Search results for: NILF

What a NILF!

@TBPInvictus here.

At some point in the not too distant past, we bid adieu to the quaint notion of taking government statistics at their face value. It may have begun with a site like ShadowStats, which purports to demonstrate that all manner of government releases are nowhere near what their true values are.

This, of course, includes inflation, which ShadowStats tells us runs considerably higher than the government lets on, which is hilarious given the fact that a subscription to ShadowStats costs the same $175 now that it did in September 2008. How does that work, exactly?

 

screen-shot-2016-11-16-at-5-31-30-pm

More recently, in the past year or two, it became fashionable to cite the BLS’ Not in Labor Force statistic as representative of how crappy the labor market has been under Obama. This number was recently prominently flogged by The Drudge Report, and I’ve seen it cited far and wide, including on a business television outlet (guess which one).

 

not-in-labor-force

It’s easy to see why the right would latch on to NILF. It’s a big and menacing number, that’s for sure. And to think so many people are not in the labor force simply has to mean that the economy’s in the crapper, right?

It’s certainly far more dramatic to say, “95 million people are not in the labor force” than it is to say, “The labor force participation rate has fallen to 62.8%.” Let’s be real about this: 95 million is a huge number on its face while 62.8% is a ratio, meaning there’s a numerator…and a denominator…and oh my god who can do all this math? (And, by the way, most of the decline in the LFPR can be attributed to our demographics.)

But what, exactly, is Not in Labor Force? What does it mean? Here’s what BLS tells us (emphasis mine):

The labor force is made up of the employed and the unemployed. The remainder—those who have no job and are not looking for one—are counted as not in the labor force. Many who are not in the labor force are going to school or are retired. Family responsibilities keep others out of the labor force. Since the mid-1990s, typically fewer than 1 in 10 people not in the labor force reported that they want a job.

screen-shot-2016-11-17-at-6-00-13-am

So, Not in Labor Force includes students, retirees, stay-at-home Moms and Dads, and many others. And the fact is that fewer than 10 percent of those categorized as Not in Labor Force even want a job!

But who can be bothered to research these things in this now fact-free world in which we live — the post-truth era — with fake news sites (this year-old story is a real dandy), Facebook, Twitter, and the like?

The sad and scary fact of the matter is that many ideologues (more on one side than the other, for sure) have figured out exactly how to stroke and feed Americans’ confirmation bias – to feed them narratives that comport with their existing beliefs or theories. Where 95 million not in the labor force = Obama sucks.

But here’s the most interesting question: Given that Obama’s been fudging the unemployment rate (~5.0%) and the jobs numbers (~200k/month), why in the world isn’t he fudging the labor force participation rate, the home ownership rate, and the not in the labor force numbers so he looks like a stud all the way around?

 

See also:

People who are not in the labor force: why aren’t they working?

More Thoughts on NILF

There was a surprising amount of pushback to yesterday’s column on the labor force participation rate. Some of the questions raised by emailers and Tweeters were interesting enough that I thought it might be worthy of a public response. (Note in today’s August non farm payroll report the labor force participation rate remained unchanged at 62.8 percent. Thus, we have no new evidence one way or another as to whether an end to the secular trend of falling participation rate is occurring).

I have been discussing NILF as an aspect of the labor pool for more than a decade (see this, this, this, this, this, this, this, this, this, and this). Whenever I try to cover a meaty subject in 600-700 words, something must be edited out; it is not my intention to make my Bloomberg columns the definitive word on the subject. Rather, I try to raise interesting points you may have not seen or thought of. Perhaps its best understood to place this column in context of that long continuum of prior columns, posts, tweets, etc.

In the case of Labor Force Participation Rate is a Tale of Two Genders, my main thesis was that huge societal forces have been driving two very different trends in those who have been entering or leaving the labor pool. Since the 1960s, the number of women entering the work force has skyrocketed, nearly doubling over half a century. Men, on the other hand, saw a decrease of over a fifth during that same time period.

These are astonishing numbers.

Now, about that pushback: Some of you raised an issue with my footnoted explanatory of how LFPR is calculated:

A quick primer on how the participation rate is calculated: Unemployment is a percentage, meaning it is actually a fraction. Total number of people in the labor pool divided by total number of employed equals employment rate. Subtract the percent employed from 100 to get the unemployment rate.

As a fraction, it looks something like this:

0D322944-F934-498C-A553-987690EAC95F

The BLS site explains the basic concept of Labor Force Participation in a fact sheet, and to be blunt, I don’t see much difference between the two explanations other than stylistically (as opposed to factually).

Next, there was some thoughtful pushback as to the two charts used as misleading:

“It was potentially misleading because he showed it on two different graphs with different scales, omitted the origin, etc. All my pet peeves for perception manipulation of data. So I got the data from FRED and graphed it myself.”

