Policy Hub: Macroblog provides concise commentary and analysis on economic topics including monetary policy, macroeconomic developments, inflation, labor economics, and financial issues for a broad audience.
Comments are moderated and will not appear until the moderator has approved them.
Please submit appropriate comments. Inappropriate comments include content that is abusive, harassing, or threatening; obscene, vulgar, or profane; an attack of a personal nature; or overtly political.
In addition, no off-topic remarks or spam is permitted.
March 22, 2021
Inflation Expectations Reflect Concerns over Supply Disruptions, Crimped Capacity
As the COVID-19 pandemic stretches into its second year, we've seen evidence of changes in how it, and attendant policy measures designed to support the economy, are affecting firms. Early in the pandemic, firms generally appeared more concerned with flagging demand and falling revenue than issues of having sufficient supplies (notwithstanding obvious acute issues at grocery stores). Rather, at least through August 2020, firms saw the COVID-19 pandemic as disproportionately a concern of demand rather than supply —so much so, in fact, that firms scaled back on wages, expected to lower near-term selling prices, and lowered their one-year-ahead inflation expectations to a series low (going back to 2011). These findings, based on our Business Inflation Expectations (BIE) survey, are consistent with other academic research based on quarterly earnings calls of public firms and research out of the Harvard Business School.
However, as the pandemic continued to unfold and as relief and support continued to flow into the economy via ongoing monetary and fiscal policy efforts, many firms have begun to indicate a shift in concerns—from flagging demand toward concerns about fulfilling demand. Although the recovery remains decidedly uneven across industries, strong shifts in consumer activity (toward durable goods purchases) amid crimped production due to COVID-19 restrictions appear to have disrupted supply chains, to the extent that shipping containers sit mired in ports amid "floating traffic jams." Along with these difficulties, firms continue to indicate issues with employee availability, which hampers their operating capacity.
To investigate the breadth and intensity of these disruptions in supply chains and business operating capacity, we posed a few questions to our BIE panel during the first week of March. Specifically, we asked whether they'd recently experienced some form of supply chain disruption (anything from supplier delays to delays in shipping to their customers) as well as their experiences with crimped operating capacity (due to a variety of issues, ranging from employee availability to physical distancing issues). While we borrowed those two questions more or less directly from the U.S. Census Bureau's Small Business Pulse Survey, we also extended them by asking firms to gauge the intensity of these disruptions (on a scale ranging from "little to none" to "severe"). In addition, we posed these questions to medium-sized and larger firms in addition to those with fewer than 500 employees.
Chart 1 below shows the results. Regarding supply chain difficulties, we found that more than half of the firms in our panel felt some form of supplier delay, and the level of disruption is "moderate to severe" for 40 percent of them—a striking finding for a few reasons. First, our panel, like the nation, is disproportionately weighted toward service-providing firms (roughly 70 percent service firms to 30 percent goods producers). Second, just a few months ago (December 2020), firms ranked "supply chain concerns" as eighth out of their top 10 concerns for 2021. These results align with well-known diffusion indexes—the Institute for Supply Management Manufacturing and Business Services surveys—that have shown that a greater share of firms are experiencing slower deliveries and lower inventories in recent months.
In addition to issues receiving raw materials and intermediate goods from suppliers, a little more than one in three firms in the BIE panel also indicated that they themselves experienced delays in fulfillment, and the responses to the question on disruptions to operating capacity allow us some insight into the potential causes of these delays.
Here, a third of firms indicated that they were having difficulties with their employees' availability for work. Presumably, these issues stem from employees' concerns over contracting the virus, outbreaks causing production delays, or employees' inability to work due to familial issues such as childcare or the care of other dependents. One out of five respondents indicated that the intensity of disruption to operating capacity stemming from employee availability was moderate to severe. The same share of panel respondents—a fifth—indicated that a lack of adequate supplies and inputs on hand (likely due to supplier delays) caused a shortfall in production relative to capacity.
