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August 05, 2014
What’s Driving the Part-Time Labor Market? Results from an Atlanta Fed Survey
A subtle shift appears to be emerging in the public discussion of part-time employment in the United States. In monetary policy circles, elevated levels of part-time employment have generally been taken as a signal of lingering weakness in the labor market. (See, for example, here and here.) In this view, the rise in the use of part-time workers is a response to weak economic conditions, and the rate of part-time utilization will return to something approaching the prerecession average as firms respond to strengthening demand by increasing the hours of some of part-time staff who want more hours (thus reducing the number and share of part-time workers who would like full-time work) and by creating more full time jobs for those who want them (thus reducing the share of involuntary part-time workers).
But some labor market observers interpret the recent rise in the share of part-time jobs as more structural in nature—and hence less likely to be remedied by demand-inducing strategies such as monetary stimulus. If the arithmetic of having full-time or part-time workers has changed (for example, we frequently hear about increased compensation costs resulting from health care changes associated with the Affordable Care Act), then employers might lean more on part-time workers, at least while they can. Employers might be more able to do so while there is an ample supply of unemployed people and fewer full-time job opportunities, or if technology has made it sufficiently easy to manage workers’ hours. Virginia Postrel at BloombergView recently wrote an essay about how technology is helping firms better manage part-time employees. From that essay:
For many part-time workers in the post-crash economy, life has become like endless jury duty. Scheduling software now lets employers constantly optimize who’s working, better balancing labor costs and likely demand.
Perhaps the “demand” aspect of that passage refers to the level of overall spending in the economy (a point made in another BloombergView piece that Postrel’s column cites). But there is an undeniable technological slant to this story—one that is not so obviously about the condition of the economy. And based on recent legislative proposals out of Congress, some lawmakers seem to see an issue that is likely to persist beyond the current business cycle.
So is our issue insufficient demand, about which monetary policy can arguably do something, or is it a change in the nature of work in the United States, which is arguably impervious to the effects of changes in monetary policy?
Both of these questions seem valid, and reasonable perspectives support both of them (see, for example, here and here). So as we try to sort this out, we turned to the Atlanta Fed’s Regional Economic Information Network of business contacts and went to the source: employers themselves.
First, though, let’s review a few facts. During the recession, full-time employment fell substantially while the number working part-time actually increased. Today, there are about 12 percent more people working part-time than before the recession and about 2 percent fewer people working full-time hours. As the chart below shows, this slow rebound in full-time employment—and the sustained level of part-time employment—has resulted in a greater share of employed working part-time: 19 percent of employed people are working fewer than 35 hours compared with 17 percent of all employed before the recession began.
To delve more deeply into these facts, we collected the responses of 339 firms with at least 20 employees to two questions: “Compared to before the recession, is your current mixture of part-time and full-time employees different? Do you think your current mixture will change over the next couple of years?” The responses (presented in the chart below) are weighted by national firm size and industry distributions.
About two-thirds of firms indicated their mixture of full-time and part-time employees was not currently different than before the recession began. One quarter of firms said they currently have a higher share of part-time employees, and 8 percent have a smaller share. Looking forward, 31 percent believe their workforce will possess a greater share of part-time workers in two years than it does now.
What did employers cite as the reason for the increase in part-time employment? Firms that currently have a higher share of part-time employees gave about equal weighting to cyclical and structural factors, as the chart below indicates. Most chose the options “Full-time employee compensation costs have increased relative to those of part time employees” and “Business conditions (sales) are not yet strong enough to justify converting part-time jobs to full-time” as either somewhat important or very important. These firms saw the other options—“Technology has made it easier to manage part-time employees” and “More job candidates are willing to take part-time jobs”—as less important.
The next chart shows that structural factors are on the minds of employers, especially among firms who haven’t yet increased their share of part-time employees. Expectations of increases in the compensation cost of full-time employees relative to part-time workers were cited as the most important factor for all firms, but the difference in the relative importance among expected compensation costs and other factors was greater among firms that have not yet increased their part-time share of employment. Expected weak sales and future ample supply of people willing to work part-time were also seen as somewhat important factors for many firms.
Do firms anticipate a return to their prerecession mix of part-time and full-time employment? Although we didn’t ask this question directly, the next chart constructs an answer based on their responses to our other two questions.
Compared with prerecession levels, 34 percent of firms indicated they expect the share of part-time employees in their firm to be higher in two years. This segment includes the vast majority (90 percent) of the 25 percent of firms who already have a higher share now than before the recession and 12 percent of other firms who currently have the same share but anticipate increases during the next two years. Surprisingly, only about 2 percent of firms currently have a higher share of part-time workers and anticipate decreases over the next two years (they are represented in the above chart in the “no change” category).
