(88 pages)
When the COVID-19 pandemic began in 2020, daily life changed for billions of people in countless ways. The most important, from the perspective of real estate in superstar cities, was a sudden and massive shift to remote work, a change that was enabled by widespread adoption of videoconferencing and file-sharing technology. In the blink of an eye, millions of employees were working not at their offices downtown but from their bedrooms and couches.
That shift affected their behavior in three main ways. First, of course, it changed where they worked. Second, it changed where they lived; untethered from their daily commutes, many of them moved away from urban cores. Third, it changed where they shopped, as online shopping and stores near home became more attractive than urban establishments. Those three behavioral changes, in turn, affected the three classes of real estate—office, residential, and retail—that we discuss in the next chapter.
The three changes were not all permanent, but they have left cities permanently altered. In this chapter, we examine them in detail. Our research suggests that remote work will continue, that accelerated urban out-migration is slowing but not reversing, and that shopping in cities will remain weaker than it used to be.
Hybrid work is here to stay
After abandoning their offices at the start of the pandemic, employees are now working there more often—though still far less than they used to. Office attendance varies by city; for example, it tends to be lower in cities with expensive housing and a large share of knowledge-economy workers. It also varies by industry and workers’ demographic characteristics. There are several reasons to think that office attendance has stabilized and will continue at current rates.
Office attendance is still 30 percent lower than it was before the pandemic
In early 2020, office attendance plummeted for workers in superstar cities. Lockdowns, office closures, and uncomfortable masks gave them a reason to work remotely, and existing technology gave them the means. Office attendance fell by 90 percent in New York City and San Francisco.1Data from Kastle, a company that manages access to office buildings in the United States. The drops in Austin, Dallas, Houston, and Los Angeles were less severe but still stark at about 70 percent.
As of fall 2022, workers were going to the office just 3.5 days per week, on average, some 30 percent below prepandemic norms.
Three years later, remote work has given way to hybrid work (a combination of in-office and remote work), and office attendance has rebounded substantially. But as of fall 2022, workers were going to the office an average of just 3.5 days per week, some 30 percent below prepandemic norms, according to our survey. (For more information about the survey, see the technical appendix.)
Of all the survey respondents, 37 percent go to the office every day (Exhibit 1). An additional 56 percent have hybrid work arrangements and thus spend one to four days per week in the office. And 7 percent work fully remotely.
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Image description: A stacked bar chart plots the distribution of workers according to how many days per week they reported going into the office, with 37% going 5 days a week, 18% going 4 days, and 19% going 3 days. A dot plot shows the average days per week reported across nine across North America, Europe, and Asia, ranging from London at 3.1 days to Beijing at 3.9 days. End of image description.
Office attendance is lower in metropolitan areas with expensive housing and a large share of knowledge-economy workers
Office attendance varies among metropolitan areas. Employees in Beijing, for example, go to the office 3.9 days per week, on average, while those in London go just 3.1 days per week. The other metropolitan areas we studied ranked between those extremes and were mostly clustered around 3.3 to 3.6 days in the office. Similarly, the percentage of workers who do not work from home at all varies by country. In Japan, more than half of all office workers spend five days per week in the office. In the United Kingdom, just 28 percent do.
Two urban characteristics seem to matter most in determining office attendance in a metropolitan area: its proportion of knowledge-economy workers and its housing costs (Exhibit 2). According to our regression analysis of US counties, the higher a county’s ratio of knowledge-economy workers to other workers, the lower its average office attendance. (We define the knowledge economy as the professional services, information technology, and finance industries.) Similarly, the higher home prices are in an urban core relative to its suburbs, the lower the metro area’s average office attendance is (see Box E1, “How we define cities,” in the executive summary). Other characteristics of US counties with lower office attendance, according to our analysis, are a larger share of commuters and a smaller share of retail employees (which suggests a more limited retail presence). It seems reasonable to think that those relationships would also exist in superstar cities elsewhere in the world, but we were not able to confirm that.
