA can be prescriptive for donors, as well as for recipients. “Part of the philosophy around effective altruism is figuring out the most effective interventions to save lives,” says Thatcher. “That often restricts the cause areas that you would be donating to. Our position is that we’re going to help you find the best organization doing what you care about.” 

That adds to the perception that the leaders of the movement are scolding or condescending about other efforts to do good and ignore the role that the business and public sectors play in advancing social change. “In practice, the ways in which some of the movement’s leaders have approached it has been a little bit of ‘We’re smarter than you.’ That tends not to hold as a movement because you’re not inviting anyone in, but instead creating a crowd that feels sort of exclusive,” says Rosqueta. 

Which brings us back to the tech billionaires, who have the most sway in the movement. Instead of being a mechanism for tackling global inequality, hasn’t “earn to give” just led to an even greater concentration of power in the hands of a few, super-wealthy donors? Berkey does not see it that way. “If more people actually took up the recommendation to earn to give, then you’d have a lot more people whose salaries are really high, but who aren’t keeping most of the money…We don’t want to cede these positions of wealth and power to people who are incorrigibly selfish,” he says.

Changing Generational Values Around Philanthropy

But it could be that the concept of ‘’earn to give,” where individuals make money in one sector of the economy and give it away elsewhere, is already outdated. “I work on a college campus and, much more than a generation ago, young people are using their money to align with their values—what they eat, where they shop, where they donate, and where they save and invest,” says Rosqueta. “Instead of saying, ‘I’m going to optimize the amount of money I make and donate it to certain causes,’ more young people are blurring those lines.”

Experts say that for effective altruism to thrive and attract a new generation of young people, it needs to be more inclusive; to listen to the views of all of its donors, not just the very wealthiest; to incorporate feedback from beneficiaries; and to refocus on what it does best—funding proven, cost-effective solutions to today’s humanitarian problems. 

In a post on the Effective Altruism Forum last June, MacAskill acknowledged some of these requirements, writing that the effective altruism movement needed a more decentralized organizational structure, a greater diversity of funding sources, and a culture emphasizing that “there are many conclusions that one could come to on the grounds of EA values and principles, and celebrate cases where people pursue heterodox paths (as long as their actions are clearly non-harmful).” 

Following Bankman-Fried’s conviction and its impact on the movement, a lot of attention will be focused on whether that happens.  

Other economists say that the Olympics can lead to some long-term benefits if planning is done well. “Some cities do [the Olympics] very well,” Dean Baim, professor of economics and finance at Pepperdine University, tells Worth. “If there’s a solid plan, it’d be a success. Los Angeles did it in 1984,” he says. “I would argue that Seoul and Atlanta did it too. Every facility that was built, they had a plan for it after the Olympics.”

France’s Big Bet on the 2004 Olympics

This preparedness that Baim thinks imperative and critical is what France boasts of against summer 2024—the centenary of the celebrated Paris 1924 games—when the eyes of the world will turn to it. The country believes it can change the opinions of Olympic naysayers with critical strategies that target gaining local public support and upholding sustainable practices. 

It is also banking on its modest $4.4 billion budget (which may change), a gender-parity pledge in athlete and event selection, and the fact that a majority of Olympic facilities (like the 1924 “Chariots of Fire” stadium) are already in place for the July-to-August games. Like most host countries who have tried to use the Olympics to sponsor an economic boom, France projects that it will make a profit—$5-10 billion from the games alone.

Still, critics like Johan Rewilak, assistant professor of sports economics and finance at the University of South Carolina, assert that hosting will be unnecessary to France’s economic growth. It’s not a sustainable financial decision, he says, as the games are inherently destructive—echoing Andrew Zimbalist’s view. 

Rewilak thinks that an already-thriving tourist destination like France does not need the Olympics to place itself on the global map. “Hosting the games may not generate the economic impact that has been previously mentioned, as Parisians may substitute spending from other areas of the local economy for sport,” says Rewilak.

He also thinks tourists will be forced to stay away from Paris for a long time for fear of being crowded or overpriced on normally affordable goods, especially as inflation is also rising (as of early 2024). “There is a sports management conference in Paris coinciding with the Olympics,” he says, “and I am choosing to stay away given how busy Paris will be!”

Accurately forecasting the economic impact of the games has remained a challenging task, but it is important to understand where the argument between optimists and skeptics is rooted and how the intricate history of the games’ economic circumstances profoundly influences present-day Olympics and ideologies about it. 

There was a time when the games were simple to host, when financial losses didn’t deplete national economies, and when failed Olympics didn’t have any colossal impact on a country’s image. In the time after, though, the Olympics became so costly that financial losses had a grave national impact. What’s more, debates over the games’ economic fairness started strong arguments that could be perceived as a reflection of one’s morality. 

“In the early days of the modern games, not much was spent in preparation and on facilities,” says Rod Skyles, an economist and seasoned business professional. “The Berlin games in 1936 changed that trend.”

The Economic Boom of the Early Modern Games 

Pierre De Coubertin served as president of the International Olympics Committee (IOC) for the first 28 years after the games’ rebirth in 1896. In that time, Olympic disasters never resulted in any major financial losses for hosting countries. The Olympics weathered setbacks like canceled games in 1916 and World War I, and experienced gradual international recognition until Paris 1924—which changed things.

These Olympics didn’t run on any obscure political or economic windfall motivations but on the French’s desire to show their sportsmanship to the world, as well as redeem themselves from the poor work they did in Paris 1900, when they hosted the games for the first time.

It was the Olympics of many firsts, recording the largest attendance yet, being broadcast over radio, and preceding the golden era of France’s booming economy. It was also the last one for Pierre De Coubertin. 

Much of Paris 1924’s success was defined by how many attendees, countries, and international delegates were present to witness and participate in it—remarkably larger than any games before. The games were especially a signifier that France’s suffering economy, fresh out of World War I, was getting back on its feet. 

Increating Revenue

France did not recover the money spent on hosting and infrastructure through ticketing. But the games had converted spectators to tourists, including frequent American visitors, and eventual permanent residents who were gob smacked by the low cost of living in France. And this boosted trade. Paris had put on a good, convincing-enough show, and this naturally yielded monetary benefits. Soon after, in 1926, the country entered its Franc Poincare (named after its finance minister) zenithal era, as rates of exchange lowered, and the economy prospered.

