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The Atlanta Fed's macroblog provides commentary and analysis on economic topics including monetary policy, macroeconomic developments, inflation, labor economics, and financial issues.

Authors for macroblog are Dave Altig, John Robertson, and other Atlanta Fed economists and researchers.


October 01, 2018


Demographically Adjusting the Wage Growth Tracker

In a recent report, the Council of Economic Advisers (CEA) referred to the Atlanta Fed's Wage Growth Tracker, noting its usefulness as a people-constant measure of wage growth because it looks at the over-the-year changes in the wages for a given set of individual workers. The CEA's preferred version of the Wage Growth Tracker is the one created by my colleague Ellie Terry and described in this macroblog post. It weights the sample of individual wage growth observations so that the worker characteristics resemble the population of wage and salary earners in every month. However, the CEA report also noted that this measure does not adjust for the fact that the characteristics of wage and salary earners have changed over time.

The following table, which shows the percent of workers in different age groups for three years (in three different decades), illustrates this point. The statistics are shown for the unweighted Wage Growth Tracker sample (the green columns), and for the population of wage and salary earners (the blue columns).

 

Wage Growth Tracker Sample

Wage and Salary Earner Population

 

16-24

25-54

55+

16-24

25-54

55+

1997

10.0

77.8

12.2

15.5

73.3

11.2

2007

8.5

71.7

19.8

14.1

69.2

16.7

2017

7.5

65.8

26.7

12.8

65.1

22.1

Source: Current Population Survey, author's calculations

The table shows that the Wage Growth Tracker sample in each year has fewer young workers (and more old workers) than does the population of all wage and salary earners, a fact for which the weighted version of the Wage Growth Tracker adjusts. However, the weighted version doesn't adjust for the fact that the workforce has also become older over time—the share of workers over 54 years old has risen nearly 11 percentage points since 1997.

Shifts in the distribution of demographic and other characteristics over time could matter for measures of wage growth because, for example, wage growth tends to be much higher for young workers. Young workers switch jobs more often, whereas workers aged 55 and older tend to have the lowest rates of job switching. Other changes in the composition of the workforce could also be important, such as changes the mix of education, the types of jobs, etc.

To investigate the impact of changes in workforce characteristics over time, we developed another version of the Wage Growth Tracker. This one weights the sample for each month so that it is more representative of the wage and salary earner population that existed in 1997. So, for instance, it always has about 15.5 percent aged 16-24, 73.3 percent aged 25-54, and 11.2 percent over 54 (the blue columns in the 1997 row of the table above).

As the following chart shows, the shifting composition of the workforce has put some additional downward pressure on median wage growth in recent years. That is, median wage growth would be even stronger if the sample each month looked more like it came from the population of wage and salary earners in 1997.

All three versions of the Wage Growth Tracker—unweighted, weighted to each month's workforce characteristics, and weighted to 1997 workforce characteristics—are available in the data download section of the Wage Growth Tracker web page. Which one you prefer depends on the question you are trying to answer. The monthly weighted version makes the Wage Growth Tracker more representative of the characteristics of the employed in each month, and in doing so gives young workers more influence, but it does not control for the fact that today's workforce has a smaller share of young workers than in the past. The 1997-weighted version fixes the workforce characteristics at their 1997 levels. It says that the median growth in individual wages would be higher than it is today if the composition of the workforce had not changed (other things equal). Nonetheless, any version of the Tracker you consult in the previous chart tells a pretty similar overall story: median wage growth is significantly higher than it was five or six years ago, but it hasn't shown much acceleration over the last couple of years.

October 1, 2018 in Employment, Labor Markets, Wage Growth | Permalink

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Please explain how to interpret the wage growth statistic in context of CPI.

My initial instinct is to simply subtract cpi growth from wage growth to normalize.

It isn't jumping out at me as to how to interpret the results in terms of standard of living for the median and quartile earners.

Posted by: John Fitzgerald | October 23, 2018 at 06:57 PM

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August 15, 2018


Does Loyalty Pay Off?