Comparing these responses to the Census Bureau's Small Business Pulse Survey, we find that the relative rankings of sources of disruption are quite similar—supplier delays far outweigh other supply chain disruptions, and the availability of employees for work are the most frequently cited sources of disrupted operations. Yet we find a greater incidence of disruption (even if we restrict our sample only to small firms). For example, 40 percent of firms surveyed by the Census Bureau indicated supplier delays, which slightly more than half of firms indicated to us. Such a discrepancy is unlike previous comparisons to other Census Bureau work (which match quite closely) and could be the result of a number of survey-specific factors. For instance, the types of respondents differ markedly—whereas the BIE elicits responses mainly from those in the C-suite and business owners, the census typically aims for someone in the accounting department. The number of response options also differs, and census respondents have seen these questions on disruption to supply chains and operating capacity numerous times over the pandemic.
Although disrupted supply chains and crimped operating capacity are significant enough to warrant attention on their own merits, another aspect of these issues deserves attention. Concurrent with widespread supply chain disruption and hobbled operating capacity, firms have ratcheted up both their perceptions of current inflation and their expectations for unit costs going forward (see chart 2).
When we survey firms' expectations around inflation, we prefer to gauge their views on the nominal aspects of the economy through the lens of their own-firm unit costs, as other Atlanta Fed research shows. After falling to the lowest levels on record during the depths of the pandemic, firms' perceptions of unit cost growth over the past year have risen sharply. Interestingly, these perceptions correlate tightly with movements in official aggregate price indexes, such as the gross domestic product price index (also called the GDP deflator) and the personal consumption expenditures price index.
Firms also appear to anticipate higher unit-cost growth in the year ahead. Since hitting a low in April 2020, firms' unit-cost (basically, inflation) expectations for the year ahead have surged to all all-time high just 11 months later. Not only does that kind of volatility speak to the dramatic and disparate impact COVID-19 has had on business activity, but it also suggests that the underlying drivers of these expectations have shifted markedly. (Incidentally, chart 2 shows that this measure of firms' inflation expectations moves in lockstep with professional forecasters' views.)
Indeed, in sharp contrast to their views early in the crisis, firms' one-year inflation expectations appear to have risen sharply alongside their views on supply chain and operating capacity disruption. Chart 3 shows a simple scatterplot between firms' one-year-ahead inflation expectations and a summary measure of the intensity of their disruption. To create this measure, we first assigned a score from 0 to 4 to each special question response based on whether they responded "None," "Little to none," "Mild," "Moderate," or "Severe." We then add their scores to obtain their disruption index. The mean disruption index value for firms in goods-producing industries is 9.3 and 6.6 for service-providing firms. And consistent with anecdotes and news stories, the disruption is highest in manufacturing industries (9.75) and trade and transportation industries (9.1).
Chart 3 visualizes the relationship between inflation expectations and the index of supply chain disruption. Although supply chain disruption isn't the only factor influencing year-ahead unit cost expectations, we can see that firms with the largest levels of disruption tend to be those that hold higher expectations for inflation in the year ahead.
For another perspective, chart 4 shows that the relationship between inflation expectations and disruption depends on whether the responding firm belongs in the goods-producing sector or the service-providing one. While both have strong positive relationships, it's interesting to note that the relationship is even stronger among firms in the goods-producing sector. While perhaps an unsurprising result, it is a reassuring one given that the most-cited reason for supply chain disruptions—supplier delays—is more likely to affect goods-producing firms.
Overall, when one contrasts the early portion of the pandemic with the more recent period, significantly more firms indicate that they are experiencing disruptions in their supply chain and operating capacity. More than 50 percent of our survey panelists indicated delayed deliveries from suppliers (and for most of those respondents, the disruption is moderate to severe). Combined with crimped operating capacity due largely to uncertain employee availability and lack of inputs, firms are beginning to view these disruptions as factors that are driving up their unit costs and leading to higher inflation expectations. We can connect the dots from firms' year-ahead inflation expectations to the intensity of these supply and production disruptions. Firms experiencing the most intense disruption tend to be those with the highest expectation of future inflation. This explanation tamps down the speculation that the potential inflationary impact of recent fiscal stimulus on demand is behind heightened year-ahead inflation expectations.