This was a massive shift—one many bidding countries looked forward to achieving and even beating—and one that may have influenced the use of the Olympics for political propaganda years later. 

The next host, Amsterdam, which had initially bid for 1924, experienced a better economic impact than Paris. It had spent $1.183 million and recovered $1.165 (about $38 million and $86 million, in today’s dollars), with a negligible loss of $18,000 ($585,000). It was also the first to introduce brand-sponsored marketing through Coca-Cola, providing American teams 1000 crates of their drink. 

The Los Angeles Olympic games of 1932 were better still—superb even—and are referenced in the list of historically successful Olympiads. It’s a usual example of why some economists posit that the Olympics could be a significant financial decision. ILA powered through the limitations of the Great Depression in America with sufficient architectural, monetary, and innovative strategies. Planners considered the futuristic use of Olympic infrastructure, the safety of local communities, and the economic recession of that time—and finished with a $1 million ($32 million today) profit. It was the first Olympics not to lose money. 

After the Olympics in Los Angeles, it had been established that the games were potentially a great tool in reaching peaceful international relations, especially after global conflict, scoring trade boosts, and championing a colossal increase in tourism. But the path the Olympics took after Los Angeles, politically and economically, was a sharp left.

Germany’s Budget-busting Extravaganza

Adolf Hitler was fascinated with the widespread popularity of the recent games. He saw the Olympics as a vehicle to demonstrate his racial superiority ideologies, highlight the power of Nazi Germany, and exert a propaganda coup. “1936 Berlin was driven by Hitler’s desire to show off Nazi Germany and announce to the world how special they were,” Skyles tells Worth. “Since then, many of the games have been driven by politics and not common sense or for the benefit of the people.”

Berlin 1936 cost more than $500 million in today’s dollars and was 10 times more expensive than any preceding games, putting Germany in more debt than all previous host countries combined. It was meant to be outrageously extravagant like nothing ever seen before and signal the return of Germany to the global stage after its defeat in World War I. Hitler’s unsuccessful plan plunged Germany into an economic crisis, but he had carved a new path for the Olympics. 

The cost of the Olympics in the interwar era had grown naturally, but not exorbitantly, as attendance increased, participating countries multiplied, and brand awareness through the games improved. But what Hitler did in 1936 changed the economy of things forever. It created a new hope: the possibility of a global legacy. The recent Olympics era strayed far from De Coubertin’s original ideas. It gave the Olympics a fresh motto and told developing countries that the games could be their ticket to gaining global recognition. At the same time, it made industrialized countries more energized than ever.

“Each city [after Berlin] had a specific reason why it wanted to host the Olympics, and in most cases, it was to make their country appear to be a global leader. To some extent, they were successful,” Baim tells Worth.

The Modern Olympics Spending Spree

There was a 12-year break due to the Second World War after Berlin in 1936. The cost of the Olympics reverted to tens of millions of dollars for a time, a typical rate for hosting it in the interwar period. But costs soon rose with economic growth.

The Olympics after the ‘60s signified the world’s recovery from the war. It was now visible that a state could assert itself through the games. Bidding became tougher as countries scurried for the chance to show how much development they had made through the world’s center stage, the idea of exerting themselves as global leaders, and the potential economic gains (which they believed would overshadow the projected costs incurred by host cities). 

Mexico, the first developing country to host the Olympics, was able to assert itself as a contemporary, cosmopolitan country through the flamboyant sports and housing architecture it built (and that remains useful). But this meant using large amounts of public funding and even massacring student protesters who sought to use the games’ global popularity to demand democracy and the elimination of authoritarianism. 

The city of Rome could flaunt its high-end urban reimagination as it was the first city to get television coverage, but it left a pile of debt ($19 billion today) in its wake. 

Tokyo, in 1964, went as far as spending over $10 billion in national makeovers—from stadiums to transportation infrastructure—which led to a large-scale displacement of citizens and substantial debts. Montreal in 1976 shackled the city with $1.5 billion in debt. “They ran such a huge deficit that the people of Montreal had to pay for it,” says Baim.

What to Expect for Paris 2024

There are decades of overwhelming evidence that hosting the Olympics is a costly investment, in which returns are vaguely probable, but governments remain ever hopeful.

This is hardly surprising as the payoff—when it pays—is also easy to see. The 1988 Seoul Olympics, for example, reimagined the war-linked image of South Korea and brought in investments. Barcelona became a Mediterranean gem after 1992 through modern renovations that showcased its culture and increased annual tourist visitors from 1.8m in 1990 to over 3 million in 2000. London, today, still generates money from its Olympics 12 years ago through several tournaments hosted in the Olympic stadium it built in 2012.

Many hosts have fruitlessly spent much money trying to recreate these successes, and France may be on track to do the same. It is faced with spiraling cost concerns, which made several cities like Boston withdraw their bids. This explains why bidding in general has dropped. There are also problems of rising inflation and existing security challenges, which were a big factor in Japan’s enormous financial losses after Tokyo 2021. Citizens will also leave the city during the games because they think it will be unbearable—hampering shopping, transportation, and basic day-to-day activities.

France could have chosen not to bid for hosting, and nothing would have changed. As Rewilak insists, countries like it don’t need to assert themselves as global leaders, nor do they need the Olympics to boost their economy. “The Olympics is not necessary to place Paris on the map. People go to Paris no matter what,” he says. 

Mixed Signals

The country’s intent for hosting the Olympics remains somewhat vague, especially with a lot of downsides threatening its success. However, France’s evacuation of homeless people out of Paris ahead of the Olympics is an angle to consider for Baim, as he thinks it is a move to hide the city’s problems from citizens and visitors.

“The Olympics are sometimes bread and circuses to keep people’s minds off of a country’s problems,” he says. “Paris may be motivated to host the Olympics to keep Parisians and the press distracted from its number of unhoused. I think it’s the most efficient way to distract people.” Rewilak adds, “If the movement and transfer of homeless people stops—or there is movement back to Paris—after the games, it may tell the full story.”

In 2020, the IOC, an institution with a history of bribery and corruption and involvement in hospitality and doping scandals, put out a strategic roadmap agenda. The agenda seeks to reform the Olympics and the IOC. And Paris, as a host choice, may be part of it. “This isn’t a sullied country using the Olympics to improve its image. This is a sullied Olympics using a country to decontaminate itself,” Jon Werthiem, Sports Illustrated executive editor writes.

