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January 12, 2022
Hybrid Working Arrangements: Who Decides?
Even after—or should we say "if"?—working from home eventually becomes less of a necessity, it's likely to stick around in a hybrid form, with some working days performed at home and some in the office. (This recent study , coauthored by three of this post's authors, also makes this case.) Still, much remains undetermined about how that hybrid arrangement will work and who at the firm decides how many and which days employers will require workers to be onsite.
To shed some light on how hybrid working arrangements are working, we posed a few special questions to executives in our Survey of Business Uncertainty (SBU) last July and again last month (December 2021). Specifically, we asked, "Does your firm currently have employees who work remotely?" If they said yes, we followed that up with the question, "Who decides which days and how many days employees work remotely?" Respondents selected options ranging from fully decentralized to company-determined schedules. (The results between the July and December surveys were nearly identical, so we've combined them here to simplify this discussion.) Among firms in our panel, 53 percent have employees who work remotely, and their survey responses are interesting (see chart 1).
As you can see, respondent firms are roughly split, with about 30 percent leaving the decisions up to their employees, 30 percent giving teams (or team leads) decision rights, and nearly 40 percent indicating the decision on how many and which days employees will be remote resides at the company (management) level.To dig into these results a bit further, we looked at who makes these decisions over working arrangements by industry and firm size. Given the differences across the industrial sector's ability to work from home (see research by Jonathan Dingel and Brent Neiman), we find it somewhat surprising that little difference exists across industries about whether the decision to work remotely is fully decentralized, made at the team level, or determined by the company (see chart 2).
However, we see a stark difference when comparing these decision rights by firm size. More than half of the smallest firms in our panel (those with fewer than 25 employees) allow the employees to decide how and when to come into the office, compared to just 10 percent of larger firms (with 250 employees or more). Instead, these larger firms have left decisions about remote work with the team. Although that's certainly far from a rigid, top-down approach, it can suggest a need for coordination among teams, and this variation highlights remote work's big trade-off: balancing employee choice with the coordination that work life sometimes requires.
Allowing employees to choose their teleworking days has the benefit of flexibility, letting them to plan their work schedules around some nonwork commitments. But it has the cost of limiting face-to-face meetings, as on any given day of the week larger teams will likely find one or more members working remotely, which forces meetings partly or completely online. In our discussions with larger firms, they highlight the importance of face-to-face interactions and so have been promoting team- or company-level coordination. Interestingly, smaller firms appear to be walking another path: providing greater individual choice. Which one of these approaches becomes prevalent should become clear by the summer, when employees can (hopefully) return to the office. Though the future of office work appears to be a hybrid one, the form of decision making that will dominate that future has yet to be determined.
November 10, 2021
Compositional Distortions to a Measure of Wage Growth during the Pandemic
Measures of year-over-year growth in wages (or hourly earnings) used in economic analysis often tell a fairly consistent story. For example, chart 1 makes it apparent that wage growth was generally higher heading into the 2007–09 recession than heading out of it and that wage growth stayed low for the first half of the 2010s before trending up moderately over the second half of the decade. However, with the onset of the COVID-19 pandemic, growth in average hourly earnings from the US Bureau of Labor Statistics' (BLS) establishment survey (the blue line in the chart) deviated substantially from the other two series depicted.
The leisure and hospitality industry provides a useful illustration of why the establishment survey measure of hourly earnings growth spiked in March and April of last year. In February 2020, average hourly earnings for production and nonsupervisory workers in leisure and hospitality were 40 percent lower than they were for all private nonfarm payroll workers. And although the leisure and hospitality industry accounted for just under 14 percent of private nonfarm production and nonsupervisory jobs in February 2020, it accounted for nearly 40 percent of the lost private production and nonsupervisory jobs in the subsequent two months. The 4.5 percentage point increase from February 2020 to April 2020 in the blue line in chart 1 falls by 1.9 percentage points if we remove leisure and hospitality from the calculation.