February 24, 2021
WFH Is Onstage and Here to Stay
Chances are you recognize the relatively new acronym WFH as "working from home." In less than a year, WFH has become a ubiquitous, inescapable facet of life for many people, so much so that newswires now ask which cities are best for WFH, and online job boards compile lists of companies that allow remote work on a full-time, permanent basis.
Many people are debating the pros and cons of WFH. For employees, gone are the long commutes and cramped cubicles, but other work-related stresses have emerged. As the pandemic drags on, some workers experience feelings of loneliness and isolation, health problems, and challenges related to work-life balance.
Back in May 2020, the Atlanta Fed's Survey of Business Uncertainty (SBU) elicited firms' views on WFH and found that, on average, firms anticipated that WFH would triple to 16.6 percent of paid workdays after the pandemic ends, up from 5.5 percent before it struck. Eight months later, we were curious to see whether and how plans had changed. So, in the January 2021 SBU, we asked two special questions very similar to ones we posed last May. Specifically, to gauge the extent of WFH, we asked, "Currently, how often do your full-time employees work from home?" To assess the future extent of WFH, we asked, "How often do you anticipate that your full-time employees will work from home after the coronavirus pandemic ends?" We asked firms to sort the fraction of their full-time workforce into six categories, ranging from five full days WFH per week to rarely or never.
It turns out that current plans are similar to those in May, with one important exception: firms increasingly favor a hybrid model for the postpandemic economy, walking back plans for the share of staff that will work exclusively from home. Chart 1 summarizes the responses to WFH questions posed in January's SBU and compares them to our May results. We also compare the results to statistics computed from the American Time Use Survey, conducted by the U.S. Bureau of Labor Statistics in 2017–18, which provides a useful benchmark. Aside from the striking similarity in pre-COVID levels of WFH across the surveys, several findings are worthy of note.
First, according to the January SBU, more than 35 percent of employees currently WFH at least one day per week. This estimate is plausible in light of work by Jonathan Dingel and Brent Neiman of the University of Chicago's Booth School of Business, which indicates that nearly 40 percent of U.S. jobs can be done at home . Moreover, the current WFH configuration tilts toward multiple days at home. All told, 25 percent of paid workdays are currently performed at home.
Second, firms report surprisingly similar figures in May 2020 and January 2021 for the share of employees whom they expect to work from home at least one day per week after the pandemic. Given the unprecedented nature of the pandemic recession, eight months is a long time over which to hold such stable expectations, suggesting that firms are serious about their intentions.
However, expectations have adjusted in one key respect: last May, firms anticipated that 10 percent of the postpandemic workforce would be fully remote, as compared to just 6 percent as of January. While still double the pre-COVID share, the revised expectation suggests many firms are coalescing around hybrid arrangements, whereby employees split the workweek between home and employer premises. These plans entail a large break from prepandemic working arrangements, but they imply more limited scope for employees to live anywhere—or for employers to hire from anywhere.
Chart 2 shows how the extent of actual and planned WFH varies by industry. Every major industry sector saw dramatic increases in WFH during the pandemic. With the exception of retail and wholesale trade, firms in every sector anticipate that a tenth or more of paid workdays by full-time employees will take place at home after the pandemic ends. For firms in business services, information, finance, and insurance, the postpandemic figure is 30.6 percent. And for the economy as a whole, it's 14.6 percent—nearly triple the prepandemic level.
Further digging into our survey results reveals the finding that COVID-19 shifted employment growth trends in favor of industries with a high capacity of employees to WFH and against those less able to accommodate remote work. Firms with a high WFH capacity experienced much higher stock returns in the past year than did firms with a low capacity. In addition, urban residences have become cheaper relative to suburban ones since the pandemic struck, suggesting that a shift to WFH has lowered the desirability of urban living. More WFH also means fewer people commuting into city centers and less worker spending on meals, coffee, personal services, shopping, and entertainment near employer premises. A recent study finds that a permanent shift to WFH will directly reduce postpandemic spending in major city centers by 5–10 percent relative to prepandemic circumstances. Of course, such changes also mean lower sales tax revenue for cities that had high rates of inward commuting before the pandemic.