There are a few economic upsides to cling to in France’s story, though. Firstly, its eco-smart and sustainability plans to make the games pro-bike, pro-pedestrian, anti-jet, and anti-car are forward-thinking and will save costs. Secondly, Paris may be able to replicate the efficiencies of London 2012 and L.A 1984, since—like those former hosts—it doesn’t need to construct any new buildings, just rehab old ones. 

France has had the ball in its court since 2017, and in a few months, it’ll play before global spectatorship. If the country has learned from mistakes of past hosts and has properly executed its pre-game strategies, it’ll be evident in the aftermath of the tournament. If not, the results would hardly be surprising.  

Several studies published last year have revealed one particular difference that should be grounds for measured optimism. Figures for office occupancy and downtown recovery tend to look a lot better in smaller cities than in the biggest markets—a fact often lost in the media. For instance, building-security firm Kastle’s heavily reported count of badge swipes covers only the top 10 metros, and shows only slow back-to-work progress. 

Big Back-to-Work Contrasts Between Cities

A fuller picture comes from a trio of academic researchers who analyzed smartphone-location data that business-intelligence firm SafeGraph had collected through mid 2022. Their “Remote Work and City Structure” study, published in July of 2023 by the National Bureau of Economic Research, found that while trips to central business districts remained at about 60% in the largest cities, they had, on average, returned to pre-pandemic levels in smaller cities. 

The central-business-district traffic stats were especially bad for the largest cities, with Chicago, Los Angeles, and New York all under 50% CBD visits—and sometimes closer to 40%—during the time frame of this study.

Research published last July by Stanford University’s Institute for Economic Policy Research adds another dimension. In the “The Evolution of Working from Home,” researchers observed that “the work-from-home rate rises strongly with population density,” accounting for more than 40% of all paid workdays in the highest tier of urban density that three researchers surveyed. 

A similar pattern surfaces in the findings of the University of Toronto’s Downtown Recovery Rankings project, also based on phone location data. Its roster of the top ten cities with the highest percentages of unique visitors to downtown (relative to a 2019 baseline) features only one city among the ten biggest in the country: Phoenix. 

That list also includes some striking contrasts between bigger and smaller cities separated by under 100 miles. Milwaukee’s 86% recovery far outpaced the 61% stat for Chicago, just down Lake Michigan, and the 87% figure for Colorado Springs easily bests Denver’s 67%. 

Experts point to a few factors that can explain this divergence: the types of employers and professions, the pain of commutes for them, where people live, and how much they might be willing to pay to live closer to those jobs.

Some Professions Demand More Office Time

“The difference is huge,” says Nicholas Bloom, an economics professor at Stanford and one author of the research paper. “The key driver of this is industry.” 

As that report notes, work-from-home rates vary widely by industry sector. Information technology was most tolerant, with employees reporting that they worked an average of 2.55 days a week from home in the first half of 2023. 

Financial and insurance came in second, with 2.28 WFH days a week reported, followed by professional and business services (for example, consulting and accounting), at 2.04 days a week.

Sectors that require hands-on, face-to-face work—hospitality and food services, transportation and warehousing, retail and manufacturing—all had employees reporting less than a day a week of remote work. 

In other words, the high profile of finance in New York and information technology in San Francisco helps explain their lagging return-to-work rates. Higher shares of blue-collar work can lead to different outcomes elsewhere—like Milwaukee.

“We’ve seen about 70 new companies move in who are mostly high-tech manufacturing,” says Corey Zetts, executive director of Menomonee Valley Partners. 

That neighborhood west of downtown Milwaukee has a history of manufacturing that left a legacy of pollution. But its 21st-century version is greener. Zetts noted the growing presence of the Spanish firm Ingeteam, which builds components for wind and solar energy installations and is now moving to build EV chargers in Milwaukee. 

“For us, we’re really seeing things return to normal,” she says. “On any given day, the parking lots, the bike racks, look like they did in 2019.”

Remote Work’s Effects on Neighborhoods

Ferdinando Monte, a professor at Georgetown University and one author of “Remote Work and City Structure” noted that when professional tasks can be done remotely, workers’ interest in going downtown can vary based on their odds of having interesting interactions with other people at work. 

“For bigger cities, a lot of the value was in personal interactions,” he says. But as more of your coworkers aren’t there, that becomes a bit of a vicious circle.

Monte added that reduced in-office populations can also drag down employment in sectors that assume in-person work, citing trends in food service work around Washington.

“Total employment in restaurants is basically at pre-pandemic levels,” he says. “But in the last year, all of the jobs that have been added have been added outside D.C. proper.” 

Long Commutes Can Hinder the Return-to-Work Process

Scoop Technologies, a San Francisco developer of workforce collaboration services, maintains a Flex Index of remote-work flexibility that reveals a similar pattern between bigger and smaller markets. 

The firm’s list of the 10 most flexible metro areas is based on estimates from employee surveys and publicly posted office-presence requirements covering 8,000+ companies. It leads off with San Francisco and San Jose, followed by Austin, Seattle and Boston. Meanwhile, its list of the 10 least flexible metros is all such smaller cities as Chattanooga, Wichita, and Tulsa. 

Rob Sadow, Scoop co-founder and CEO, pointed to another key issue: “the underlying traffic and pain in getting back to the office.”

In other words: more stoplights and brake lights ahead mean less willingness to get in the car and turn the key (or press a “start” button). 

“Atlanta tends to have a little bit lower return to office rates compared to more suburban or rural areas in Georgia and the Southeast,” Sadow says, nodding to the commuter congestion routinely clogging the ribbons of concrete that slice through the Peachtree City. “And part of that is driven by the traffic situation.”

The Stanford paper observed that firms in the information, finance, and business-services sectors are particularly prone to inflicting bad commutes on their employees because they cluster in dense urban centers.

As the report concluded: “That makes it all the more appealing to avoid the commute, thereby saving time, money, and aggravation.”

Census Bureau data about pre-pandemic commute times may also serve as a forward-looking indicator about workers’ willingness to get in a car, board a train or bus, or hop on a bike. Compare, for example, the 2019 one-way averages for New York and San Francisco—38 minutes and 35 minutes—with Milwaukee’s 24 minutes. 

“Our commute times have never been very bad,” says Zetts—who also says she’d like to see the neighborhood’s pre-pandemic bus service restored.

Monte noted that larger metros should be able to offset bad driving commutes with better public transit: “Bigger cities tend to be the ones that have better transportation infrastructure.” 

