The Atlanta Fed's macroblog provides commentary and analysis on economic topics including monetary policy, macroeconomic developments, inflation, labor economics, and financial issues.
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June 01, 2016
Putting the Wage Growth Tracker to Work
The April pop in the Atlanta Fed's Wage Growth Tracker has attracted some attention in recent weeks, resulting in some interesting analysis. What is the tracker telling us about the tightness of the labor market and the risks to the inflation outlook?
We had earlier noted the strong correlation between the Wage Growth Tracker and the unemployment rate. Tim Duy took the correlation a step further and estimated a wage Phillips curve. Here's what he found:
The chart shows that lower unemployment generally coincides with higher wage growth (as measured by the Wage Growth Tracker), but wage growth varies a lot by unemployment rate. In the past, an unemployment rate around 5 percent has often been associated with higher wage growth than we currently have.
If the Wage Growth Tracker increased further, would that necessarily lead to an increase in inflation? Jared Bernstein suggests that there isn't much of an inflation signal coming from the Wage Growth Tracker. His primary evidence is the insignificant response of core personal consumption expenditure (PCE) inflation to an increase in the Wage Growth Tracker in a model that relates inflation to lags of inflation, wage growth, and the exchange rate.
However, I don't think the absence of a wage-push inflation connection using the Wage Growth Tracker is really that surprising. The Wage Growth Tracker better captures the wage dynamics associated with improving labor market conditions than rising labor cost pressures per se. For example, if firms are replacing departing workers with relatively low-wage hires, then the wages of incumbent workers could rise faster than do total wage costs (as this analysis by our colleagues at the San Francisco Fed shows). That said, as Bernstein also pointed out in the Washington Post, it's also pretty hard to find evidence of wage pass-through pushing up inflation in his model using more direct measures of labor costs.
I look forward to seeing more commentary about Atlanta Fed tools like the Wage Growth Tracker and how they can be part of the broader discussion of economic policy.
May 19, 2016
Are People in Middle-Wage Jobs Getting Bigger Raises?
As observed in this Bloomberg article and elsewhere, the Atlanta Fed's Wage Growth Tracker (WGT) reached its highest postrecession level in April. This related piece from Yahoo Finance suggests that the uptick in the WGT represents good news for middle-wage workers. That might be so.
Technically, though, the WGT is the median change in the wages of all continuously employed workers, not the change in wages among middle-income earners. However, we can create versions of the WGT by occupation group that roughly correspond to low-, middle-, and high-wage jobs, which allows us to assess whether middle-wage workers really are experiencing better wage growth. Chart 1 shows median wage growth experienced by each group over time. (Note that the chart shows a 12-month moving average instead of a three-month average, as depicted in the overall WGT on our website.)
Wage growth for all three categories has risen during the past few years. However, the timing of the trough and the speed of recovery vary somewhat. For example, wage growth among low-wage earners stayed low for longer and then recovered relatively more quickly. Wage growth of those in high-wage jobs fell by less but also has recovered by relatively less. In fact, while the median wage growth of low-wage jobs is back to its 2003–07 average, wage growth for those in high-wage jobs sits at about 75 percent of its prerecession average.
Are middle-wage earners experiencing good wage growth? In a relative sense, yes. The 12-month WGT for high-wage earners was 3.1 percent in April compared with 3.2 percent and 3.0 percent for middle- and low-wage workers, respectively. So the typical wage growth of those in middle-wage jobs is trending slightly higher than for high-wage earners, a deviation from the historical picture.
Interestingly, this pattern of wage growth doesn't quite jibe with the relative tightness of the labor market for different types of jobs. As was shown here, the overall WGT appears to broadly reflect the tightness of the labor market (possibly with some lag).
In theory, as the pool of unemployed shrinks, employers will face pressure to increase wages to attract and retain talent. Chart 2 shows the 12-month average unemployment rates for people who were previously working in one of the three wage groups.