To summarize, firms have largely stuck to their early expectations about the extent of WFH in the postpandemic economy. There has, however, been a notable drop in plans for employees to work from home five days a week. Remarkably, in every major industry sector except retail and wholesale trade, firms anticipate that WFH will account for one-tenth or more of full workdays by full-time employees, far above prepandemic levels. These shifts toward more remote work are driving a reallocation of jobs across industries and locations, contributing to fewer jobs, lower sales tax revenues, and lower property values in city centers. Our results suggest that these effects are likely to persist.
November 12, 2020
A Dashboard Approach to Monitoring Underlying Inflation
Editor's note: In December, macroblog will become part of the Atlanta Fed's Policy Hub publication.
Measuring progress toward the Federal Open Market Committee's (FOMC) dual mandates of maximum sustainable employment and price stability is often reduced to shorthand: Simply, monitoring the level of the unemployment rate relative to its longer-run trend, and tracking the level of a specific measure of underlying inflation—the so-called "core" measure of personal consumption expenditure (PCE) inflation (which excludes food and energy prices)—relative to the FOMC's 2 percent price stability goal. This ex food and energy "core" measure is often taken as a de facto proxy for the trend in overall (or "headline") inflation. While the unemployment rate and core PCE inflation are, indeed, useful in measuring the FOMC's progress toward its objectives, they are not perfect.
In an influential speech in 2013, Janet Yellen (then chair of the FOMC) argued for a broader, more inclusive approach to monitoring the health of the labor market. The unemployment rate, she pointed out, had significant shortcomings—namely, when unemployed workers became discouraged and stopped looking for work, the unemployment rate would decline. Hence, monitoring a basket or dashboard of indicators (such as payroll employment, data on gross job flows, and quits rates) could help paint a more accurate picture of the health of the labor market.
And, much like former Chair Yellen highlighted the need for a dashboard approach to monitoring the employment mandate, simply using core PCE inflation to track the underlying inflation trend is insufficient. An analogous dashboard approach is needed to monitor progress toward the FOMC's price stability mandate.
For some obvious reasons, movements in the aforementioned core PCE price measure do not always reflect changes in inflation. Explaining why gets a bit academic, but embedded in every price change are, at least, two components. The first is a real component, reflecting changes in the supply and demand for a particular good or service relative to others in the consumers' market basket. The second component is a nominal component, reflecting the supply of money (or the stance of monetary policy) relative to what's needed to facilitate purchases of goods and services in the economy during a given time period. It is that second component—the inflation component—that we are attempting to uncover. Efforts to do this rely on discerning measures of underlying inflation—measures that attempt to remove transitory effects and noise from the price data.
Implicit in using an underlying inflation measure that excludes only food and energy prices is the assumption that every other price change is a reflection of a change in underlying inflation. However, that assumption is off base. Large relative price changes outside of food and energy items, having nothing to do with the FOMC's price stability mandate, often occur. In the abstract, these can be any relative price change, such as a sharp increase in excise taxes, subsidies on prices in particular markets, or temporary supply chain disruptions resulting from natural disasters, pandemics, or a disruption in global trade.
Specifically, over the past six years or so, we've seen at least three of these large and salient relative price changes that have materially affected core PCE inflation. The first example is changes in administered health care prices that lead to a sharp slowing in the price index for hospital services (and thus health care prices in general) shortly after the passage of the Affordable Care Act (often referred to as Obamacare). The second is a methodological change that the U.S. Bureau of Labor Statistics enacted in January 2017, which made cell phone service prices more sensitive to quality changes. In March 2017, a few large national carriers switched to offering largely unlimited data packages, yielding a 50 percent (annualized) decline in this component and having a striking impact on year-over-year core PCE inflation through March 2018. The third is a series of huge price swings in imputed financial services prices in late 2018 and early 2019.