A newspaper article last week posed the question: Why do bosses pay new hires better than loyal staffers? The article looked at the Atlanta Fed's Wage Growth Tracker data on job stayers versus job switchers and noted that job switchers are getting a bigger percentage gain in their pay than job stayers.

Does that mean that people who switch jobs are paid better than those who stay with their employer? Well, it's useful to keep in mind that job switchers and job stayers differ along a number of dimensions, and perhaps the most important is that job switchers tend to earn less than job stayers. For example, using the data that go into constructing the Wage Growth Tracker we see that the median job switcher's pay in 2017 was around 9 percent lower than the median pay of those who stayed in their job. So even though the 2017 median wage growth for job switchers was 3.9 percent versus 3.0 percent for job stayers, those who change jobs are typically paid less than those who don't.

Why is the median pay higher for people who remain in their jobs? For one thing, job stayers in Wage Growth Tracker data are relatively older, with commensurately more work experience. In addition, job stayers tend to be more educated and hence more likely to be in jobs that require specialized skills. Economic theory also suggests that holding a higher-paying job reduces the likelihood of quitting. The argument goes that as a worker's wage increases, other employers will make fewer offers that exceed the person's minimally acceptable wage (their reservation wage). As a result, as an individual moves into better paying jobs, on-the-job search efforts and expected wage growth decline.

So what should you make of the higher median wage growth enjoyed by job switchers in the Wage Growth Tracker data? I view it as an indication that the demand for labor is strong and provides plentiful opportunities for less experienced and less educated workers to improve their circumstances by changing jobs. A job has an option value, and the possibility of getting a better-paying job offer is high when the worker's reservation value is low and the frequency of offers is high.

August 15, 2018 in Employment, Labor Markets, Wage Growth | Permalink

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Another possibility: periods between jobs. If job switchers are out of work for a percentage of their work life, their overall earnings would be lower than the loyal, continuously-employed worker.

Posted by: RepubAnon | August 16, 2018 at 10:22 PM

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August 08, 2018


Immigration and Hispanics' Educational Attainment

In a previous macroblog post, Whitney Mancuso and I wrote about the improved labor market outcomes for workers with the least amount of formal education. We attributed this improvement mostly to a combination of a secular decline in the supply of these workers over time and a shift in the composition of the low-skilled workforce toward Hispanic immigrants—a group that has an especially high rate of workforce attachment.

In a related article by colleagues at the St. Louis Fed, Alexander Monge-Naranjo and Juan Ignacio Vizcaino explore how the employment characteristics of the Hispanic population have grown increasingly concentrated in low-skilled occupations over time, and they relate this to the relatively smaller gains in the average educational attainment of the Hispanic population.

The authors ask why the education level of Hispanics has lagged behind other groups and suggest that it could be a consequence of intergenerational persistence; it takes a while for the children of poorly educated immigrants to catch up with the rest of the population. This explanation is likely to play a role, especially when considering why a relatively smaller share of U.S.-born Hispanics go to college. The study also notes differences across gender, showing that Hispanic men are less likely than Hispanic women to continue their education after high school, and although the college rate has been rising for all Hispanics, it is growing faster for women.

I also want to note that a large share of the Hispanic population in the United States are foreign born, and these immigrants have a much lower average level of educational attainment than do U.S.-born Hispanics. This observation is evident in table 1, which is based on data on individuals aged 25-54 (prime age) from the Current Population Survey. For instance, in 2017, 57 percent of the U.S. prime-age Hispanic population was foreign born, and 21 percent of these prime-age foreign born Hispanics had a college degree (associate degree or higher). In contrast, 36 percent of U.S.-born prime-age Hispanics had a degree.