Like the relationship between overall WGT and the unemployment rate, wage growth and the unemployment rate within these wage groups are negatively correlated (in other words, when the unemployment rate is high, wage growth is sluggish). The correlation ranges from minus 0.81 for low-wage occupations to minus 0.88 for middle-wage occupations.
However, notice that although the current gap between unemployment rates across the wage spectrum is similar to prerecession averages, the current relative gap in median wage growth is different than in the past. In particular, the wage growth for those in higher-wage jobs has been sluggish compared to middle- and lower-wage occupations.
Nonetheless, it's clear that the labor market is getting tighter. Wage growth overall has moved higher over the past year, driven primarily by those working in low- and middle-wage jobs. Is firming wage growth starting to show up in price inflation? Perhaps.
The consumer price index inflation numbers moved higher again in April, and Atlanta Fed President Dennis Lockhart said on Tuesday that—from a monetary policy perspective—recent inflation readings and signs of better growth in economic activity during the second quarter (as indicated by the Atlanta Fed's GDPNow tracker) are encouraging signs.
May 04, 2016
What's behind the Recent Uptick in Labor Force Participation?
The labor force participation rate had been generally declining since around 2007. However, that trend has partially reversed in recent months. As noted in the minutes of the March meeting of the Federal Open Market Committee, this rise was interpreted as further strengthening of the labor market. But will the increase persist?
As shown in a previous macroblog post, the dominant contributor to the decline in participation during the last several years has been the aging of the population. To see what's behind the increase in participation during the last few months, the following chart breaks the participation rate change between the first quarters of 2015 and 2016 into a part that is the result of shifts in the age distribution (holding behavior within age groups fixed), and the parts that are the result of changes in behavior (holding the age distribution fixed).
During the last year, the negative effect on participation attributable to an aging population (0.22 percentage points) has been offset by a 0.23 percentage point decline in the share of people who want a job but are not counted as unemployed (including people who are marginally attached). This decline is an encouraging sign, and consistent with a tightening labor market.
How much more can the want-a-job category improve? We don't really know. But that category's share of the population is currently about 0.3 percentage points above the prerecession trough of 2.0 percent. So at the current pace we would be at prerecession levels in about a year.
Despite the recent uptick, projections over the next decade or so have the labor force participation rate moving lower, chiefly because of an aging population. But how much farther participation actually declines will also depend on the evolution of various behavioral factors. The employment report for April will be released this Friday by the U.S. Bureau of Labor Statistics, and it will be interesting to see whether the number of people on the margin of the labor force continues to shrink.
April 29, 2016
Is the Number of Stay-at-Home Dads Going Up or Down?
A recent Wall Street Journal post observed that most of the recession's "stay-at-home dads" are going back to work. Specifically, data from the U.S. Labor Department shows that the share of married men with children under 18 who are not employed (but their spouse is) rose during the recession and has since given back much of that increase, as the Journal's chart below indicates.
Of course, being a stay-at-home dad in the sense defined in the previous chart (that is, not employed) can be either involuntary because of unemployment, or it can be the result of a voluntary decision to not be in the workforce. Most of the variation in the previous chart is cyclical, suggesting that it is related to the rise and fall in unemployment. But it also looks like the share of stay-at-home dads is higher now than it was a decade or so ago. So perhaps there is also an increasing trend in the propensity to voluntarily be a stay-at-home dad.
To explore this possibility, the next chart shows the annual average share of married men ages 25–54 who have children and who say the main reason they do not currently want a job is because of family or household responsibilities. (This reason doesn't necessarily imply that they are looking after children, but it is likely to be the leading reason.) The fraction is very small—about 1.3 percent in 2015, or 285,000 men—but the share has more than doubled during the last 15 years and would account for about half of the elevated level of the stay-at-home rate in 2015 relative to 2000.
So although large numbers of unemployed stay-at-home dads have been going back to work, it also appears that there's a small but growing group of men who are choosing to take on household and family responsibilities instead.