These are just a few of the most salient relative price changes that have altered a "core PCE-centric" view of inflation over the prior expansion, but there have been many more. Thankfully—and in large part due to great work throughout the Fed system to understand and measure inflation—we have a variety of alternative inflation measures designed to limit the influence of these large, idiosyncratic price changes. A few of the better-known ones are the Cleveland Fed's median and 16 percent trimmed-mean CPI and the Dallas Fed's trimmed-mean PCE measure. These measures remove the influence of sharp component price swings on a monthly basis and, as a result, tend to have a lower variance than the usual "core" measures, leading to superior forecasting performance over most time horizons and in a variety of inflation forecasting models.
Another set of inflation indicators reweights, or classifies, detailed components in the consumers' market basket into different groups based on characteristics that a monetary authority (such as the Federal Reserve) should be interested in. First, let's consider indicators such as the San Francisco Fed's Cyclical Core PCE Inflation index and Stock and Watson's Cyclically Sensitive Inflation Index. These measures either exclude or deemphasize the weight of prices that do not move in tandem with the business cycle. The argument goes that certain components of the consumer's market basket (such as health care and education prices) follow strong, idiosyncratic trends, and therefore price changes among these components are more likely to reflect relative price changes rather than the influence of monetary policy working through the pricing mechanism.
A third type of inflation indicator is the Atlanta Fed's Sticky Price CPI. This measure tracks a set of CPI components that are slow to react to changing economic conditions (and hence are "stickier" than other components) and appear to incorporate expectations about future inflation to a greater degree than prices that change on a frequent basis. This measure tends to forecast inflation over longer time horizons more accurately than headline or core inflation measures.
We have pulled together these various measures into the Underlying Inflation Dashboard, which allows users to see a more complete picture of underlying inflation. A quick overview of this dashboard is in order (see chart 1). The first section of the table shows the 12-month growth rate of each underlying inflation measure. It compares the most current data to the value of a measure from one year prior. Each measure is color-coded, in 25 basis point (bp) increments, relative to its price stability target. Admittedly, the choice for each measure's price stability target is somewhat arbitrary, but given the primacy of core PCE inflation in the communications of the FOMC and the Federal Reserve, we chose to express each measure's target as 2 percent plus its average difference with core PCE inflation over the past decade. For example, the growth rate in the core CPI over the past 10 years is 30 bp higher than that of the core PCE, yielding a price stability target of 2.3 percent.
What's interesting to see is the narrative that emerges by taking the dashboard approach to monitoring underlying inflation.
Prior to the onset of COVID-19 earlier this year, the consensus view surrounding inflation was one of persistent shortfall, even after (at least) achieving maximum employment by most measures. Indeed, at least through the beginning of 2020, core PCE inflation continued to trend below target (see chart 2).
However, every other measure of underlying inflation in the dashboard had converged to a growth rate consistent with the Fed's price stability mandate by early in 2018 and stayed there up until the onset of the pandemic (see charts 1, 3, and 4). Taking a dashboard approach leads us to the conclusion that, while it took some time following the Great Recession, inflation had converged to our price stability target and remained on target until March 2020.
The previous discussion made the case for using a dashboard approach when evaluating underlying inflation prior to the onset of the COVID-19 pandemic. Since then, a series of dramatic relative price swings, along with direct complications in the physical measurement of prices, have further complicated the measurement of underlying inflation.
One particularly salient example comes from used auto prices. Auto prices have surged, rising at a record annualized rate of 75 percent from July to September. This spike is likely the result of a combination of increased demand stemming from commuters attempting to avoid mass-transit options, less confidence over future incomes, and a temporarily reduced supply of new vehicles. This relative price change alone has pushed the 12-month growth rate in core PCE goods prices up by nearly a full percentage point and added nearly three tenths of a percent to the 12-month trend in core PCE inflation. In contrast, trimmed-mean estimators (such as the Cleveland Fed's 16 percent trimmed-mean CPI and the Dallas Fed's trimmed-mean PCE) have largely ignored (hence the "trimmed") the influence of this rather dramatic price swing over the prior three months—leading to much more stable month-to-month estimates of underlying inflation.
