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March 06, 2019
X Factor: Hispanic Women Drive the Labor-Force Comeback
The share of the prime-age population engaged in the U.S. labor market is on the rise, led by a sharp rebound in the labor force participation (LFP) rate by prime-age female workers (those ages 25–54). This point was highlighted in a recent Wall Street Journal article.
Since 2015 the LFP rate for prime-age women has increased by about 1.8 percentage points, reversing an almost 16-year slide. Using the data underlying the Atlanta Fed’s new Labor Force Participation Dynamics tool, some of the factors behind this increase become apparent. Of particular note is that Hispanics (people of Cuban, Mexican, Puerto Rican, South or Central American, or other Spanish culture or origin regardless of race) account for a bit less than one-fifth of the prime-age female population, but they accounted for almost two-thirds of the increase in female LFP during the last three years. This increase was the result of both a rising share of the population that is Hispanic and the rising LFP rate among Hispanic women. The share of the prime-age, Latina population increased by 1 percentage point between 2015 and 2018, and the LFP rate for this group increased 3 percentage points. (The reason why rising Hispanic LFP didn’t result in the overall female LFP rate increasing by more than 1.8 percentage points is because Hispanic women are still 8 percentage points less likely to be in the labor force than non-Hispanic women. But this participation gap is closing rapidly.)
The Atlanta Fed’s web tool also allows us to further explore what is behind the 3 percentage point LFP rate increase for prime-age Latinas in the last three years. (My Atlanta Fed colleague Ellyn Terry provides a longer-term view on Hispanic female labor force dynamics in this related macroblog post.) It’s particularly noteworthy that almost two-thirds of the recent increase is the result of a decline in family or household responsibilities keeping people out of the labor force (see the chart).
This shift away from household duties is attributable to a combination of the shifting demographics of the Hispanic population (such as being more likely to have a college degree and thus obtaining a higher-wage job and being better able to afford child care) and a lower propensity to not participate for family reasons within Hispanic age and education groups.
The rebound in female LFP in the last three years is good news, with rising wages, particularly at the low end, and higher demand in traditionally female-dominated occupations contributing to the increase. But making the labor market a truly viable option for women still poses a number of challenges. The LFP rate of U.S. women has fallen behind that of many other countries, many of which have enacted family-friendly policies to help support women in the workplace.
February 14, 2019
Trends in Hispanic Labor Force Participation
Although the labor force participation (LFP) rate has fallen significantly for the overall population during the past two decades, the trends can differ a great deal depending on which demographic group you examine. One way to view these varied, ever-changing patterns is to use the Atlanta Fed's Labor Force Participation Dynamics tool. We recently redesigned the tool, adding a new interface and more options for understanding specific demographic groups' LFP. The tool also allows users to see what factors (such as disability/illness, being in school, retirement, or family responsibilities) influence changes in the LFP rate for different groups.
While the tool shows us many stories, a particularly interesting one is the experience of people of Cuban, Mexican, Puerto Rican, South or Central American, or other Spanish culture or origin regardless of race (henceforth referred to as Hispanic). Hispanics are a growing share of the U.S. population (the U.S. Bureau of Labor Statistics [BLS] projects that nearly a fifth of the people in the labor force will be Hispanic by 2024, up from a tenth in 1994), and therefore Hispanics' differences in attitudes and preferences for work will exert an increasingly great effect on headline LFP numbers.
Let's parse the LFP rate among Hispanics. First, the Hispanic population is more likely to engage in the labor force than non-Hispanics. (In 2017, the LFP rate of Hispanics was 66.1 percent, compared to 62.2 percent for non-Hispanics). Second, their LFP has fallen by less during the past two decades.
The pictures below come from the redesigned tool. The first two charts compare the decline in the LFP rate for all ethnicities (Chart 1) versus Hispanic (Chart 2) as the combination of six nonparticipation categories. Each colored bar represents how much a particular category of nonpartipation has changed since the fourth quarter of 1998. The red line shows the summation of the change in each nonparticipation category, or the net change in the LFP rate. For example, the LFP rate overall has declined 4.2 percentage points (ppts) during the past two decades. However, among Hispanics, it has fallen significantly less—just 1.0 ppt. A comparison of the size and direction of each of the nonparticipation categories between the two charts shows many differences in the factors affecting the decline in the LFP rate of each group.