Anytime two charts have different scales you must be on guard for data manipulation, si this is a valid concern.

However, I reached a different conclusion than that assessment for several reasons: First, I thought that the “U.S. Bureau of Labor Statistics via Federal Reserve Bank of St. Louis” sourcing on each chart was sufficient for anyone else to find the data if they wanted; this was not a general interest column, it was a wonky dissection of an aspect of NFP. Most sophisticated readers interested in this sort of economic data know exactly what FRED is.

I tweeted the two links yesterday; however, it might have been helpful to include the links to the original data sources as a reference in the column under each chart.

That sourcing is:

Civilian Labor Force Participation Rate: Men (LNS11300001)

Civilian Labor Force Participation Rate: Women (LNS11300002)

Perhaps I can prevail upon the Bloomberg style guide to include those links in future usage of FRED data.

Next, the complaint was that the interactive charts posted used similar – but not identical – scales. I thought the scales were similar enough — about 30% and 20% — not to matter. I eyeballed the charts prepublication, and they did not leap out as misleading to me.

However, the suggestion was made to use a chart like this:

 

fred

 

I like this chart, but I thought the two we used told the tale much better.

If this was a News article, perhaps identical scales and an all in one chart would be preferred. But it’s an Opinion and Commentary piece, and I thought the two distinct charts told the story better than the single chart.

I have warned repeatedly of the dangers narratives present to investors, but this was not that sort of stock/market column where that bias impacted a final investment decision.1

Finally, as long as I am responding to emailers, I might as well answer the person who wrote “Way to go out on a limb!!!!!!” in response to my acknowledging that recent data might not mean anything (e.g., “Or it could just be ordinary noise in a volatile data series”)

Recognizing that a single noisy data point may not be all that is simply good analysis of a data series. Recall the weak NFP in May or the poor GDP in Q1. Those who made trade decisions based on these single data points likely made expensive mistakes.

My response is that I simply prefer not to make stuff up – especially the usual forecasts, expectations and “soft” predictions (“this or that could happen”).

It is a quirk of human psychology that people prefer to be told lies – they want confident and specific forecasts, not honest accurate ones that acknowledge the unknown and unknowable future. I’ve written enough columns about Cognitive Foibles and Human Psychology that I have learned people vastly prefer a false certainty from pseudo-gurus then honest admission that we simply do not know what the future holds.

That’s a wetware problem I seek to avoid. To those readers who wants to play the future forecasting or market prediction game, it is respectfully suggested you might look elsewhere for that sort of stuff. I find it worse than useless, it is truly misleading.

 

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  1.  If you feel like catching up with my past tirades on the failures of narratives, see thisthis, this, this,this, this, this, this, this, this, and this.

NILF: Drop in Participation Rate Bodes Well

For years I have been a regular reader of David Rosenberg’s. Back when he was Merrill Lynch’s chief economist, to more recently at Canada’s Gluskin Sheff, I have enjoyed his daily “Breakfast with Dave.”

Sometimes, it is because we disagree, and I am looking for an intelligent challenge my pre-existing notions. Other times, it is to see where Dave and I agree. And sometimes, as with his missive yesterday, it is simply to see something different and interesting.

The pair of charts here are what leaped out at me. The first shows Labor Force Participation Rate. It peaked in the late 1990s. Particpation has plummeted since. This usually gets trotted out to show how weak the job market is.

With masses of baby boomers retiring, some of that is a secular issue. But the acceleration during and after the Great Recession suggests that some of this is cyclical.

116944410

The NILF chart (Not in Labor Force) was the big surprise to me. The rise in the number of people leaving the labor force because they could not find work was deeply troubling. Those who believe the employment situation is bad and getting worse frequently point to this metric as proof.

That seems to be changing. Note the collapse in the number of people leaving the workforce who still want full time jobs:

116944518

Dave writes:

No wonder the Fed is now starting to focus back on the inflation part of its mandate. The unemployment rate is falling at a pace that would augur for an end to all the Fed intervention, but these policymakers want to remain aggressive and as such continue to shift the focus and the goal posts to fit their needs. The bottom line is that it is not going to be hard to see the unemployment rate at 6% by the end of next year — even with no change in the participation rate, all it would take is for +250k payroll gains per month (hey — we had nearly +200k in 2013 with sub-2% growth … imagine what we get with 3%+ growth next year!).

I am not quite as rosy as Rosie. I am unsure if we are going to see 3 percent gross domestic product growth next year, but I like his spin on labor force participation rate. The percentage of people who say they are dropping out of the labor pool because they cannot find a job is falling.

This is a positive economic development.

 

 

Originally published here

More on NiLF & the Unemployment Rate

We mentioned Labor Force Participation Rate over the weekend.  It is worth exploring a bit further.