But many transportation services, such as the Washington area’s Metro heavy-rail system, face severe funding shortfalls in part because fewer people are working in offices and paying transit fares. 

Many employers have now moved to parcel out the pain by requiring workers to show up in the office for only part of the week. Kastle’s stats now include a peak-day graph, which has been showing Tuesday as the top in-office day for hybrid workers.

“I think we will increasingly settle into two to three days at the office, two to the three at home,” Sadow says. “When three goes to four is when employees find they’re really frustrated.” 

Monte says he’s seen the same, calling three days of five in an office “kind of the norm.”

Longer Commutes from Big Suburban Homes

Where and how people live can also affect how anxious they are to resume working in offices. The Stanford paper noted another reason for high work-from-home rates in information, finance and insurance, and professional and business services. They pay more, and that additional income often results in larger abodes that people may be more reluctant to leave.

As the paper’s authors write: “Higher earners typically have nicer homes with more room for a home office.”

In a guest post on Scoop’s blog last April, University of Southern California economics professor Matthew E. Kahn crunched Flex Index workplace-flexibility metrics with Zillow median home-price data and found a link. A doubling of home prices was correlated with a six percentage-point drop in onsite-only workers. 

He also found that companies based in more liberal states, as measured by President Biden’s share of the popular vote in 2020, were more likely to allow WFH. Commented Kahn: “Blue State bosses of firms are more likely to be progressives who prioritize worker quality of life and want to help family-focused workers to ‘have it all’.”

That may track with all 10 of the cities at the least-flexible end of the Flex Index being in states that voted for Trump (Arkansas, Florida, Oklahoma, Kansas, Kentucky, and Tennessee), many of which also have smaller cities. 

The NBER paper, meanwhile, found that the economic incentives worked the other way in cities with higher return-to-work metrics: Workers were more willing to pay extra for housing closer to their jobs.

What Monte described as “that willingness to pay to be close to office work”—more inelastic demand, in economic terms—declined for both large and small cities at the start of the pandemic. “But then it returned to where it was for these smaller cities.” 

Either way, an employee’s choice of housing can constrain their future workplace choices for years to come. As Monte put it: “The people that used to live there now live outside.” 

Remaking Cities for Workers

Many cities are now working to square the circle by moving away from neighborhood monocultures, with offices in a business district and housing nowhere close, in favor of mixed-use quarters that have office and residential on the same block or within blocks. 

One common shortcut to that is to convert office buildings into housing—assuming their floor layouts allow a subdivision of a cubicle farm into apartments. That has the added advantage of eliminating the need to find new office tenants for those structures.

And even cities that have done well at getting people back to offices are taking this route. “We are seeing some conversions to residential,” Zetts says of downtown Milwaukee.

“We are moving increasingly to a world where people are going to live and work close to each other,” says Sadow. “The era of Microsoft creating the Redmond campus where 50,000 people work is probably past.”  

Consumers are choosing to go out earlier, if at all, to then enjoy the comforts of home and connected entertainment, such as catching up on favorite Netflix shows. Consumers are also becoming more risk-averse in social settings, choosing screens over face-to-face engagements, especially when it comes to talking to strangers. This is also creating a consumer that’s increasingly single and lonelier. 

A January article in Bloomberg, by economist Allison Schrager, was titled “The Introverts Have Taken Over the U.S. Economy.” In it, Schrager highlights a marked shift in consumer preferences from late-night dining to early-evening reservations, underscoring the growing influence of introverted behaviors. Such changes, spotlighted by Schrager, signal a deeper transformation in consumer habits and norms post-pandemic, representing an ongoing shift that requires understanding and further study.

What does this mean for businesses? Consumer-facing industries such as entertainment, hospitality, and personal tech will have to find new ways to meet people where they are (which might be their bedrooms). Offerings might include restaurant quiet hours, or virtual cooking lessons that give the benefits of collaboration in a less-intimidating setting. Hospitality companies might show more tolerance, and even encouragement, for people to use their devices—including to pay restaurant bills.

But before we dig deeper into how to respond to these changes in society, let’s examine how we got here.

What Early Dining Says About Societal Change

The Bureau of Labor Statistics recently reported that people under 50 are increasingly frequenting bars and eateries earlier, a trend that started before the 2020 pandemic.

Schrager points to New York as an example of noteworthy shifts in dining behavior. Typically, 8 pm or later was considered the desirable time for dinner reservations. But according to Resy, a hospitality platform for restaurants, 5 p.m. is the new 8 p.m.

Resy data shows that since the pandemic, reservations across New York City made at 5:30 p.m. have jumped from an average of 7.75% over the past two years to 8.31% in the last six months. Meanwhile, 8 p.m. reservations have fallen to 7.8% of total dinner reservations in the city, down from 8.31%. 

While a change of about 7.2% may not seem huge, it’s in sync with other sources. Yelp Data found that, in 2023, 10% of all diners were seated between 2 and 5 p.m., which doubled from 5% compared to the same period in 2019. Simultaneously, 10% fewer reservations were made between 6 p.m. and midnight.

These shifts are enough to make some restaurateurs pay attention. 

Danny Meyer is the founder of Union Square Hospitality Group and Shake Shack. In a recent post on X, Meyer asked, “When did a 6:00 dinner reservation become the new 8:00, most prized table of the night—and will it last?”

Meyer also shared his theories behind the shift. He pondered whether working from home contributed to social isolation. “That’s why restaurant bars and seats are filling up ever earlier,” he observed on X. 

Meyer also acknowledged the new reality, that consumers have more entertainment and content than ever waiting for them back home. “Dine early, home earlier,” he said.

In response to Meyer, founder of Hint Water, Kara Goldin, also observed that more and more restaurants in San Francisco and Marin County in California, are closing earlier. “…so many restaurants close the kitchen at 8 and 9,” she shared.

I have first-hand experience with Goldin’s point. I was dining out recently in Orange County, Calif., and our waiter informed us that the kitchen was taking its last call at 8 p.m.

Jeffery Bank, CEO of Alicart Restaurant Group, shared with Marketplace that his restaurants are extremely busy between 4 and 6 p.m. “I do think you’re seeing a cultural shift, and I think that started with the pandemic,” he said. “People are just trying to enjoy themselves, I think, differently.”