To sum up, the results have something for people on either side of the cyclical-versus-structural debate. Weak business conditions and the increase in the relative cost of full-time employees have been about equally important drivers of the increase in the use of part-time employees thus far. Thinking about the future, firms mostly cite an expected rise in the relative cost of full-time workers as the reason for shifting toward more part-time employees. So while there are some clear structural forces at work, a large amount of uncertainty around the future cost of health care and the future pace of economic growth also exists. The extent to which these factors will ultimately affect the share working part-time remains to be seen.
By Ellyn Terry, an economic policy analysis specialist in the Atlanta Fed’s research department
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July 18, 2014
Part-Time for Economic Reasons: A Cross-Industry Comparison
With employment trends having turned solidly positive in recent months, attention has focused on the quality of the jobs created. See, for example, the different perspectives of Mortimer Zuckerman in the Wall Street Journal and Derek Thompson in the Atlantic. Zuckerman highlights the persistently elevated level of part-time employment—a legacy of the cutbacks firms made during the recession—whereas Thompson points out that most employment growth on net since the end of the recession has come in the form of full-time jobs.
In measuring labor market slack, the part-time issue boils down to how much of the elevated level of part-time employment represents underutilized labor resources. The U-6 measure of unemployment, produced by the U.S. Bureau of Labor Statistics, counts as unemployed people who say they want to and are able to work a full-time schedule but are working part-time because of slack work or business conditions, or because they could find only part-time work. These individuals are usually referred to as working part-time for economic reasons (PTER). Other part-time workers are classified as working part-time for non-economic reasons (PTNER). Policymakers have been talking a lot about U-6 recently. See for example, here and here.
The "lollipop" chart below sheds some light on the diversity of the share of employment that is PTER and PTNER across industries. The "lolly" end of the lollipop denotes the average mix of employment that is PTER and PTNER in 2013 within each industry, and the size of the lolly represents the size of the industry. The bottom of the "stem" of each lollipop is the average PTER/PTNER mix in 2007. The red square lollipop is the percent of all employment that is PTER and PTNER for the United States as a whole. (Note that the industry classification is based on the worker's main job. Part-time is defined as less than 35 hours a week.)
The primary takeaways from the chart are:
- The percent of the workforce that is part time varies greatly across industries (compare for example, durable goods manufacturing with restaurants).
- All industries have a greater share of PTNER workers than PTER workers (for example, the restaurant industry in 2013 had 32 percent of workers who said they were PTNER and about 13 percent who declared themselves as PTER).
- All industries had a greater share of PTER workers in 2013 than in 2007 (all the lollipops point upwards).
- Most industries have a lower share of PTNER workers than in the past (most of the lollipops lean to the left).
- Most industries have a greater share of part-time workers (PTER + PTNER) than in the past (the increase in PTER exceeds the decline in PTNER for most industries).
Another fact that is a bit harder to see from this chart is that in 2007, industries with the largest part-time workforces did not necessarily have the largest PTER workforces. In 2013, it was more common for a large part-time workforce to be associated with a large PTER workforce. In other words, the growth in part-time worker utilization in industries such as restaurants and some segments of retail has bought with it more people who are working part-time involuntarily.
So the increase in PTER since 2007 is widespread. But is that a secular trend? If it is, then the increase in the PTER share would be evident since the recession as well. The next lollipop chart presents evidence by comparing 2013 with 2012:
This chart shows a recent general improvement. In fact, 25 of the 36 industries pictured in the chart above have experienced a decline in the share of PTER, and 21 of the 36 have a smaller portion working part-time in total. Exceptions are concentrated in retail, an industry that represents a large share of employment. In total, 20 percent of people are employed in industries that experienced an increase in PTER from 2012 to 2013. So while overall there has been a fairly widespread (but modest) recent improvement in the situation, the percent of the workforce working part-time for economic reasons remains elevated compared with 2007 for all industries. Further, many people are employed in industries that are still experiencing gains in the share that is PTER.
Why has the PTER share continued to increase for some industries? Are people who normally work full-time jobs still grasping those part-time retail jobs until something else becomes available, has there been a shift in the use of part-time workers in those industries, or is there a greater demand for full-time jobs than before the recession? We'll keep digging.
By John Robertson, a vice president and senior economist, and
Ellyn Terry, a senior economic analyst, both of the Atlanta Fed's research department
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June 30, 2014
The Implications of Flat or Declining Real Wages for Inequality
A recent Policy Note published by the Levy Economics Institute of Bard College shows that what we thought had been a decade of essentially flat real wages (since 2002) has actually been a decade of declining real wages. Replicating the second figure in that Policy Note, Chart 1 shows that holding experience (i.e., age) and education fixed at their levels in 1994, real wages per hour are at levels not seen since 1997. In other words, growth in experience and education within the workforce during the past decade has propped up wages.