Table 1: Selected Characteristics of the U.S. Prime-age Population (percent)

 

Foreign born

Completed a college/associate degree

 

Hispanic

Non-Hispanic

Hispanic

Non-Hispanic

 

 

 

Foreign born

U.S. born

Foreign born

U.S. born

1997

62

9

13

22

48

37

2007

64

12

15

29

56

43

2017

57

14

21

36

64

51

Source: Current Population Survey, author's calculations

As the St. Louis Fed study concludes, a primary factor distinguishing the Hispanic workforce in the United States is their lower average level of educational attainment. Further distinguishing between foreign and U.S.-born Hispanics shows the role that immigration has played in holding down the average education level since a large fraction of Hispanic immigrants have less education.

The Hispanic/non-Hispanic college completion gap remains large and has not closed over time. However, there has been relative improvement in high school completion, as table 2 shows.

Table 2: Selected Characteristics of the U.S. Prime-age Population (percent)

 

Foreign born

Completed 12th grade

 

Hispanic

Non-Hispanic

Hispanic

Non-Hispanic

 

 

 

Foreign born

U.S. born

Foreign born

U.S. born

1997

62

9

50

81

92

92

2007

64

12

55

87

93

94

2017

57

14

65

92

95

96

Source: Current Population Survey, author's calculations

Since 1997, the share of the prime-age foreign born Hispanic population who have finished 12th grade has increased by 15 percentage points. At the same time, the share of prime-age U.S.-born Hispanics completing high school has increased by 11 percentage points and is now not much lower than for non-Hispanics. While relatively low college attendance remains a major obstacle, greater high school completion is encouraging for Hispanics' future role in the workforce.

August 8, 2018 in Education, Immigration, Labor Markets | Permalink

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July 20, 2018


Improving Labor Market Fortunes for Workers with the Least Schooling

A recent Wall Street Journal story observed that the strong labor market is having a particularly positive impact on those with the least amount of formal schooling. Research by our colleague Julie Hotchkiss has also highlighted the potential lasting benefits of a strong labor market for groups of workers who often struggle to find employment. For example, as chart 1 shows, the unemployment rate gap for those 25 years or older and for the same age cohort but with the least formal education is currently near the narrowest gap on record.

The narrowing of this gap over time probably reflects many factors, but one important development has been a systematic shift in the ethnic composition of the least educated workforce. Specifically, as chart 2 shows, the Hispanic (predominantly foreign born) share of the labor force without a high school diploma has increased from about 35 percent two decades ago to almost 60 percent today.

This shift in composition matters because, as chart 3 shows, the unemployment rate for Hispanics without a high school diploma is generally lower than for other ethnicities. Combined with the growing share of the least educated members of the workforce who are Hispanic, this shift in composition acts to lower the overall unemployment rate for that education group.

What's behind the lower unemployment rate for Hispanic workers? It's not clear. But among unemployed workers 25 and older who haven't completed high school, Hispanic workers generally have a higher likelihood of finding a job than do non-Hispanics, and in recent years they are also likelier to remain employed. Both factors have contributed to the relatively better labor market outcomes we have seen develop.

The narrowing unemployment rate gap for those with the least amount of schooling is good news. However, the continuing decline in the share of population without a high school diploma is probably even better news. This share is down from around 16 percent in the late 1990s to 9 percent today. For Hispanics, the decline is even more pronounced. But that decline might also reflect changes in immigration patterns, as it is mostly the result of a decline in the number of foreign-born Hispanics without a high school diploma starting in 2006—the peak of the last housing boom.

July 20, 2018 in Employment, Labor Markets | Permalink

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June 01, 2018


Part-Time Workers Are Less Likely to Get a Pay Raise

A recent FEDS Notes article summarized some interesting findings from the Board of Governors' 2017 Survey of Household Economics and Decisionmaking. One set of responses that caught my eye explored the connection between part-time employment and pay raises. The report estimates that about 70 percent of people working part-time did not get a pay increase over the past year (their pay stayed the same or went down). In contrast, only about 40 percent of full-time workers had no increase in pay.

This pattern is broadly consistent with what we see in the Atlanta Fed's Wage Growth Tracker data. As the following chart indicates, the population of part-time workers (who were also employed a year earlier) is generally less likely to get an increase in the hourly rate of pay than their full-time counterparts. Median wage growth for part-time workers has been lower than for full-time workers since 1998.