Labor_force_particpation_rate

One of the lesser noted aspects of the NFP report Friday was the drop in the Labor Participation Rates. It is the percentage of the total population that is either working or potentially working. In the US, it is about ~170 million people, and excludes children, retirees, non-employed (work at home moms, etc.).     That Labor Pool measure peaked in 2000 at just under 67.4%. Following the market crash and recession, it subsequently fell about 1.5% to about 65.8%. This accounted in no small part for the falling Unemployment rate from 2001 – 05.

Now, a 1.5% or so drop doesn’t sound like a lot, but remember there
are 143 million workers in the US. That drop equals about 3 million
people. These are folks who are willing to take a full time job, have
been unable to find work, and have exhausted their unemploment
benefits.

The Labor pool drop appeared to have bottomed and reversed it self late 2005 (see chart above). The 5 year downtrend channel was broken, and  a new uptrend — higher highs and higher lows — was beginning.

Until recently.   

Augmented
It has since started heading lower again. They do not count in the "official" Unemployment Rate statistics. However, BLS actually does measure these folks in their "augmented unemployment rate" — the jobless people who aren’t counted among the officially unemployed. That measure is 7.4%.

There is a good definition of this here. The longer term chart below parallels the unemployment rate — but from higher levels.

Some people have asked if this 7.4% level is a good or a bad thing. That qualitiative description is less relevant to me than the quantitative cobnclusion that the 4.5% Unemployment Rate is very misleading.

David Altig at Macroblog thinks it is mostly due to secular changes, and I do not disagree. But for policy makers — such as the Federal Reserve — the belief that the labor market is very tight with no slack is clearly belied by the data.

The significance:  It may have an impact as to whether they have the room to cut rates or not.

The Return of NILF

Over the years, we have mentioned on more than one occasion the not-as-dirty-as-it-sounds measure, NILF. No, it has nothing to do with moms — rather, it stands for Not In Labor Force.

It is one of the reasons the official BLS unemployment rate is actually understating the actual unemployment rate.

A quick primer on how this works: The Unemployment rate is depicted as a percentage, and like all percentages, it is actually a fraction. You take the total number of people in the labor pool, the total number of workers:

Employed Individuals
_________________    =   Percent Employed 

Total Labor Pool

Subtract the percent employed from 100% and you get the unemployment rate.

Most of us think about the unemployment rate going down due to more people getting jobs. But there’s also another way the official unemployment rate can go down. It happens when the denominator — the bottom number of the fraction — goes down.

And that is what has been occurring again recently. The Labor Pool has shrunk, making the unemployment rate look better than it actually is.   

One of the confirming signs of this is the Temporary help. It declined in May (by almost 9K), indeed, it has been declining for the past six months. These are the first employes to be laid off, and it disputes the so-called tightness or lack of slack int he labor market.

Consider the following from Liscio Report, Philippa Dunne and Doug Henwood via Barron’s Alan Abelson:

"Moreover, the so-called household report, which
bulls used to gush over until the numbers went south, registered a job
gain of only 66,000, after a drop of 70,000 in April. And it also,
comment Philippa and Doug, "showed signs of slack developing in the
labor market."

There were other indications that far from being
tight, as the bulls on the economy contend, the labor market is
manifesting some troubling trends. Folks not officially in the labor
force but who’d love a job increased by 155,000 to the "highest level
since early 2006." That suggests the real unemployment rate is over 5%.
And thousands more toilers are working part-time because they can’t
latch on to full-time jobs."

Like so many other government stats, we remain quite skeptical that the 4.5% unemployment rate corresponds to reality.

>

Source:
Quickie Tour
ALAN ABELSON
UP AND DOWN WALL STREET 
Barron’s Monday, June 4, 2007
http://online.barrons.com/article/SB118015926416915717.html

Read it here first: NILFs, Women, and the declining Labor Force

In case you missed it, there was a front page NYT story on Women’s decreasing work force participation.

We have covered the issue of NILFs and decreasing labor force participation rates repeatedly over the past year.

Here’s a quick excerpt:

“For four decades, the number of women entering the workplace grew at a blistering pace, fostering a powerful cultural and economic transformation of American society. But since the mid-1990’s, the growth in the percentage of adult women working outside the home has stalled, even slipping somewhat in the last five years and leaving it at a rate well below that of men.

While the change has been under way for a while, it was initially viewed by many experts as simply a pause in the longer-term movement of women into the work force. But now, social scientists are engaged in a heated debate over whether the gender revolution at work may be over.

Is this shift evidence for the popular notion that many mothers are again deciding that they prefer to stay at home and take care of their children?

Maybe, but many researchers are coming to a different conclusion: women are not choosing to stay out of the labor force because of a change in attitudes, they say. Rather, the broad reconfiguration of women’s lives that allowed most of them to pursue jobs outside the home appears to be hitting some serious limits.

