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October 7, 2020
Two Quite Different Paths for U.S. Unemployment
Editor's note: In December, macroblog will become part of the Atlanta Fed's Policy Hub publication.
Here are two charts that I think are very telling for the recovery of the U.S. labor market. Chart 1 shows the unemployment rate for people who reported being temporarily laid off from their job and anticipate being recalled. Chart 2 shows the unemployment rate for those who reported being laid off permanently, with no prospect of being recalled. They are on very different trajectories.
I've computed these rates as a share of the civilian labor force. Other reasons for unemployment include reentrants or new entrants to the labor force as well as those completing temporary jobs and are not shown.
The good news is that after increasing to a never-before-seen level in April, the temporary unemployment rate has improved markedly as many businesses have reopened and recalled their temporarily laid-off staff. The bad news is that as the pandemic has unfolded, an increasing number of unemployed workers are reporting being laid off permanently—and they account for a rising share of the labor force. Those on permanent layoff have a lower rate of reemployment in general than those on temporary layoff, and the flow into employment is currently similar to the low level seen in the wake of the Great Recession. Also troubling is the fact that the reemployment rate of those on temporary layoff is also lower than normal—meaning that for some, temporary is starting to look more permanent.
While the level of permanent layoffs is not close to that seen during the Great Recession, the increase indicates that a near-term return to prepandemic labor market conditions is unlikely. In fact, as last week's macroblog post pointed out, survey evidence suggests that many firms don't anticipate getting back to prepandemic employment levels for several years.
May 27, 2020
COVID-19 Mortgage Relief—The Role of Income Support
The COVID-19 pandemic has led to a large number of furloughs, layoffs, reductions in hours worked, and wage cuts. Anticipating that many homeowners would consequently have problems paying their monthly mortgage bill, the U.S. Department of Housing and Urban Development ordered all mortgage servicers of federally backed debt to provide forbearance to any homeowners affected by the crisis. In addition, bank regulators encouraged lenders to forbear and restructure mortgages for borrowers affected by the shutdown, actions that staved off an immediate wave of foreclosures. At the end of the forbearance window, borrowers will likely be offered a series of repayment schemes: starting with a period of catch-up payments, then moving to extended terms on their mortgage or possibly even rate reductions. However, if the borrower has not returned to work, paying for what is effectively a new mortgage obviously poses a challenge. Options such as creating a modified repayment plan, lowering the mortgage interest rate, or extending the term of the loan might not be enough for a borrower who has experienced a substantial income loss.
In 2009, researchers at the Boston Fed proposed an alternative policy of supplemental mortgage payment assistance targeted to underwater borrowers experiencing a significant reduction in disposable income due to factors such as employment loss or medical costs associated with illness. That 2009 research built on earlier Boston Fed research demonstrating that—during a previous housing market downturn—most underwater households continued to pay their mortgages unless they were hit with a further reduction in earnings or increase in expenses. The idea that mortgage default is caused by both a negative house price shock and a negative income/employment shock is known as the "double trigger" theory of default. However, the empirical evidence on the double trigger theory was limited. Underwater homeowners in areas with increased unemployment appeared to default more, but this was mostly an interesting correlation, not necessarily a causal relationship.
Since the Great Recession, considerable research (here, for example) has tried to identify the central role income shocks play in default. The econometric challenge is that shocks to income from changes in employment or wages tend to be capitalized into house prices. So a community experiencing the second trigger from widespread job loss, say, will likely also experience a drop in house prices, making it difficult to isolate the real cause of default. In a forthcoming paper we consider the unique sources of changes in employment and income arising from the hydraulic fracking boom in Pennsylvania in the late 2000s to isolate the second trigger from the first.
Fracking involves injecting large amounts of water, sand, and potentially toxic chemicals underground at great pressure to break shale formations and release the trapped natural gas. The fracking process also involves piercing aquifers, storing and treating large quantities of contaminated water, and employing heavy equipment. Some evidence shows that these real or perceived negative features lower the value of homes near fracking wells. At the same time, the shale boom increased demand for middle- and low-skilled workers and generated significant royalty payments to many property owners.
