Macro Roundup

“…Evidence from both recent worker surveys and historical data on quits shows that the “Great Resignation” is not as unusual as one might think.Waves of quits have been common during fast recoveries in the postwar period. In line with this historical evidence, the recent wave reflects the rapid rebound in labor demand for young and less-educated workers, largely driven by the retail, leisure and hospitality, and accommodation and food services sectors.... The relationship between high payroll growth and elevated quits rates is not only true across industries and occupations—it is also true over time. Figure 4 shows this, comparing the quits rate in the manufacturing sector with payroll job growth in the overall economy and in manufacturing. The figure shows that the quits waves in manufacturing in 1948, 1951, 1953, 1966, 1969, and 1973 are of the same order of magnitude as the current wave. All of these waves coincide with periods when payroll employment grew very fast, both in the manufacturing sector and the total nonfarm sector...Figure 2 shows that the increase in the quits rate is particularly pronounced for younger workers, including millennials (ages 25 to 34) in the current wave. That is reflective of a normal cyclical pattern in which the quits rate of younger workers responds more to business cycle conditions and drives a large part of the movements in the overall quits rate….”

Bart Hobijn, "“Great Resignations” Are Common During Fast Recoveries,"Federal Reserve Bank of San Francisco, April 2022, https://www.frbsf.org/economic-research/publications/economic-letter/2022/april/great-resignations-are-common-during-fast-recoveries/

“Great Resignations” Are Common During Fast Recoveries

The record percentage of workers who are quitting their jobs, known as the “Great Resignation,” is not a shift in worker attitudes in the wake of the pandemic. Evidence on which workers are quitting suggests that it reflects the strong rebound of the demand for younger and less-educated workers. Historical data on quits in manufacturing suggest that the current wave is not unusual. Waves of job quits have occurred during all fast recoveries in the postwar period.

The labor market recovery since the depth of the COVID-19 pandemic in the spring of 2020 has been the fastest in postwar history. This historic rebound is evidenced by the steepest decline of the unemployment rate and the fastest growth in payroll employment on record (Hall and Kudlyak 2021).

At the same time, the share of workers quitting their jobs—either to take new jobs or to exit the labor force—has also hit its highest level since 2000, when the data began being collected. This recent spike in quits has been referred to as the “Great Resignation.” Some have interpreted it as a wave of resignations, driven by people reconsidering their career prospects and work-life balance, that is drastically altering the labor supply. In this Economic Letter, I provide two pieces of evidence that cast doubt on this narrative and, instead, suggest that the high rate of quits is simply a reflection of the rapid pace of overall labor market recovery.

First, I find that the increase in the quits rate is driven by young and less-educated workers in industries and occupations that were most adversely affected by the pandemic. This is also where payroll employment growth has been high recently, offsetting the job losses incurred in 2020.

Secondly, the Great Resignation is not so great after all. Historical data on the quits rate in manufacturing point to waves of quitting being common during fast recoveries when employment growth was high. Thus, it is not an anomaly, but instead fits the pattern of many past rapid recoveries.

The quits rate and the Great Resignation

In the past few months, a record share of workers in the nonfarm sector quit their jobs each month. A quit is an employee who leaves their job voluntarily, either to go to another job, search for another job while unemployed, or drop out of the labor market. This share, known as the quits rate, reached 3.0% in November and December 2021—its highest level since it was first reported in December 2000 as part of the Bureau of Labor Statistics’ (BLS) Job Openings and Labor Turnover Survey (JOLTS) release.

The record level of the “Total” quits rate in Figure 1 is often pointed to as signaling a Great Resignation. This supposedly reflects a wave of people reconsidering their career prospects, opportunities for hybrid and remote work, and work-life balance—and ultimately resigning in such numbers that it is drastically altering the labor supply in the wake of the pandemic.

The earlier manufacturing data reveal several waves of quits that rival the current wave. Though the 2.3% rate in December 2021 is a record-high since 2000, the manufacturing sector hit comparable highs between 1948 and 1973.

Quits and rebound in demand for young and less-educated workers

One limitation of the JOLTS data is that they do not reveal what type of workers are quitting or whether they quit for career-changing reasons, such as switching industries or occupations, versus exiting the labor force. However, one can supplement the JOLTS information with evidence from the Current Population Survey (CPS; see Flood et al. 2021).