Nyt_work_graphic

I find it to be more economic than attitudinal in nature:

“To be sure, mothers’ overcrowded lives have not been the only factor limiting
their roles in the work force. The decline in participation rates for most
groups of women since the recession of 2001 at least partly reflects an overall
slowdown in hiring, which affected men and women roughly equally.

“The main reason for women’s declining labor-force participation rates over
the last four years was the weakness of the labor market,” said Heather Boushey,
an economist at the Center for Economic and Policy Research, a liberal research
institute in Washington. “Women did not opt out of the labor force because of
the kids.”

To be fair, the decline did begin “well before the economic slump a few
year ago.”

 

>

 

Source:
Stretched to Limit, Women Stall March to Work
EDUARDO PORTER
NYT, March 2, 2006
http://www.nytimes.com/2006/03/02/business/02work.html

Wages Accelerating

What Will Finally Lift Wages for Middle Earners
It’s not just the unemployment rate.
Bloomberg, February 28, 2018

 

 

Over the past few years, I have consistently argued that wages were on the verge of moving higher. Earlier this year, we looked at how increases in state and city minimum-wage laws were driving the wages of the lowest-paid decile of workers higher. Today, we are going to look at some of the factors driving the middle of the pay scale higher. At a later date, we can analyze what has been responsible for gains driving the top of the pay scale.

The current economic environment — with increased hiring but without much wage growth — has been developing since the great financial crisis ended. We continue to read stories anecdotally about pockets of wage gains in certain industries or areas. (Look at what rising competition is doing for forklift drivers’ hourly wages, in Bloomberg Businessweek.)

But to understand what might happen with wages over the next 12 to 24 months, we need to consider the full spectrum of employment data. To get a richer sense of the state of the labor market, let’s review five data points.

Unemployment rate: The gradual recovery since 2010 has led to a tight labor market, as unemployment fell from 10 percent to 4.1 percent. If the unemployment rate chart were a stock trend, every investor would want to be short it.

Under normal circumstances, 4.1 percent would be full employment. However, these are not normal circumstances. Recoveries after a credit crisis are different from the normal cyclical recession recoveries (see e.g., this and this). Those differences manifest themselves in many ways, including delayed retirement and (I suspect) increased number of former workers on disability.

Labor-force-participation rate: The civilian labor-force-participation rate peaked in the 1990s, and has been falling steadily ever since.

There are many factors that have been driving this lower, including demographics. The gender differential is noteworthy: For men, labor-force participation began moving steadily lower right after World War II around 1948; for women, it peaks around 1999, started drifting lower and then really took a leg down after the financial crisis.

After that crisis, many frustrated workers decided to leave the labor force rather than accept a significantly lower-paying job. These folks are not retired or on disability, but simply become NILFs (“not in labor force”). There have been recent signs that they are coming back into the labor pool.

Quits rate: This technically measures the rate at which people leave one place of employment for another. What the quits rate really measures is employee confidence. It includes their expectations of getting a better-paying job, or finding employment with better benefits or working conditions. Individually, it is their subjective reflection of the state of the economy, a self-assessment of how scarce and therefore valuable their skills and experience might be. Collectively, it is an overall confidence measure.

After bottoming in May 2009 at 1.3 percent, the quits rate has gradually improved, and now sits at 2.2 percent.

Job openings and labor turnover: This is the availability of unfilled jobs in the economy. About 90 percent of the openings are private companies, while about 10 percent are government (of which a little more than three-quarters are state and local).

As the economy has recovered, this data series has steadily improved: It bottomed at 2.2 million positions in July 2009, up to the most recent reading in December 2017 of 5.8 million openings. That is a lot of jobs that have not yet been filled.

Job-openings-to-unemployment ratio: This is the big one: We take the number of unemployed people — the folks without jobs but who want one — and compare it with the total number of job openings. (You can play with the data at FRED or BLS.) What this creates is the job-openings-to-unemployment ratio, which is quite revealing about the overall state of the labor market — with big implications for wages, especially in middle- and upper-middle-income employment.

As the crisis came to an end in July 2009, there were 6.6 people looking for work for each available job opening. Competition for jobs was fierce. Employers did not need to compete on wages, benefits, working environment, 401(k) match, stock options, etc. With employees just happy to have a job — any job — there was little upward pressure on wages.

Over the ensuing years, more workers found work and businesses created more new jobs — but not in equal numbers. Although both sides of this ratio saw improvement, they did so at differing rates. Today, there is but 1.1 unemployed person looking for a job for each opening.

This changes the dynamics between employers and new hires. In fact, skilled employee scarcity changes the power so much so that companies have to raise the salaries associated with open positions just to get tenable candidates to apply.

