Category Archives: Labor

The Unemployment Rate, the Growth in Employment, and Productivity

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A.  Introduction

The January jobs report (more properly the “Employment Situation” report) released by the Bureau of Labor Statistics (BLS) on February 3, was extraordinarily – and surprisingly – strong.  The unemployment rate fell to 3.4% – the lowest it has been since May 1969 more than a half-century ago.  And despite the low unemployment rate, the number of “new jobs created” (also a misnomer – it is actually the net increase in non-farm payroll employment) was a surprising 517,000.  But it was not only this.  The regular annual revisions undertaken each January to reflect revised population controls and weights for the employment estimates led this year to significantly higher labor force and employment estimates.  With the new industry weights, the increase in the estimated number of those employed in 2022 (the number of `”new jobs”) rose to 4.8 million.  The earlier estimate had been 4.5 million.

All this is an extraordinarily strong jobs report.  However, one should not go too far.  It is important to understand what lies behind these estimates, as well as some of the implications.  For example, strong growth in the total number employed while GDP growth is more modest implies that productivity (GDP per person employed) went down.  That could be a concern, except that when viewed in the context of the last several years we will see that productivity growth has in fact been rather good.

This post will first examine the new figures on unemployment and then on employment growth.  We will then look at the change in productivity – both in the recent past and from a longer-term perspective.

B.  The Unemployment Rate and Its (Non)-Impact on Inflation

The unemployment rate in January fell to 3.4%.  This is the lowest it has been since May 1969.  And if it falls a notch further to 3.3% in some upcoming month, it will have fallen to the lowest since 1953.

A 3.4% unemployment rate is certainly low.  But what is more significant is that the unemployment rate has been almost as low for most of the past year.  It fell to just 3.6% in March 2022, and until last month varied within the narrow range of 3.5 to 3.7% – hitting the 3.5% rate several times.  It is now at 3.4%, but what is most significant is that it has been at 3.7% or less for almost a year.

One needs to recognize that the unemployment rate is derived from a survey of a sample of households (implemented by the Census Bureau) called the Current Population Survey (CPS).  The CPS sample includes approximately 60,000 households each month, in a rotating panel, and from this they derive estimates on the labor force participation rate, the unemployment rate, and much more.  It complements the Current Employment Statistics (CES) survey, which covers a much larger sample of 122,000 businesses and government agencies representing 666,000 individual worksites (with each employing many workers).  Hence employment figures are generally taken from the CES as there will be less statistical noise.  But the employers surveyed for the CES cannot know how many workers are unemployed (they will only know how many workers are employed by them), so the smaller CPS needs to be used for that.  (A brief explanation of the CPS and CES is provided by the BLS as a “Technical Note” included in each of the monthly Employment Situation reports.)

Due to the size of the sample, the estimated unemployment rate is actually only known within an error limit of +/- 0.2 percentage points, using a 90% confidence interval.  That is, simply due to the statistical noise a change in the unemployment rate of 0.1 percentage point from one month to the next should not be considered statistically significant, and 10% of the time even a 0.2 percentage point change may have just been a consequence of the statistical variation.  However, repeated observations over several months in a row of an unemployment rate at some level will be a measurement one can have much more confidence in.  That can no longer be a consequence of simply statistical noise.  Thus one should not place too much weight on the January change in the unemployment rate to 3.4% from 3.5% the month before.  But the fact that the unemployment rate has consistently been within the relatively narrow – and extremely low – range of 3.4 to 3.7% since March 2022 is highly significant.

An unemployment rate anywhere close to a range of 3.4 to 3.7% is also far below the rate at which economists used to believe would be possible without the rate of inflation accelerating – i.e. without inflation going higher and higher.  This was given the acronym name of “NAIRU” (for Non-Accelerating Inflation Rate of Unemployment).  It was held that at an unemployment rate of less than the NAIRU rate, the rate of inflation would rise from whatever pace it was at to something higher.  This was viewed as unsustainable, and hence the proper goal of economic policy was, in this view, to manage macro conditions so that the unemployment rate would never fall below the NAIRU rate.  That rate was also sometimes called the “full employment rate of unemployment”.

The question then is what the NAIRU rate might be.  While different economists came up with different estimates, estimates generally fell within the range of 5 to 6%.  An unemployment rate of less than this would then (under this theory) lead to a rise in inflation.

But that did not happen.  The unemployment rate fell to below 5% in 2016, and inflation remained low.  It fell to below 4% in 2018 and inflation remained low.  It fell to 3.5% in 2019 and into early 2020 and inflation remained low.