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Image description: A pair of scatterplots show dozens of circles representing U.S. metro areas. The vertical axis plots the change in foot traffic near offices over 2020 to 2022, with all cities decreasing up to 50%. The first horizontal axis plots typical home value in each metro area creating a downward trend in the circles position from left to right, indicating a slower return to the office in more expensive areas. The second horizontal axis plots the share of knowledge-economy workers in each metro area, revealing a similar downward trend from left to right, indicating a slower return to the office in places with more knowledge workers. End of image description.
Culture and government policy also play a role in office attendance. For example, Chinese cities’ high rates of office attendance today can probably be explained by the widespread “996” office culture (for “9 a.m. to 9 p.m. in the office, six days a week”). And Beijing’s and Shanghai’s citywide lockdowns reduced office attendance to near zero when they were in effect.
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Employees in the knowledge economy go to the office less often than do those in other industries.
A businessman standing at desk in an empty office looking down at his computer monitor with his arms on his hips.
Office attendance is lower in large firms in the knowledge economy
Employees at larger firms report significantly lower office attendance than do those at smaller firms (Exhibit 3). For example, at firms with 1,000 to 9,999 employees, workers go to the office 3.3 days per week, on average; at firms with 50 to 99 employees, attendance averages 3.7 days. One potential reason is that larger companies tend to have more resources and technology to support working from home. Another is that the sense of community may be stronger at smaller companies, prompting more employees to visit the office.
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Also, client meetings are less of a reason to come to the office for employees at larger companies than for those at smaller ones. At companies with 1,000 to 24,999 employees, 25 percent of survey respondents ranked meeting with clients as one of the top three reasons to come to the office, whereas at companies with fewer than 100 employees, 32 percent did. A similar pattern exists for employees in client-facing roles: among salespeople at companies with 1,000 to 24,999 employees, 42 percent go to the office five days per week, a share that grows to 54 percent at companies with 2 to 99 employees.
And employees in the knowledge economy go to the office 0.2 fewer days per week than do those in other industries. One reason could be that knowledge-economy industries are highly digitized and therefore amenable to remote work. Another could be that employees in those industries therefore see less need for commuting and have a lower tolerance for it. Even though their commutes are no longer than those of other workers, they were much likelier than other workers to call saving commuting time one of their top three reasons for working from home.
Office attendance varies in subtle ways by age, income, and seniority
The average number of days that respondents work in the office does not vary much by age, income, or seniority (Exhibit 4, left side). For example, millennials reported working 3.4 days per week in the office, and members of Generation X and baby boomers reported 3.5. The starkest variation we found was among millennials in senior positions, who go to the office 3.7 days per week, more than any other group we studied.
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Image description: A package of charts show color-coded rectangles to summarize office attendance by age, income, and job seniority, with darker colors indicating more days per week. Across all categories, Baby Boomers generally went into the office more than Generation X or Millennials. Lower-income workers making less than $50,000 a year went into the office more, as did junior-level workers. End of image description.
However, there are some differences in the likelihood of those groups to go to the office a particular number of days per week (Exhibit 4, right side). Two differences in particular stand out. First, baby boomers are much likelier to go to the office five days per week than younger workers are. Second, junior-level workers are much likelier to go to the office five days per week than midlevel and senior employees are; perhaps counterintuitively, they are also more likely to work entirely remotely, never going to the office at all.
Furthermore, cluster analysis of respondents in the United States reveals statistically significant groups among those who mostly go to the office and those who mostly work from home. There are two such groups among people who mostly go to the office: high-earning male C-suite employees and low-earning female junior employees. There are also two such groups among people who mostly work from home: knowledge-economy workers who earn over $200,000 per year and, again, low-earning female junior employees.
Employees work from home to save commuting time, and they work from the office to see their teams
When we asked survey respondents who were able to work from home what their top reason was for doing so, the most popular answer globally, as we expected, was to save commuting time, followed by increasing productivity and saving money (Exhibit 5). The answers varied by country, however. For example, 38 percent of respondents in Japan cited saving commuting time as their top reason, whereas just 11 percent of those in China said the same. Saving money was the top reason for 11 to 15 percent of respondents in Europe but for just 3 percent of those in Japan. In all countries, however, respondents called increasing productivity one of the top reasons.