While globalization and technology have kept a cap on wage gains for at least three decades, we might be on the verge of a significant improvement. So long as an imbalance exists between the number of new job openings relative to the number of people looking for work, wages are likely to begin and continue to rise.

We will find out next week whether wage gains are accelerating, when we get a clean Employment Situation report unaffected by hurricanes or seasonal disturbances.

 

Originally: What Will Finally Lift Wages for Middle Earners

 

Employed workers leaving the labor force: an analysis of recent trends

This article looks at the large increase in the number of people who moved from employed to not in the labor force during the 2013–14 to 2015–16 period, both overall and for workers ages 25–54. Although some of this increase can be attributed to the business cycle, there has been a greater flow from employment to retirement or to schooling than at the peak of the previous business cycle. Demographic changes explain relatively little of the increase, especially for the 25–54 age group. This movement may reflect long-term changes in the labor market.

The labor force participation rate—the percentage of the population that is either employed or unemployed (that is, either working or actively seeking work)—has been declining in recent years, from a peak of 67.3 percent in early 2000 to an average of 62.8 percent in 2016.1 Most of this decline is associated with the Great Recession and its aftermath, as the rate was still 66.0 percent as of 2008. A large part of the decline in labor force participation is due to the aging of the population, as the proportion ages 65 and older increased from about 16 percent in 2008–09 to about 19 percent in December 2016. However, even within the 25–54 age group, the participation rate declined from about 83 percent in 2008 to below 81 percent in 2014–15; the rate had recovered somewhat to 81.5 percent as of December 2016. The decline in the labor force participation rate has given rise to concerns that the postrecession decline in the unemployment rate to below 5 percent may overstate the health of the labor market.2

Changes in labor force participation can be analyzed by looking at trends in entering and exiting the labor force. While month-to-month changes in the proportion of the population participating in the labor force are fairly small, each month millions of people enter and exit the labor force, as well as moving into or out of employment or unemployment. The U.S. Bureau of Labor Statistics (BLS) reports estimates of the number of people changing their labor force status from one month to the next.3

This article concentrates on exits from the labor force—in particular, trends in labor force exit by the employed. While trends in exits from the labor force for the unemployed may be explained principally by the business cycle, trends in exits from employment are not as clearly influenced by the business cycle and may suggest longer term changes in the desirability of work. Within the article, we sometimes show employment as E, unemployment as U, not in the labor force as NILF, flows from employed to NILF as EN, and flows from unemployed to NILF as UN.

Labor force entrances and exits

Before turning to labor force exits, we begin by looking briefly at trends in labor force entrances, which are also important in determining labor force participation. Figure 1 shows labor force entrance flows as a percentage of the population from 2004 to the present. The figure shows the sum of flows from not in the labor force to employment and from not in the labor force to unemployment. Entrances as a proportion of the population declined heading into the 2007–2009 recession, climbed in the immediate aftermath, but have decreased in recent years. Figure 2 shows entrance rates as a percentage of people who were NILF the previous month instead of as a percentage of the population; these entrance rates show a much more marked decline in recent years because people who are NILF are an increasing proportion of the population. One should note that the proportion of NILF ages 55 and older has increased over the period from a 12-month average of 53.3 percent in 2004 to 56.8 percent in 2016; this increase would typically depress labor force entrance rates.

We now turn our attention to labor force exits. Figure 3 shows 12-month moving averages of exits from the labor force, along with its components. The graph shows flows from unemployed to NILF and employed to NILF as a percentage of the population, as well as the total percentage of the population that exited the labor force. The general pattern is for overall exits from the labor force to show less variation over time than the UN and EN components. As a percentage of the population, UN flows increase during recessions but EN flows decline. During the last recession, overall exits from the labor force increased; such exits gradually declined during the recovery. UN flows increased from 2008 to 2010 and then declined. However, the pattern for UN flows is counteracted by an opposite pattern for EN flows: EN flows declined at first, were more or less stable for several years, and increased over the last few years. The increase in EN flows for 2015 is comparatively large and of sufficient magnitude to completely counteract the large decline in UN flows so that total exits stopped decreasing in 2015 before resuming their decline in 2016.

Trends in transitions from employed to not in labor force

The 2015–16 increase in EN flows as a percentage of the population is particularly striking because the employment–population ratio had not recovered to prerecession levels. The ratio went from 62.9 percent in January 2008 to 58.2 percent in June 2011 and only recovered to 59.7 percent by the end of 2016. Figure 4 shows EN flows as a percentage of the previous month’s employment rather than as a percentage of the population. This graph shows that the series, which began in 1990, increased to a high in 2015 before declining somewhat in 2016. The magnitude of the increase is substantial. If EN flows as a percentage of the employed had remained at the levels of the previous cyclical peak of 2005–07 during 2015–16, with no changes in other flows, the employment–population ratio and labor force participation rate would both have been about 2 percentage points higher by the end of 2016.