With the once again very strong labor market – with unemployment hitting 3.4% – has this now changed?  The rate of inflation did rise in 2021 and into 2022.  But if one looks at this chart, one sees that the timing is wrong:  Inflation rose earlier – in 2021 – when the unemployment rate was still well over 6% early in the year.  Furthermore, nominal wages only rose later:

Inflation (measured here by the consumer price index – the CPI – for all goods and services) can be volatile, but the upward trend began already in the second half of 2020 (although in part this was initially due to a recovery in prices from depressed levels earlier in 2020 due to the Covid crisis).  The chart shows the rates in terms of 3-month rolling averages (at annual equivalent rates and in arrears, so the figure for a January, say, would be for the months of November through January).  The pace of change in nominal wages (also as 3-month rolling averages and at annual rates) did not start to rise until mid-2021.  The increase in nominal wages appears to be more in response to the prior increase in prices – as firms found it profitable to employ more workers in an economy that grew strongly in 2021 – rather than a cause of those higher prices.  This is consistent with the view that the inflation was primarily due to demand-pull, rather than cost-push, factors.

[Technical Note:  The figures on changes in the nominal wage come from data assembled by the Federal Reserve Bank of Atlanta, drawing on data that can be obtained in the underlying micro-data files of the CPS.  The rotating panel of households in the CPS are interviewed for four months, not interviewed for the next eight months, and then interviewed again for four months.  New households are added each month and then removed after month 16 for them.  This allows the researchers to match individuals with their reported wages to what they had earned 12 months before.  It also allows them to examine the wage changes broken down by individual characteristics – such as age, gender, race, education level, occupation, where they are in the income distribution, and more – as these are all recorded in the CPS.  It is all very interesting, and worth visiting their website where they make it easy to see the impact on the measured changes in wages of many of these different factors.

The matching of wage changes by individuals also provides a much more reliable index than the commonly cited changes in average wages provided in the monthly Employment Situation report.  The latter comes from what employers report in the CES survey on the average wages they are paying.  Those averages will be affected by compositional effects.  For example, the reported average wages will often jump at the start of an economic downturn – such as it did in 2020 – as the less experienced and lower-wage workers are generally laid off first.  This leaves a greater share of more highly paid workers, which will lead the reported average wage to rise even though the economy had entered into a downturn.]

Not only did the rise in inflation precede the more modest increase in the pace at which nominal wages rose, but since mid-2022 the rate of inflation has come down while the job market has, if anything, become tighter.  The unemployment rate, as noted above, has been in the 3.4 to 3.7% range since March 2022, and is now at 3.4%.  Despite this, the three-month average increase in the seasonally adjusted CPI fell from 11.0% (at an annual rate) in the three months ending in June 2022, to just 1.8% in the three months ending in December.  If a tight labor market was driving inflation, one would have expected inflation to have kept going up rather than fall – and certainly not to fall by such a degree.

Furthermore, growth in nominal wages fell slightly from a peak of over 6.7% in the three months ending in June and also July 2022 (at an annual rate), to 6.1% as of December.  One would have expected the pace of change in wages to have continued to go up, rather than start to ease.

It is still early to be definitive on any of this.  Trends could change again.  Importantly, a significant part of the sharp fall in inflation in the second half of 2022 (when measured by the full CPI) was due to a fall in the prices of oil and other energy products.  However, while more recent, there are also early indications that core inflation (where food and energy prices are left out) is also falling.  In terms of the core CPI (again the seasonally adjusted index), the pace of inflation fell from a peak of 7.9% (at an annual rate) in the three months ending in June 2022, to just 3.1% in the three months ending in December.

That measure of inflation – the core CPI, which is often taken to be a better measure of underlying inflationary trends than the overall CPI as food and energy prices are volatile and go down as well as up – is now falling despite unemployment at the lowest rate it has been in more than a half-century.  If a tight labor market was driving inflation, then one would expect the pace of inflation to be rising, not falling.

C.  Employment Growth

The January jobs report was also noteworthy for its figures on employment growth.  Nonfarm payroll employment rose by 517,000 – far higher than most expected.  It is not that an increase in employment of a half million in a month is unprecedented.  It is rather that there was such an increase even though the unemployment rate was already at an extremely low 3.5% in the prior month.  (And while nonfarm payroll employment excludes those working in agriculture, that number is now small at only 1.4% of the labor force – based on estimates from the CPS and including those in agriculture who are self-employed.  It also excludes the self-employed outside of agriculture – a more substantial 5.6% of the labor force according to the CPS – but still not that large.  In terms of changes in the numbers from one period to the next, the impact on the employment estimates will be small.)

In addition, the January report also reflected revisions – undertaken every January – where new weights are used to generalize from what is found in the sample in the CES of firms and other entities (such as government agencies) that employ workers to what is estimated for the economy as a whole.  The re-weighting is based on a comprehensive count of payroll jobs in March of the year, with this then used to revise the estimates for all of the year (2022 in this case).

Due to the new weights, the increase in the number of jobs in the economy rose from the earlier estimate of 4.5 million in 2022 (i.e. from December 2021 to December 2022) to 4.8 million.  Between January 2022 and January 2023 the increase was an estimated 5.0 million additional jobs.  That is, between January 2022 and January 2023, the number employed increased by an average of 414,000 per month.