It is not possible to construct the direct equivalent of the JOLTS quits rate in the CPS because of conceptual, sampling, and scope differences between the two. With that in mind, I construct a proxy by measuring a quit in the CPS as someone who is payroll employed one month and, the next month, either reports to have switched job-to-job within payroll employment, switched to another type of employment, become unemployed and reports to have quit, or dropped out of the labor force and reports to have done so because of unsatisfactory working conditions.

The CPS data reveal four important facts. First, the industries with the biggest increase in their quits rate during the pandemic also saw the fastest job growth in 2021. Among these sectors are retail trade; arts, entertainment, and recreation; and accommodation and food services. These are also the sectors hit hardest by the pandemic. More generally, the correlation across industries between the change in the quits rate between November 2019 and November 2021 and payroll employment growth in the 12 months preceding November 2021 is positive in both the CPS (0.46) and JOLTS (0.49) data.

Second, a similar pattern holds across occupations. For example, the occupation with the highest increase in its quits rate is food preparation and service, which saw rapid employment growth over 2021. The cross-occupation correlation in the CPS between the quits rate change over the pandemic and 2021 employment growth is 0.38. Workers in these most-affected occupations tend to have less education.

Third, there was not a particularly large increase in the share of job quitters that changed either industry of employment or occupation. Such an increase would be expected if the current wave involved a broad reconsideration of career choices. The absence of such an increase is consistent, however, with the observation by David (2021) that there has not been a large net reallocation of payroll jobs across industries after the onset of the COVID recession.

The fourth fact is that the increase in the quits rate is largely due to younger and less-educated workers, as seen in Figures 2 and 3.

Figure 2 shows that the increase in the quits rate is particularly pronounced for younger workers, including millennials (ages 25 to 34) in the current wave. That is reflective of a normal cyclical pattern in which the quits rate of younger workers responds more to business cycle conditions and drives a large part of the movements in the overall quits rate.

Quits waves common during fast recoveries

The relationship between high payroll growth and elevated quits rates is not only true across industries and occupations—it is also true over time. Figure 4 shows this, comparing the quits rate in the manufacturing sector with payroll job growth in the overall economy and in manufacturing.

Thus, when the data are extended back prior to the JOLTS time frame beginning in 2000, the Great Resignation does not appear unusual. The current level of the quits rate is at a record high since 2000 because the recoveries of the 2001 and 2008 recessions were very slow by historical standards and thus did not put the same upward pressure on the quits rate as during other recoveries.

Wages and the “Great Renegotiation”

The link between employment growth and the quits rate that I document across sectors and occupations and over time is consistent with the model commonly used to assess the U.S. labor market conditions for low-skilled workers (Burdett and Mortensen 1998). That model explains how the quits rate is related to the frequency of job offers from other employers.

After a temporary spike in layoffs, like the one during the pandemic, employers post many vacancies to restaff and satisfy the rebound in demand for their goods and services. This explains the highly elevated job openings rate that has coincided with the record quits rate.

These vacancies do not only attract applicants who are unemployed. They also draw workers from other employers. Workers who receive a better offer will either quit their current job for another higher-paying job or renegotiate their wage, benefits, and work arrangements with their current employer. So, the “Great Resignation” is actually better interpreted as a “Great Renegotiation.”

As Manning (2006) points out, this can be interpreted as a temporary reduction in the bargaining power of employers that puts upward pressures on wages. His interpretation is consistent with recent wage pressures being highest in the retail and the leisure and hospitality sectors, which have also seen the highest employment growth and increases in job openings and quits rates.

These upward pressures on wages wane as the fast employment recovery slows down, the job openings rate tapers off, and the fraction of workers being poached by competitors declines.

It might take until late 2022 before this happens, however. Respondents to the November 2021 Survey of Professional Forecasters (Federal Reserve Bank of Philadelphia 2021) generally expect nonfarm payroll growth to remain high in 2022. If these forecasts are correct, the job openings and quits rates are likely to remain elevated and wage growth is likely to remain strong for the rest of the year.

