The Atlanta Fed's macroblog provides commentary on economic topics including monetary policy, macroeconomic developments, financial issues and Southeast regional trends.
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April 04, 2016
Which Wage Growth Measure Best Indicates Slack in the Labor Market?
The unemployment rate is close to what most economists think is the level consistent with full employment over the longer run. According to the Federal Open Market Committee's latest Summary of Economic Projections, the unemployment rate is currently only 15 basis points above the natural rate. Yet, average hourly earnings (AHE) for production and nonsupervisory workers in the private sector increased a paltry 2.3 percent in March from a year earlier (as did the AHE of all private workers), and is barely above its average course of 2.1 percent since 2009.In contrast, the Atlanta Fed's Wage Growth Tracker (WGT) suggests that wage growth has been increasing. The February WGT reading was 3.2 percent (the March data will be available later in April), considerably higher than its post-2009 average of 2.3 percent.
Why is there such a large difference between these measures of wage growth? Besides differences in data sources, the primary reason is that they measure fundamentally different things. The WGT is an estimate of the wage growth of continuously employed workers—the same worker's wage is measured in the current month and a year earlier.
In contrast, the AHE measure is an estimate of the change in the typical wage of everyone employed this month relative to everyone employed a year earlier. Most of these workers are continuously employed, but some of those employed in the current month were not employed the prior year, and vice versa. These changes in the composition of employment can have a significant effect.
A recent study by Mary C. Daly, Bart Hobijn, and Benjamin Pyle at the San Francisco Fed shows that while growth in wages tends to be pushed higher by the wage gains of continuously employed workers, the net effect of entry and exit into employment tends to put a drag on the growth in wages. Moreover, the magnitude of the entry/exit drag can be relatively large, varies over time, and differs by the type of entry and exit.
For example, older workers who have retired and left the workforce tend to come from the higher end of the wage distribution, and their absence from the current period wage pool exerts downward pressure on the typical wage. The greater number of baby boomers starting to retire is having an even larger depressing effect on growth in wages than in the past. Because the WGT looks only at continuously employed workers, it is not influenced by these net entry/exit effects.
To the extent that firms adjust the pay for incumbent workers in response to labor market pressures to attract and retain workers, the WGT should reasonably capture changes in the tightness of the labor market.
Economists at the Conference Board modeled the relationship between different wage growth series and measures of labor market slack. One of the slack measures they use is the unemployment gap—the difference between an estimate of the natural rate of unemployment and the actual unemployment rate.To illustrate their findings, the following chart shows the WGT and AHE measures along with the unemployment gap lagged six months (using the Congressional Budget Office estimate of the natural rate).
The WGT appears to move more closely with the lagged unemployment gap than does the growth in AHE, and a comparison of the correlation coefficients confirms the stronger relationship with the WGT. The correlation between the lagged unemployment gap and the change in average hourly earnings is 0.75.
In contrast, the correlation with the wage growth tracker is higher at 0.93. Moreover, the unemployment gap-AHE relationship appears to be particularly weak since the Great Recession. The correlation since 2009 falls to just 0.08 for the AHE, whereas the WGT correlation is still 0.93.
Our colleagues at the San Francisco Fed concluded their analysis of the effect of flows into and out of the employment on wage growth by suggesting that:
"... wage growth measures that focus on the continuously full-time employed are likely to do a better job of gauging labor market strength, since they are constructed to more clearly capture the wage dynamics associated with improving labor market conditions. The Federal Reserve Bank of Atlanta's Wage Growth Tracker is an example."
That assessment is consistent with the Conference Board study, and suggests that labor markets may be tighter than is commonly believed based on sluggish growth in measures of average wages such as AHE.
February 17, 2016
Are Paychecks Picking Up the Pace?
From the minutes of the January 26–27 meeting of the Federal Open Market Committee, it's clear that many participants saw tightening labor market conditions during 2015:
In their comments on labor market conditions, participants cited strong employment gains, low levels of unemployment in their Districts, reports of shortages of workers in various industries, or firming in wage increases.
Based on the Atlanta Fed's Wage Growth Tracker (WGT), the median annual growth in hourly wage and salary earnings of continuously employed workers in 2015 was 3.1 percent—up from 2.5 percent in 2014 and 2.2 percent in 2013. That is, the typical wage growth of workers employed for at least 12 months appears to be trending higher.