The 4.8 million growth in the number employed in 2022 was remarkable not only because it is a big number, but also because it came after the even stronger growth in employment in 2021.  Employment grew by 7.3 million in 2021.  In absolute terms, the 4.8 million figure in 2022 is higher than that of any year (other than 2021) in the statistics going back to when they started to be collected in the present form in 1939 (using BLS data).  Such a comparison is more than a bit unfair, of course, as the US economy has been growing and there are far more people employed now than decades ago.  But taking 2021 and 2022 together, the percentage growth over the two years – at 8.5% – was exceeded since 1951 only by greater increases in 1977-78 (10.2%), in 1965-66 (9.7%), and in 1964-65 (8.7% – that is, there was strong growth in the three straight years of 1964, 1965, and 1966).  Joe Biden was right when he said job growth in the first two years of his presidency (of 12.1 million) was greater than that of any other president, but it is not really a fair comparison as the economy is now larger.  But even in percentage terms, his record is excellent.

But such growth in the number employed cannot continue much longer.  To put this in perspective, the total adult population in the US (as reflected in the CPS, and with the new population controls) rose by only 1.8 million between January 2022 and January 2023, or 150,000 per month on average.  And the labor force figure, as estimated in the CPS, grew by only 1.3 million over that period, or 111,000 per month.  One cannot keep adding 414,000 per month to the number employed (as we saw in the year to January 2022) when the labor force is only growing by 111,000 per month, when the unemployment rate is already at a historical low of 3.4%.

[Note that one cannot simply subtract the January 2022 figures reported from the new January 2023 figures, since in the CPS they do not go back and revise the previous year figures to reflect the new population controls.  But they do show what the impact would have been on the December 2022 figures, and I assumed that they would have had the same impact on the January 2023 numbers.  The impacts should be similar.  One can then do the subtractions on a consistent basis.]

An increase in the number employed of an estimated 414,000 per month when the labor force was growing by only an estimated 111,000 per month was possible in 2022 in part because the unemployment rate came down (from 4.0% in January 2022 to 3.4% in January 2023), and in part because the labor force participation rate went up slightly (from 62.2% in January 2022 to 62.4% in January 2023).

But also a factor is that these are surveys from two different sources (households for the CPS and firms and other employers for the CES), and the sample estimates will not always be fully consistent with each other.  As was discussed in an earlier post on this blog, the estimates can differ from each other sometimes for significant periods of time.  However and importantly, over the long term the two estimates will eventually have to approach each other.  The population estimates used for the CPS will yield (for a given labor force participation rate) figures on the labor force, and hence growth in the adult population will yield figures on growth in the labor force.  For a given unemployment rate, the number employed – within the bounds of the statistical estimates – cannot grow faster than this.

With the unemployment rate now at 3.4%, one should not expect much if any further fall.  Indeed, the general expectation (and the more or less openly stated hope of the Fed) is that it will start to rise.  It is possible that the labor force participation rate will rise, but changes in this are generally pretty slow, driven mostly by demographics and social factors (the share of people aging into the normal age of retirement; the share of the young entering into the labor force given their decisions on whether and for how long to enroll in colleges and universities; decisions by households on whether one or both spouses will work; and similarly).

While there will be uncertainty in what will happen to the unemployment rate and the labor force participation rate, for given levels of each of these, employment cannot grow any faster than the labor force does.  (Indeed it is slightly less:  At an unemployment rate of 3.4%, employment will only grow at 96.6% of what the labor force grows by.)  With the labor force growing by 111,000 per month in the year ending in January 2023 (with this already reflecting a small increase in the labor force participation rate from 62.2% to 62.4%), it will not be possible for the monthly increase in employment to grow by much more than this.

Looking forward, one should not, therefore, expect growth in the number employed to be sustained at a level that is anywhere close to the 517,000 we had in January.  There will be month to month fluctuations, but one should not expect an average increase over several months that would be much in excess of the 111,000 figure for the growth in the labor force seen in the year ending in January 2023.

D.  Productivity

Politicians like strong job growth.  It is indeed popular.  But the flip side of this is that while the number employed grew rapidly in 2021 (by 3.2% December to December), GDP growth was less (1.0% from the fourth quarter of 2021 to the fourth quarter of 2022, based on the most recent estimates).  With the number employed growing faster than GDP, the mathematical consequence is that GDP per person employed went down.  That is:  Productivity fell in the year.