The implication for inequality of this growth in education and experience was only touched on in the Policy Note that Levy published. In this post, we investigate more fully what contribution growth in educational attainment has made to the growth in wage inequality since 1994.
The Gini coefficient is a common statistic used to measure the degree of inequality in income or wages within a population. The Gini ranges between 0 and 100, with a value of zero reflecting perfect equality and a value of 100 reflecting perfect inequality. The Gini is preferred to other, simpler indices, like the 90/10 ratio, which is simply the income in the 90th percentile divided by the income in the 10th percentile, because the Gini captures information along the entire distribution rather than merely information in the tails.
Chart 2 plots the Gini coefficient calculated for the actual real hourly wage distribution in the United States in each year between 1994 and 2013 and for the counterfactual wage distribution, holding education and/or age fixed at their 1994 levels in order to assess how much changes in age and education over the same period account for growth in wage inequality. In 2013, the Gini coefficient for the actual real wage distribution is roughly 33, meaning that if two people were drawn at random from the wage distribution, the expected difference in their wages is equal to 66 percent of the average wage in the distribution. (You can read more about interpreting the Gini coefficient.) A higher Gini implies that, first, the expected wage gap between two people has increased, holding the average wage of the distribution constant; or, second, the average wage of the distribution has decreased, holding the expected wage gap constant; or, third, some combination of these two events.
The first message from Chart 2 is that—as has been documented numerous other places (here and here, for example)—inequality has been growing in the United States, which can be seen by the rising value of the Gini coefficient over time. The Gini coefficient’s 1.27-point rise means that between 1994 and 2013 the expected gap in wages between two randomly drawn workers has gotten two and a half (2 times 1.27, or 2.54) percentage points larger relative to the average wage in the distribution. Since the average real wage is higher in 2013 than in 1994, the implication is that the expected wage gap between two randomly drawn workers grew faster than the overall average wage grew. In other words, the tide rose, but not the same for all workers.
The second message from Chart 2 is that the aging of the workforce has contributed hardly anything to the growth in inequality over time: the Gini coefficient since 2009 for the wage distribution that holds age constant is essentially identical to the Gini coefficient for the actual wage distribution. However, the growth in education is another story.
In the absence of the growth in education during the same period, inequality would not have grown as much. The Gini coefficient for the actual real wage distribution in 2013 is 1.27 points higher than it was in 1994, whereas it's only 0.49 points higher for the wage distribution, holding education fixed. The implication is that growth in education has accounted for about 61 percent of the growth in inequality (as measured by the Gini coefficient) during this period.
Chart 3 shows the growth in education producing this result. The chart makes apparent the declines in the share of the workforce with less than a high school degree and the share with a high school degree, as is the increase in the shares of the workforce with college and graduate degrees.
There is little debate about whether income inequality has been rising in the United States for some time, and more dramatically recently. The degree to which education has exacerbated inequality or has the potential to reduce inequality, however, offers a more robust debate. We intend this post to add to the evidence that growing educational attainment has contributed to rising inequality. This assertion is not meant to imply that education has been the only source of the rise in inequality or that educational attainment is undesirable. The message is that growth in educational attainment is clearly associated with growing inequality, and understanding that association will be central to the understanding the overall growth in inequality in the United States.
By Julie L. Hotchkiss, a research economist and senior policy adviser at the Atlanta Fed, and
Fernando Rios-Avila, a research scholar at the Levy Economics Institute of Bard College
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June 20, 2014
The Wrong Question?
Just before Wednesday's confirmation from Fed Chairwoman Janet Yellen that the Federal Open Market Committee (FOMC) does indeed still see slack in the labor market, Jon Hilsenrath and Victoria McGrane posted a Wall Street Journal article calling notice to the state of debate:
Nearly four-fifths of those who became long-term unemployed during the worst period of the downturn have since migrated to the fringes of the job market, a recent study shows, rarely seeking work, taking part-time posts or bouncing between unsteady jobs. Only one in five, according to the study, has returned to lasting full-time work since 2008.
Deliberations over the nature of the long-term unemployed are particularly lively within the Federal Reserve.... Fed officials face a conundrum: Should they keep trying to spur economic growth and hiring by holding short-term interest rates near zero, or will those low rates eventually spark inflation without helping those long out of work?
The article goes on to provide a nice summary of the ongoing back-and-forth among economists on whether the key determinant of slack in the labor market is the long-term unemployed or the short-term unemployed. Included in that summary, checking in on the side of "both," is research by Chris Smith at the Federal Reserve Board of Governors.
We are fans of Smith's work, but think that the Wall Street Journal summary buries its own lede by focusing on the long-term/short-term unemployment distinction rather than on what we think is the more important part of the story: In Hilsenrath and McGrane's words, those "taking part-time posts."