However, wage growth by job type varies considerably. For example, the WGT for part-time workers has been unusually low since 2010. The following chart displays the WGT for workers currently employed in part-time and full-time jobs. For those in part-time jobs, the WGT was 1.9 percent in 2015, versus 3.3 percent for those in full-time jobs. The part-time/full-time wage growth gap has closed somewhat in the last couple of years but is still large relative to its size before the Great Recession. Note that full-time WGT is similar to the overall WGT because most workers captured in the WGT data work full-time (81 percent in 2015).
In addition to hours worked, median wage growth also tends to vary across occupation. The following chart plots the WGT for workers in low-skill jobs, versus those in mid- and high-skill jobs. (We define low-skill jobs as those in occupations related to food preparation and serving; building and grounds cleaning; and maintenance, protection, and personal care services.)
Notably, after lagging during most of the recovery, median wage growth in low-skill occupations increased 2.8 percent in 2015, versus 2.0 percent in 2014 and compared to 3.2 and 2.7 percent for other occupations in 2015 and 2014, respectively.
The improvement in wage growth for low-skill occupations seems mostly attributable to full-time workers; wage growth for people in low-skill jobs working part-time was about half that (1.6 percent versus 3.0 percent) of those working full-time (see the chart).
This pickup in low-skill wage growth fits with some anecdotal reports we've been hearing. Some of our contacts in the Southeast have reported increasing wage pressure for workers in lower-skill occupations within their businesses. One can also see evidence of growing tightness in the market for low-skill jobs in the help-wanted data. As the following chart shows, the ratio of unemployed to online job postings for low-skill jobs is always higher than for middle- and high-skill occupations. But the ratio for low-skill jobs is now well below its prerecession level, and the tightness has increased during the last two years.
The take-away? Wage growth for continuously employed workers appears to have picked up some steam in 2015, and the recent trend in wage growth is positive across a variety of job characteristics. Wage growth for people in lower-skill jobs has increased during the last couple of years, consistent with evidence of increasing tightness in the market for those types of jobs. The largest discrepancy in wage growth appears to be among part-time workers, whose median gain in hourly wages in 2015 still fell well short of those in full-time jobs.
February 05, 2016
Introducing the Refined Labor Market Spider Chart
In January 2013, Atlanta Fed research director Dave Altig introduced the Atlanta Fed's labor market spider chart in a macroblog post.
In a follow-up post that June, Atlanta Fed colleague Melinda Pitts and I introduced a dedicated page for the spider chart located at the Center for Human Capital Studies (CHCS) webpage. It shows the distribution of 13 labor market indicators relative to their readings just before the 2007–09 recession (December 2007) and the trough of the labor market following that recession (December 2009). The substantial improvement in the labor market during the past three years is quite evident in the spider chart below.
As of December 2012, none of the indicators had yet reached their prerecession levels, and some had a long way to go. Now, many of these indicators are near their prerecession values—and some have blown by them.
To make the spider chart more relevant in an environment with considerably less labor market slack than three years ago, we are introducing a modified version, which you can see here. Below is an example of a chart I created using the menu-bars on the spider chart's web page:
In this chart, I plot the May 2004 and November 2015 percentile ranks of labor market indicators relative to their distributions since March 1994. As with the previous spider chart, indicators such as the unemployment rate, where larger values indicate more labor market slack, have been multiplied by –1. The innermost and outermost rings represent the minimum and maximum values of the variables from March 1994 to January 2016. The three dashed gray rings in between are the 25th, 50th, and 75th percentiles of the distributions. For example, the November 2015 value of 12-month average hourly earnings growth (2.26 percent) is the 23rd percentile of its distribution. This means that 23 percent of the other monthly observations on hourly earnings growth since March 1994 are lower than it is.
I chose May 2004 and November 2015 because they had the last employment situation reports before "liftoffs" of the federal funds rate. November 2015 appears to be stronger than May 2004 for some indicators (job openings, unemployment rate, and initial claims) and weaker for others (hires rate, work part-time for economic reasons, and the 12-month growth rate of the Employment Cost Index).
The average percentile ranks of the variables for these two months are similar, as the chart below depicts:
Also shown in the chart is the Kansas City Fed's Level of Activity Labor Market Conditions Indicator. It is a sum of 24 not equally weighted labor market indicators, standardized over the period from 1992 to the present. In spite of its methodological and source-data differences with the average percentile rank measure plotted above, it tracks quite closely, especially since 2004. However, as shown in the spider chart that I referred to above, there is quite a bit of variation within the indicators that may provide additional information to our analysis of the average trends.
