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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.


December 04, 2018


Defining Job Switchers in the Wage Growth Tracker

Among the questions we receive about the Atlanta Fed's Wage Growth Tracker, one of the most frequent is about the construction of the job switcher and job stayer series. These series are derived from data in the Current Population Survey (CPS) and are intended to show how median wage growth differs for those who change their job from last year versus those who are in the same job. However, the monthly CPS does not actually ask if the person has the same job as a year ago.

So how to proceed? The CPS does contain information about the person's industry and occupation that we aggregate into consistent categories that can be compared to the person's industry/occupation reported a year earlier. If someone is in a different occupation or industry category, then we can reasonably infer that the person has changed jobs. To illustrate, for 2017, 18.8 percent of people in the Wage Growth Tracker data are in a different industry category than they were in 2016, and 28.6 percent are in a different occupation category. Of those who remain in the same industry, 23.9 percent changed occupation group, and of those in the same occupation group, 13.5 percent are in a different industry. However, this information doesn't allow us to identify all job switchers because being in the same industry and occupation group as a year earlier does not preclude having changed jobs.

Fortunately, the CPS also has questions based on who a person said their employer was in the prior month. It asks if that person still works there and if the employee's activities and job duties are the same as last month. If someone answers either of these questions in the negative, then it is likely that person is also in a different job than a year earlier. In 2017, 1.5 percent of people in the Wage Growth Tracker data said they have a different employer than in the prior month, and 0.9 percent report having different job responsibilities at the same employer.

Unfortunately, the dynamic structure of the CPS means that the responses to these "same employer/activity" questions can only potentially be matched with an individual's response in the prior two months, and not a year earlier. Moreover, some responses to those questions are blank, even for people whom we identify as being employed in the prior month. For those individuals, we simply don't know if they are in the same job as a month earlier. Of the non-null responses, the vast majority do not change job duties or employer from one month to the next. So if we assume the blank responses are randomly distributed among the employed population, it's reasonable to also treat the blanks as job stayers.

Previously, we had treated the blank "same employer/activity" observations as job switchers, but that approach almost certainly misclassified some actual job stayers as job switchers. Instead, we now define a job switcher as someone in the Wage Growth Tracker data who is in a different occupation or industry group than a year earlier, or someone who says no to either of the "same employer/activity" questions in the current or prior two months. We label everyone else a job stayer.

Does the definition matter for median wage growth? The following chart shows the annual time series of the difference between the median wage growth of job switchers and job stayers based on both the old and new definitions.

As you can see, the results are not qualitatively different. Job switchers have higher median wage growth during strong labor market conditions and lower growth during bad times. Not surprisingly, the gap in median wage growth is generally lower (more negative) using the old definition.

The next chart shows the annual time series of the share of job switchers in the Wage Growth Tracker data based on the new and old definitions. A caveat: we have been unable to construct occupation and industry groupings for 2003 that are completely consistent with the groupings used in 2002. This results in an erroneous spike in measured job switching for 2003.

Notice that the share of job switchers under the new definition peaked prior to the last two recessions, declined during the recessions, and then recovered. That share is now at a cyclical high. A discrete jump in the number of blank responses recorded for the "same employer/activity" questions in the CPS starting in 2009 masked this cyclicality under the old definition.

In about a week from now, the next update of the Wage Growth Tracker data will implement the new and improved definition of job switchers—I hope you'll check it out, and I'll be writing about it here as well.

December 4, 2018 in Employment, Labor Markets, Wage Growth | Permalink

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November 16, 2018


Polarization through the Prism of the Wage Growth Tracker (Take Two)

In a previous macroblog post, I thought I had discovered an interesting differential between the wage growth of middle-wage earners and that of low/high-paid workers. It turns out that what I actually discovered is that my programming skills could be improved upon. The following is an update to the post, written after correcting the coding error. Although there is no obvious wage growth polarization story, the wages of low-wage workers are currently rising at a faster median rate than for other workers.

Updated Post:

One of the most frequent questions we receive about the Atlanta Fed's Wage Growth Tracker (the median of year-over-year percent changes in individuals' hourly wage) is about the relationship between wage level and wage growth. For example, do high-wage earners also tend to experience greater wage growth?

When looking at wage growth by wage level, whether you use the prior or current wage level as the reference point matters—a lot. If we looked at wage growth categorized by the prior year's wages, we would find higher median wage growth for low-wage earners than for high-wage earners. This is because some workers who earned low wages last year earn middle or high wages this year, and some of last year's high-wage workers earn middle or low wages this year. If we instead categorized people based on current-year wages, we would see exactly the opposite: lower median wage growth for low-wage workers than for high-wage workers (see here for more discussion).