We are specifically talking about the group officially designated as part-time for economic reasons (PTER). This is the group of people in the U.S. Bureau of Labor Statistics' Household Survey who report they worked less than 35 hours in the reference week due to an economic reason such as slack work or business conditions.
We have previously noted that the long-term unemployed have been disproportionately landing in PTER jobs. We have also previously argued that PTER emerges as a key negative influence on earnings over the course of the recovery, and remains so (at least as of the end of 2013). For reference, here is a chart describing the decomposition from our previous post (which corrects a small error in the data definitions):
Our conclusion, clearly identified in the chart, was that short-term unemployment and PTER have been statistically responsible for the tepid growth in wages over the course of the recovery. What's more, as short-term unemployment has effectively returned to prerecession levels, PTER has increasingly become the dominant negative influence.
Our analysis was methodologically similar to Smith's—his work and the work represented in our previous post were both based on annual state-level microdata from the Current Population Survey, for example. They were not exactly comparable, however, because of different wage variables—Smith used the median wage while we use a composition-adjusted weighted average—and different regression controls.
Here is what we get when we impose the coefficient estimates from Smith's work into our attempt to replicate his wage definition:
Some results change. The unemployment variables, short-term or long-term, no longer show up as a drag in wage growth. The group of workers designated as "discouraged" do appear to be pulling down wage growth and in ways that are distinct from the larger group of marginally attached. (That is in contrast to arguments some of us have previously made in macroblog that looked at the propensity of the marginally attached to find employment.)
It is not unusual to see results flip around a bit in statistical work as this or that variable is changed, or as the structure of the empirical specifications is tweaked. It is a robustness issue that should always be acknowledged. But what does appear to emerge as a consistent negative influence on wage growth? PTER.
None of this means that the short-term/long-term unemployment debate is unimportant. The statistics are not strong enough for us to be ruling things out categorically. Furthermore, that debate has raised some really interesting questions, such as Glenn Rudebusch and John Williams's recent suggestion that the definition of economic slack relevant for the FOMC's employment mandate may be different from the definition appropriate to the FOMC's price stability mandate.
Our message is pretty simple and modest, but we think important. Whatever your definition of slack, it really ought to include PTER. If not, you are probably asking the wrong question.
By Dave Altig, executive vice president and research director, and
Pat Higgins, a senior economist, both of the Atlanta Fed's research department
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June 09, 2014
Looking Beyond the Job-Finding Rate: The Difficulty of Finding Full-Time Work
Despite Friday´s report of a further solid increase in payroll employment, the utilization picture for the official labor force remains mixed. The rate of short-term and long-term unemployment as well as the share of the labor force working part time who want to work full time (a cohort also referred to as working part time for economic reasons, or PTER) rose during the recession.
The short-term unemployment rate has since returned to levels experienced before the recession. In contrast, longer-term unemployment and involuntary part-time work have declined, but both remain well above prerecession levels (see the chart).
Some of the postrecession decline in the short-term unemployment rate has not resulted from the short-term unemployed finding a job, but rather the opposite—they failed to get a job and became longer-term unemployed. Before the recession, the number of unemployed workers who said they had been looking for a job for more than half a year accounted for about 18 percent of unemployed workers. Currently, that share is close to 36 percent.
Moreover, job finding by unemployed workers might not completely reflect a decline in the amount of slack labor resources if some want full-time work but only find part-time work (that is, are working PTER). In this post, we investigate the ability of the unemployed to become fully employed relative to their experience before the Great Recession.
The job-finding rate of unemployed workers (the share of unemployed who are employed the following month) generally decreases toward zero with the length of the unemployment spell. Job-finding rates fell for all durations of unemployment in the recession.
Since the end of the recession, job-finding rates have improved, especially for shorter-term unemployed, but remain well below prerecession levels. The overall job-finding rate stood at close to 28 percent in 2007 and was about 20 percent for the first four months of 2014. The chart below shows the job-finding rates for select years by unemployment duration:
What about the jobs that the unemployed find? Most unemployed workers want to work full-time hours (at least 35 hours a week). In 2007, around 75 percent of job finders wanted full-time work and either got full-time work or worked PTER (the remainder worked part time for noneconomic reasons). For the first four months of 2014, the share wanting full-time work was also about 75 percent. But the portion of job finders wanting full-time work and only finding part-time work increased from about 22 percent in 2007 to almost 30 percent in 2014, and this job-finding underutilization share has become especially high for the longer-term unemployed.
The chart below displays the job-finding underutilization share for select years by unemployment duration. (You can also read further analysis of PTER dynamics by our colleagues at the Federal Reserve Board of Governors.)