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Image description: Bar charts plot survey respondents' answers to why they chose to work in the office or from home when they had the option to do either. Top among those who went to the office was to work with my team, while top among those working at home was to save commuting time. End of image description.
The most popular reasons given by workers with flexible work arrangements for choosing to come to the office were to be able to work with their teams, to comply with an employer’s policy, and to increase productivity. (The fact that increasing productivity was cited as a top reason for both going to the office and working from home suggests that where employees feel most productive may differ by individual or task.) Those findings were substantially consistent in France, Germany, the United Kingdom, and the United States. In China and Japan, however, few respondents cited an employer’s policy as their top reason for going to the office.
The current rate of office attendance may persist
Three indicators suggest that the current rate of office attendance may have stabilized. First, in ten of the most populous cities in the United States, office attendance has held roughly steady since mid-2022, aside from a normal seasonal dip around the winter holidays (Exhibit 6).2Data from Kastle. Note that the access badges that the data are drawn from are mostly used in large, Class A office buildings. Second, three numbers—the number of days per week that survey respondents go to the office, the number of days that they expect to go to the office after the pandemic ends, and their preferred number—are not far apart (Exhibit 7).
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Image description: A line chart plots the change in office attendance from 2020 to early 2023 in 10 large U.S. cities, initially plunging to about 17% of prepandemic levels and gradually rising to a range of 40% to 65%. Three Texas cities — Austin, Houston, and Dallas — remained above average throughout, while the rest were mostly below average. End of image description.
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Image description: A dot plot shows the number of days worked in the office across nine international cities, along with survey respondents' ideal number of days, plus the number of days they expect after the pandemic ends. The values across all categories range from 2.5 to 4.5 days, with the ideal number lower than the expected number in each city. End of image description.
Third, a sizable and influential group of office workers strongly prefer to continue working remotely. About 10 percent of respondents worldwide said that they were both likely to quit their jobs if required to work at the office every day and willing to trade more than 20 percent of their compensation to work their preferred number of days from home. That group is comparatively senior and well paid; 44 percent of them are in senior roles, and 33 percentof them earn more than $150,000 per year (Exhibit 8). Their seniority and high incomes suggest that they are probably decision makers who can protect remote work at the team or company level.
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Image description: A histogram-style bar chart plots the income distribution of workers who strongly prefer to work from home, with 33% making more than $150,000 a year and 31% making $100,000 to $150,000. Another chart shows a distribution of job seniority, with 44% of workers who strongly prefer to work from home holding senior positions and 50% holding midlevel positions. End of image description.
Nevertheless, it is not certain that office attendance will stay at its current level. For example, employees might gain bargaining power and reduce the number of days they work in the office, or employers might gain bargaining power (in the event of a recession, for example) and increase that number. Improvements in hybrid work technology and processes could make it less necessary to come to the office.
Office attendance could also rise if employers find ways to attract workers back to the office. As pandemic restrictions loosened, employers often offered perks, such as free meals and in-office recreational areas, to encourage employees to return. But that approach appears to have succeeded only on a very limited scale; just 3 percent of respondents who were able to choose where to work called such perks their top reason for going to the office.
In the long run, what chiefly determines the rate of office attendance will be its impact on productivity. If research conclusively indicates either a negative or a positive relationship between hybrid work and productivity, that could push office attendance up or down, respectively. Studies conducted by companies and research institutions have so far shown no negative relationship between hybrid work and productivity. 3See The next great disruption is hybrid work—are we ready? Microsoft, March 2021; State of remote work 2020, Buffer, February 2020; and Nicholas Bloom et al., “Does working from home work? Evidence from a Chinese experiment,” The Quarterly Journal of Economics, volume 130, number 1, February 2015. For example, a previous MGI report found that about 20 to 25 percent of the workforces in advanced economies could work from home between three and five days a week without a loss of productivity.4The future of work after COVID-19, McKinsey Global Institute, February 2021. Employees themselves seem to believe that hybrid work helps productivity; in our survey, 87 percent of survey respondents indicated that they would be more productive if they worked their desired number of days at home than if they had to work at the office five days per week.