The flows shown in figures 1 through 4 are from the official BLS flows series, which are adjusted so that total flows correspond to the change in levels for each labor force state each month.4 These flows are only available at the aggregate level, not for specific subcategories of labor force states or for specific demographic groups aside from men and women. In what follows, flows that were not adjusted to match labor market levels were used so that we can look at data for various demographic groups. While unadjusted EN flows are higher on average than adjusted ones, the correlation between EN flows as a percentage of the previous month’s employment is 0.98, so it seems reasonable to use the unadjusted series without being concerned that its properties are different from the adjusted series.

The NILF category is divided into three subcategories: retired, disabled, and other. In addition, respondents who are less than 50 years old or who state that they are not retired are asked, “What best describes your situation at this time? For example, are you disabled, ill, in school, taking care of house or family, or something else?” Trends in EN flows are divided into selected components in figures 5 and 6 (for ages 16 and older) and figures 7 and 8 (for ages 25 to 54) from 2004 through early 2016. For respondents in the “NILF-other” category, we examine the three most common answers to this question: “in school,” “taking care of house or family,” and “other.”

Figures 5 and 6 show that within EN flows for ages 16 and older, the “other” category and its largest subcomponents—housekeeping and school—exhibit a pronounced cyclical pattern, with levels in 2015–16 roughly equal to those before the recession. Overall flows are higher in 2015–16 because of upward trends in exits to retired and, to some extent, to disabled and “other-other.” For EN flows for ages 25–54 (figures 7 and 8), exits to retired and disabled are not as prominent as exits to housekeeping and school. In this age group, most components show some upward trend over the period, especially exits to school.

Can the increase in EN flows be explained?

Can we explain the increase over time in EN flows? I examined five possible factors: (1) the age and gender composition of the employed, (2) workers’ full-time or part-time status, (3) the percentage of workers who are self-employed, (4) the percentage of workers who are married, and (5) the composition of educational attainment among the employed. I examined changes in the composition of the workforce and whether increases in EN flows were associated with particular groups.

The age composition of the labor force has obvious implications for the probability of labor force exit: older workers are more likely to retire or become disabled, while younger workers are more likely to exit for schooling or because of family responsibilities, leaving middle-aged workers as the most stable group. The data confirm that the other variables are also associated with the likelihood of exiting employment to NILF. Part-time status and self-employment are associated with a higher probability of exit, whereas marriage and higher levels of education are associated with lower probability.

Table 1 shows how the composition of the employed has changed between the three sets of years 2005–07, 2013–14, and 2015–16, with respect to the characteristics mentioned in the last paragraph. In addition, table 1 shows EN flows as a percentage of the previous month’s employment for subgroups with these characteristics. The years 2005–07 were chosen as the period leading to the peak of the previous business cycle, while 2013–14 was chosen to determine whether the current dramatic increase in EN flows was associated with particular groups. Comparing 2015–16 with the other two sets of reference years, we see that EN flows increased for most groups shown in the table, so the increase is not associated with just one group. Changes in the composition of the labor force over the relatively brief period from 2013–14 to 2015–16 have (not surprisingly) been small, so I instead discuss the trends over the longer period from 2005–07 to 2015–16.

Changes in the age composition of the labor force and in marital status over the approximately decade-long period would be expected to increase EN flows. The proportion of the employed who were ages 55 and over during this period rose substantially, from 17.6 percent to 23.2 percent, and the proportion ages 25 to 54 registered a corresponding decline. Because the older group consistently exits the labor force at greater than twice the rate of workers ages 25 to 54, the aging of the population would be expected to increase the EN flow rate. With regard to marital status, the percentage of workers who were married with spouse present decreased over the period from 57.4 percent to 54.3 percent. As EN flows for married workers are smaller than for unmarried workers, the decline in the proportion of workers who are married would also be expected to increase EN flows.

However, changes in other characteristics imply that EN flows should have decreased. The percentage working part time for noneconomic reasons declined over the 2005-to-2016 period; workers in this category exited the labor force at a rate of over 8 percent in each of the three subperiods in table 1, compared with rates close to 2 percent for full-time workers and 4–5 percent for workers employed part-time for economic reasons. Self-employment, which is also associated with a high rate of labor force withdrawal, declined over the period. Higher levels of education are associated with lower rates of labor force exit. The educational attainment of workers increased over the period; in particular, the percentage of workers with a bachelor’s degree or higher increased from 30.5 percent to 36.3 percent.