The Pandemic Has Shifted Social Activities Earlier

During the pandemic, it was common for networking events, wine tastings, celebrations, and happy hours to be conducted online, during the workday, for long enough that it further shifted the trajectory of our social behaviors and norms. People learned to interact earlier.

“Afternoon parties have 100 % taken off since the pandemic,” Min Brown, a sales manager for the corporate event planning group Yaymaker, shared with the New York Times.

These new digital-first activities would leave people ready to unwind at home, as opposed to going out afterward.

Schrager also observed that, although going out on weekends spiked in 2022, it appears that, since then, fewer people are choosing to socialize on weekends than did in the past.

Instead, according to the U.S. Bureau of Labor Statistics, they’re opting for in-home activities such as watching TV or playing video games.

Seeking Safety at Home

The shifts in social norms go beyond dining and weekend planning.

Last year, Date Psychology published findings that corroborate evolving “introverted” behaviors. The article cites a representative sample from the Centers for Disease Control and Prevention (CDC) that found younger singles, particularly those who are part of Generation Z, are becoming increasingly more risk-averse. 

A 2021 sample from the CDC study also found teens are using drugs less, drinking less, having less sex, and attending fewer in-person parties or gatherings, which is also leading to increased loneliness.

When it comes to dating, for instance, they’re less likely to approach strangers in real life to interact or attempt to date. 

Psychologist Andrew Thomas recently conducted a poll and asked on X, “have you ever felt a profound and enduring state of unhappiness, uneasiness, and discontent about your singlehood?” 

More than half of men (55.1%) and just under half of women (44.9%) responded yes. 

The introvert economy and digital-first engagement could be perpetuating the situation. If you don’t talk to people IRL (in real life), then you either depend on others to talk to you in person or lean on apps to solve your craving for interpersonal connections. 

But Thomas’ approach spotlights this important shift in introverted or risk-averse behaviors. They contribute to the rise and impact of the new realities of unwanted singlehood. This results in developing the unintended emotions that arise from being excluded from relationships, even if their behaviors contribute to this state.

These trends and more could have staying power.

Digital Introverts Unite as a Generation of Connected Consumers

These observed “introverted” behavioral patterns may have accelerated during the stay-at-home days of COVID-19, but their evolution dates back years.

Well before 2020, my research into digital consumerism explored how social media, mobile devices, and on-demand apps were already nurturing digital-first behaviors and keeping people engaged on their screens at the cost of IRL interactions.

I referred to this emerging group of digital-first consumers as its own psychographic, “Generation-Connected” or Gen-C. This group was not organized by dates of birth but by shared digitally influenced behaviors, interests, values, and norms.

Living a digital-first lifestyle offered newfound conveniences and empowered consumers to take control of their own life narratives and experiences. Need a ride somewhere? There’s an app for that. Don’t want to go to your favorite restaurant but still craving that meal? There’s an app for that. Need groceries or supplies or electronics delivered within the hour? There’s an app for that. Want to find a date? You guessed it. There’s an app for that.

Nowadays, consumers have anything and everything they may want, all within reach.

These connected consumers intuitively turn to e-commerce and social commerce. They move faster. They are becoming less and less patient with digital-first convenience services such as ride-sharing, food delivery, curbside pickup, dating, and even the drone delivery services that are ramping up to serve them.

Observing these shifting digital-first activities gave way to what I described as “digital introverts.” Digital introversion wasn’t literal in its interpretation. It was a way of making these behavioral shifts relatable in a more general sense. 

The Move to a Screen-First Lifestyle

In my work over the years, I described how screen time, transacting in the sharing and on-demand economies, and exposure to online cultures and norms influenced screen-first actions. This was important to understanding cultural trends and documenting the differences in digital and traditional influence, decision-making, and outcomes.

For example, with Gen-C, it’s quite common to see people in social settings, at dinner, at live events, walking, and physically sharing space with others while immersed in their mobile devices. Anyone following the release of Apple’s Vision Pro spatial computing headset is already witnessing what “next” looks like.

While I recognized Gen-C as digital- or mobile-first, their behaviors are simply native and intuitive. Digital is just a way of life, and with it comes new behaviors, expectations, norms, and aspirations.

Because these behaviors are second nature, introversion became a function of efficiency and, perhaps, common sense.

We can all relate in many cases. Think about these scenarios for a moment.

Do you ask for help or read instructions for a new purchase, or do you watch a YouTube video to learn how to use or perform something?

When in a store, do you flag a representative to learn more about a product, or do you first look it up on your phone?

Have you ever broken up with or been broken up with by a text message?

Have you ghosted or ever been ghosted by someone in messaging?

Do you opt to date via apps instead of approaching someone in person?

Have you ever said something to someone online you’d never say to their face?

In many cases, doing something online is easier or more efficient than IRL. Digital introverts have become skilled at optimizing their decision-making and action-taking processes by first consulting and navigating their screens. This may have come at the cost of societal skills to interact and communicate with others in the way previous generations navigated the world. 

For better or worse, this is a new reality. Over time, these shifts will only develop into larger societal trends.

“Introversion” and Awareness May Be a Result of Growing Screen Time

When I published my book, Lifescale, I studied the effects of screen time and digital-first behaviors. I found an astonishing series of effects that made users more conscious, self-conscious, and introverted, without realizing it.

Their behaviors weren’t just changing due to using new devices or apps; they were evolving because they were introduced to new realities IRL and new possibilities on screen. Because of the reality of what these new worlds look like—and how they influence values—they were exposed to new norms and aspirations, too. 

Everything has changed and is still changing. The people you follow and interact with online and the new things you do and experience introduce distinct customs, ways, and habits. Over time, they reshape traditional conventions resulting in ever-shifting standards for what normal looks like.

New Opportunities and Challenges for Companies

The introvert economy is an emergent shift that’s worth paying attention to. And like all economies, it’s evolving. Consumer behaviors are evolving, too. Added up, the introvert economy signifies new market opportunities and potential threats. Those paying attention will better understand where to make changes, experiment, and learn.

Companies—especially those in entertainment, hospitality, technology, and consumer goods—can add value in key moments of truth by offering products and services that support engagement, well-being, and meaningful experiences that make going out matter. 

I call this an “ignite moment”—a moment when consumer engagement is intentional and in the experience, someone feels special, heard, recognized, or satisfied. With consumers becoming more conscious of their needs and priorities, businesses will benefit by creating products and services designed for them. It’s these thoughtful touches that make going out, meeting someone, shopping, etc., become more meaningful and desirable.