Higher productivity is ultimately what allows for higher living standards.  Falling productivity would thus be a problem.  However, in the context of the last several years, productivity growth has in fact been pretty good:

We are once again seeing the consequences of the highly unusual circumstances surrounding the Covid crisis.  With the onset of a downturn, firms will lay off workers.  But they may often lay off more workers than their output falls.  This might be because of uncertainty on how much the demand for whatever they make will fall in the downturn (and they will wish to be careful and if anything to overcompensate, given the difficulty of obtaining finance in a downturn and the very real possibility of bankruptcy); or because special government programs during the downturn reduce the cost to them and their workers of these layoffs (for example through the common response of extending unemployment benefits and making them more generous); or because the first workers being laid off are the least productive ones (possibly because they are relatively new and do not yet have as much experience as others working there) so that they end up with a workforce which is on average more productive.  Or, and very likely, it could be a combination of all three factors.  It looks very much like Schumpeter’s “creative destruction”.

The consequence is that productivity can in fact jump up in a downturn.  One sees such a clear jump in the chart in 2020, at the time of the sharp collapse due to the Covid crisis.  One also sees it in 2008-09, with the financial and economic collapse in the last year of the Bush administration and then the turnaround that began in mid-2009.  In terms of the numbers:  Real GDP fell by 1.3% between the first quarter of 2020 and the third quarter of 2020 (in absolute terms – not annualized).  But employment over this period fell by 7.4%.  As a result, productivity (real GDP per person employed) jumped by 6.6% in this half year.  In 2008/2009, real GDP was basically flat between the last quarter of 2008 and the last quarter of 2009 – rising by just 0.1%  But employment over this period fell by 4.1%, leading to an increase in productivity of 4.4%.

Following these brief periods where businesses are scrambling to survive the downturn by producing more (or perhaps not too much less) with many fewer workers, firms then enter into a more normal period where, as the economy recovers, they are able to sell more of their product.  They hire additional workers who are, by definition, less experienced in the work of that firm than their existing workforce.  The new workers might also be less capable or have a less applicable skill mix.  Productivity may then level off or even go down.  The latter situation is in particular likely when the economy recovers quickly and firms scramble to keep up with the increased demand for their product.

The latter fits well with what we saw in 2021.  GDP in 2021 rose by 5.9%, the highest of any year since 1984.  And the Personal Consumption component of GDP rose by 8.3% in 2021, the highest of any year since 1946.  This was spurred by the series of Covid relief packages passed in 2020 (under Trump) and in 2021 (under Biden), which totaled $5.7 trillion in the two years, or 12.8% of GDP of 2020 and 2021 together.  Personal savings rose to an unprecedented level as a share of GDP (other than during World War II, with data that go back to 1929), which then supported the strong growth in personal consumption in 2021.  This is consistent with a demand-led inflation that got underway in late 2020 or early 2021 (discussed above) – a risk of inflation that Larry Summers had warned of in early February 2021 when Biden’s $1.9 trillion Covid package was first proposed (and eventually passed, largely as proposed).

But what matters to long-term living standards is not so much the changes in average productivity in the periods surrounding economic downturns, but rather the trends in productivity growth over time.  A ten-year moving average is a useful metric:

The chart shows rolling ten-year averages starting from 1947/57 through to 2012/22 of the growth in GDP, in employment, and in productivity (GDP per person employed).  Productivity growth was relatively high at about 2% per annum in the 1950s and through most of the 1960s.  But it then started to fall in the 1970s to less than 1% a year before recovering and returning to about 2% a year in the ten-year period ending in 2004.  It then fell to roughly 0.8% a year since about 2017 (in terms of the ten-year averages), with some sharp fluctuations around that rate associated with the 2020 Covid crisis.  As of the end of 2022, the most recent ten-year average growth rate for productivity was 0.80%.

This has important implications for GDP growth might be going forward.  The labor force grew by 0.8% in 2022 (the adult population grew by 0.7%).  With unemployment close to a record low, employment will not be able to grow faster than the labor force – as discussed above.  And the labor force cannot grow faster than the adult population unless labor force participation rates increase.  But while there major disruptions in labor force participation in 2020 and 2021 surrounding the Covid crisis – with its lockdowns, economic collapse and then recovery, as well as health concerns affecting many – labor force participation largely returned to previous patterns in 2022.  Labor force participation rates have been slowly trending downwards since the late 1990s, and while it is possible this pattern might be reversed, it is difficult to see why it would.  There might well be short-term fluctuations for a period of a few years, but longer-term patterns are driven mostly by demographics (the age structure of the population) and social customs (e.g. whether women decide to enter into the paid labor force).

What follows from this is that if the labor force continues to grow at 0.8% a year (as it did in 2022 – and it grew only at a lower rate of 0.6% a year in the ten-year period ending in 2022), and productivity grows at 0.8% a year (as it did in the ten-year period ending in 2022), then GDP can at most grow at 1.6% a year on average.  This would be disappointing to many.  While there certainly can be and will be significant year to year variation around such a trend, faster growth would require either higher productivity growth or more entering into the labor force.