Conclusion

Evidence from both recent worker surveys and historical data on quits shows that the “Great Resignation” is not as unusual as one might think. Waves of quits have been common during fast recoveries in the postwar period. In line with this historical evidence, the recent wave reflects the rapid rebound in labor demand for young and less-educated workers, largely driven by the retail, leisure and hospitality, and accommodation and food services sectors.

This analysis covers data through February 1, 2022.

“….Were wages flat during the Obama administration? Did they rise appreciably faster in the first three years of Trump...the answer is “no”...Annualized growth rate of real (PCE deflated) wage was about 0.6% during Obama administration. It was about a 0.6 percentage point higher during the first three years of the Trump administration, but that difference was nowhere near statistically significant.…”

Menzie Chinn, "Average Hourly Earnings, 2000-2022M02,"Econbrowser, March 31, 2022, http://econbrowser.com/archives/2022/03/average-hourly-earnings-2000-2022m02

Average Hourly Earnings, 2000-2022M02

Were wages flat during the Obama administration? Did they rise appreciably faster in the first three years of Trump (as asserted by this commentator)? 30 seconds of data retrieval reveals the answer is “no”.

Here’s the picture:

Maxim Massenkof and Aaron Chalfin, "Beyond Crime Rates: How Did Public Safety in U.S. Cities Change in 2020?,"Working Paper, March 8, 2022, http://maximmassenkoff.com/papers/victimization_rate.pdf

We plot crimes known to law enforcement for our combined NYC-Los Angeles-Chicago sample in panel Aof Figure 2, presenting monthly counts of violent crimes separately for 2019 and 2020. Public violence was approximately 10% higher in the winter of 2020 than the winter of 2019 but began to fall steeply after March 2020. In April 2020, public violence was approximately one third lower than it had been in April 2019. Consistent with the seasonality documented in prior research…public violence rose during the spring and summer months in both years. However, throughout the summer and into the fall months, these crimes remained between 5-20% lower in 2020 than they had been in 2019. Aggregating across the entire pandemic period of 2020 (March through December), public violence was 19% lower in 2020 than it had been in 2019. Next, Panel B plots violent street crime risk per 100,000 people using Safegraph data to measure the change in exposure. In March 2020, street crime victimization risk was roughly equal to risk in the previous year at approximately 5 violent street crimes per month per 100,000 person-visits to a community. However, at the same time that street crimes fell by more than 30% in April 2020, the risk of street crime victimization rose by nearly 40%. Victimization risk remained elevated throughout the summer approximately 12% higher in July 2020 than July 2019|and never fully returned to trend, even by the end of the year. For the March-December period, street crime victimization risk was approximately 14% higher in 2020 than it had been in 2019, despite a 19% decline in the incidence of public violence. Taken together, these results suggest that the increase in risk was not restricted to an aberration in gun violence. While gun violence rose by 47% in the three largest cities in the United States, the risk of other violent street crimes rose as well. Though street crimes appear to be less sensitive to the effects of the pandemic than shootings, the trends are much more similar after accounting for changes in criminal opportunities.

The Evidence

Using a variety of administrative and survey sources, as well as information on the movement of people based on mobile location data, we study the risk of public victimization in 2020. Newly-available survey data from the American Time Use Survey as well as foot traffic data from Google, Apple, Facebook and Safegraph, show that time spent outdoors fell rapidly in March 2020 before slowly rebounding thereafter. While Americans eventually began to return to many of their normal activities,even at the end of 2020, time spent outdoors remained about 20% lower than in 2019.We then compare the number of violent crimes known to law enforcement to measures of time spent away from home in order to calculate the risk of street crime victimization. We formulate this as the count of violent crimes occurring in public spaces divided by a measure of public foot traffic, inferred from SafeGraph data. While analyses of traditional crime data show discrete drops in opening during the post-pandemic lockdown period, we find that, in 2020, the risk of outdoor street crimes initially rose by more than 40% and was consistently between 10-15% higher than it had been in 2019 through the remainder of the year In the cities we study, people were more likely to be robbed or assaulted while spending time in public.