Added up, the introvert economy represents customers and employees who are experiencing changes from previous norms. No one has this figured out. No one knows how these shifts will play out. But if you’re willing to pay attention, to understand the people on the other side of a reservation, potential date, social gathering, or purchase, you can shift your perspective. In doing so, you will identify new opportunities to improve service and experience in these “ignite moments.” 

How to Create New Experiences and Convenience

Assess current products, services, and experiences from the perspective of these “introverted” customers, with the intention of introducing more introvert-friendly technology, services, and spaces.

For example, promote earlier specials that offer exclusivity for introverted consumers, like “quiet hours” or chef-curated experiences during earlier hours, or low-key entertainment experiences. Create solo or private spaces that allow people to experience your space while also engaging with their devices. Experiment with lower lighting and noise-canceling materials.

Innovate in digital platforms and partnerships to create new engagement opportunities. For example, mobile apps in stores or in restaurants that allow for collaborative commerce are gaining traction. Beyond promoting QR code menus, launch an app to let people order and pay from their devices between server visits.

Self-service becomes key. Launching a chatbot or knowledge base isn’t enough. ChatGPT and generative AI are teaching all consumers that they can control their experiences. Explore ways to put consumers in front of their experiences, end-to-end. This reduces unnecessary social interaction and the potential anxiety that goes along with it.

Reimagine virtual events and co-hosted experiences. New engagement opportunities could bridge the gap between online and offline interactions. For example, consider chef-hosted virtual experiences that teach consumers unique cooking methods in the comfort of their homes. Connect shoppers to experts who can help them navigate style, entertainment, beauty, or technology trends. Engage consumers by placing bartenders and sommeliers as hosts in virtual wine or cocktail classes and experiences. 

Foster an inclusive community. Hosting workshops, social clubs, or community service events can offer alternative ways for people to connect and support each other, to counter the effects of increased isolation or celebrate shared interests in what pulls them back home. For example, introvert hours during off-peak times, curated menus, props, solo experiences that include games or entertainment, can make people like they’re home.

Even if you’re not part of the introvert economy, understanding them and how these consumers evolve is how you gain understanding and empathy to better serve and engage them. Monitor trends. Stay informed about evolving consumer preferences and societal trends.

As society continues to navigate these changes, the ability to adapt and innovate in response to shifting consumer behaviors will be crucial for businesses looking to thrive in the evolving landscape.

Venture capital firms are partnering with software engineers to train AI-driven machine learning systems (AIML) to provide a competitive advantage in key industry sectors. The most promising of these is weather prediction. Moreover, hedge funds are seizing on these systems to identify weather-related risks to their portfolios better—be it predicting regional citrus harvests or managing energy generation sources for the electric grid. And achieving advantages over their competitors could be worth tens of billions of dollars.

Julie Pullen is a partner at Propeller Ventures, a VC firm specializing in businesses developing ocean and climate technologies. She is building teams to use AIML techniques to enable organizations to customize forecasts for their commercial or scientific needs. Such systems can use proprietary and unique data sources for focused and precise short- and long-term weather prediction not currently available from government sources. 

A research scientist at Columbia University’s Earth Institute and former head of the U.S. National Maritime Security Center, Pullen has stepped into the venture capital world to apply her meteorology, oceanography, and climate science knowledge to train AIML systems. 

“I see a lot of companies being formed around teams of data scientists to improve weather prediction with AI,” Pullen says, citing Google GraphCast, Huawei Pangu, and Nvidia FourCastNet. “There is a lot of competition entering the field. My team is working on achieving a deeper understanding of the Earth’s atmosphere and oceans for people across an array of disciplines and industries.”

Hedge funds are not only eager customers of weather information; their relative success in using it to improve their portfolios (or not) is an excellent way to validate AIML algorithms. 

Customizable Forecasts for Investors

Until recently, weather prediction was such a high-end computing problem that only government agencies, such as the U.S. National Weather Service or the European Center for Medium-Range Weather Forecasts, could pull it off. Moreover, weather forecasting requires many sensors—satellites, ground stations, aircraft, ocean buoys, and other sources—to inform the models. 

While forecasting has made great strides in recent decades, the scarcity of government service providers, reliable as they are, means everybody essentially has access to the same data. This is great for people planning their day, but it does not offer a competitive advantage to firms whose fortunes depend on atmospheric conditions. 

Weather is a valuable industry because everybody needs information about it at some level. With the primary data sources homogenized, the opportunity is to customize forecasts for specific users who then apply them to their activities. 

For example, IBM acquired its Weather Company business in 2015, integrating the company’s assets with its own data analysis, presentation, and Watson AI tools. In August, IBM signed a deal to sell The Weather Company to private equity firm Francisco Partners. However, IBM says it will continue providing software support and development. But acquisitions or partnerships like these have their limits: The sources of raw data are essentially the same as what everybody else gets—largely from government agencies.

Satellites, radar, terrestrial stations, and oceanographic sensors feed data into the great, government-supported forecasting service computing systems, which analyze them using some of the most complicated software systems on the planet. The atmosphere is a tremendous fluid, and few things are harder to model than a fluid. One of the areas for improvement of government weather service-supplied information is that the massive computing power needed to process complex models limits the number of forecasts to a few per day.

Trained AIML systems can make calculations based on pattern recognition processes much more quickly and as accurately, according to a study published in the journal Science. Another advantage is AIML’s ability to take in various unstructured and custom datasets, including text documents, photographs, audio, video, and other sources not in a machine-recognized format. The key is in the training: Specialists teach the AI to recognize patterns and readings from historic data sources, formatting unstructured data as needed. These may come from government weather services, scientific research, and even fossils and paleoceanography (e.g., core samples of arctic ice or deep ocean mud) from millions of years ago. 

Expanding Risk Assessment with AI

Julie Pullen says the widespread affordability of AIML platforms means that individual systems can be trainable in a wide range of specific tasks and open to an expanding range of sources to inform their analyses.

“Venture capital is actively making bets in that space,” Pullen says. “And one of the best ways of getting feedback on those bets is from the hedge fund industry when it uses those tools. It’s the intersection of the scientific with the financial that demonstrates value for predictions along a range of timescales.”