E.  Summary and Conclusion

The January jobs report was strong.  The unemployment rate is now at the lowest it has been in more than a half-century, and the number employed grew by more than a half million – a very high figure when the unemployment rate is so low.  While these are still preliminary figures and are subject to change as additional data become available, they present a picture of an extremely strong labor market.

The fall in the unemployment rate by one notch to 3.4% from the previous 3.5% should not, in itself, be taken too seriously.  That is well within the normal statistical error for this figure.  But what is indeed significant is that the unemployment rate has been within the narrow range of just 3.4 to 3.7% since March 2022.  That is low.  And it was in this low range during a period (in the second half of 2022) when inflation was coming down.  While changes in the price of oil have been a major factor in driving the inflation rate in 2022, the core rate of inflation (which excludes energy prices as well as those for food) has also started to come down.  The rate of change in nominal wages did start to grow in mid-2021, but this appears more to be a consequence of the rising prices rather than a cause of them.  And there has been a slight reduction in the pace of change in wages in recent months.

One does not see in this any evidence that a tight labor market with extremely low unemployment (the lowest in more than a half-century), has led to higher inflation.  The opposite has happened.  Inflation has come down at precisely the time the labor market has been the tightest.

GDP grew rapidly in 2021, but then slowed to a more modest 1.0% rate in 2022 (from fourth quarter to fourth quarter).  Coupled with rapid employment growth in the year, productivity (as measured by GDP per employed person) fell.  However, this appears more to be a continued reaction to changes surrounding the disruptions resulting from the 2020 Covid crisis.  During that crisis, GDP fell but employment fell by much more, leading to a jump in productivity despite the downturn.  As the economy recovered and the situation normalized, workers were hired to bring workforces back to desired levels.  Viewed in a longer timeframe, productivity growth has been similar to what it has now been since the mid-2010s.

That productivity growth is not especially high.  It was 0.8% at an annual rate in the most recent ten-year average.  Coupled with a labor force that grew at 0.8% in 2022, and going forward might grow by even less (it grew at 0.6% a year in the ten-year period ending in 2022), the ceiling on GDP growth would be 1.6% a year, or less.  That is not high, but expectations need to adjust.

That is also a ceiling on what GDP growth might be.  Many expect that there very well could be a recession either later in 2023 or in 2024.  Much will depend on whether the government will be able to respond appropriately if the economy appears to be heading into a downturn.  But with Republicans now in control of the House of Representatives, and threatening to force the US Treasury into default on the nation’s public debt if their demands for drastic spending cuts are not met, one cannot be optimistic that the government will be allowed to respond appropriately.

The Great Resignation Has Been Greatly Exaggerated

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I would like to acknowledge and thank Mr. Steve Hipple, Economist at the Bureau of Labor Statistics, for his generous assistance in assembling the data used in this post from the public-use micro data files of the Current Population Survey.  This post would not have been possible without his help.

A.  Introduction

There has been much discussion in recent months about workers resigning from their jobs at record high levels.  This has often been attributed to workers reassessing their lives and deciding their jobs are simply not worth it.  A new name has even been coined for this:  the “Great Resignation”.

But while resignations have indeed been high, two quite distinct matters have often been confounded.  One is workers resigning from a position in order to move to a new, more attractive and usually higher-paying, position with a different employer.  The other is workers resigning from a position with no intention to take a new job, but rather to leave the labor force and do something else.  The former reflects a reshuffling in the economy, with workers moving to positions where they will likely be better paid and more productive.  This should raise the overall productivity of the economy.  The latter (those leaving the labor force) would reduce the overall capacity of the economy, if significant.  But as we will see below, while quits from jobs in order to move to a new job is, indeed, at record high levels, the number quitting in order to drop out of the labor force is at this point quite modest, and likely also to prove temporary.  While the Covid pandemic led to a major shock in the labor market, previous trends in labor market participation rates are reasserting themselves.

This post will look at the data on each of these two issues – both important but also both quite different.  It will start with the figures on turnover in the labor market, and present these figures in the context of the net number of new jobs being created.  Quits are high, but hiring is also at record highs.  Workers are quitting their jobs largely to switch to more attractive jobs.

While far more modest, some workers have, however, left the labor market.  The second part of this post will look at the reasons given by those not in the labor force for why they are not, and how this has changed from before the pandemic hit.  This is based on original data assembled from the public use micro data files of the Current Population Survey (CPS).  While publicly accessible by scholars and researchers, these figures are not presented in the regular monthly reports of the Bureau of Labor Statistics on the CPS.  This data will hopefully serve to better inform the discussion on what has been termed by some as the “Great Resignation”.

We will see that the changes in the number of US adults deciding whether or not to participate in the labor force are now modest compared to pre-pandemic trends, and are mostly accounted for by older workers deciding to retire earlier than what would have been expected, on average, under previous patterns.  But to the extent some worker decides to retire now, a year or two earlier than when they had earlier planned, there will then be one less worker retiring a year or two from now.  That is, there will not be a long-term impact, and one should expect to see a return to previous trends.  And so far, that is precisely what we have been seeing.