Methodology

In this paper, we illustrate how changes in human activity during the COVID-19 pandemic led to an unusual divergence between crime rates and victimization risk. Beginning in March 2020, public violence/assaults and robberies occurring in public or commercial space declined by approximately 35% as people responded to disease risk and mandated lockdowns by spending more time at home. These offenses remained 10-15% below 2019 levels throughout the summer before returning to 2019 levels in the fall. But what happened to the risk of violent crime that people faced in while spending time in public spaces? Because our principal measure of public safety the crime rate is so limited, conventional analyses are unable to answer this question

Divergence btw crime rate and “victimization rate”

The 1997 Asian Financial Crisis scared developing countries into accumulating more funds to shield their currencies from crashes,pushing official reserves from less than $2 trillion to a record $14.9 trillion in 2021, according to the International Monetary Fund. While central banks have lately sought to buy and repatriate gold, it only makes up 13% of their assets. Foreign currencies are 78%. The rest is positions at the IMF and Special Drawing Rights, or SDR—an IMF-created claim on hard currencies. Many economists have long equated this money to savings in a piggy bank, which in turn correspond to investments made abroad in the real economy. Recent events highlight the error in this thinking: Barring gold, these assets are someone else’s liability—someone who can just decide they are worth nothing.... China itself owns $3.3 trillion in currency reserves. Unlike Russia, it cannot usefully hold them in renminbi, a currency it prints. Stockpiling commodities is an alternative. The conundrum creates another incentive for Beijing to reduce its trade surplus by reorienting its economy toward domestic consumption, though it has proven challenging.

The risk to King Dollar’s status is still limited due to most nations’ alignment with the West and Beijing’s capital controls. But financial and economic linkages between China and sanctioned countries will necessarily strengthen if those countries can only accumulate reserves in China and only spend them there. Even nations that aren’t sanctioned may want to diversify their geopolitical risk. It seems set to further the deglobalization trend and entrench two separate spheres of technological, monetary and military power.

China itself owns $3.3 trillion in currency reserves. Unlike Russia, it cannot usefully hold them in renminbi, a currency it prints. Stockpiling commodities is an alternative. The conundrum creates another incentive for Beijing to reduce its trade surplus by reorienting its economy toward domestic consumption, though it has proven challenging.

What can investors do? For once, the old trope may not be ill advised: buy gold. Many of the world’s central banks will surely be doing it.

Jon Sindreu, "If Russian Currency Reserves Aren’t Really Money, the World Is in for a Shock,"Wall Street Journal, March 3, 2022, https://www.wsj.com/articles/if-currency-reserves-arent-really-money-the-world-is-in-for-a-shock-11646311306

If Russian Currency Reserves Aren’t Really Money, the World Is in for a Shock

“What is money?” is a question that economists have pondered for centuries, but the blocking of Russia’s central-bank reserves has revived its relevance for the world’s biggest nations—particularly China. In a world in which accumulating foreign assets is seen as risky, military and economic blocs are set to drift farther apart.

After Moscow attacked Ukraine last week, the U.S. and its allies shut off the Russian central bank’s access to most of its $630 billion of foreign reserves. Weaponizing the monetary system against a Group-of-20 country will have lasting repercussions.

The 1997 Asian Financial Crisis scared developing countries into accumulating more funds to shield their currencies from crashes, pushing official reserves from less than $2 trillion to a record $14.9 trillion in 2021, according to the International Monetary Fund. While central banks have lately sought to buy and repatriate gold, it only makes up 13% of their assets. Foreign currencies are 78%. The rest is positions at the IMF and Special Drawing Rights, or SDR—an IMF-created claim on hard currencies.

Recent events highlight the error in this thinking: Barring gold, these assets are someone else’s liability—someone who can just decide they are worth nothing. Last year, the IMF suspended Taliban-controlled Afghanistan’s access to funds and SDR. Sanctions on Iran have confirmed that holding reserves offshore doesn’t stop the U.S. Treasury from taking action. As New England Law Professor Christine Abely points out, the 2017 settlement with Singapore’s CSE TransTel shows that the mere use of the dollar abroad can violate sanctions on the premise that some payment clearing ultimately happens on U.S. soil.

To be sure, the West has frozen Russia’s stock of foreign exchange, but hasn’t blocked the inflow of new dollars and euros. The country’s current-account surplus is estimated at $20 billion a month due to exports of oil and gas, which the U.S. and the European Union want to keep buying. While these balances go to the private sector, officials have mobilized them. Stopping major banks like Sberbank from using dollars and excluding others from the Swift messaging system still plunges the economy into chaos, especially if foreign businesses are afraid to buy Russian energy despite the sector’s explicit exclusion from sanctions. But hard currency will probably keep gushing in through energy-focused lenders like Gazprombank, and can theoretically be used to pay for imports and buy the ruble.