Wage Growth Tracker

This wage growth premium for full-time work is partly accounted for by the fact that the typical part-time and full-time worker are different along several dimensions. For example, a part-time worker is more likely to have a relatively low-skilled job, and wage growth tends to be lower for workers in low-skilled jobs.

As the chart shows, the wage growth gap widened considerably in the wake of the Great Recession. The share of workers who are in part-time jobs because of slack business conditions increased across industries and occupation skill levels, and median part-time wage growth ground to a halt.

While part-time wage growth has improved since then, the wage growth gap is still larger than it used to be. This larger gap appears to be attributable to a rise in the share of part-time employment in low-skilled jobs since the recession. In particular, relative to 2007, the share of part-time workers in the Wage Growth Tracker data in low-skilled jobs has increased by about 3 percentage points, whereas the share of full-time workers in low-skilled jobs has remained essentially unchanged. Note that what is happening here is that more part-time jobs are low skilled than before, and not the other way around. Low-skilled jobs are about as likely to be part-time now as they were before the recession.

How does this shift affect an assessment of the overall tightness of today's labor market? Looking at the chart, the answer is probably “not much.” As measured by the Wage Growth Tracker, median wage growth for both full-time and part-time workers has not been accelerating recently. If the labor market were very tight, then this is not what we would expect to see. The modest rise in average hourly earnings in the June 1 labor report for May 2018 to 2.7 percent year over year, even as the unemployment rate declined to an 18-year low, seems consistent with that view.  A reading on the Wage Growth Tracker for May should be available in about a week.

June 1, 2018 in Data Releases, Economic conditions, Employment, Labor Markets, Wage Growth | Permalink

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April 18, 2018


Hitting a Cyclical High: The Wage Growth Premium from Changing Jobs

The Atlanta Fed's Wage Growth Tracker rose 3.3 percent in March. While this increase is up from 2.9 percent in February, the 12-month average remained at 3.2 percent, a bit lower than the 3.5 percent average we observed a year earlier. The absence of upward momentum in the overall Tracker may be a signal that the labor market still has some head room, as suggested by participants at the last Federal Open market Committee (FOMC) meeting, who noted this in the meeting:

Regarding wage growth at the national level, several participants noted a modest increase, but most still described the pace of wage gains as moderate; a few participants cited this fact as suggesting that there was room for the labor market to strengthen somewhat further.

Although wages haven't been rising faster for the median individual, they have been for those who switch jobs. This distinction is important because the wage growth of job-switchers tends to be a better cyclical indicator than overall wage growth. In particular, the median wage growth of people who change industry or occupation tends to rise more rapidly as the labor market tightens. To illustrate, the orange line in the following chart shows the median 12-month wage growth for workers in the Wage Growth Tracker data who change industry (across manufacturing, construction, retail, etc.), and the green line depicts the wage growth of those who remained in the same industry.

As the chart indicates, changing industry when unemployment is high tends to result in a wage growth penalty relative to those who remain employed in the same industry. But when the unemployment rate is low, voluntary quits rise and workers who change industries tend to experience higher wage growth than those who stay.

Currently, the wage growth premium associated with switching employment to a different industry is around 1.5 percentage points and growing. For those who are tempted to infer that the softness in the Wage Growth Tracker might signal an impending labor market slowdown, the wage growth performance for those changing jobs suggests the opposite: the labor market is continuing to gradually tighten.

April 18, 2018 in Data Releases, Employment, Labor Markets, Wage Growth | Permalink

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March 06, 2018


A First Look at Employment

One Friday morning each month at 8:30 is always an exciting time here at the Atlanta Fed. Why, you might ask? Because that's when the U.S. Bureau of Labor Statistics (BLS) issues the newest employment and labor force statistics from the Employment Situation Summary. Just after the release, Atlanta Fed analysts compile a "first look" report based on the latest numbers. We have found this initial view to be a very useful glimpse into the broad health of the national labor market.