Observing the performance of mortgages that originated before fracking began allows us to treat the resulting shale boom as an experiment where household incomes were sustained (or increased) even as housing prices were flat or declining. Using geological information to predict the location of fracking activity, we find that fracking wells significantly raised total household income, from both wages and royalties, and the wells appear to have increased employment in fracking-related industries. At the same time, fracking does not appear to have raised house prices or made it less likely that a household has negative equity. However, fracking does significantly reduce the probability that a mortgage becomes seriously delinquent (that is, when a borrower misses more than a few payments).
In addition, when we use only geology to predict the location of fracking wells, we get a much larger decline in mortgage delinquency, suggesting that more vulnerable communities were quicker to embrace fracking. Finally, the ameliorative effects of fracking were concentrated among borrowers who are likely to be underwater on their mortgages (the first trigger), consistent with the double trigger hypothesis, since the theory predicts that borrowers with positive equity are unlikely to default in the first place.
Our results suggest that an effective strategy for preventing a foreclosure crisis in the current situation is direct support of household income. Indeed, the Coronavirus Aid, Relief, and Economic Security Act (commonly known as the CARES Act) contains several income transfers to help sustain household budgets, including expanded unemployment insurance, direct cash payments to most households, and loans to small firms that are forgivable on the condition that they sustain employment through the shutdown. It is our view that these programs are not simply helping to sustain families during the crisis, but they're also limiting disruption to the housing market. Depending on how the crisis evolves in the coming months, further income support for affected households may forestall the need for less efficacious interventions to aid distressed borrowers.
April 17, 2020
Businesses Are in Uncharted Waters
Inflation expectations in our April Business Inflation Expectations (BIE) survey fell to an all-time low (going back to October 2011) of 1.4 percent, plunging far below its next lowest level of 1.7 percent (most recently observed in February 2020). Perhaps unsurprisingly, firms have bigger worries on their minds. And our boss, President Raphael Bostic, agreed, noting on Wednesday that "inflation at this point is not something I'm particularly worried about."
The drop in inflation expectations was not the only historical low that our survey results uncovered. Firms' assessments of current sales levels relative to what they consider "normal" levels fell precipitously. Recovering from the 2007–09 financial crisis and recession, this quantitative sales gap measure had slowly been moving toward zero (or "normal" sales levels) alongside solid gains in gross domestic product growth and previously strong job gains. However, that all changed in April. Our survey, which was in the field from April 6 to 10, showed an extraordinarily large decline in sales levels relative to normal—from 2.5 percent below normal in the first quarter to 32 percent below normal in April (see the charts). The decline in sales had an impact on firms of all sizes, but smaller firms reported a much larger hit to sales than did firms with more than 100 employees.
Our survey's special questions this month focused on the level of disruption the coronavirus outbreak was causing for southeastern firms. We asked participating firms to assess disruption to their business operations and sales activity, on a scale of "no disruption" to "severe disruption," and it's obvious that a majority of firms in our panel have experienced severe disruption to their sales activity (see chart 2). The table indicates how disrupted firms' operations and sales were. Among those firms experiencing severe disruption, current sales levels have been roughly halved relative to normal conditions. The results suggest that the disruption associated with the outbreak has not hit all firms equally. There is also some evidence of dispersion (reallocation) across firms, as a small share of firms that indicated they are experiencing low levels of disruption are seeing stronger-than-usual sales levels.
As firms continue to grapple with the unprecedented impact and uncertainty that the coronavirus outbreak has inflicted, we wanted to get a rough sense of how long they expect these unusual conditions to persist and how long they can weather the economic shutdown without seeking new sources of funding. The left-hand graph in chart 3 shows the cumulative distribution function (CDF) for how many months before business operations return to normal. The CDF on the right-hand side plots how long firms can continue to operate in the current environment without seeking additional funding to backstop operations.
The typical (median) response was an expectation that it will be about four more months for business operations to return to normal (though the tail is long, and about 10 percent thought a year or longer is in order). Perhaps the silver lining here is that the typical response was an expectation to be able to operate for another six months before needing to tap additional sources of funding. Assuming that much of the economic activity that has been shuttered begins to resume by the beginning of the fourth quarter and conditions do not deteriorate further, the "typical" firm in our panel should be able to continue to operate.