Russia has spent the last few yearsshifting reserves into gold and theChinese renminbi...Russia, official reserves in gold and foreignexchange, by share of currencySource: Bank of Russia

Yet the entire artifice of “money“ as a universal store of value risks being eroded by the banning of key exports to Russia and boycotts of the kind corporations like Apple and Nike announced this week. If currency balances were to become worthless computer entries and didn’t guarantee buying essential stuff, Moscow would be rational to stop accumulating them and stockpile physical wealth in oil barrels, rather than sell them to the West. At the very least, more of Russia’s money will likely shift into gold and Chinese assets.

Wells Fargo economists, using labor market data, calculated that the drop in daycare employment from pre-pandemic levels has left about 460,000 families still in need of alternative arrangements. The latest data adds to evidence that a shortage of child-care workers is rippling throughout the U.S. workforce, hampering companies who are trying to hire more workers and particularly affecting the careers of women...But as parents struggle to find care for their children, the responsibility of staying home more often falls on the mother, Wells Fargo said. The labor-force participation rate among women has fallen to the lowest levels in decades during the pandemic, according to government data. “There are no overnight fixes to this issue,” Sarah House, a senior economist at Wells Fargo and co-author of the report, said in an interview. She added that there were broader implications for overall economic growth as a result of the child-care labor shortage.

Camille Furst, "Nearly Half a Million Families Are Hurt by the Child-Care Labor Shortage,"Wall Street Journal, March 2, 2022, https://www.wsj.com/articles/nearly-half-a-million-families-are-hurt-by-the-child-care-labor-shortage-11646237879

Nearly Half a Million Families Are Hurt by the Child-Care Labor Shortage

A daycare worker shortage has left nearly half a million families without child care, according to a new report, keeping many parents at home and hindering the labor market.

Wells Fargo economists, using labor market data, calculated that the drop in daycare employment from pre-pandemic levels has left about 460,000 families still in need of alternative arrangements.

The latest data adds to evidence that a shortage of child-care workers is rippling throughout the U.S. workforce, hampering companies who are trying to hire more workers and particularly affecting the careers of women.

Broadly, the U.S. labor market has recently shown signs of improvement as employers hired rapidly late last year and in January. The economy added 467,000 jobs in January and job growth in November and December was revised higher. The unemployment rate is 4%.

But as parents struggle to find care for their children, the responsibility of staying home more often falls on the mother, Wells Fargo said. The labor-force participation rate among women has fallen to the lowest levels in decades during the pandemic, according to government data.

“There are no overnight fixes to this issue,” Sarah House, a senior economist at Wells Fargo and co-author of the report, said in an interview. She added that there were broader implications for overall economic growth as a result of the child-care labor shortage.

President Biden, in his State of the Union address on Tuesday, urged lawmakers to take up a proposal to cut child-care costs for families. He said many families pay as much as $14,000 a year on child care per child.

“Middle-class and working families shouldn’t have to pay more than 7% of their income for care of young children,” Mr. Biden said. He said his plan, part of the Build Back Better bill that passed the House of Representatives in November but has stalled in the Senate, could cut the cost in half for many families.

Stephanie Schmit, director of child care and early education at the Center for Law and Social Policy, said the child-care industry has suffered from a declining number of workers for years, even before the Covid-19 pandemic, amid low wages and poor benefits. She said the pandemic gave more awareness to the issue, highlighting longstanding problems in the industry.

Cindy Lehnhoff, the director of the National Child Care Association, said the child-care industry needs the federal funding to attract workers.

“We definitely have to have some government assistance, similar to public school systems, if we want early education and child care to be at its very best,” Ms. Lehnhoff said.

Christopher Mims, "How the Pandemic Broke Silicon Valley’s Stranglehold on Tech Jobs,"Wall Street Journal, March 12, 2022, https://www.wsj.com/articles/how-the-pandemic-broke-silicon-valleys-stranglehold-on-tech-jobs-11647061211

How the Pandemic Broke Silicon Valley’s Stranglehold on Tech Jobs

Silicon Valley, make way for Silicon U.S.A.