Up to 7 percent of the people in urban cores left for good
For more than 20 years, superstar cities were the center of global growth. Just 1 percent of the Earth’s surface was home to more than 50 percent of global GDP growth and population growth from 2000 to 2019.5Pixels of progress: A granular look at human development around the world, McKinsey Global Institute, December 2022. The two types of growth reinforced each other: “agglomeration economies” fueled economic and productivity growth in these cities, resulting in high-income jobs that attracted still more people.6See, among others, Greg Howard and Jack Liebersohn, “Why is the rent so darn high? The role of growing demand to live in housing-supply-inelastic cities,” Journal of Urban Economics, volume 124, July 2021; Kathleen Bolter and Jim Robey, Agglomeration economies: A literature review, W. E. Upjohn Institute for Employment Research, June 2020; and Edward L. Glaeser, ed., Agglomeration economics, National Bureau of Economic Research, February 2010. Glaeser defines agglomeration economies as “the benefits that come when firms and people locate near one another together in cities and industrial clusters.” They came even though housing tended to be expensive—especially in superstar cities where the supply of housing was very constrained, such as San Francisco.
Then the pandemic began, prompting a wave of households to leave superstar cities and thus driving down population (Exhibit 9). Munich’s population grew by 1.0 percent per year from 2014 to 2019, for instance, but it grew by only 0.3 percent per year from 2020 to 2022. In Boston, population growth during the first period turned into population decline during the second. Urban cores were particularly affected. For example, New York City’s urban core lost 5 percent of its population from mid-2020 to mid-2022, and San Francisco’s lost 7 percent. One reason for the surge of out-migration was hybrid work. Now that people were not working at the office, they cared less about living nearby and could instead prioritize better housing conditions.
Image description: A bar chart plots annual population growth in 24 international metro areas during the prepandemic years of 2014 to 2019, with most showing growth up to 2%. A second chart shows the population change during the pandemic years of 2020 to 2022, with most showing losses up to 2%, or gains just above 0%. End of image description.
Out-migration has since declined, but it has neither ended nor reversed, and it seems to remain higher than it was before the pandemic began. That is, the people who left the urban cores are not coming back, and many others are still leaving.
During the pandemic, a wave of households in superstar cities moved from the urban cores to the suburbs, a trend that was strongest in the United States
In all but two of the superstar cities we studied, after the pandemic began, the difference between urban and suburban population growth shifted to the suburbs’ advantage (Exhibit 10).7Those two cities are Beijing and Munich. The time in question is the 2020–22 period, except for Beijing, London, and Shanghai, where data about population changes in 2022 were not available; for those cities, we studied the 2020–21 period. Also, the month in which the 2020–22 period begins differs from country to country. For example, for the United States, the period begins in July 2020 and ends in July 2022, but for France, it begins in January 2020 and ends in January 2022. Exactly how much varied from city to city. The difference between urban and suburban population growth was largest in London, Dallas, Houston, New York City, and San Francisco. In most US cities, suburbanization had already been happening and was simply accelerated by the pandemic. By contrast, all the European cities that we studied except Paris and Munich had been urbanizing before the pandemic, so the suburbanization represented a reversal. The Japanese cities had also been growing more urban before the pandemic, but there, the trend continued even after the pandemic started.
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Image description: A dot plot shows growth rates in urban and suburban areas around 24 cities across North America, Europe, and Asia. Comparing growth in the pandemic years of 2020 to 2020 versus the five prior years, nearly all of the metro areas saw greater growth rates in their suburbs, especially in U.S. cities. End of image description.