Finding a job is one thing, but finding a satisfactory job is another. Since the end of the recession, the number of unemployed has declined, thanks in part to a gradually improving rate of job finding. But the job-finding rate is still relatively low, and the ability of an unemployed job seeker who wants to work full-time to actually find full-time work remains a significant challenge.
John Robertson, a vice president and senior economist and
Ellyn Terry, a senior economic analyst, both of the Atlanta Fed's research department
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June 02, 2014
How Discouraged Are the Marginally Attached?
Of the many statistical barometers of the U.S. economy that we monitor here at the Atlanta Fed, there are few that we await more eagerly than the monthly report on employment conditions. The May 2014 edition arrives this week and, like many others, we will be more interested in the underlying details than in the headline job growth or unemployment numbers.
One of those underlying details—the state of the pool of “discouraged” workers (or, maybe more precisely, potential workers)—garnered special attention lately in the wake of the relatively dramatic decline in the ranks of the official labor force, a decline depicted in the April employment survey from the U.S. Bureau of Labor Statistics. That attention included some notable commentary from Federal Reserve officials.
Federal Reserve Bank of New York President William Dudley, for example, recently suggested that a sizeable part of the decline in labor force participation since 2007 can be tied to discouraged workers exiting the workforce. This suggestion follows related comments from Federal Reserve Chair Janet Yellen in her press conference following the March meeting of the Federal Open Market Committee:
So I have talked in the past about indicators I like to watch or I think that are relevant in assessing the labor market. In addition to the standard unemployment rate, I certainly look at broader measures of unemployment… Of course, I watch discouraged and marginally attached workers… it may be that as the economy begins to strengthen, we could see labor force participation flatten out for a time as discouraged workers start moving back into the labor market. And so that's something I'm watching closely.
What may not be fully appreciated by those not steeped in the details of the employment statistics is that discouraged workers are actually a subset of “marginally attached” workers. Among the marginally attached—individuals who have actively sought employment within the most recent 12-month period but not during the most recent month—are indeed those who report that they are out of the labor force because they are discouraged. But the marginally attached also include those who have not recently sought work because of family responsibilities, school attendance, poor health, or other reasons.
In fact, most of the marginally attached are not classified (via self-reporting) as discouraged (see the chart):
At the St. Louis Fed, B. Ravikumar and Lin Shao recently published a report containing some detailed analysis of discouraged workers and their relationship to the labor force and the unemployment rate. As Ravikumar and Shao note,
Since discouraged workers are not actively searching for a job, they are considered nonparticipants in the labor market—that is, they are neither counted as unemployed nor included in the labor force.
More importantly, the authors point out that they tend to reenter the labor force at relatively high rates:
Since December 2007, on average, roughly 40 percent of discouraged workers reenter the labor force every month.
Therefore, it seems appropriate to count some fraction of the jobless population designated as discouraged (and out of the labor force) as among the officially unemployed.
We believe this logic should be extended to the entire group of marginally attached. As we've pointed out in the past, the marginally attached group as a whole also has a roughly 40 percent transition rate into the labor force. Even though more of the marginally attached are discouraged today than before the recession, the changing distribution has not affected the overall transition rate of the marginally attached into the labor force.
In fact, in terms of the propensity to flow into employment or officially measured unemployment, there is little to distinguish the discouraged from those who are marginally attached but who have other reasons for not recently seeking a job (see the chart):
What we take from these data is that, as a first pass, when we are talking about discouraged workers' attachment to the labor market, we are talking more generally about the marginally attached. And vice versa. Any differences in the demographic characteristics between discouraged and nondiscouraged marginally attached workers do not seem to materially affect their relative labor market attachment and ability to find work.
Sometimes labels matter. But in the case of discouraged marginally attached workers versus the nondiscouraged marginally attached workers—not so much.
By Dave Altig, executive vice president and research director,
John Robertson, a vice president and senior economist, and
Ellyn Terry, a senior economic analyst, all of the Atlanta Fed's research department
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May 09, 2014
How Has Disability Affected Labor Force Participation?
You might be unaware that May is Disability Insurance Awareness Month. We weren’t aware of it until recently, but the issue of disability—as a reason for nonparticipation in the labor market—has been very much on our minds as of late. As we noted in a previous macroblog post, from the fourth quarter of 2007 through the end of 2013, the number of people claiming to be out of the labor force for reasons of illness or disability increased almost 3 million (or 23 percent). The previous post also noted that the incidence of reported nonparticipation as a result of disability/illness is concentrated (unsurprisingly) in the age group from about 51 to 60.
In the past, we have examined the effects of the aging U.S. population on the labor force participation rate (LFPR). However, we have not yet specifically considered how much the aging of the population alone is responsible for the aforementioned increase in disability as a reason for dropping out of the labor force.