In a feedback loop that could transform the economic geography of the U.S., millions of Americans are moving, and companies are following them—tech companies in particular. In turn, this migration of companies and investment is attracting more workers to places that in the past usually lost talent wars. This is a reversal of a decadelong trend in the opposite direction. It could have big implications for which parts of the U.S. will prosper and for income inequality, and so possibly also for politics, innovation and America’s overall ability to compete.

For decades, the success of America’s so-called “superstar cities” was driven by the tendency of the nation’s most productive workers and firms to cluster in a handful of places such as Silicon Valley. Now, in the economic equivalent of the blink of an eye—the two-year span of the pandemic—that has begun changing.

Until very recently, evidence for this shift has been mostly anecdotal and preliminary. But a cornucopia of Research has yielded eyebrow-raising statistics documenting the scale and speed of this change in how people with jobs that can be done remotely work and live:

Nearly 5 million Americans say they have moved since 2020—and 18.9 million more are planning to do so—on account of remote work, according to a survey released this past week by Upwork, a platform connecting employers and freelance workers.

In the U.S., nearly a quarter of all full work days will happen at home after the pandemic ends, as opposed to 5% before the pandemic, according to survey data published in December that was gathered by economists at Stanford University, University of Chicago and the Instituto Tecnológico Autónomo de México.

A paper from researchers at Oxford Universify, the OECD Economics Department and Indeed, the job-postings site, found that as of December 2021, the proportion of job listings in 20 countries that mentioned the possibility of remote work had more than tripled from before the pandemic, to 8.5% from 2.5%. The same researchers also tracked how such postings changed as pandemic restrictions ebbed and flowed, and found evidence these figures are unlikely to budge after pandemic restrictions end.

Yet another paper published this past week, from economists at Stanford, MIT Sloan, Princeton University and other institutions, makes the case that the U.S. government has undercounted the share of Americans working remotely by 33 percentage points, and about half of all U.S. workers currently perform their jobs remotely at least some of the time.

Finally, research out this past week from the Brookings Institution provides fresh evidence that the rise of work-from-anywhere as both a technological and cultural phenomenon is driving a mass migration of capital, companies and workers. They are heading to a diverse array of cities that for decades saw their best and brightest drained away to places like the San Francisco Bay Area, New York City and Seattle. These new “rising star” cities include Atlanta, Dallas, Denver, Kansas City and St. Louis, according to Brookings.

“We knew remote work was feasible, and we knew job seekers wanted it, but it was the pandemic that made it an actual day-to-day experience, and once it happened it stuck,” she adds.

The surge in pandemic-induced remote work happened to coincide with another phenomenon, years in the making, according to data from Brookings: a decade or more of increased investment in tech firms clustered in cities outside regions that typically consume the lion’s share of investment and talent.

The result of the convergence of these two reinforcing trends is that, in 2021, six of nine rising-star cities all saw growth in the number of postings for tech jobs, a proxy for future employment in those cities. During the same period, postings in Boston, the Bay Area, New York and Los Angeles declined, according to data from Brookings.

Commentators and local boosters have been proposing for decades, perhaps wishfully, that this sort of thing might happen. From the “Silicon Prairie” to “Philicon Valley,” it’s been a slow build to the present inflection point, and some regional tech hubs are growing more quickly than others.

The movement of capital, talent and companies has typically been a relatively slow process, and can take decades, says Margaret O’Mara, a professor of history at the University of Washington and author of “The Code,” a history of Silicon Valley. The development of America’s existing superstar tech hubs are the clearest example of that—after all, the term “Silicon Valley” was coined a half-century ago.

“One of the secrets of Silicon Valley is time,” says Dr. O’Mara. “No mayor or county executive wants to hear that answer, which is why I don’t have a multimillion-dollar economic-development consulting career.”

The ascension of these new tech hubs is hardly an apocalypse for America’s superstar cities or the tech companies and tech workers in them, says Mark Muro, who conducted the research for Brookings. But it does seem to be the first full-year data in a shift that is just getting under way. Data in 2022 and beyond should show an even more profound shift in employment away from what have in the past been dominant cities for tech, he adds, especially as a number of tech companies, such as Oracle and Tesla, transfer workers as a result of moving their headquarters out of the Bay Area.