B.  Quits, Job Openings, and Net New Jobs

The number of workers quitting their jobs each month has indeed risen – and to the highest levels of at least two decades (the data do not go back further).  But the number of workers being hired each month to fill open positions has also increased – to even higher levels.  And despite the record pace of hiring, the number of open jobs employers are seeking to fill has grown to especially high levels.

The figures are shown in this chart:

The data come from the Job Openings and Labor Turnover Surveys (JOLTS) of the Bureau of Labor Statistics (BLS), a monthly survey of employers (although with reports that lag one month compared to the more closely watched monthly BLS report titled “The Employment Situation”, with its figures on such estimates as the unemployment rate and on the net number of new jobs in the economy).  The JOLTS surveys are relatively recent, with data going back only to December 2000, in contrast to the CPS, which goes back to 1948.  The chart here is shown in terms of the absolute number of workers or jobs in each group.

[Side Note: One might sometimes see a chart similar to this but shown in terms of rates:  Hires and Quits shown as a percentage share of the number employed, and Job Openings as a percentage share of the number employed plus the number of job openings.  However, for the relatively short period here (21 years) the patterns in the two presentations look very much the same,]

The number of “Hires” are the number of workers added to the payroll in the given month, according to this survey of employers.  Employers are also asked how many workers left the payroll (“Total Separations”) and whether they were workers who left voluntarily (“Quits”), were laid off or discharged involuntarily (“Layoffs & Discharges”), or left for some other reason (“Other Separations”).  The BLS includes in the Other Separations category those who left to go into retirement, or due to a new disability, or due to deaths.  Hence quits are only one reason for workers leaving their jobs, although its share has been growing:  Layoffs & Discharges have been falling, while the number in the “Other Separations” category has been flat and relatively low. (These latter two categories were not included in the chart to reduce the clutter.)

Hires and the various categories of separations are all flows, measured by the BLS over the course of a full month (and then seasonally adjusted, which among other effects will compensate for the different number of days in different months).  The “Job Openings” estimate, in contrast, is a stock, reporting the number of open job positions the employer is actively seeking to fill as of the last business day of each month.  Its scale on the chart therefore should not be taken as directly comparable to the number of Hires or Quits on the chart, which are flows over the course of a one-month period.  While they happen to be similar in number, one could have reported the number of Hires or Quits over, say, a two-month period (in which case they would have been about twice as much).  One needs to remember that stocks and flows are different.

As the chart shows, open jobs that employers are seeking to fill (“Job Openings”) have grown sharply over the last year.  While the monthly rate of hires has also grown – to record levels – the hiring could not keep up.  And with more workers being hired and actively recruited to fill the open job positions, it should not be at all surprising that the number of workers quitting their old jobs to take a new job – a job that is more attractive to them that probably also pays more –  has also been increasing.  Thus there are resignations, but not to leave the labor force.  Rather, workers are resigning to switch to a new, more attractive, job.

Such “churn” in the labor market is a good thing.  Not only are workers moving to what is for them a more attractive (and likely higher-paying) job, but the productivity of the economy as a whole will also go up as a result.  Employers are able to pay more to attract the workers to these jobs because the workers hired into those jobs will likely be producing more than they had in their old jobs.

How do we know that the quits were largely in order to move to a new job?  It is clear from the magnitudes.  The number of quits in the JOLTS data from March 2020 through February 2022 totaled over 85 million over the two-year period.  And this does not even include those quitting in order to retire (they are included in the “other” category in JOLTS).  Yet as will be discussed in the next section below, the labor force in February 2022 totaled only about 2.7 million less as of February 2022 than what would have been the case had the pre-pandemic shares of participation in the labor force continued.  And close to three-quarters of that 2.7 million reduction was due to workers entering into retirement at somewhat greater rates than was the pattern before.  This is nowhere close to the 85 million quits over the period.

One can also compare the monthly averages for the labor turnover figures with the net figures for new jobs:

The chart shows the average monthly figures for 2021, all from the BLS (either from JOLTS or the CPS).  January figures are excluded as the BLS changes each January the population controls it receives from the Census Bureau for its CPS figures, without revising earlier estimates.  This can lead to an abrupt one-month change in January, making it not comparable to the changes found in other months.

The first three columns show the average monthly growth in 2021 in the adult population (117,000), in the labor force (192,000), and in the number of net new jobs (547,000).  Over the long term, the labor force cannot grow faster than the adult population, but it did in 2021 as the labor force participation rate rose in 2021 following the turmoil of 2020.  And the net number of new jobs could grow faster in 2021 than the increase in the labor force as the number of unemployed fell rapidly in this first year of the Biden administration.  But the economy is now at full employment, and unemployment will not be able to fall much further.  Thus over the longer-term one cannot expect the net number of new jobs to grow faster than the increase in the labor force, and one cannot expect the labor force to grow faster than the adult population (and indeed normally by substantially less, as not all adults choose to be part of the labor force).