The following chart depicts over time the percent (by age group) reporting disability or illness as a reason for not participating in the labor force. Each line represents a different year, with the darkest line being 2013. The chart reveals a long-term trend of rising disability or illness as a reason for labor force nonparticipation for almost every age group.
The chart also shows that disability or illness is cited most often among people 51 to 65 years old—the current age of a large segment of the baby boomer cohort. In fact, the proportion of people in this age group increased from 20 percent in 2003 to 25 percent in 2013.
How much can the change in demographics during the past decade explain the rise in disability or illness as a reason for not participating in the labor market? The answer seems to be: Not a lot.
Following an approach you may have seen in this post, we break down into three components the change in the portion of people not participating in the labor force due to disability or illness. One component measures the change resulting from shifts within age groups (the within effect). Another component measures changes due to population shifts across age groups (the between effect). A third component allows for correlation across the two effects (a covariance term). Here’s what you get:
To recap, only about one fifth of the decline in labor force participation as a result of reported illness or disability can be attributed to the population aging per se. A full three quarters appears to be associated with some sort of behavioral change.
What is the source of this behavioral change? Our experiment can’t say. But given that those who drop out of the labor force for reasons of disability/illness tend not to return, it would be worth finding out. Here is one perspective on the issue.
You can find even more on this topic via the Human Capital Compendium.
By Dave Altig, research director and executive vice president at the Atlanta Fed, and
Ellyn Terry, a senior economic analyst in the Atlanta Fed's research department
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April 17, 2014
Using State-Level Data to Estimate How Labor Market Slack Affects Wages
At a recent speech in Miami, Atlanta Fed President Dennis Lockhart had this to say:
Wage growth by most measures has been very low. I take this as a signal of labor market weakness, and in turn a signal of a lack of significant upward unit cost pressure on inflation.
This macroblog post examines whether the data support this assertion (answer: yes) and whether wage inflation is more sensitive to some measures of labor underutilization than other measures (answer: apparently, yes). San Francisco Fed President John Williams touched on the latter topic in a recent speech (emphasis mine):
We generally look at the overall unemployment rate as a good yardstick of labor market slack and inflation pressures. However, its usefulness may be compromised today by the extraordinary number of long-term unemployed—defined as those out of the workforce for six months or longer... Standard models of inflation typically do not distinguish between the short- and long-term unemployed, because they're assumed to affect wage and price inflation in the same way. However, recent research suggests that the level of long-term unemployment may not influence inflation pressures to the same degree as short-term unemployment.
And Fed Chair Janet Yellen said this at her March 19 press conference:
With respect to the issue of short-term unemployment and its being more relevant for inflation and a better measure of the labor market, I've seen research along those lines. I think it would be tremendously premature to adopt any notion that says that that is an accurate read on either how inflation is determined or what constitutes slack in the labor market.
The research to which President Williams refers are papers by economists Robert Gordon and Mark Watson, respectively. (For further evidence, see this draft by Princeton economists Alan Krueger, Judd Cramer and David Cho.)
The analysis here builds on this research by broadening the measures of labor underutilization beyond the short-term and long-term unemployment rates that add up to the standard unemployment rate called U-3. The U-5 underutilization measure includes both conventional unemployment and "marginally attached workers" who are not in the labor force but who want a job and have actively looked in the past year. The difference between U-5 and U-3 is a very close proxy for the number of marginally attached relative to the size of the labor force.
U-6 encompasses U-5 as well as those who work less than 35 hours for an economic reason. The difference between U-6 and U-5 is a very close proxy for the share of "part-time for economic reason" workers in the labor force. These nonoverlapping measures of labor underutilization rates are all shown in the chart below.
The series are highly correlated, making it difficult to isolate the impact of any particular labor underutilization rate on wage inflation (e.g., "How much will wage inflation change if the short-term unemployment rate rises 1.0 percentage point, holding all of the underutilization measures in the above figure constant?").
We follow the approach of Staiger, Stock, and Watson (2001) by using state-level data to relate wage inflation to unemployment in a so-called "wage-Phillips curve." Because the 2007–09 recession hit some states harder than others, we can use the cross-sectional variation in outcomes across states to arrive at more precise estimates of the separate impacts of the labor underutilization measures on wage inflation (see the chart).
Five-year state-level wage inflation rates for 2008–13, using monthly Current Population Survey(CPS) microdata, are shown on the vertical axis. The CPS microdata are also used to construct all of the labor underutilization measures. Each circle represents an individual state (red for long-term unemployment and blue for short-term unemployment), and each circle's area is proportional to the state's population share. Two noteworthy states are pointed out for illustration. North Dakota has had lower unemployment and (much) higher wage inflation than the other states (presumably because of its energy boom). And California has had higher unemployment and (somewhat) lower wage inflation than average. Even after excluding North Dakota, we see a clear negative relationship between wage inflation and underutilization measured with either short-term or long-term unemployment.