We made a number of other changes to the spider chart to ensure it reflects current labor market issues. These changes are documented in the FAQs and "Indicators" sections of the new spider chart page. Of particular note, users can choose not only the years for which they wish to track information, but also the period of reference that provides the basis of the spider chart. The payroll employment variable is now the three-month average change rather than a level. Temporary help services employment has been dropped, and two measures of 12-month compensation growth and the employment-population ratio (EPOP) for "prime-age workers" (25 to 54 years) have been added.
Some care should be taken when comparing recent labor market data values with those 10 or more years ago as structural changes in the labor market might imply that a "normal" value today is different than a "normal" value in, say, 2004. The variable choices for the refined spider chart were made to mitigate this problem to some extent. For example, we use the prime-age EPOP as a crude adjustment for population aging, putting downward pressure on the labor force participation rate and EPOP over the past 10 years (roughly 2 percentage points). This doesn't entirely resolve the comparability issue since, within the prime-age population, the self-reporting rate of illness or disability as a reason for not wanting a job has increased about 1.5 percentage points since 1998 (see the macroblog posts here and here and the CHCS Labor Force Participation Dynamics webpage). If this increase in disability reporting is partly structural—and a Brookings study by Fed economist Stephanie Aaronson and others concludes it is—some of the decline in the prime-age EPOP since the late 1990s may not be a result of a weaker labor market per se.
Other variables in the spider chart may have had structural changes as well. For example, a study by San Francisco Fed economists Rob Valleta and Catherine van der List concludes that structural factors explain just under half of the rise in the share of workers employed part-time for economic reasons over the 2006 to 2013 period.
To partially account for structural changes in trends, we allow the user to select one of 11 time periods over which the distributions are calculated. The default period is March 1994 to present, which is what was used in the example above, but users can choose a window as short as five years where, presumably, structural changes are less important. A trade-off with using a short window is that a "normal" value may not produce a result close to the median. For example, the median unemployment rate is 5.6 percent since March 1994 and 7.3 percent since February 2011. The latter value is much farther away from the most recent estimates of the natural rate of unemployment from the Congressional Budget Office and the Survey of Professional Forecasters (both 5.0 percent).
In our June 2013 macroblog post introducing the spider chart, we wrote that we would reevaluate our tools and determine a more appropriate way to monitor the labor market when "the labor market has turned a corner into expansion." The new spider chart is our response to the stronger labor market. We hope users find the tool useful.
June 29, 2015
New Atlanta Fed Series Shows Wage Growth Held Steady in May
According to the Atlanta Fed's Wage Growth Tracker, a new series constructed using data from the Current Population Survey, the median increase in wages for individuals working in May 2014 and May 2015 was 3.3 percent (reported as a three-month average).
Wage growth by this measure was essentially unchanged from April and 1 percentage point higher than the year-ago reading. The current pace of nominal hourly wage growth is similar to that seen during the labor market recovery of 2003–04 and about a percentage point below the pace experienced during 2006–07, which was the peak of the last business cycle. You can download the data going back to March 1997 from our website by clicking "export," shown in the upper right of the chart below.
Wage growth differs by job and worker characteristics. For prime-age individuals and full-time employees, for example, the Wage Growth Tracker recorded slightly higher readings than the group overall. The median wage growth of these individuals was 3.5 percent compared to 3.3 percent for all individuals. To see more cuts of the data, check out our website.
June 23, 2015
Approaching the Promised Land? Yes and No
Last Friday, we released our June installment of the Business Inflation Expectations (BIE) survey. Among the questions we put to our panel of businesses was a quarterly question on slack, asking firms to consider how their current sales levels compare to what they would consider normal.
The good news is, on average, the gap between firms' current unit sales levels and what they would consider normal sales levels continues to close (see the chart).
By our measure, firm sales, in the aggregate, are 1.9 percentage points below normal, a bit better than when we polled them in March (when they were 2.1 percent below normal) and much improved from this time last year (3.7 percent below normal). For comparison, the Congressional Budget Office's (CBO) estimate of slack on a real gross domestic product (GDP) basis was 2.6 percent in the first quarter (though this estimate will almost certainly be revised to something closer to 2.4 percent when the revised GDP estimates are reported later today). And if GDP growth this quarter comes in around 2.5 percent as economists generally expect, the CBO's GDP-based slack estimate will be 2.2 percent this quarter, just a shade larger than what our June survey data are saying.
Now, as we have emphasized frequently (for example, in macroblog posts in May 2015, February 2015, and June 2013), performance in the aggregate and performance within select firm groups can differ widely. For example, while small firms continue to have greater slack than larger firms, their pace of improvement has been much more rapid (see the table).