Population trends in Beijing were very different from those in other cities. For years before the pandemic, the government had relocated Beijing’s residents to suburban areas. During the pandemic, however, it imposed policies restricting movement; as a result, population growth in Beijing’s urban core nearly matched that in its suburbs.8In 2020, domestic migration declined by 40 percent in 369 Chinese cities. See Debin Lu et al., “Spatiotemporal patterns and influencing factors of human migration networks in China during COVID-19,” Geography and Sustainability, volume 2, issue 4, December 2021.
The suburbanization effect may have been stronger in US superstar cities than in European and Japanese ones because the urban cores of US superstar cities tend to be office-dense and retail-poor, whereas the European and Japanese urban cores tend to follow a mixed-use model in which office, residential, and retail space exist alongside one another. Supporting that contention is our statistical analysis of US counties, which indicates that those experiencing the highest rates of out-migration during the pandemic tended to have four characteristics: expensive homes, high office density, a high share of workers in the knowledge economy, and a low share of workers in retail, which suggests a more limited retail presence (Exhibit 11).9Specifically, we studied about 130 counties in the Atlanta, Boston, Chicago, Dallas, Houston, Los Angeles, New York City, Philadelphia, San Francisco, Seattle, and Washington, DC, metropolitan areas. As a proxy for home price, we used the Zillow Home Value Index at the county level; to measure office density, we used employment as a share of population.
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Image description: A package of four scatterplots shows dozens of circles, each representing a county around one of 11 large U.S. cites. The vertical axis for all four charts plots the share of people migrating in or out of the county, ranging from negative 6% to positive 6%, with about half of the circles on either side of the 0% lines. The horizontal axis is different for each of the four charts, plotting the counties' typical home values, share of employment, share of knowledge-economy workers, and share of nonretail workers. Each chart shows a similar downward trend from left to right, indicating that counties with higher values on the horizontal axis saw greater out-migration. End of image description.
The same patterns held true at the zip code level during the pandemic. When we conducted an analysis of neighborhoods in San Francisco County, New York County (Manhattan), and Harris County (which is mostly Houston), we found that people moved out of expensive, office-dense zip codes and into cheaper ones with more mixed use of real estate.
Hybrid work encouraged the out-migration
To learn more about why people left urban cores during the pandemic, we identified survey respondents who had moved after March 2020 for pandemic-related reasons. They represented the majority of all respondents who had moved after March 2020 (Exhibit 12). Roughly a third of them said that their moves would not have been possible without remote work.
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Image description: A treemap-style chart shows that 19% of respondents moved for pandemic-related reasons and 69% had not moved during the pandemic. Next, a pair of gridplot charts shows that among those who moved, 39% were likely or extremely likely to quit a job if forced to attend the office five days a week, compared with 26% among those who didn't move. A second pair of gridplots shows that 59% of those who moved reported being a primary caregiver, compared with 44% among those who didn't move. End of image description.
Pandemic-related out-migration after March 2020 was led by young households, and in particular by young people who had caregiving responsibilities and who valued remote work. Respondents who moved because of the pandemic were younger than those who did not move (averaging 36 years of age as opposed to 43); were more prone to say that they were “likely” or “extremely likely” to quit their jobs if forced to go to the office five days a week (39 percent versus 26 percent); were likelier to be caregivers (59 percent versus 44 percent); and had bigger households, on average (3.1 people versus 2.9).
Many of these moves happened because employees untethered from their daily commutes began to care less about how far they lived from the office. Of all survey respondents who went to the office less than five days per week, 38 percent said that remote work had made them more willing to live farther from the office. In the United States, 55 percent of respondents who moved during the pandemic went to places that were farther from the office than their previous homes had been, while just 33 percent moved closer.
Out-migration has since slowed, but people are still leaving urban cores
Out-migration from superstar cities’ urban cores seems to have slowed of late. Between 2020 and 2021, 0.32 percent of the US population left superstar urban cores; the following year, that share fell to 0.24 percent (Exhibit 13).10Data from the US Census Bureau. But that loss is still larger than it was before the pandemic. In other words, the people who moved out during the pandemic are not moving back, at least not yet. The main beneficiaries of out-migration seem to be rural and suburban areas near non-superstar cities.