April 15, 2016
Labor Force Participation: Aging Is Only Half of the Story
The labor force participation rate (LFPR) is an important ingredient in projecting employment growth and the unemployment rate. However, predicting the LFPR has proven difficult. For example, in 2011 the Congressional Budget Office (CBO) projected that the LFPR in 2015 would be about 64.3 percent. In reality, the LFPR turned out to be 62.6 percent. Based on the CBO projection, the economy would have needed to create about 4 million more jobs to reach the 2015 unemployment rate of 5.3 percent.
Why is the LFPR so hard to predict? Leaving aside the challenge of projecting the size of the population, movements in LFPR primarily reflect shifts in the age distribution of the population as well as a number of behavioral factors. Although the aging trends are largely baked in, the behavioral factors vary over time. According to our estimates, about half of the 3.4 percentage-point decline in the LFPR between 2007 and 2015 is the result of the aging of the population, while behavioral factors account for the rest.
The complication is that the specific behaviors can change. The following chart shows a decomposition of the change in LFPR from 2007 to 2011 and from 2011 to 2015. Though the aging of the population contributed about the same amount to the decline in LFPR in both periods, the contributions from other factors have varied a lot. (We delve into the changes in the factors following the chart.)
Aging: The single largest factor contributing to the decline in the overall LFPR has been the rising share of older Americans in the population. In 2007, about one in five Americans were over 60 years old. In 2015, almost one in four were over 60. Moreover, this demographic force will continue to suppress the overall LFPR as the share of older Americans increases further in coming years. (For an in-depth discussion of the economic implications of an aging population—including changes in the labor market—please read the Atlanta Fed's 2015 annual report.)
Later retirement: One countervailing factor to an aging population has been the rising LFPR of older individuals. The retirement rate of those over 60 declined between 2007 and 2011 by a similar amount as it had before the recession. However, the trend toward later retirement has slowed considerably in recent years. The reason for this slowing is a puzzle and has important implications for the future course of overall LFPR.
Schooling among the young: The enrollment in educational programs by American youth has been generally rising over several decades, and this trend has put downward pressure on the overall LFPR. During the 2007–11 period, the share of 16- to 24-year-olds who do not want a job because they were in school or college accelerated relative to the prerecession trend. However, enrollment rates have since flattened out. The slowing may reflect enrollment rates catching up to the longer-term trend or may be a result of changes in the opportunity cost of education.
Not in the labor force but want a job: The share of the population saying they want a job but are not classified as unemployed by the U.S. Bureau of Labor Statistics definition is countercyclical—it tends to go up during bad times and down during good times. The relative size of this group increased between 2007 and 2011 and has since retraced about half of that increase as the economy has strengthened. We expect that this category will continue to shrink some more as the economy continues to expand.
Health: The share of individuals who do not want a job because they were too ill or disabled to work has increased over time. The relative size of this group increased between 2007 and 2011. Since 2011, the rate of increase has slowed, and it actually declined in 2015. It is not clear what drove the larger increase during the 2007–11 period, but there is some literature linking weak labor market conditions to poor health outcomes.
Prime-age reasons for not wanting a job (other than health): During the recession, the share of prime-age (ages 25 to 54) women not wanting a job because of household or family responsibilities decreased. One explanation is that some women entered the labor force to help make ends meet. At the same time, there was an offsetting effect from a rise in educational enrollment. Since the recession, nonparticipation because of household or family responsibilities has returned to near prerecession levels, and educational enrollment has leveled off.
To summarize, we find that relative to the 2007–11 period there has been a:
- flattening in the rate of retirement by older individuals,
- flattening in the rate of educational program enrollment by younger individuals,
- declining share of the population saying they want a job but not officially counted as unemployed,
- smaller drag from nonparticipation because of health, and
- larger drag for reasons other than health among prime-age individuals.
Where will LFPR be by the end of 2016? What about five years from now?
During the first three months of 2016, there has been an increase in the overall LFPR. This was largely the result of a decline in the share of prime-age people citing health reasons for nonparticipation, with some contribution from a decline in the share who want a job but are not "unemployed."
