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Policy Hub: Macroblog provides concise commentary and analysis on economic topics including monetary policy, macroeconomic developments, inflation, labor economics, and financial issues for a broad audience.

Authors for Policy Hub: Macroblog are Dave Altig, John Robertson, and other Atlanta Fed economists and researchers.

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December 4, 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.

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 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.

October 1, 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.