When all of these characteristics are combined, to what extent does the changing composition of the labor force account for the increase in EN flows? To answer this question, I used data from 2005–07 and regressed a 0–1 variable for EN flows on these characteristics; I used a cubic in age and otherwise used indicator variables for the categories shown in table 1. (For purposes of the regression, age is topcoded at 80 years.5) All variables are interacted with an indicator for female, so that I am in essence running separate regressions for men and women. The sample comprises all the employed who are present in both a given month’s and the previous month’s Current Population Survey sample. I run separate regressions for each calendar month, pooling the sample across the years 2005–07. I then use the coefficients from these regressions to predict 2015–16 EN flows. These predicted flows show how EN flows would have changed if employed people with given characteristics had left the labor force at the same rate as in 2005–07 and if the change in the overall rate of withdrawal were solely due to changes in the composition of the employed. I average results over the 12 calendar months.

Table 2 shows that the changing composition of the labor force accounts for only 18 percent of the increase in EN flows from 2005–07 to 2015–16. This small amount is predominantly due to the countervailing effects of age and education. The aging of the labor force would be expected to increase EN flows by 0.12 percentage point per month, about two-thirds of the increase observed over the period. However, the increase in workers’ education levels would be expected to decrease EN flows by 0.09 percentage point, largely negating the effect of the increase in age. Other variables have only small effects, and the effects of changes in part-time status and the gender composition of the workforce are not statistically significant.

For workers ages 25 to 54, results for an analogous regression are shown in the bottom panel of table 2. Rather than predicting the substantial increases that occurred, the regression predicts small decreases in EN flows because of changes in labor force composition. If we use the 2005–07 coefficients, changes in education levels between 2005–07 and 2015–16 by themselves would imply a (statistically significant) reduction in EN flows of 0.07 percentage point per month. The effect of the other variables mitigates the reduction in flows to 0.04 percentage point, though out of these variables only the effects of the change in the percent married and percent self-employed are statistically significant.6

Conclusion

In summary, we have observed a large increase in the number of people who transition from employed to not in the labor force over the last 2 years, both overall and for workers ages 25–54. To some extent, this increase can be attributed to a cyclical recovery consistent with a pattern we see in earlier business cycles. However, EN flows have increased beyond levels seen at similar points in previous business cycles. For workers ages 16 and over, retirement makes up a large portion of the increase, while for workers ages 25–54, many categories―especially exits to schooling―contribute to the increase.

I have been unable to identify why the increase in EN flows has occurred. The aging of the population would be expected to increase labor force exits, but the increase in the education level of the labor force would be expected to decrease it. For workers ages 25–54, increases in education would similarly be predicted to lead to a decrease in exits (with little effect caused by aging within this group) instead of resulting in the substantial increase we observe. This increase may point to longer term changes in the desirability of work. This explanation is consistent with the analysis by Federal Reserve researchers that persistent declines in participation for some demographic groups are not cyclical but “appear to have their roots in longer run changes in the labor market.”7

Notes

1 For a discussion of this trend, see Steven F. Hipple, “Labor force participation: what has happened since the peak?” Monthly Labor Review, September 2016, https://doi.org/10.21916/mlr.2016.43.

2 For example, see Patricia Cohen, “Slower growth in jobs report may give Fed pause on interest rates,” New York Times, September 2, 2016, https://www.nytimes.com/2016/09/03/business/economy/jobs-report-hiring-unemployment-wages-fed-interest-rates.html?_r=0: “Jonas Prising, chairman and chief executive of theManpowerGroup, one of the largest recruiters in the United States, agreed that low participation rates were troubling, despite the improving labor market. ‘It may look like full employment,’ he said, ‘but it’s not full employment.’ ”

3 Estimates and links to a fuller explanation of the methods employed in generating the published series are available at https://www.bls.gov/cps/cps_flows.htm.

4 See Harley J. Frazis, Martha A. Duff, Thomas D. Evans, and Edwin L. Robison, “Estimating gross flows consistent with stocks in the Current Population Survey,” Monthly Labor Review, September 2005.

5 Regressions using dummy variables for individual years of age give very similar results.

6 One can argue that the negative association between education and employment exit is more of a reflection of differences in people who acquire different amounts of education than of a causal effect of education itself. In that case, the changing composition of education groups as education increases might cause exit rates to increase for each education group without causing an increase in exit rates as a whole. In response to this argument, I ran regressions similar to those underlying the text but excluding education. The results still indicate a substantial unexplained component to the increase in EN flows—over one-third of the increase for EN flows for workers ages 16 and over and almost 80 percent for workers ages 25–54.

7 See Stephanie Aaronson, Tomaz Cajner, Bruce Fallick, Felix Galbis-Reig, Christopher Smith, and William Wascher, “Labor force participation: recent developments and future prospects,” Brookings Papers on Economic Activity, Fall 2014, pp. 197–255. Note that their data predate the jump in EN flows considered here.