The August 2020 FRBSF Economic Letter—aptly titled "The Illusion of Wage Growth"—by Erin E. Crust, Mary C. Daly, and Bart Hobijn shows that restricting the sample to people employed in the second quarters of 2019 and 2020 reduced growth in median usual weekly earnings over that period by nearly 8 percentage points from the published rate of 10.4 percent. The Atlanta Fed's Wage Growth Tracker, which uses the same type of restriction, and the Employment Cost Index (ECI), which controls for employment share changes among industries and occupations , were not subject to the illusion of wage growth shown by the blue line in chart 1.
Unfortunately, the adjustments used in the Wage Growth Tracker and the ECI are not feasible with the establishment survey measure of hourly earnings because that measure is constructed solely from the information in each month's employment report. As an alternative, Goldman Sachs provides an adjustment for what it terms the composition bias in the establishment survey measure. This adjustment keeps hours worked fixed at their year-ago level in the wage calculation using industry-level data.
I've written an appendix that provides the details of a related approach for calculating a composition-adjustment term from the monthly establishment survey data. Besides adjusting for industry composition, this approach also adjusts for types of workers: production and nonsupervisory workers versus nonproduction/supervisory employees. The appendix also shows that adjusting for worker type and industry rather than industry alone materially affects the composition-adjusted measure of average hourly earnings for April 2020. It also shows that—unlike measures from the BLS and the San Francisco Fed, which control for educational attainment—the measure of labor composition (sometimes called labor quality ) constructed with only establishment survey data has not trended up much since the mid-2000s.
The basic intuition underlying the approach described in the appendix is that, apart from some trivial rounding error, the BLS measure of aggregate weekly payrolls is equal to the product of average hourly earnings and aggregate weekly hours worked. So, in much the same way that we can express nominal gross domestic product (GDP) as the product of real chain-weighted GDP and a GDP price deflator, aggregate weekly payrolls can also be decomposed as the product of composition-adjusted measures of wages and hours worked. This approach maintains the equality with aggregate payrolls since the composition adjustments to hourly earnings and hours worked offset each other exactly.
Chart 2 shows the results of adjusting for changes in both industry and worker type for measures of average hourly earnings growth and aggregate hours worked during the pandemic. Adjusting for composition makes average hourly earnings growth during the pandemic more like the ECI and Wage Growth Tracker measures, but, nevertheless, some important differences exist. Unlike the composition-adjusted measure of nominal wage growth, the ECI and Wage Growth Tracker measures languished in the second half of 2020 and surged in their most recent readings. Composition-adjusted hourly earnings grew 1.1 percent from March 2020 to April 2020, which is less than the 4.6 percent spike in the unadjusted measure but still strong enough to suggest that the adjustments made here still miss some meaningful changes in worker composition in the earliest months of the pandemic.
As you look at this chart, note that the adjustment is constructed using wage and hours data for 253 industry groups, all but 10 of which are further split into production and nonsupervisory and nonproduction/supervisory employee groups.
The right panel in chart 2 shows private nonfarm payroll employment alongside the standard measures of aggregate hours worked and a measure adjusted for industry and worker-type composition. In October, private nonfarm payroll employment, hours worked, and composition-adjusted hours worked were 2.5, 1.7, and 1.2 percentage points, respectively, below their February 2020 levels.
The composition-adjustment factor (industry by production/supervisory worker employment type) as well as the associated measures of composition-adjusted hours worked and hourly earnings are available here . Future updates of this Excel file will also be available at this link.
August 10, 2021
Do Rising Retirements during COVID Reflect Demographic Trends?
Data from the Current Population Survey tell us that, in the second quarter of 2019, 47.8 percent of those aged 55 and older said they didn't want a job because they were retired. By the second quarter of 2021, that share had risen more than 2 percentage points, to 49.9 percent, which is an increase of around 2 million retirees over what would have been expected if the retirement rate for those aged 55 and older had not changed.