She points out that the trainable, customizable features of AIML enable hedge fund managers to look at very specific weather conditions with fine regional detail. Funds can better predict extreme weather events such as heat waves and droughts on time horizons ranging from weeks to months to years. These forecasts make a difference to the bets fund managers make. Then they can get rapid feedback on the models, looking at results from shorter time horizons. 

According to Harun Dogo, manager of quantitative analysis at Los Angeles-based hedge fund TCW, widely used weather models are informative. But they make positions in certain commodities expensive to hold because everybody comes to the same conclusion. These widely held positions also come with various levels of risk, not just because they are expensive but also because, at some point, unexpected events—weather-related or geopolitical—will intervene to undermine the common wisdom and destabilize markets. The trick is to be able to make bets against the prevailing wisdom in time and be right about them.

“Artificial intelligence, and really it’s machine learning, is a way to classify patterns in the market and use that information to optimize your positioning,” Dogo says. “What do you think the expected volatility will be? A machine learning algorithm can help you identify risks you didn’t even know you had, things that other quantitative analysts might have missed.”

For example, the world has transitioned from a La Niña weather cycle over the Pacific to an El Niño cycle that shifts global rainfall patterns. Funds dealing in soft commodities (e.g., cocoa futures), energy, and even mining will factor how these predicted patterns may affect portfolios incorporating these sectors. However, everybody has this information. Dogo says AILM offers the opportunity to look at very specific localities on shorter time horizons and discern patterns not covered by historic models of La Niña-El Niño periods.

“So really, the question is, what’s the new information that AIML-enabled climate or weather datasets add to your ability to think about where a particular asset pricing will go?” Dogo says. “How volatile [is it] going to be and what the potential downsides of holding it on particular time horizons will be.”

TCW works with third-party partners to receive AIML information to supplement its analysis activities. At this state of the technology’s development, it is not clear that having an in-house capability is worth the time or the resources. In January, Nvidia announced an agreement with datacenter operator Equinox to offer corporate clients AI and machine learning systems. The field is still in its infancy, and questions of whether AIML is better as a third-party service, or an in-house proprietary tool have yet to be answered.

Hedge fund Citadel reportedly made a significant investment in scientists and computer engineers to develop in-house forecasting tools for giving it competitive advantage for trading commodities, especially in the energy sector. Last year, the Financial Times reported that the weather team helped the company earn $16 billion in 2022 to become the most successful hedge fund. The team produces forecasts that are focused on conditions in regions where opportunities for trading in raw materials are most promising. 

Hedge Funds Mirror Scientific Researchers

The advent of AIML systems that can run on modest networks of desktop computers is expanding the scope of private weather prediction, opening a new professional track for meteorologists. The website eFinancialCareers.com says meteorologist is becoming a hot job opportunity at hedge funds, with top annual salaries north of $1 million.

From Pullen’s perspective, hedge funds are great as enablers of AIML systems development and validators of analyses and forecasts from such systems. Her team at Propeller is not specifically interested in hedge funds as clients: Its mission is nurturing technologies for improving ocean and climate conditions. However, Pullen is focused on the incredible potential of AILM systems for better understanding marine and weather dynamics on Earth. It just so happens that hedge funds value this information as well and offer an excellent proving ground for the technology.

While hedge funds are notoriously secretive organizations and are not prone to sharing their competitive advantages openly, their requirements for using unstructured data from a variety of sources mirror those of the scientific community. The convergence of science with better financial returns is a powerful dynamic for proving AIML algorithms. 

Gordon Gould at San Francisco-based hedge fund Numerai is developing an AIML model that takes information supplied by data scientists to predict the stock market. The fund pays out to subscribers based on how good their data is at enabling the algorithm to foresee market movements. The providers whose data make the most money get the best returns. This sort of on-the-fly data validation is invaluable for better training AIML systems. 

AI Opens Up New Business Understanding

The ability to incorporate and analyze unstructured data will be what separates AIML systems from each other. That’s where the competitive advantage lies. It is also how we will better understand our rapidly changing world.

The reliable, routine sources of data that make it into the government service forecasts and supply private weather services are not going to be enough for hedge funds and other users hungry for information from multiple sources in granular detail. Nor, Julie Pullen adds, will it be enough for the development of breakthrough AILM systems for better understanding the Earth and its atmosphere and oceans.

“It’s the datasets that don’t get incorporated into the top forecasts that you want,” she says.

Mainstream forecasts are not necessarily getting data sets acquired by, for example, scientists who might be going out on a research cruise, dropping sensors over the side of a ship, or releasing weather balloons off the deck. There are a lot of observations going on by commercial ships and aircraft just going about their routine business that could be valuable. Private companies are getting into the instrumentation business, including satellites.

Pullen says that part of the challenge in building standout AILM systems is identifying unique sources of data and then providing a pathway for that information to be incorporated into your model. Not only will this data arrive in a huge number of formats, but it may also not always be available from one forecast to the next. Customers want reliability as well as uniqueness.

“The data can be a little wacky,” she says. “Sometimes it’s [something] buried in the deep mud of the Pacific that tells us just what the temperature was at a certain point in time. Sources can be wildly unstructured.”  

For an idea of how times have changed, consider trends in the 3-month Treasury bill, according to the St. Louis Federal Reserve System. On September 1, 1981, it was a whopping 14.70%; by September 1, 2021, it was just 0.04%. But on September 1, 2023, it was up to 5.32%.

Data from the Fed show that investors are responding to this recent rebound by pouring money into Treasuries and other fixed-income securities. And some ETFs make it easier to trade in Treasuries, as well as in municipal and corporate bonds. 

Bonds vs. Stocks

Treasuries are one of the most popular income investments. They are safe, being guaranteed by the full faith and credit of the U.S. Government. They pay a good return. And unlike some lesser-known bonds or those not actively traded, Treasury securities are liquid. There is always a market for them. But how do Treasuries compare to other investments, such as stocks?

McKinsey & Company reports that, for the 25-year period ending in mid-June 2022, the S&P 500 returned 6.8 percent a year, including dividends. This is better than the return of today’s relatively high 3-month Treasury bill, which is a little over 5%. But the risk of losing money is higher in the stock market. Although equity market returns have been higher than fixed-income securities like bonds in many periods, there are also periods—in recent memory—when the stock market has had flat to negative returns. 

Bonds offer portfolios a return on money that is parked for expenses that are coming up or might arise. People feel comfortable having cash on hand for such expenses. But with inflation eating away at spending power, it is a waste of resources, especially when an investor can get around 5 percent today in relatively safe, liquid securities like Treasury Bills and investment-grade bonds.