In contrast to the figures seen in the first three columns, the average monthly number of workers hired is far higher.  So is the number of separations, and it is the relatively small difference between the number of workers hired into positions and those separated from them for whatever reason that equals the number of net new jobs in the economy.  The separations in 2021 mostly came from quits (70% of the total), with smaller numbers from layoffs or discharges and from the “other” category (where, as noted before, the BLS includes those choosing to quit due to retirement).

All this is consistent with a very strong labor market.  Workers are indeed resigning, but this is largely due to the opportunity to move to a more attractive, better paying, open job.  As we will discuss in the next section, relatively few are resigning to leave the labor force altogether.

C.  The Extent to Which the Labor Force Fell, and the Factors Behind It

As of February 2022, there were 592,000 fewer US residents in the labor force (in the seasonally adjusted figures) than there were in February 2020, just before the lockdowns due to Covid began.  This is not much:  Just 0.4% of the labor force.  But it is not a fair comparison.  The adult population grew over those two years, and thus one would expect that in normal circumstances, the labor force would also have grown.  The question is by how much.  For this one needs to construct some counter-factual scenario of what the labor force would have been (in normal circumstances) and compare that to what it in fact was (given the consequences of Covid) to see how much of a change there was.  Is there evidence here for a “Great Resignation”, of people leaving the labor force in high numbers?

A simple and reasonable counterfactual would be to assume the labor force (in a breakdown by individual groups based on gender and age) would have grown in the absence of the crisis at the same rate as their population.  Population growth is determined by long-term demographics.  That is, in this scenario it is assumed that the rates at which those in the individual demographic groups chose to be part of the labor force (the labor force participation rate) would have remained the same as what they were in February 2020.  Similarly, the rates of those choosing not to be part of the labor force would be the same as in February 2020 (it will simply be one minus the labor force participation rates), and similarly for the reasons given for not participating in the labor force (e.g. retirement, home or family care, full-time students, disability, and so on).  One can then compare changes in the labor force and in the numbers not in the labor force (by the reasons given for this), under a scenario where the participation rates in February 2022 were the same as they were in February 2020, to what they actually were in February 2022.

The households surveyed in the monthly CPS are asked, when they respond that they are not employed and have not been actively seeking a job, the major reason for why they are not in the labor force.  However, the BLS monthly report on the findings of that month’s CPS survey does not report these reasons.  The monthly report is already pretty long.  However, one can obtain these results from the CPS public-use micro data files on the CPS.  The results reported here come from those files (and were assembled by Mr. Steve Hipple of the BLS for this post).

The basic results for the whole population, and for men and all women separately, are summarized in this chart:

Had the participation rates remained the same as in February 2020, there would have been an extra almost 2.7 million workers in the labor force in February 2022.  The labor force would have been 1.6% higher than what it was.  While significant, I would not see this as qualifying as a “Great Resignation”.

[Technical note:  The calculations for those in the labor force and those not in the labor force (by reason) were worked out first for the most basic groups examined:  men and women, each in three different age groups of ages 16 to 24, 25 to 54, and 55 and above, for a total of six groups.  The aggregations for all men or all women, for both men and women in each age group, and for everyone together, were then calculated by summing over the relevant groups.]

Almost three-quarters of the 2.7 million reduction (2.0 million, or 73% of the total) reflected a higher share of adults choosing to retire.  This is consistent with the story that with the disruption in the last two years, coupled also with significant income supplements being provided to most households through the various Covid relief measures passed by Congress during the administrations of both Trump and Biden, a significant number of workers decided to retire earlier than they had previously planned.  It might be a year or two earlier, or possibly longer.  The implications of this are important, as it implies that the changes in the labor force will be temporary rather than permanent.  One more person retiring now, earlier than they had previously planned, means there will be one less person retiring at whatever that future date was to have been.

The second most important reason for leaving the labor force was to take care of home or family, with this accounting for 582,000 workers – 22% of the total reduction in the labor force in the scenario being examined.  This is also understandable in the context of the Covid crisis.  Many workers had to leave the labor force during the midst of the crisis to take care of school-age children when the schools were closed, but almost all schools are now once again open (albeit with some occasional disruption due to Covid outbreaks).  There might also have been a need to take care of family members who became sick during the crisis with Covid itself, and that might still have been a factor in February 2022 (as the Omicron wave subsided).  To the extent this has been Covid driven, these effects should also prove to be temporary as the Covid crisis recedes.

There are, in addition, a list of other possible reasons given in the CPS survey for not participating in the labor force (such as full-time studies as a student, disability, illness, and a catch-all “other” category).  In the aggregate the difference these made in the scenario being examined was small:  only 138,000 – or only 5% of the total reduction in the labor force in this scenario.