Though these boosts to participation may offset the effect of an aging population in the short term, most forecasts have the LFPR declining over the next several years. How much participation will actually decline depends on the answers to several difficult questions, such as: Will older individuals push retirement out even farther? Will school enrollment rates rise more rapidly again? Will the health status of the population improve? The difficulty of answering these questions helps explain why making accurate labor force projections is challenging.
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.
January 29, 2016
Shrinking Labor Market Opportunities for the Disabled?
The labor force participation rate (LFPR) among prime-age (25–54 years old) people averaged 80.8 percent in 2015, down 1.8 percentage points (2.6 million people) from 2009, according to the U.S. Bureau of Labor Statistics. According to our calculations from the Current Population Survey (CPS), a drop in LFPR among individuals with disabilities accounts for about a fifth of that decline.
Many people with disabilities are active in the labor force, working or looking for work. But the disabled LFPR has fallen a lot in recent years—it's down from 39.3 percent in 2009 to 34.5 percent in 2015. In other words, for some reason, more prime-age individuals with disabilities have opted out of the labor market.
A rising share of the prime-age population with a disability is not the culprit. In fact, the 2015 average disability rate was 6.4 percent, the same as in 2009. It is possible that the severity rather than incidence of disabilities has increased in recent years; labor market attachment does vary with type of disability, as this report shows.
But we suspect that the relatively large decline in disabled labor market attachment probably has also to do with shifts in employment opportunities for those with a disability. Some insight into this issue can be seen by looking at the change in employment shares in occupations that tend to have relatively low pay.
Workers with a disability tend to make less than nondisabled workers. We estimate the median wage of a worker with a disability in 2009 to have been 76 percent that of a nondisabled worker. In 2015, the relative median wage had declined to 74 percent. This drop is partly related to a relative increase in the share of employment for workers with a disability in low-paying occupations (which we define as jobs in personal care, food services, janitorial services, etc.), as the chart shows. The employment news has not been all bad for workers with a disability, however. There has been a rise in the share of employment of people with disabilities in higher-paying occupations since 2009, although they do tend to earn less than other workers in those types of occupations.
For some workers with disabilities, the financial return to employment versus nonemployment may have become somewhat less attractive in recent years. One factor related to the decision to engage in the labor market is the ability to collect Social Security Disability Insurance (SSDI). SSDI claims rose notably when the unemployment rate was high, which is consistent with the idea that the expected return to labor market activity for some individuals with a disability declined.
Job seekers with a disability have also struggled to find jobs offering the hours they desire. For example, the share of unemployed people finding full-time or voluntary part-time employment within a month, or "the hours-finding rate," is much lower for the prime-age disabled than for the nondisabled, and this share has improved relatively less over the recovery. Between 2009 and 2015, the average disabled hours-finding rate improved 4.7 percentage points, from 9.5 to 14.2 percent. During the same period, the nondisabled hours-finding rate increased 6.3 percentage points, from 13.0 to 19.3 percent.
The incidence of disability among prime-age individuals has not increased in recent years. But the labor market attachment of the disabled has declined, and this decline accounts for about one-fifth of the 1.8 percentage point fall in prime-age labor force participation between 2009 and 2015. Those with disabilities already have a harder time finding well-paying jobs, but that difficulty appears to have increased in that time span.
By John Robertson, a senior policy adviser in the Atlanta Fed's research department, and
January 07, 2016
What Occupational Projections Say about Entry-Level Skill Demand
On December 8, 2015, the U.S. Bureau of Labor Statistics (BLS) released its latest projections of labor force needs facing the U.S. economy from now until 2024.
Every two years, the BLS undertakes an extensive assessment of worker demand based on a number of factors: projected growth in the overall economy, dynamics of economic growth (such as which industries are growing fastest), labor force demographics (for example, the aging of the labor force), and expected changes in the labor force participation rate. Total worker demand includes both the number of workers needed to meet economic growth as well as the number of workers needed to replace current workers expected to retire.