Because we find this report useful, we thought you might also find it of interest. To that end, we have added the Labor Report First Look tool to our website, and we'll strive to post updated data soon after the release of the BLS's Employment Situation Report. Our Labor Report First Look includes key data for the month and changes over time from both the payroll and household surveys, presented as tables and charts. 

Additionally, we will also use the bureau's data to create other indicators included in the Labor Report First Look. For example, one of these is a depiction of changes in payroll employment by industry, in which we rank industry employment changes by average hourly pay levels. This tool allows us to see if payrolls are gaining or losing higher- or lower-paying jobs, as the following chart shows.

But wait, there's more! We will also report information on the so-called job finding rate—an estimate of the share of unemployed last month who are employed this month—and a broad measure of labor underutilization. Our underutilization concept is related to another statistic we created called Z-Pop, computed as the share of the population who are either unemployed or underemployed (working part-time hours but wanting full-time work) or who say they currently want a job but are not actively looking. We have found this to be a useful supplement to the BLS's employment-to-population ratio (see the chart).

The Labor Report First Look tool also allows you to dig a bit deeper into Atlanta Fed labor market analysis via links to our Human Capital Data & Tools (which includes the Wage Growth Tracker and Labor Force Dynamics web pages) and links to some of our blog posts on labor market developments and related research. (In fact, it's easy to stay informed of all Labor Report First Look updates by subscribing to our RSS feed or following the Atlanta Fed on Twitter.

We hope you'll look for the inaugural Labor Report First Look next Friday morning...we know you'll be as excited as we will!

March 6, 2018 in Economic conditions, Employment, Labor Markets | Permalink

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February 28, 2018


Weighting the Wage Growth Tracker

The Atlanta Fed's Wage Growth Tracker (WGT) has shown its usefulness as an indicator of labor market conditions, producing a better-fitting Phillips curve than other measures of wage growth. So we were understandably surprised to see the WGT decline from 3.5 percent in 2016 to 3.2 percent in 2017, even as the unemployment rate moved lower from 4.9 to 4.4 percent.

This unexpected disconnect between the WGT and the unemployment rate naturally led us to wonder if it was a consequence of the way the WGT is constructed. Essentially, the WGT is the median of an unweighted sample of individual wage growth observations. This sample is quite large, but it does not perfectly represent the population of wage and salary earners.

Importantly, the WGT sample has too few young workers, because young workers are much more likely to be in and out of employment and hence less likely to have a wage observation in both the current and prior years. To examine the effect of this underrepresentation, we recomputed median wage growth after weighting the WGT sample to be consistent with the distribution of demographic and job characteristics of the workforce in each year. It turns out that this adjustment is important when the labor market is tight.

During periods of low unemployment, young people who stay employed tend to experience larger proportionate wage bumps than older workers. In 2017, for example, the weighted median is 40 basis points higher than the unweighted version. However, both the unweighted version (the gray line in the chart below) and the weighted version of the WGT (the blue line) declined by a similar amount from 2016 to 2017. The decline in the weighted median is also statistically significant (the p-value for the test is 0.07, indicating that the observed difference is unlikely to be due to chance).

Another issue that could affect comparisons of wage growth over time is the changing demographic characteristics of the workforce. In particular, we know that workers' wage growth tends to slow as they approach retirement age, and the fraction of older workers has increased markedly in recent years. To examine this trend, we re-computed the weighted median, but fixed the demographic and job characteristics of the workforce so they would look as they did in 1997.

Our 1997-fixed version shows that median wage growth in recent years would be a bit higher if not for the aging of the workforce (the dashed orange line in the chart below). Moreover, this demographic shift appears to explain some of the slowing in median wage growth from 2016 to 2017. Whereas the 1997-fixed median also slows over the year, the difference is not statistically significant (a test of the null hypothesis of no change in the 1997-fixed weighted median between 2016 and 2017 yielded a p-value of 0.38).