Because short-term and long-term unemployment are highly correlated (also apparent in the above plot), one can't tell visually if one underutilization measure is more important for wage inflation than the other. To make this assessment, we need to estimate a regression. The regression—which also includes both U-5 minus U-3 and U-6 minus U-5—adjusts wages for changes in the composition of the workforce. This composition adjustment, also made by Staiger, Stock and Watson (2001), controls for the fact that lower-skilled workers tend to be laid off at a disproportionately higher rate during recessions, thereby putting upward pressure on wages. The regression also weights observations by population shares.
The regression estimates imply that short-term unemployment is the most important determinant of wage inflation while U-6 minus U-5—the proxy for "part-time for economic reason" workers—also has a statistically significant impact. The other two labor underutilization measures do not affect wage inflation statistically different from zero. Rather than provide regression coefficients, we decompose observed U.S. wage inflation for 1995–2013 into contributions from the labor underutilization measures, workforce composition changes, and everything else (see the chart).
Both short-term unemployment and workers who are part-time for economic reasons have pushed down wage inflation. But the "part-time for economic reason" impact has become relatively more important recently because of the stubbornly slow decline in undesired part-time employment.
By Pat Higgins, a senior economist in the Atlanta Fed's research department
Editor’s note: Upon request, the programming code used in this macroblog post is available from the author.
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April 10, 2014
Reasons for the Decline in Prime-Age Labor Force Participation
As a follow up to this post on recent trends in labor force participation, we look specifically at the prime-age group of 25- to 54-year-olds. The participation decisions of this age cohort are less affected by the aging population and the longer-term trend toward lower participation of youths because of rising school enrollment rates. In that sense, they give us a cleaner window on responses of participation to changing business cycle conditions.
The labor force participation rate of the prime-age group fell from 83 percent just before the Great Recession to 81 percent in 2013. The participation rate of prime-age males has been trending down since the 1960s. The participation rate of women, which had been rising for most of the post-World War II period, appears to have plateaued in the 1990s and has more recently shared the declining pattern of participation for prime-age men. But the decline in participation for both groups appears to have accelerated between 2007 and 2013 (see chart 1).
We look at the various reasons people cite for not participating in the labor force from the monthly Current Population Survey. These reasons give us some insight into the impact of changes in employment conditions since 2007 on labor force participation. The data on those not in the official labor force can be broken into two broad categories: those who say they don't currently want a job and those who say they do want a job but don't satisfy the active search criteria for being in the official labor force. Of the prime-age population not in the labor force, most say they don't currently want a job. At the end of 2007, about 15 percent of 25- to 54-year-olds said they didn't want a job, and slightly fewer than 2 percent said they did want a job. By the end of 2013, the don't-want-a-job share had reached nearly 17 percent, and the want-a-job share had risen to slightly above 2 percent (see chart 2).
Prime-Age Nonparticipation: Currently Want a Job
Most of the rise in the share of the prime-age population in the want-a-job category is due to so-called marginally attached individuals—they are available and want a job, have looked for a job in the past year, but haven't looked in the past four weeks—especially those who say they are not currently looking because they have become discouraged about job-finding prospects (see the blue and orange lines of chart 3). In 2013, there were about 1.1 million prime-age marginally attached individuals compared to 0.7 million in 2007, and the prime-age marginally attached accounted for about half of all marginally attached in the population.
The marginally attached are aptly named in the sense that they have a reasonably high propensity to reenter the labor force—more than 40 percent are in the labor force in the next month and more than 50 percent are in the labor force 12 months later (see chart 4). This macroblog post discusses what the relative stability in the flow rate from marginally attached to the labor force means for thinking about the amount of slack labor resources in the economy.
Prime-Age Nonparticipation: Currently Don't Want a Job
As chart 2 makes evident, the vast majority of the rise in prime-age nonparticipation since 2009 is due to the increase in those saying they do not currently want a job. The largest contributors to the increase are individuals who say they are too ill or disabled to work or who are in school or training (see the orange and blues lines in chart 5).
Those who say they don't want a job because they are disabled have a relatively low propensity to subsequently (re)enter the labor force. So if the trend of rising disability persists, it will put further downward pressure on prime-age participation. Those who say they don't currently want a job because they are in school or training have a much greater likelihood of (re)entering the labor force, although this tendency has declined slightly since 2007 (see chart 6).
Note that the number of people in the Current Population Survey citing disability as the reason for not currently wanting a job is not the same as either the number of people applying for or receiving social security disability insurance. However, a similar trend has been evident in overall disability insurance applications and enrollments (see here).