A number of observations about these projections have already been identified. For example: overall employment growth will be slower, health care jobs will continue growing, and computer programmer jobs will lose ground.
In addition to the number of workers that will be in demand in different occupations in the U.S. economy, the BLS reports the skills that are needed for entry into those occupations—skills pertaining to both education levels and on-the-job training. As I perused this report, I was surprised at how much attention the press pays to the growth in high-skilled jobs at the expense of attention paid to those occupations requiring less skill but actually employ the greatest number of workers.
To be clear, the BLS does not project the educational requirements that will be needed for entering each occupation in 2024. It merely reports the most common education, training, and experience requirements needed to enter each occupation in the base year (in this case, 2014). Also it's important to note that these estimates of education needed to enter an occupation do not necessarily (and almost surely do not) match the average education of workers in that occupation at any given time, as those averages will reflect workers of many different ages and experience. The BLS gives a detailed description of how it identifies the entry-level educational and training requirements for each occupation. With those caveats in mind, let's take a look at the current distribution of jobs across the most common educational requirement for entering occupations.
The chart below tells us that, together, the typical entry-level requirement of a high school degree or less corresponds to nearly 64 percent of all jobs in the U.S. economy in 2014, while those typically requiring at least a bachelor's degree for entry represent 25.6 percent of jobs. The projected distribution of jobs in 2024 looks nearly identical: entry-level requirements (based on 2014 assessments) for 63 percent of all jobs requiring a high school degree or less and 26.2 percent requiring a bachelor's degree or more.
To be sure, the growth in higher-skill jobs far outpaces that for low- or middle-skill jobs. The number of jobs requiring a bachelor's degree or more for entry (in 2014) is expected to grow by 34 percent, whereas the number of jobs requiring less than a bachelor's degree is expected to grow by only 6 percent. This difference in growth rates reflects, in part, an expected continuation of the phenomenon of declining middle-skill jobs that my Atlanta Fed colleagues (and others) have discussed previously. Although labeled "middle-skill," entry into these occupations (such as office support and many manufacturing occupations) is not likely to require more than a high school degree.
However, even though the growth in low- and middle-skill jobs is expected to be slower than in higher-skill jobs, the total number of job openings based on predicted growth and replacement needs between 2014 and 2024 is expected to be nearly 32 million for jobs requiring less than a bachelor's degree for entry (based on 2014 assessments), with 30 million of those requiring only a high school degree or less. The total number of job openings requiring at least a bachelor's degree is expected to be about 12 million. In other words, the number of jobs requiring a high school degree or less in order to enter is twice as large as the number of jobs that require a college degree to enter.
The other side of this story, however, is that those jobs typically requiring less education at entry don't pay nearly as much as jobs requiring higher levels of education. The dollar figures in parentheses on the chart reflect the median annual salary of jobs with the different entry-level educational requirements. What we see is that while the majority of U.S. jobs require a high school degree or less at entry, those jobs pay less than half of what a job requiring at least a college degree pays.
So let's say a worker wants good job prospects (with a large number of job openings over the next decade), doesn't want to go to college, and wants to optimize chances for the highest salary possible. What is this worker to do? Fortunately, some of my colleagues at the Atlanta Fed, Cleveland Fed, and Philadelphia Fed have produced a report identifying what they call "opportunity occupations," which they define as those paying salaries higher than the geographically-adjusted national median for at least 70 percent of adults who have less than a college education. Some jobs among their top opportunity occupations are nurses, bookkeepers, first-line supervisors of retail workers, truck drivers, computer user support specialists, police officers, and electricians and workers in several other construction trades. Their report also identifies the U.S. metropolitan areas possessing a high share of opportunity occupations.Even though the share of jobs in the U.S. economy requiring less than a college degree at entry is getting smaller (very slowly), the largest number of jobs in the economy is, by far, jobs requiring less than a college degree at entry, and those jobs offer a wide range of options that pay above the national median wage.
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- Examining Changes in Labor Force Participation
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