Likewise, some industries (such as transportation and finance) see current sales as better than normal. But others, like manufacturers, are currently reporting considerable slack—and findings from this group appear to show a marginal worsening in sales levels over the past 12 months.
Another item that caught our attention this month was the differing pace of narrowing in the sales gap among those firms with significant export exposure (greater than 20 percent of sales) relative to those with no direct export exposure. We connected these dots using responses to this month's special question, in which responding firms specified their share of customers by geographic area: local, regional (the Southeast, in our case), national, and international (see the table).
So things are still getting better for the economy overall, and the small firms in our panel have displayed particularly rapid improvement during the last year. But if you've got exposure to the "soft" export markets, as mentioned in the June 17 FOMC statement, you've likely experienced a slower pace of improvement.
May 18, 2015
Sales Flexing Muscle at More Firms
The news in this month's Business Inflation Expectations (BIE) report is that, in the aggregate, firms' unit sales levels continue to strengthen: Specifically, the survey question measures firms' perceptions of current unit sales levels relative to "normal times."
This month, 70 percent of firms indicated their sales levels are at or above what they consider normal. Last November, that share was 61 percent, and one year ago, it was only 54 percent. We typically report the aggregate results in a diffusion index (see the chart), which also shows the overall progression toward "normal times" (a value of 0).
But, typical of aggregate statistics, these results obscure the diversity of experience among sectors. Digging deeper, we found that most (but not all) of the sectors represented in our panel have shown further improvement in their sales performance relative to last November (see the chart).
Retailers and those in the real estate and rental leasing/construction sectors reported the most significant improvement since November, with retailers approaching what they consider normal sales levels. This news is likely to be most welcome to Dennis Lockhart, our boss here in Atlanta, who has put the performance of the consumer on his "must watch" list. Two industries—finance and insurance, and transportation and warehousing—reported above-normal sales levels in our recent survey.
Only the manufacturers in our panel indicated that their sales performance has deteriorated since November, and they are now reporting sales well below normal. Of course, this news shouldn't be terribly surprising given the recent softness in the manufacturing indexes from both the Institute for Supply Management and industrial production data. This information was also on the boss's watch list, as he made clear in his speech:
Well, judging from our May BIE report, manufacturers aren't seeing improvement quite yet.
The stronger dollar was likely reflected in a drag on net exports...[and] looking ahead, I expect net exports to be a modest drag on economic activity over much of the year.... It should be noted, however, that in recent weeks the dollar has stabilized and oil prices have begun to move up a little. These developments, if they stick, could dilute somewhat what would otherwise be drags on the economy in the near term. We shall see.
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May 07, 2015
All Eyes on the Consumer
It appears that the first quarter may have been even worse than we thought. The CNBC rapid update—consensus estimates from a panel of forecasters—registered a decline of 0.3 percent as of yesterday.
Clearly, the year didn't start out so well, but here at the Atlanta Fed we have not yet lost faith. We are sticking to the narrative that 2015 will be another solid year of recovery.
That said, our faith is not blind and, befitting data-dependent policymakers, we need to make some call about what it will take to shake our confidence. In a speech delivered yesterday (May 6) in Baton Rouge, Louisiana, Atlanta Fed President Dennis Lockhart pointed to our current lodestar:
As I assess the possible and necessary contributors to a rebound in the second quarter and thereafter, attention has to fall on consumer spending, in my view.
Is there a case for optimism? We think so, and it is based on the assumption that the fundamentals supporting consumer spending have been stronger than the actual recent pace of expenditures. President Lockhart continues:
What's up with the consumer? It's puzzling. The fundamentals supporting consumption growth seem strong. I consider consumer fundamentals to be real personal income growth, household wealth, access to credit, and consumer confidence. Consumer confidence is, in turn, highly influenced by the broad employment outlook.
To be more precise about that sentiment, the chart below illustrates an experiment based on a simple model that incorporates President Lockhart's description of "fundamentals." To be even more precise, we ask the following question: What would we have predicted for consumer spending growth during the past four months based on the history of actual consumer spending and its relationship to income, employment (and unemployment), confidence measures, and wealth (specifically, equity prices)? We also threw inflation and oil prices into the mix for good measure.
Here's what we got:
In other words, the "fundamentals" suggest the four-month annualized growth of consumer spending should have been in excess of 4 percent, as opposed to the approximately 1.5 percent we actually saw. That is a story we don't expect to persist, and our current view of the year is that first-quarter consumer spending results are not indicative of future performance.