Long story short, our analysis suggests that median wage growth of the population of wage and salary earners is currently higher than the WGT would indicate, reflecting the strong wage gains young workers experience in a tight labor market. Moreover, the increasing share of older workers is acting to restrain median wage growth. Although the decline in median wage growth from 2016 to 2017 appears to be partly the result of the aging workforce, there still may be more to it than just that, and so we will continue to monitor the WGT and related measures closely in 2018 for signs of a pickup. We also want to note that with the release of the February wage data in mid-March, we will make a monthly version of the weighted WGT available.

 

February 28, 2018 in Data Releases, Employment, Labor Markets, Wage Growth | Permalink

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January 18, 2018


How Low Is the Unemployment Rate, Really?

In 2017, the unemployment rate averaged 4.4 percent. That's quite low on a historical basis. In fact, it's the lowest level since 2000, when unemployment averaged 4.0 percent. But does that mean that the labor market is only 0.4 percentage points away from being as strong as it was in 2000? Probably not. Let's talk about why.

As observed by economist George Perry in 1970, although movement in the aggregate unemployment rate is mostly the result of changes in unemployment rates within demographic groups, demographic shifts can also change the overall unemployment rate even if unemployment within demographic groups has not changed. Adjusting for demographic changes makes for a better apples-to-apples comparison of unemployment today with past rates.

Three large demographic shifts underway since the early 2000s are the rise in the average age and educational attainment of the labor force, and the decline in the share who are white and non-Hispanic. These changes are potentially important because older workers and those with more education have lower rates of unemployment across age and education groups respectively, and white non-Hispanics tend to have lower rates of unemployment than other ethnicities.

The following chart shows the results of a demographic adjustment that jointly controls for year-to-year changes in two sex, three education, four race/ethnicity, and six age labor force groups, (see here for more details). Relative to the year 2000, the unemployment rate in 2017 is about 0.6 percentage points lower than it would have been otherwise simply because the demographic composition of the labor force has changed (depicted by the blue line in the chart).

In other words, even though the 2017 unemployment rate is only 0.4 percentage points higher than in 2000, the demographically adjusted unemployment rate (the green line in the chart) is 1.0 percentage points higher. In terms of unemployment, after adjusting for changes in the composition of the labor force, we are not as close to the 2000 level as you might have thought.

The demographic discrepancy is even larger for the broader U6 measure of unemployment, which includes marginally attached and involuntarily part-time workers. The 2017 demographically adjusted U6 rate is 2.5 percentage points higher than in 2000, whereas the unadjusted U6 rate is only 1.5 percentage points higher. That is, on a demographically adjusted basis, the economy had an even larger share of marginally attached and involuntarily part-time workers in 2017 than in 2000.

The point here is that when comparing unemployment rates over long periods, it's advisable to use a measure that is reasonably insulated from demographic changes. However, you should also keep in mind that demographics are only one of several factors that can cause fluctuation. Changes in labor market and social policies, the mix of industries, as well as changes in the technology of how people find work can also result in changes to how labor markets function. This is one reason why estimates of the so-called natural rate of unemployment are quite uncertain and subject to revision. For example, participants at the December 2012 Federal Open Market Committee meeting had estimates for the unemployment rate that would prevail over the longer run ranging from 5.2 to 6.0 percent. At the December 2017 meeting, the range of estimates was almost a whole percentage point lower at 4.3 to 5.0 percent.

January 18, 2018 in Business Cycles, Economic conditions, Labor Markets, Unemployment | Permalink

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November 15, 2017


Labor Supply Constraints and Health Problems in Rural America

A recent research study by Alison Weingarden at the Federal Reserve's Board of Governors found that wages for relatively low-skilled workers in nonmetropolitan areas of the country have been growing more rapidly than those in metropolitan areas. In a talk yesterday in Montgomery, Alabama, Atlanta Fed President Raphael Bostic provided some evidence that differences in labor supply resulting from disability and illness may be behind this shrinking urban wage premium.