One way to lessen this wage-level base effect is to categorize an individual's wage growth according to their average wage across the two years. The following chart shows this categorization for the 2016–17 wage growth distribution of all workers in the Wage Growth Tracker data. (Note that since 1997, the annual salary for people whose earnings are only reported on a weekly basis is top-coded at $150,000 a year—these masked observations are excluded from the analysis). In the chart, the first quartile depicts the lowest-paid 25 percent of workers based on their average 2016–17 hourly wage, and so on. The center line of the box for each quartile is the median of that group's wage growth distribution, and the lower and upper boundaries of the box are the 25th and 75th percentiles, respectively. The outer lines are the thresholds for outlier observations (see here for the calculation.)

Macroblog - November 16, 2018 - chart 1: Distribution of Growth in Hourly Wage

The chart shows that the wage growth distribution across the average-wage quartiles does, in fact, differ. In particular, the median wage growth for the lowest-paid workers is higher than the median for other types of workers. The median wage growth from 2016 to 2017 for the lowest quartile is 3.8 percent, 3.0 percent for the second quartile, and 3.2 percent for the third and fourth quartiles.

However, the pattern of relatively higher median wage growth for low-wage workers is not uniform over time. This difference is apparent in the following chart, which plots median wage growth over time for each average-wage quartile.

Macroblog - November 16, 2018 - chart 2: Median Wage Growth by Average-Wage Quartile

As the chart shows, median wage growth of low-wage workers (the green line, representing the first quartile) currently exceeds that of higher-wage workers, but it was below the median for higher-paid workers in the wake of the Great Recession. This pattern is consistent with the both the severity of the recession and what we have been hearing more recently about emerging shortages of low-skilled workers. It also appears that the median wage growth of the highest-paid workers (the blue line, representing the fourth quartile) slows by a bit less than that of other workers during downturns but is otherwise not much different than for workers in the middle of the wage distribution.

So, relative to the incorrect charts I had in the previous version of this post, there is no obvious wage growth polarization story here. The wages of low-wage workers are currently rising at a faster median rate than for other workers, and these other workers are experiencing broadly similar median wage growth.

November 16, 2018 in Employment, Labor Markets, Wage Growth | Permalink

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November 14, 2018


Polarization through the Prism of the Wage Growth Tracker

One of the most frequent questions we receive about the Atlanta Fed's Wage Growth Tracker (the median of year-over-year percent changes in individuals' hourly wage) is about the relationship between wage level and wage growth. For example, do high-wage earners also tend to experience greater wage growth?

An earlier macroblog post explored this question. Unfortunately, answering it is not as easy as it might appear. When looking at wage growth by wage level, whether you use the prior or current wage level as the reference point matters—a lot. If we looked at wage growth categorized by the prior year's wages, we would find higher median wage growth for low-wage earners than for high-wage earners. This is because some workers who earned low wages last year earn middle or high wages this year, and some of last year's high-wage workers earn middle or low wages this year. If we instead categorized people based on current-year wages, we would see exactly the opposite: lower median wage growth for low-wage workers than for high-wage workers.

One way to lessen this wage-level base effect is to categorize an individual's wage growth according to their average wage across the two years. The following chart shows this categorization for the 2016 to 2017 wage growth distribution of all workers in the Wage Growth Tracker data. In the chart, the first quartile (labeled <$13.8) depicts the lowest-paid 25 percent of workers based on their average 2016–17 hourly wage, and so on. The center line of the box for each quartile is the median of that group's wage growth distribution, and the lower and upper boundaries of the box are the 25th and 75th percentiles, respectively. The outer lines are the thresholds for outlier observations (see here for the calculation.)

The chart shows that the wage growth distribution across the average-wage quartiles does, in fact, differ. For example, the median wage growth from 2016 to 2017 for the lowest quartile is 3.9 percent, 1.6 percent for the second quartile, 1.9 percent for the third quartile, and 3.2 percent for the top quartile.

The pattern of higher median wage growth in the lower and upper quartiles, compared with the middle part of the wage distribution, is reasonably uniform over time.  However, there is a cyclical difference between the median wage growth of high- and low-wage earners. This difference is apparent in the following chart, which plots median wage growth over time for each average-wage quartile.

As the chart shows, median wage growth of low-wage workers (the green line, first quartile) currently exceeds that of high-wage workers (the blue line, fourth quartile), but it was below the median for high-wage workers in the wake of the Great Recession. This pattern is consistent with the both the severity of the recession and what we have been hearing more recently about emerging shortages of low-skilled workers. In contrast, median wage growth for workers in the middle of the wage distribution (the orange and purple lines) remains lower than for either high- or low-wage workers. Overall, these findings reinforce the idea of polarization, where the demand for workers has generally grown more in the tails of the skill/wage distribution than in the middle.

November 14, 2018 in Employment, Labor Markets, Wage Growth | Permalink

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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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