New Ways to Buy Bonds  

The growth of exchange traded funds has changed the way many investors approach the stock and bond markets. With ETFs, an investor can pick the asset class they want and buy a package of securities that meets their needs, instead of trying to pick individual stocks or bonds. Owning many securities, even if it is in the same asset class, offers diversification, cutting a portfolio’s concentration risk. 

Recently F/m Investments, a provider of financial strategies to money managers and institutions, released the U.S. Benchmark Series Single Treasury ETFs. They make it possible to buy Treasury ETFs during stock market hours and lock in the current on-the-run yield—that is, the price and yield of the latest Treasury offering. 

These securities include a full maturity range of Treasury bills, bonds, and notes, from the 3-month Treasury Bill ETF (symbol: TBIL) to the 30-year Treasury Bond ETF (UTHY). But whatever the maturity term of the Treasuries, they remain in the ETF only until the next monthly rebalancing, and then those Treasury funds are rolled into the most recently Treasury offering of the same maturity. This usually changes the fund’s yield. Also keep in mind: The market price of publicly traded Treasuries and other income securities, in an ETF structure or as individual securities, will fluctuate, and money can be made or lost. 

But Treasury yields are attractive, especially on the short maturity end. At press time, the TBIL yield was 5.44%, and UTHY was 4.36%, although this yield will change constantly throughout a trading day as the market price changes.

These rates reflect an inverted yield: The shorter-term maturity bonds pay more than longer term maturity bonds. Usually, it is the opposite: Longer-maturity fixed-income securities pay a higher yield because of a perceived higher risk of climbing interest rates, which can cause the security to lose market value. 

The US Benchmark Series offers maturity date diversification. As interest rates fluctuate between the series offerings, investors can switch to a higher-yielding Treasury. The ETF series aims (but doesn’t guarantee) to pay interest monthly, another advantage over holding individual Treasuries. The expense ratio—operating costs, including any management fee—is reasonable at 0.15 % per annum. 

In July, Alex Morris, F/m’s president and CIO, announced that the US Benchmark Series had raised over $2.0 billion in assets under management (AUM) in less than a year—a substantial amount in that time period. Last May, TBIL won the ETF.com award for the Best New ETF of 2023. “The last thing you should do is worry about your Treasuries,” Morris tells Worth, saying that the simplest construction is to use the current series of outstanding Treasuries for the ETF. That would solve another problem: Treasuries have various maturities. A desired feature in the series, he felt, is that buyers should have access to the different maturities.

Bonds vs. Money Market and Savings Accounts

With the rise of short-term interest rates, some investors would rather keep things simple and hold money market funds, which provide returns by investing in high-quality debt securities. At press time, 3-Month Treasury ETFs had a higher return than many money-market funds, which hovered around 4.35% to 5.15%. But since ETF prices can and do fluctuate, and MMF’s attempt to stay at $1.00 a share, MMFs could be a more stable investment from a principal risk standpoint.

Investors looking for a fixed rate of interest with no market fluctuation could also consider high-interest savings accounts from providers such as CIT Bank or American Express National Bank. At press time, they went up to 5.05%. But that was still below the yield of the 3-month Treasury bill. And these savings accounts may have conditions or restrictions that ETFs don’t. A high-interest account might charge fees, require maintaining a minimum balance, or require leaving money in for a certain time period.  

Other Bond Investment Options 

Some investors may expect interest rates to dip and want to lock in the high yields of medium- and longer-term bonds by holding them until maturity. This isn’t possible with the US Benchmark, which continues rolling new Treasury issuances into the ETF. Also, there is the possibility of capital gains: The market price of higher-yielding bonds will rise if interest rates drop, and a bond holder can take a capital gain or continue holding.  

Invesco offers an alternative with its BulletShares ETFs, which hold hundreds of bonds in each maturity date, those bonds maturing from 2024 through 2033. BulletShares pay interest monthly and are actively traded. (Full disclosure: My clients and I own shares of TBIL and BulletShares.) 

BulletShares offers an investment-grade corporate bond series, which has a lower credit risk; a higher-risk high-yield corporate bond series; and a tax-free municipal bond series. Interest rates are attractive. The investment-grade 2026 maturity ETF (BSCQ) had a yield to worst, or YTW—the lowest possible potential yield—of 4.96% at press time. The high-yield series (BSJQ), maturing in 2026, had a YTW of 7.38%; the municipal bond (BSMQ) YTW was 3.03%.

Invesco provides an online “bond laddering” tool. It lets you create a portfolio by selecting the mix of bond series (based on risk/return), the timeframe for payouts, and the distribution of your investment across the various funds.

Unlike Treasury offerings, there is no Federal government backing in BulletShares. Payment obligations are from the issuing corporations in the investment-grade and high-yield ETFs; and local government authorities back the municipal ETFs. Of note: Municipal bonds are known to default at lower rates than corporate bonds, according to the Chicago Fed.

 The BulletShares offering has really grown since it launched in 2010. Jason Bloom, the head of fixed income, ETF strategy at Invesco, says he spent two years educating the market about target maturities, helping it raise its first $1 billion. He has since seen the ETF series grow to over $16 billion today and says it is growing faster than ever. 

Where is the Bond Market Headed?

Financial advisors feel confident that the Fed won’t be raising interest rates any more in the near future. “Clearly the consensus makes sense, and the Fed is not raising rates at the front end,” says Bloom, referring to short-term interest rates. Bloom said that further interest rate cuts, if and when they are made, all depend on inflation. “The Fed is slowing the economy to slow inflation,” he says, and this year everything depends on “how fast rates are going to come down at the front end of the curve.”

Bloom feels that the curve will un-invert soon, with short-term bond rates dropping and longer-term rates rising. And he sees an opportunity today in mid-term bonds. “I really think that in the 2- to 5-year maturity band is really where you’ll pick up a higher yield, because of the inverted curve,” he says, “and [it] has the most chance for capital appreciation if the Fed cuts rates.”

BulletShares can also effectively be used for bond laddering, as the following graphic shows.

There is an opportunity to receive a good return with a reasonable risk today in the bond market, and new financial products make it possible to select the degree and type of risk that you want. The objective of using them is the same as it has always been in this market: get a good return and understand what the risks are and how to avoid or minimize them.