However, digging into the individual responses reveals some nuance in this relationship. The cross-sectional relationship between a business decision-maker's assessments of the length of time he or she can continue to operate without securing additional funding and the length of time before resuming normal activity carries a correlation coefficient of just 0.2. (This finding essentially means that survey respondents often had different notions of when they would be able to resume normal business operations and need to tap additional funding.) The typical firm expects to be able to resume normal operations about a week or so before they need to tap additional funding. And, perhaps more importantly, nearly 40 percent of firms in our sample expect they'll need to secure additional funding before their operations return to normal.
Finally, although inflation isn't the first thing on everyone's mind at the moment, we did ask firms about their price expectations (see chart 4). While roughly 60 percent expect to hold steady on prices over the next six months, roughly a quarter of the panel expect to lower prices, and just 15 percent expect to increase them. On average, firms expect to lower prices by 2.2 percent, and there appears to be a relationship between COVID-related disruption to sales activity and expected price declines.
Across many dimensions, the disruption caused by the current pandemic is without precedent. Many firms headquartered in the Southeast have indicated severely disrupted business operations and sales activity, disruptions that appear to have caused incredibly sharp declines in sales levels. The typical firm in the panel expects this disruption to persist at least through the summer months (which may foreshadow the likely shape of the recovery). And—though not a primary concern at the moment—inflation expectations are the lowest we've recorded in more than 100 consecutive months of conducting this survey. In many ways, we appear to be in uncharted waters.
April 13, 2020
Unpaid Absence from Work Because of COVID-19
As has been widely reported, the March employment report shed light on the early impact of the COVID-19 pandemic on the U.S. labor market. One telling number is the official unemployment rate, which tallies the share of the labor force made up of people out of work (but who are looking for a job) plus those who have been laid off and expect to be recalled. The official unemployment rate increased from 3.5 percent in February to 4.4 percent in March. My own preferred measure is the share of the working-age population who are unemployed, working part-time because of economic conditions, or outside the labor force but still want to work. This underutilization rate is featured in the Atlanta Fed's Labor Report First Look analysis of the U.S. Bureau of Labor Statistics (BLS) labor report. The First Look shows that this measure increased from 5.8 percent in February to 7.1 percent in March.
According to the BLS, people who did not work "because of the coronavirus" were supposed to also be classified as unemployed (on temporary layoff). However, relative to February, it appears that around 1 million more people were classified as employed but absent from work and not getting paid for "other reasons" (reasons other than illness, childcare problems, bad weather, being in school, etc.). If those people were instead counted as unemployed, then the unemployment rate in March would have been closer to 5.0 percent, and the underutilization rate would have been 7.5 percent. The data in the table below break down the various components of these measures, if you want to perform your own calculations.
Part-time for economic reasons
Unpaid absence from work for other reasons
Want a job
Don't want a job
Note: Data represent thousands of people and are seasonally adjusted except for unpaid absence. People in the "Want a job" category include those who currently want a job but are not counted as unemployed. The "Don't want a job" category includes people not in the labor force who say they don't currently want a job (see here for more details). "Unpaid absence" includes those who have a job but are on an unpaid absence from work for an unspecified reason.
Source: BLS, Federal Reserve Bank of Kansas City's Center for the Advancement of Data and Research in Economics, and author's calculations
A few observations about the absence-from-work data for March. First, a marked increase in absence from work across occupations took place, in both paid and unpaid absences. However, being paid while absent from work for "other reasons" was disproportionately prevalent among professional occupations, likely reflecting those workers' relatively greater ability to continue to work remotely. Second, unpaid absence from work was disproportionately common among food-preparation and building-maintenance occupations, as well as jobs providing personal services—the types of occupations most directly affected by social distancing mandates.
The April BLS labor report (due on May 8) will provide a clearer picture of the depth and breadth of the impact of COVID-19 on the labor market, and it will be important to include unpaid absences from work in the analysis. In the meantime, I'm keeping a close eye on the weekly unemployment insurance claims data as well as other high-frequency surveys (such as this one from Gallup).
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