These data raise the question of how much of the increase in retirements is over and above what would have been expected based on the ongoing aging of the baby boomer generation—the movement of more people into ages that are more likely to retire. In other words, did the COVID-19 pandemic contribute to an increase in retirements?
The Atlanta Fed's Labor Force Participation Dynamics tool, which we recently updated with data through the second quarter of 2021, allows us to investigate the source of the change in retirement. The increase in the overall retirement rate for those aged 55 and older can be broken into two parts. The first one is the part due to a shift in the distribution of age, sex, race/ethnicity, and educational attainment toward demographics with higher retirement rates. For example, a 65-year-old is more likely to retire than a 63-year-old, and we have more 65-year-old people today than two years ago. The second part is the increase due to higher retirement rates within the age, sex, race/ethnicity, and educational attainment groups.
To illustrate how the decomposition works, let's look at just two factors: age and sex. The following table shows the average retirement rates of men and women aged 55 and older by five-year age groups for the second quarters of 2019 and 2021. The numbers in parentheses show the share of the 55-and-older population in each age/gender group. For example, in the second quarter of 2019, 51.5 percent of women 55 and older were retired, and women made up 53.7 percent of the overall population of people 55 and older.
Looking down the columns of the table, notice that for both men and women, retirement rates are much higher for those in their 70s than in their 60s—and much higher for those in their 60s than in their 50s. This matters because, comparing 2021 with 2019, the share of the population in the older of the age groups for both men and women has increased. This fact alone puts upward pressure on the overall retirement rate for the 55-and-older population between 2019 and 2021.
But in addition to an aging 55-and-older population, the table above shows that retirement rates have also increased within the age/gender groups. Looking across the age rows of the table we see that the retirement rate for each age/gender group is higher in 2021 than in 2019. So not only are there more women and men of ages that have higher retirement rates, the retirement rates themselves have increased.
Chart 1 displays the results of the complete decomposition. The blue line is year-over-year change in the retirement rate of those 55 and older going back to the second quarter of 2006. The orange bars represent the part of the change in the overall retirement rate accounted for by changes in the demographic composition (the distribution of age, sex, race/ethnicity, and educational attainment), while the green bars depict the contribution to the overall change from changes in retirement rates within the demographic groups (labeled as behavior).
Notice that up until 2020, behavioral changes were generally contributing to lowering the overall retirement rate of the 55-and-older population. The loss of retirement savings during the Great Recession was arguably an important factor in reducing the ability to retire during that period. At the same time, demographics were also putting mild downward pressure on retirement, with the leading edge of the baby boomer generation still within an age range with relatively low retirement rates. However, since 2013 underlying demographic shifts have been putting upward pressure on the overall retirement rate.
During the COVID-19 pandemic, demographic and behavioral factors appear to have contributed roughly equally to the rise in retirements. Perhaps, for some baby boomers who were already likely to retire within a few years, the pandemic created an incentive to retire sooner than they might have otherwise. A look at the Federal Reserve's Distributional Financial Accounts Overview shows that the annual growth in the net worth of those 55 and older now puts them, on average, in a much better financial position to retire than was the case during the Great Recession (see chart 2).
The ongoing aging of the baby boomer generation will continue to put upward pressure on the retirement rate over the next few years. How much the recent behavioral change will persist is much less clear, and a great deal will undoubtedly depend on the future path of the pandemic and the financial resources of older Americans. The Atlanta Fed's Labor Force Participation Dynamics tool will allow you to investigate the changes for yourself—with data for the third quarter of 2021 available sometime in October—but I'll be back to discuss my own findings with you here.
April 7, 2021
CFOs Growing More Optimistic, See Only Modest Boost from Stimulus Plan
During the past few months, alongside an increase in COVID-19 vaccinations and amid a fresh round of fiscal support, optimism about the economic recovery from the COVID-19 pandemic has grown. Although reasons for concern over the potential unevenness of the recovery still exist, many economists, policymakers , and market participants have ratcheted up their growth expectations for 2021.