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Image description: A line chart plots migration in and out of U.S. counties from 2011 to 2022, with one pair of lines showing the urban and suburban areas of 11 large superstar cities and a second pair showing the urban and suburban areas elsewhere. The two urban lines slope downward, including a 0.3% population drop in 2021 in superstar cities. And the two suburban lines rise upward, including an increase of more than 0.3% in 2021 in non-superstar areas. End of image description.
Our survey suggests that the people who left urban cores in other countries are not coming back either. In China, 41 percent of pandemic-related movers said that they might move back, but that share was less than a quarter in France, Germany, Japan, and the United Kingdom. Pandemic-related movers’ strong preference for hybrid work—and their professed willingness to quit their jobs if denied it—also implies that they are unlikely to move back.
Shopping remains depressed, especially in urban cores
Just as the shift to hybrid work has changed people’s residential preferences, it has changed their shopping preferences. During the height of the pandemic, foot traffic near brick-and-mortar stores plummeted, especially in urban cores. The office workers who used to sustain those stores shopped there far less, shifting their purchases to the internet and to stores near their homes in the suburbs. More recently, foot traffic near urban stores has risen again, but it remains lower than it was before the pandemic, spelling problems for retailers.
As people stayed home during the pandemic, they radically changed the way they shopped
In March and April 2020, as the pandemic began, foot traffic near stores plummeted in the superstar cities we studied (Exhibit 14).11Data from Google’s COVID-19 Community Mobility Reports. The declines were starkest in London and Paris, where it fell by about 80 percent. In New York City and San Francisco, it fell by 50 to 60 percent during the same period, while in Houston and Tokyo, it declined by only about 30 percent. The different outcomes may have been due to variations in government policies, degrees of tourism, acceptance of remote work, and other cultural norms. For example, the strict lockdowns that London and Paris imposed in March may have contributed to those cities’ precipitous declines.
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Image description: A line chart plots foot traffic near stores in six international cities from 2020 through 2022, with lines initially dropping as low as 20% of prepandemic levels and recovering in 2022 to a range of 75% to 90%. End of image description.
One trend that helped consumers visit stores less often was a quickening shift to online shopping (Exhibit 15). Online spending as a share of all retail spending had already been growing; in the three years before the pandemic, that share grew by 0.4 percentage point per year in Japan and by 2.2 percentage points per year in China, for example. But then the pandemic began, and the share spiked from the end of 2019 to the end of 2020. The spike occurred in all the countries we studied; it was smallest in Japan (1.3 percentage points) and largest in China (9.9 percentage points). The pandemic effectively accelerated the use of online spending by three to four years.
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Image description: A line chart plots online spending as a share of all retail spending from 2016 to 2022 in six countries. Each line starts in the range of 5% to 15%, spikes upward in 2020 and then settles in the range of 12% to 35%, with China and the United Kingdom leading the way. End of image description.
An interesting fact is that the countries seeing the sharpest increases, China and the United Kingdom, were the ones where online spending represented the largest share of all retail spending before the pandemic. Perhaps those countries were the most primed for e-commerce growth—with greater customer awareness, more mature distribution, and more adept retailers—and were therefore best able to meet the surge in demand during the pandemic.
Shopping behavior has started to return to prepandemic trends, yet foot traffic and purchasing in stores remain lower
Although it spiked during the first year of the pandemic, online spending as a share of retail spending is now at the same level that it would have reached by now if the pandemic had not happened. It has done that either by growing more slowly (as in France and Germany) or by shrinking (as in China and the United States), though of course it remains higher everywhere than it was before the pandemic.
Yet foot traffic near stores remains down. As of October 2022, it appeared to have stabilized at a level 10 to 20 percent lower than the prepandemic level in the metropolitan areas we studied.