It is precisely these types of dramatic relative price swings that argue for the broader approach we've sought to provide with the Underlying Inflation Dashboard. We hope you'll give it a whirl and let us know what you think.
October 22, 2020
COVID, Election Uncertainty Weigh Heavily on Firms' Outlook
Editor's note: In December, macroblog will become part of the Atlanta Fed's Policy Hub publication.
The book A Mathematician Plays the Market, written by the mathematician and writer John Allen Paulos, includes this line, which is a fitting description of the current economic outlook: "Uncertainty is the only certainty there is, and knowing how to live with insecurity is the only security." At the moment, two sources of uncertainty in particular—COVID-19 and the 2020 election—appear to be weighing very heavily on firms' decision-making. And firms in our Survey of Business Uncertainty (SBU) also appear to know how to "live with insecurity," as they are slashing their capital expenditures budget over the next two years by 20 percent, on average.
During the past two months, we've asked firms in our SBU to rank the top three sources of uncertainty influencing their business decisions at the moment. The results, seen in chart 1, show that firms are most concerned about uncertainty surrounding the coronavirus and the upcoming 2020 election. Together, these were firms' top sources of uncertainty and account for close to half of all responses, regardless of whether they are ranked as the first, second, or third source of uncertainty.
While it likely comes as no surprise that COVID-19 and the pending election are front and center as sources of uncertainty affecting business decisions at the moment, what is interesting is how firms are choosing to deal with these uncertainties. In October, we asked a follow-up question: "By what percentage has the net budgeted dollar amount of your capital expenditures for calendar years 2021 and 2022 changed due to the uncertainties you identified [in the previous question]?" The responses, shown in chart 2, suggest that uncertainty is weighing quite heavily on firms' collective outlook for capital investment.
Of the 407 responses we've collected so far, more than half of firms responded that the uncertainties they identified caused them to decrease their net budgeted amount of capital expenditures over the next two years. Furthermore, just 5 percent (20 firms) have increased their capex budget as a result of uncertainties they identified (with the remaining 44 percent leaving their current budgets intact). On average, firms are slashing their capital spending budgets over the next two years by nearly 20 percent. Across major industry sectors, the impact of uncertainty on capital budgets is uniformly negative. However, it appears more severe for capital-intensive industries such as manufacturing, construction, and mining and utilities.
To put these results in context, we previously posed a battery of special questions to this panel in 2018 and 2019 concerning the impact of tariff hikes and trade policy uncertainty on capital expenditures and found only modest (low single-digit) impacts for the overall panel and across most broad industries.
Turning to comprehensive gross domestic product (GDP) data for the U.S. economy, business fixed investment posted its second steepest decline on record (decreasing at an annualized pace of 27.2 percent) in the second quarter of 2020. Our current results imply a sluggish trajectory for business fixed investment for continuing firms (those that are not just starting up), which may contribute to a tepid recovery for overall GDP growth. One caveat worth mentioning is that recent business formation statistics from the U.S. Census Bureau suggest an increase in high-quality business startups, potentially offsetting some anticipated weakness in business fixed investment.
In sum, it's fairly certain (to us at least) that uncertainty—particularly surrounding the COVID-19 pandemic and the outcome of the 2020 election—is weighing heavily on firms at the moment. Consequently, many firms have chosen to slash their capex budgets over the next two years.
As current uncertainties become eventualities, it will be interesting to see if, and to what extent, firms reassess their plans. We'll continue to put the SBU to good use for just that purpose, so watch this space.
- Business Cycles
- Business Inflation Expectations
- Capital and Investment
- Capital Markets
- Data Releases
- Economic conditions
- Economic Growth and Development
- Exchange Rates and the Dollar
- Fed Funds Futures
- Federal Debt and Deficits
- Federal Reserve and Monetary Policy
- Financial System
- Fiscal Policy
- Health Care
- Inflation Expectations
- Interest Rates
- Labor Markets
- Latin AmericaSouth America
- Monetary Policy
- Money Markets
- Real Estate
- Saving Capital and Investment
- Small Business
- Social Security
- This That and the Other
- Trade Deficit
- Wage Growth