Because differences across ethnicity could reflect differences in their age distributions—Hispanics are younger on average than the population as a whole—it is important to control for this difference. Using the tool, it's easy to narrow this comparison to look specifically at 26–55 year olds.
In particular, the LFP rate for women of all ethnicities from 26 to 55 years old has declined by 1.0 ppt since 1998. In sharp contrast, the LFP rate for Hispanic women 26 to 55 years old has actually increased by 3.8 ppts. Compared to 20 years ago, this group is less likely to say they don't want a job because of disability/illness (1.1 ppt) and family responsbilities (1.4 ppt). This group is also less likely to be part of the shadow labor force (1.4 ppt) compared to two decades ago. (The shadow labor force, as we define it, is made up of individuals who say they want a job but are not considered unemployed by the BLS.) This article from the BLS delves into more detail about Hispanics in the labor force.
The LFP tool allows you to explore many other labor force stories. Users can cut the LFP data by three education categories (less than a high school degree, high school or some college, or associate's degree or higher), two age groups (26–55 or all ages), three race/ethnicity categories (white non-Hispanic, black non-Hispanic, and Hispanic) and for men and women. One thing that the tool makes clear is that the factors that influence individual decisions to work, look for work, or to pursue other activities vary across demographic groups, and each group's experience contributes to our understanding of movements in the overall LFP rate.
January 11, 2019
Are Employers Focusing More on Staff Retention?
Many people are quitting their current job. According to data from the Job Openings, Layoffs, and Turnover Survey (JOLTS) from the U.S. Bureau of Labor Statistics, workers are voluntarily leaving their current workplace (for reasons other than retirement or internal company transfers) at rates not seen since the late 1990s.
A high rate of quits is consistent with a tightening labor market. In such a market, the promise of more pay elsewhere lures an increasing share of workers away from their current employer. The potential benefit of changing jobs is also evident in the Atlanta Fed's Wage Growth Tracker, which typically exhibits a positive differential between the median wage growth of people changing jobs versus those who don't.
However, this Wage Growth Tracker pattern has changed in recent months. Since mid-2018, the median wage growth of job stayers has risen sharply and is at the highest level since 2008. As the following chart shows, the gap between the wage growth of job switchers and stayers has narrowed.
Is it possible that this new pattern is just noise and will disappear in coming months? After all, the wage growth for job stayers has spiked before. But taken at face value, it suggests that the cost of losing staff (recruiting cost, cost of training new employees, productivity loss from having a less experienced workforce, etc.) might be forcing some employers to boost current employees' pay in an effort to retain staff. Interestingly, the pattern is most evident among prime-age workers in relatively high-skill professional occupations.
Firms are always focused on staff retention and employ various strategies to reduce turnover in key positions. One of those strategies—larger pay increases—might now be taking a more prominent role.
We will closely monitor the Tracker for further evidence on this emerging trend. However, that might be later rather than sooner because the source data is provided by the U.S. Census Bureau, which has cut most services because of the current lapse in congressional funding. But when information becomes available, we'll be ready to parse it—so stay tuned!
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.
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.
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.)
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.
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 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
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.
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.
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.
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.
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.
- X Factor: Hispanic Women Drive the Labor-Force Comeback
- Tariff Worries and U.S. Business Investment, Take Two
- Trends in Hispanic Labor Force Participation
- Quantitative Frightening?
- Are Employers Focusing More on Staff Retention?
- Defining Job Switchers in the Wage Growth Tracker
- Cryptocurrency and Central Bank E-Money
- Polarization through the Prism of the Wage Growth Tracker (Take Two)
- Polarization through the Prism of the Wage Growth Tracker
- On Maximizing Employment, a Case for Caution
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