Consumers are, of course, a forward-looking bunch, and it is possible the recent weak spending reflects a looming reality not captured by the simple model described above. But our forecast for now is that consumers will move to the fundamentals, and not vice versa.
As President Lockhart said in Louisiana: "Stay tuned."
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April 20, 2015
What the Weather Wrought
At Seeking Alpha, Joseph Calhoun responds to Friday's macroblog post, which noted that, over the course of the recovery, first-quarter gross domestic product (GDP) growth has on average been slower than the quarterly performance over the balance of the year:
... the "between-the-lines" meaning of the Atlanta post is to ignore all of this since this weakness is being portrayed as "just like last year" a statistical problem in the one measure that economists think most represents the economy.
Rest assured, we try pretty hard to not place any messages "between the lines," and the penultimate sentence of Friday's piece was meant to strike the appropriately tentative tone: "As for the rest of the year, we'll have to wait and see."
We do believe, like others, that weather was at play in the subpar performance of 2015's debut. Severe weather, in February in particular, can explain some of the first-quarter weakness, but "some" is the operative qualifier.
As the following chart illustrates, relative to a baseline forecast without weather effects—proxied with National Oceanic and Atmospheric Administration measures of heating and cooling days through March—we estimate that the severity of the winter subtracted about 0.6 percentage point from GDP growth:
Two points: First, to the extent that weather is a culprit in subpar first-quarter growth, we should see some payback in the current quarter (as, dare we say, we saw last year).
Second, we (the Atlanta Fed staff) did not begin the year projecting first-quarter growth at a mere 1.8 percent annualized (as the benchmark forecast in the experiment illustrated above implies). That rate of growth is a considerable step-down from our forecast at the beginning of the year, forced by the realities of the incoming data (as captured, for example, by GDPNow estimates). That gap leaves plenty of explaining left to do.
Observable developments can plausibly explain much of the forecast miss—mainly the initial, somewhat ambiguous, impact of energy price declines and the rapid, steep appreciation of the dollar, which has clearly been associated with a suppression of export activity. Our current view is that, as energy prices and the exchange rate stabilize, we will see a return to growth patterns that are closer to 3 percent than 1 percent.
We are not, however, selling the position that it is wise to be completely sanguine about the rest of the year. Here is the official word from Dennis Lockhart, president of the Atlanta Fed (subscription required for full citation):
I lean to a later lift-off date [for the federal funds rate target]. To the extent you want to simplify that debate to June versus September, I lean to September. I don't think, given the progress we have made, the state of the economy, and my confidence that the first quarter was an aberration, that it would be horribly damaging to go a little earlier versus later. But my preference would be to wait for more confirming evidence that we are on the track we think we are on and we expect to carry us back to inflation toward target.
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March 06, 2015
Signs of Improvement in Prime-Age Labor Force Participation
This morning's job report provided further evidence of a stabilizing labor force participation (LFP) rate. After falling over 3 percentage points since 2008, LFP has been close to 62.9 percent of the population for the past seven months. Although demographics and behavioral trends explain much of the overall decline (our web page on LFP dynamics gives a full account), there is a cyclical component at work as well. In particular, the labor force attachment of "prime-age" (25 to 54 year olds) individuals to the labor force is something we're watching closely. Federal Reserve Bank of Atlanta President Dennis Lockhart noted as much in a February 6 speech:
Over the last few years, there has been a worrisome outflow of prime-age workers—especially men—from the labor force. I believe some of these people will be enticed back into formal work arrangements if the economy improves further.
There are signs that some of the prime-age individuals who had retreated to the margins of the labor market have been flowing back into the formal labor market.For one thing, LFP among prime-age individuals stopped declining 16 months ago for women and nine months ago for men. By our estimates, declining LFP in this age category accounts for about one-third of the overall decline in LFP since 2007, so 25- to 54-year-olds' decision to engage in the labor market has a big effect on the overall rate (see the chart). Even with an improving economy, however, a turnaround in LFP among prime-age individuals might not occur.
The reason an improving economy might not reverse the LFP trends is that LFP for both prime-age men and women had been on a longer-term downward trend even before the recession began, suggesting that factors other than the recession-induced decline in labor demand have been important. But the decline in the "shadow labor force"—the share of the prime-age population who say they want a job but are not technically counted as unemployed—demonstrates the cyclical nature of the labor market. For the last year and half, the share of these individuals in the labor force has been generally declining (see the chart).