Spending in stores also remains down, though not as much as foot traffic (Exhibit 16). In most metropolitan areas, it was estimated to be as much as 10 percent lower in 2022 than it had been in 2019 in real terms—though in Beijing, where lockdowns remained in force through most of 2022, it was far lower. Although this is bad news for stores, at least the decline in spending has not been as steep as the decline in foot traffic: shoppers have consolidated trips, making purchases more frequently when they do visit stores and spending more per trip.
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Image description: A line chart plots spending in stores as a percentage on prepandemic 2019 levels across eight international cities. Spending dropped in 2020 but mostly recovered by 2020 with most cities a little below 100% of 2019 levels. End of image description.
And though consumers famously shifted their spending from services to goods during the pandemic, they have been slowly shifting it back to services since mid-2021. In the United States, for instance, spending on goods has stabilized since the end of 2021, but spending on services has continued to grow past prepandemic levels in real terms (Exhibit 17). In France, spending on services grew in 2021 in real terms; in 2022, it grew again, even as spending on goods fell.
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Image description: A line chart plots US monthly consumer spending on goods and services from 2013 to 2023. The vertical axis is indexed to 2015 levels with goods rising above 130% and services above 110%. Both lines dropped in 2020 at the onset of the pandemic, with goods spending recovering within a few months and services spending not recovering until late 2021. But over 2022, goods spending line stays about flat while services spending rises. End of image description.
Those trends will pose challenges for brick-and-mortar stores’ sales. The upward march of online sales will eat away at the stores’ revenues, even though that march has slowed since 2020. Lost foot traffic will do the same unless stores find ways to improve their marketing or encourage the customers who do visit to make more and larger purchases. (The most successful retailers are rethinking their store formats to support omnichannel experiences—those in which customers’ in-store and online experiences, including the marketing aimed at them, are integrated.) The spending shift from goods back to services may further reduce foot traffic to stores selling goods. And other trends could further complicate stores’ prospects. For example, “revenge spending,” consumers’ tendency to spend heavily after the pandemic to make up for lost time, will dissipate, or economies around the world could enter recessions.
Declines in foot traffic near stores have been particularly persistent in urban cores and office-dense neighborhoods
Retailers in urban cores confront even greater challenges. As of October 2022, foot traffic had recovered noticeably less near those stores than near suburban ones (Exhibit 18). In New York, for example, foot traffic near suburban stores was 16 percent lower than it had been in January 2020, but foot traffic near urban stores was 36 percent lower.
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Image description: A package of line charts compare foot traffic near stores during the pandemic years of 2020 to 2022 in urban and suburban areas around six cities. All traffic plunged initially and then gradually climbed back near 2020 levels, with suburban areas outperforming urban areas across each metro. End of image description.
And retail traffic has been still lower in cities’ office-dense neighborhoods. For example, the City of London, the borough in London with the highest ratio of office jobs to residents, experienced a nearly 50 percent decrease in foot traffic near stores from February 2020 to June 2022—by far the most severe and sustained decline of any borough in London. Foot traffic near stores was also hurt by declines in tourism, but more mildly; in London, boroughs that are popular with tourists, such as Kensington and Westminster, fared much better than the City of London.
Part of the reason for office-dense neighborhoods’ declines in foot traffic seems to be that many of the employees who might shop there spend more time working from home than they used to. In our survey, respondents in the United States who worked at the office no more than one day per week reported doing much less of their total retail spending near the office than those who worked in the office for two to five days a week reported (Exhibit 19).
However, the struggles of stores in urban cores may present opportunities for those in the suburbs. The same survey respondents—those who spent less at stores near the office—also spent more at stores near home.
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Image description: Stacked bar charts plot a breakdown of people's weekly retail spending, by how many days they reported working in the office. Those who worked in the office zero or one day per week did about 35% of their spending online (about 10 percentage points more than those who worked in the office more. The trend was the same for spending near home: another 35% of their spending, compared with about 10 points lower for those who worked in the office more. End of image description.