This growing optimism extends to decision makers who participate in The CFO Survey—a collaborative effort among the Atlanta Fed, Duke University's Fuqua School, and the Richmond Fed. CFOs and other financial decision makers in our survey grew more optimistic about the U.S. economy and their own firms' financial prospects, according to the first quarter's data released on April 7. Moreover, these firms see stronger prospects for sales revenue and employment growth in 2021 (similar to results from other business surveys, including the Atlanta Fed's Survey of Business Uncertainty).
Many people think the recently passed $1.9 trillion American Rescue Plan Act (ARPA) is behind these brighter expectations. However, the results of our CFO Survey suggest that many firms anticipate that the fiscal stimulus will have only a modest impact on their own future business activity.
In the first-quarter CFO Survey (fielded March 15–26, 2021), we posed a question asking respondents about the impact that ARPA might have their own firm's revenue growth, number of employees, representative price (the price of the product, product line, or service that accounts for the majority of their revenue), and total wage and salary costs (see chart 1). Firms had five response options, ranging from "decrease significantly" to "increase significantly." A majority of firms expect the recent fiscal measure to have "little to no impact" across all areas of their business activity. The results are perhaps most striking for employment, as nearly 80 percent of firms anticipate ARPA to bring little to no change in that area.
Considering the tepid impact of the stimulus on employment expectations, the survey results for total wage and salary costs are also interesting. Here, nearly 30 percent of the panel anticipates modest to moderate upward pressure on wage and salary costs, with another 5 percent or so expecting "significant" impact on their wage bill. The reasons for the expected effect on firms' total wage and salary costs are unclear, but we should note that labor quality and availability remain very high on CFOs' list of most pressing concerns.
Expectations around ARPA's impact on revenue growth appear a bit more diffuse. Though the survey's typical (or median) firm still anticipates that the bill will bring little to no change in sales revenue growth, nearly 40 percent of respondents expect the legislation to have a positive impact on sales, and a very small share of firms anticipate a negative impact on revenue.
Given the nature of these responses, we were curious whether CFOs who anticipated a positive impact from ARPA also held higher quantitative expectations for firm-level growth than firms who saw little-to-no impact. t. The CFO Survey elicits firms' quantitative expectations for sales revenue, employment, price, and wage growth early in the questionnaire, providing a useful way to check for consistency. Table 1 reports these results.
Apart from firms' anticipated growth in wage and salary costs, it does appear that firms that foresee a boost from the fiscal stimulus also hold higher growth expectations. The increase in expectations is particularly stark for employment growth and prices.
If we dig a little deeper into the small share of firms anticipating increased employment due to the stimulus—45 total—we find that 40 of them are in service-providing industries and employ fewer than 500 workers. We know from academic research, government statistics, and anecdotal reports that the COVID-19 pandemic has hit smaller, service-providing firms particularly hard, so it's perhaps not surprising to see these types of firms expecting the stimulus to aid in a rebound. These firms are also anticipating a stimulus-induced boost to the prices they can charge. The price growth for services has slowed markedly since the onset of the pandemic. As the economy begins to open up more fully, these firms might believe that measures to bolster household income (among other aspects of ARPA) will lead to a bit more pricing power.
Overall, however, our results suggest that the majority of firms anticipate ARPA to have little to no impact on their sales revenue, employment, prices, and wages. The smaller share of firms that do anticipate increased activity resulting from the stimulus largely expect the increase to be modest to moderate.
Importantly, these results do not rule out a surge in growth as the pandemic recedes and the vaccination rollout continues. As we've noted, most CFOs expect growth to occur regardless of ARPA's role in that growth. But the survey shows that firms, in general, do not pin any surge in demand on the legislation.
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