Moreover, the job-finding success of the shadow labor force has improved. Although the 12-month flow into the official labor force has remained reasonably close to 50 percent, the likelihood of flowing into unemployment (as opposed to employment) rose during the recession. But during the past two years, that trend appears to be reversing (see the chart).
The ability of the prime-age shadow labor force to find work is improving at the same time that the LFP rate of the prime-age population is stabilizing. Taken together, this trend is consistent with improving job market opportunities and further absorption of the nation's slack labor resources.For a more complete analysis of long-term behavioral and demographic effects on LFP for the prime-age and non-prime-age populations, see our Labor Force Participation Dynamics web page, which now includes 2014 data.
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February 12, 2015
Are We Becoming a Part-Time Economy?
Compared with 2007, the U.S. labor market now has about 2.5 million more people working part-time and about 2.2 million fewer people working full-time. In this sense, U.S. businesses are more reliant on part-time workers now than in the past.
But that doesn't necessarily imply we are moving toward a permanently higher share of the workforce engaged in part-time employment. As our colleague Julie Hotchkiss pointed out, almost all jobs created on net from 2010 to 2014 have been full-time. As a result, from 2009 to 2014, the part-time share of employment has declined from 21 percent to 19 percent and is about halfway back to its prerecession level.
But the decline in part-time utilization is not uniform across industries and occupations. In particular, the decline is much slower for occupations that tend to have an above-average share of people working part-time. This portion of the workforce includes general-service jobs such as food preparation, office and administrative support, janitorial services, personal care services, and sales.
The following chart compares the share of part-time employment for these general-service occupations with the share for production-type occupations (such as machine operators, fabricators, construction workers, and truck drivers).
The above chart suggests that if you talk to retailers or restaurateurs, they will say that they always relied pretty heavily on part-time workers. Their utilization increased during the recession, and it really hasn't changed much since then. But manufacturers or construction firms are more likely to say that part-time work is not that common, and although they did increase their utilization of part-time workers during the recession by quite a lot, things have been gradually returning to normal.
Why is the part-time share of employment declining more slowly in general-service occupations? The economy has been generating full-time general-service jobs at a much slower pace than in the past. Of the approximately 7.6 million full-time jobs created between 2010 and 2014, only about 17 percent have been in general-service occupations, versus about 32 percent of the 7.8 million full-time jobs created between 2003 and 2007. At the current rate of full-time job creation in general-service occupations, it would take more than 10 years for the part-time share of employment in general-service occupations to return to its prerecession average.
From the workers' perspective, a relevant question is whether these part-time utilization rates are desirable. Some people work part-time and do not currently want or are not available for full-time work (so-called part-time for noneconomic reasons, PTNER). Others are available and want full-time work but are working part-time because of slack business conditions or the unavailability of full-time jobs (so-called part-time for economic reasons, PTER). The following chart shows the share of employment in the general-service and production occupation groupings that is PTER and PTNER.
The chart indicates that most of the movement in the part-time share of employment is coming from people who want full-time work. In both cases, the share of involuntary part-time employment rose during the recession, but for general-service occupations it has been more persistent than for production jobs.
Why has the demand for full-time workers in general-service occupations been more subdued than for other jobs? As the following chart shows, wage growth for these occupations has been quite weak in the past few years, suggesting that employers have not been experiencing much tightness in the supply of workers to fill vacancies for these occupations. Presumably, then, the firms generally find it acceptable to have a greater share of part-time workers than in the past.
The overall share of the workforce employed in part-time jobs is declining and is likely to continue to decline. But the decline is not uniform across industries and occupations. Working part-time has become much more likely in general-service occupations than in the past—and a greater share of those workers are not happy about it.
By John Robertson, vice president and senior economist, and
Ellie Terry, an economic policy analysis specialist, both of the Atlanta Fed's research department
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- Is the Number of Stay-at-Home Dads Going Up or Down?
- Labor Force Participation: Aging Is Only Half of the Story
- Putting the MetLife Decision into an Economic Context
- The Rise of Shadow Banking in China
- Which Wage Growth Measure Best Indicates Slack in the Labor Market?
- Collateral Requirements and Nonbank Online Lenders: Evidence from the 2015 Small Business Credit Survey
- Are Paychecks Picking Up the Pace?
- Introducing the Refined Labor Market Spider Chart
- Shrinking Labor Market Opportunities for the Disabled?
- Are Long-Term Inflation Expectations Declining? Not So Fast, Says Atlanta Fed
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