For prime-age workers (those between 25 and 54 years old), the dynamics of labor force participation (LFP) differ widely between metropolitan and nonmetropolitan areas. (These data define a metropolitan statistical area, or MSA). The LFP rate in MSAs declined by about 1.1 percentage points between 2007 and 2017 versus a 3.3 percentage point decline in non-MSA areas.

The disparity is also evident within education groups. For those without a college degree, the MSA LFP rate is down 2.6 percentage points, versus 5.0 percentage points in non-MSAs. For those with a college degree, the MSA LFP rate is down 0.7 percentage points, versus a decline of 2.5 percentage points for college graduates in non-MSAs. Moreover, although LFP rates in MSAs have shown signs of recovery in the last couple of years, this is not happening in non-MSAs.

A recent macroblog post by my colleague Ellyn Terry and the Atlanta Fed's updated Labor Force Dynamics web page have shown that the decline in prime-age LFP is partly a story of nonparticipation resulting from a rise in health and disability problems that limit the ability to work. This rise is occurring even as the population is gradually becoming more educated. (Better health outcomes generally accompany increased educational attainment.)

The following chart explores the role of disability/illness in explaining the relatively larger decline in non-MSA LFP. It breaks the cumulative change in the LFP rates since 2007 into the part attributable to demographic trends and the part attributable to behavioral or cyclical changes within demographic groups.

The demographic changes—and especially the increased share of the population with a college degree—has put mild upward pressure on the prime-age LFP rate for both the MSA and non-MSA population. Controlling for the contribution from these demographic trends, increased nonparticipation because of poor health and disability pulled down the LFP rate in MSAs by 0.8 percentage points and lowered the rate in non-MSAs by 2.0 percentage points over the past decade. For those without a college degree, disability/illness accounted for about 1.2 percentage points of the 2.6 percentage point decline in the MSA participation rate, and it accounted for 2.6 percentage points of the 5.0 percentage point decline in the non-MSA participation rate.

Taken together with evidence from business surveys and anecdotal reports about hiring difficulties, it appears that the non-MSA labor market is relatively tight. The greater inward shift of the rural supply of labor is showing through to wage costs, and especially for rural jobs that require less education.

Although the move to higher wages is welcome news for those with a job, it also raises troubling questions about why labor force nonparticipation because of disability and illness has increased so much in the first place—especially among those with less education living in nonmetropolitan areas of the country.

It is clear that the health problems for rural communities have been intensifying. Several interrelated factors have likely contributed to this worsening trend, including poverty, deeply rooted cultural and social norms, and the characteristics of rural jobs, as well as geographic barriers and shortages of healthcare providers that have limited access to care. This complex set of circumstances suggests that finding effective solutions could prove difficult.

November 15, 2017 in Health Care, Labor Markets, Unemployment | Permalink

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What I have seen is many people who get on disability or trying to get on disability are moving to country because of much cheaper housing costs. For many people living in the city would use up almost their entire disability check. If you're trying to get on disability and and have no work check the cheapest rent is in the country period. This distorts figures to a significant degree also note many people of disability try to have side non 'official" jobs so areas showing high levels of disability might have more available workers then official records might indicate our system seems designed to create a black market of sorts for jobs!

Posted by: rodger chinery | November 15, 2017 at 02:30 PM

Does the decrease in LFP in non-MSA reflect in part workers moving from MSA to non-MSA due to cost of living while on disability?

Posted by: Generic Preacher | November 15, 2017 at 03:58 PM

Rural areas have suffered from GOP refusal to maintain health care access, with some exceptions, notably Kentucky.

Kentucky saw it's SSDI rates fall since Kynect, reversing increasing rates of disabled workers.

And it's ironic that GOP State fund worker job training only as part of deals including tax breaks for foriegn corporations building factories in the GOP States. Otherwise, tax cuts drive cutting worker education, ending trade training in public education.

In the MSAs the public education and businesses are much more likely to partner on education for business needs, especially when business and management pay significant taxes.

Posted by: mulp | November 17, 2017 at 04:41 AM

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