Source: Monthly Labor Review

Labor Force Participation Rate is a Tale of Two Genders

Labor Force Participation Rate: Men (Percent, Seasonally Adjusted)
fredgraph LNS11300001
Source: Fred

 

 

Many observers will be focused on tomorrow’s jobs numbers as they wonder aloud if, when or even how much the Federal Reserve will raise interest rates. My own best guess is that short of another blowout number — 250,000 or more jobs added — the Fed will likely wait until December, if only to avoid any appearance of trying to tilt the election.

Tomorrow, I will be looking specifically at the labor force participation rate. It has seen some modest recovery from the lows of last year in recent months, and that could be a sign of the end of a secular cycle. Or it could just be ordinary noise in a volatile data series.

Over the years, I have written about an interesting aspect of the employment data: what I call NILF (I’m typing carefully here), or not in the labor force. It describes those workers who have dropped out of the labor pool.

The impact of people leaving the labor force tends to lower the official unemployment rate. When the denominator is smaller and the numerator remains unchanged, all else being equal, the outcome is a higher percentage of employed and a lower percentage of unemployed.

This isn’t necessarily a sign of economic health. No wonder certain politicians love to focus on this data point as proof that the U.S. is on the wrong track.

Why leave the labor force? It’s more than mere economics — demographics play a large role, along with wages, technology and globalization. It could be that the type of work you do no longer exists, and it isn’t worth taking a much lower-paying job. Much of the time, people leave the labor force for things like going back to school, having kids, retiring or going on disability. And, of course, mortality is constantly taking people out of the labor market.

But there is an unusual confluence of forces at this particular moment that makes tomorrow’s nonfarm payroll number more interesting than usual. So let’s take a closer look at the number I find most interesting.

The labor force participation rate since World War II tells a muddled tale. For sure, cultural changes are reflected in its rise and fall. However, the total rate obscures the full story. To unpack some of the details, we must break the rate into two parts: men and women in the workforce.

A good conceptual starting point is Rosie the Riveter: Women went to work in great numbers during World War II, including in traditional male jobs such as heavy manufacturing. Perhaps that helped change views on women in the workplace. But it wasn’t until the 1960s that women began entering the work force in great enough numbers to raise their participation rate. You can surely credit the rise of feminism and improved contraception as factors, but there are no doubt many others.

As the chart below shows, participation rates for women in the early 1950s were less than 35 percent. But beginning in the mid-1950s, it climbed, passing 40 percent by 1966, 50 percent by 1978 and more than 55 percent by 1986. Participation rates for women plateaued at 60 percent in the late 1990s and since fallen slightly to a little less than 57 percent.

 

Big Gains, Then Blah
Labor force participation rate of women, age 16 and older
big-gains-then-blah
Source: U.S. Bureau of Labor Statistics via Federal Reserve Bank of St. Louis

 

Men’s participation rate tells a very different story, as you can see from the next chart. It is noteworthy that since it peaked in 1949 at 87 percent, the labor force participation rate for men has been falling ever since. Keep this chart in mind when you hear pundits talk about angry male voters. The forces behind this have been building for a long, long time.

 

What Gives, Guys?
Labor force participation rate of men, age 16 and older
what-gives-guys
Source: U.S. Bureau of Labor Statistics via Federal Reserve Bank of St. Louis

 

There have been five notable periods when the rate of men leaving the labor force has accelerated. Each time was marked by a significant recession. The rate today for men hovers at about 69 percent, a 70-year low, and only some 12 percentage points higher than women.

Which leads to one observation: Maybe we’re getting closer to some kind of economic and social parity between the sexes. That range, or maybe somewhere in the middle, reflects a form of workplace gender balance. Is this narrowing difference reaching its end point? Does the male-female participation gap reflect anything other than women leaving the work force to have children? I have not seen hard data on that, but perhaps fresh numbers might help us determine what has driven the trends of gender participation rates.

One final observation: It looks like women’s participation rates have found equilibrium. Let’s hope that the same can be said of men.

 

________

1. A quick primer on how the participation rate is calculated: Unemployment is a percentage, meaning it is actually a fraction. Total number of people in the labor pool divided by total number of employed equals employment rate. Subtract the percent employed from 100 to get the unemployment rate.

 

Originally:  A Job-Market Tale in Two Charts

 

 

Tweets of the Week 5.9.14

Markets and Investing

Consensus on interest rates has been all wrong

Fill in the blank

Strong profit growth for wirehouses

Guess which one we did? (The dumb one . . . )

Clash of the Financial Pundits, now on sale

Economy

Interesting divergence

This is a good thing:

Eejits!

Magic

NILF:

Random Items

Hardly at all

Convenience versus Quality

Me likey!

Go NASA

Cool idea