Some of the rise in the share of prime-age individuals who say they don't want a job could be linked to erosion of skills resulting from prolonged unemployment or permanent changes in the composition of demand (a different mix of skills and job descriptions). It is likely that the rise in share of prime-age individuals not currently wanting a job because they are in school or in training is partly a response to the perception of inadequate skills. The increase in recent years is evident across all ages until about age 50 but is especially strong among the youngest prime-age individuals (see chart 7).
But lack of required skills is not the only plausible explanation for the rise in the share of prime-age individuals who say they don't currently want a job. For instance, the increased incidence of disability is partly due to changes in the age distribution within the prime-age category. The share of the prime-age population between 50 and 54 years old—the tail of the baby boomer cohort—has increased significantly (see chart 8).
This increase is important because the incidence of reported disability within the prime-age population increases with age and has become more common in recent years, especially for those older than 45 (see chart 9).
The health of the labor market clearly affects the decision of prime-age individuals to enroll in school or training, apply for disability insurance, or stay home and take care of family. Discouragement over job prospects rose during the Great Recession, causing many unemployed people to drop out of the labor force. The rise in the number of prime-age marginally attached workers reflects this trend and can account for some of the decline in participation between 2007 and 2009.
But most of the postrecession rise in prime-age nonparticipation is from the people who say they don't currently want a job. How much does that increase reflect trends established well before the recession, and how much can be attributed to the recession and slow recovery? It's hard to say with much certainty. For example, participation by prime-age men has been on a secular decline for decades, but the pace accelerated after 2007—see here for more discussion.
Undoubtedly, some people will reenter the labor market as it strengthens further, especially those who left to undertake additional training. But for others, the prospect of not finding a satisfactory job will cause them to continue to stay out of the labor market. The increased incidence of disability reported among prime-age individuals suggests permanent detachment from the labor market and will put continued downward pressure on participation if the trend continues. The Bureau of Labor Statistics projects that the prime-age participation rate will stabilize around its 2013 level. Given all the contradictory factors in play, we think this projection should have a pretty wide confidence interval around it.
Note: All data shown are 12-month moving averages to emphasize persistent shifts in trends.
By Melinda Pitts, director, Center for Human Capital Studies,
John Robertson, a vice president and senior economist in the Atlanta Fed's research department, and
Ellyn Terry, a senior economic analyst in the Atlanta Fed's research department
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March 18, 2014
Human Capital Topics Now Searchable
A little more than a week ago, all eyes were on the February Employment Situation report released by the U.S. Bureau of Labor Statistics. The Establishment Survey surprised on the upside: nonfarm payrolls rose 175,000 in February, and payrolls were revised upward for December and January. The Household Survey indicated that the unemployment rate edged up slightly to 6.7 percent in February from 6.6 percent the prior month, and the labor force participation rate held steady at 63.0 percent.
These are some of the facts on the table as the Federal Open Market Committee meets today and tomorrow and, judging from recent comments from the folks who will be at that meeting, those facts (and more like them) will be very much front of mind.
These days, multiple tools are available to assist both casual and expert observers in navigating the rich and sometimes baffling story of labor markets in the post-Great Recession world. Just last week, you could find a new "Guide for the Perplexed" on labor market slack in The New York Times and an interactive feature on the "Eight Different Faces of the Labor Market" at the New York Fed's Liberty Street Economics blog. And that's not to mention the most recent update of the Atlanta Fed’s own 13-headed Labor Market Spider Chart.
All of these contributions reflect a great deal of effort to understand the story of what's happening in labor markets. As part of that effort, our colleagues across the Federal Reserve System have been taking deeper dives into employment statistics and reaching out into their communities to get a better understanding of labor force dynamics and workforce development issues. This research can be found on the various Reserve Bank and Board websites.
To facilitate access to that work, the Atlanta Fed's Center for Human Capital Studies has worked to bring those resources together in the Federal Reserve Human Capital Compendium (HCC). We are pleased to announce that we have recently enhanced the HCC so you can perform simple or advanced searches that allow you to research whatever facet of that research strikes your fancy (see the figure):
We encourage you to take your own deeper dive into the latest research across the Federal Reserve System by browsing the HCC or searching out those labor topics that have piqued your interest lately.
By Whitney Mancuso, a senior economic analyst in the Atlanta Fed's research department
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- And the Winner Is...Full-Time Jobs!
- For Middle-Skill Occupations, Where Have All the Workers Gone?
- A Closer Look at Employment and Social Insurance
- Wage Growth of Part-Time versus Full-Time Workers: Evidence from the CPS
- Wage Growth of Part-Time versus Full-Time Workers: Evidence from the SIPP
- Data Dependence and Liftoff in the Federal Funds Rate
- What's behind Declining Labor Force Participation? Test Your Hypothesis with Our New Data Tool
- On Bogs and Dots
- The Changing State of States' Economies
- What Kind of Job for Part-Time Pat?
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