After the rise of remote work and the growth of more tech hubs, a third underlying trend could also be driving this geographic shift: the maturation of some of the technologies that for decades have underpinned Silicon Valley and other hubs, in particular the microchip and the internet itself.

The “silicon” in Silicon Valley is, after all, a reference to what microchips are made of. The first commercially available integrated circuit was produced in 1961 by Fairchild Semiconductor, in Santa Clara, Calif. The PC revolution and later the internet created the tech giants of today, mostly in and around the Bay Area and Seattle.

But the outsourcing of electronics manufacturing and the rise of cloud services have made it much easier to build a tech startup anywhere. The dispersal of the knowledge required to build companies, and the precipitous drop in the cost to launch a startup in the tech industry, are both hallmarks of what historians call a “mature” set of technologies. This doesn’t mean these technologies are done evolving, just that the rate of breakthroughs has slowed enough that companies built far from where they were first invented can now participate in their development.

Some historians and economists have declared our current age the “fourth industrial revolution.” If that’s so, then in some ways it might be following the path of past industrial revolutions, says Dr. O’Mara. From England’s 18th-century Industrial Revolution—which quickly became America’s, after the requisite expertise and technologies were transplanted across the Atlantic—to the rise of Detroit, history is full of new technologies that started in one place, made those who lived there enormously wealthy, and eventually became global phenomena, leading to specialized hubs of knowledge and production all across the world.

While it’s impossible to precisely copy the formula that worked for the Bay Area and build the “next Silicon Valley,” regional tech hubs can prosper by finding their own niches, she adds.

Atlanta is a good example of these trends. While it was largely left out of the early decades of the rise of the PC and the internet, the presence of corporate headquarters and the Georgia Institute of Technology meant it had both demand for the products of enterprise tech startups and the talent to build them.

America’s ninth-largest metro area has quietly become an assembly line for tech unicorns, with five of its startups topping $1 billion valuations in 2021 alone, including Calendly, which streamlines the process of scheduling meetings, and Stord, which helps businesses with fulfillment and logistics. The result of successive waves of startup exits, followed by mentorship and reinvestment from startup founders, plus the proximity of potential customers in the headquarters of Fortune 500 companies like Home Depot and United Parcel Service, means that the city has built up all the elements necessary to churn out tech startups.

Combined with the relatively low cost of living and the availability of housing—both in sharp contrast to superstar cities—Atlanta has attracted workers in a way that gives it a talent pool ready-made for new startups, says Adam Steinberg, a serial entrepreneur in the Atlanta area and CEO of Fetch, a startup that allows individuals and small businesses to rent trucks and utility vans by the hour.

Mr. Steinberg went through the storied startup-accelerator program Y Combinator, where he was advised he would have better access to funding and talent if he moved his company to the Bay Area. But other variables, such as his existing professional network in Atlanta, being close to family and friends, and the fact that he could sustain his company longer on the same amount of investment because of Atlanta’s lower costs, kept him in that city.

The pandemic has made finding talent easier, he adds, because with the rise of the remote-first work culture across the tech industry, he can hire workers anywhere in the world.

Also, he felt that for a truck-rental company it was important to start in a city typical, in its layout and demographics, of most of America: “We figured if we could make it in Atlanta, we could make it anywhere.”

Nearly 5 million Americans say they have moved since 2020—and 18.9 million more are planning to do so—on account of remote work, according to a survey released this past week by Upwork….In the U.S., nearly a quarter of all full work days will happen at home after the pandemic ends, as opposed to 5% before the pandemic, according to survey data published in December that was gathered by economists at Stanford University, University of Chicago and the Instituto Tecnológico Autónomo de México....The surge in pandemic-induced remote work happened to coincide with another phenomenon, years in the making, according to data from Brookings: a decade or more of increased investment in tech firms clustered in cities outside regions that typically consume the lion’s share of investment and talent. The result of the convergence of these two reinforcing trends is that, in 2021, six of nine rising-star cities all saw growth in the number of postings for tech jobs, a proxy for future employment in those cities. During the same period, postings in Boston, the Bay Area, New York and Los Angeles declined, according to data from Brookings.