In terms of the gender breakdown, more women than men left the labor force in the given scenario (1.7 million women vs. 1.0 million men) even though the share of the labor force made up of women (47% in 2022) is less than the share made up of men (53%).  The shares of this due to more entering retirement or for taking care of home or family are broadly similar between men and women, which is perhaps surprising.  Indeed, the share reporting that they are not in the labor force due to home or family care was somewhat higher for men (25.2% of their total) than for women (19.4%), but it is not clear whether such differences should be considered significant.  The underlying data comes from surveys, there will be statistical noise, and these figures are all based on changes between what the February 2022 levels were and what they would have been in a scenario where we assume the February 2020 participation patterns had remained.

The figures broken down by age group were:

The largest single cause leading to lower participation in the labor force (in the scenario where prior patterns would have remained) was an increase in the share of retirees among those aged 55 and above.  This accounted for 1.5 million workers, which was 3.9% of adults in this age group.  Surprisingly (at least to me) was that there was essentially no difference in this age group of those who were not in the labor force due to home or family care.

Among prime-age workers (ages 25 to 54) there were roughly similar shares among those no longer in the labor force who gave as their reason retirement or for home or family care.  The total number no longer in the labor force (relative to the scenario being examined) was also relatively small for this 25 to 54 age group, at just 0.9% of the population in the age group.  The share no longer in the labor force in the group aged 55 and above was substantially higher, at 3.1% of the population of that age group.  This is as one would expect when the primary factor behind those leaving the labor force was early retirement.

The share of the youngest age group (ages 16 to 24) no longer in the labor force fell by 2.6%, but primarily here for reasons lumped into the “all other” category.  The largest single factor here was full-time studies, but this accounted for just 144,000 of the 414,000 (about 35%) in this “all other” category.  One should also note that while there is a small number in the “retired” category (19,000), this is probably just a reflection of the fact this is a survey.  Respondents do not always fully understand the nature of the questions or may have been in some unusual circumstance that does not fit in well with any of the listed possible responses.

Graphically, how much of a difference has it made?  Not much.  In terms of the labor force participation rates, one has for men and for women, as well as overall:

And by age group, as well as overall:

The “X” on each category shows where the labor force participation rates would be had the February 2020 rates (for the underlying groups of men or women by each age group) continued to hold.  There was certainly a large shock to the system at the start of the pandemic, with the lockdowns that suddenly became necessary in March 2020.  There was then a partial bounceback, followed by a leveling off but with a continued but slow recovery to the earlier patterns of participation rates.  While still not fully back to what they were, the difference is now relatively modest.

This return to previous patterns in the participation rates is likely also to continue.  With the single most important factor (almost three-quarters of the total) being people retiring earlier than what they had planned (or to be more precise, earlier than in the observed pattern in prior years, before the pandemic), the labor force numbers should be expected to return to their previous path in a few years.  As noted before, if some worker retires a year or two earlier than they had earlier planned, then there will be one less retirement in a year or two (as that worker is already retired).  This is consistent with the observed slow return to previous labor force participation rates.

D.  Conclusion

The number of workers quitting their jobs has been high.  But the quits are not a reflection of workers dropping out of the labor force.  Rather, quits have been high as workers quit one job to move to another job – more attractive and likely better paying.  Hires have also been exceptionally high.  And despite the high rate of hiring, employers could not keep up and the number of open jobs they have been seeking to fill has grown.  While some workers have left the labor force during the disruptions of the Covid pandemic, about three-quarters of this (as of February 2022) stemmed from a somewhat higher share of workers choosing to retire.  But unless there has been a permanent change in retirement patterns (and there is no indication that there has been), decisions during the pandemic to retire earlier than previously planned will be self-correcting.

The high level of quits reflects, rather, an extremely strong labor market.  Indeed, the number of net new jobs created in 2021, the first year of the Biden administration, came to 6.7 million – the highest in any one year in US history.  (To be fair one should also note that the fall in the number of jobs in the US in 2020, the last year of the Trump administration, was also the highest in US history.  Thus the Biden record was made possible by the low starting point.)  With this strong labor market, workers have more of an opportunity to move to jobs that can make better use of their talents.  And they have taken advantage of this opportunity, which will be a boost both to the workers and to productivity in the economy as a whole.

The November Jobs Report Was Actually Quite Solid: One Should Not Expect More Going Forward

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A.  Introduction

The Bureau of Labor Statistics (BLS) released its regular monthly “Employment Situation” report, for November 2021, on Friday, December 3.  The report is always eagerly awaited.  It provides estimates for the net number of new jobs created in the most recent month, as well as figures on the unemployment rate, certain wage measures, and much else.

The initial reaction to the report by the media was negative.  Net job growth, estimated at 210,000 in the month, was viewed as disappointing.  This was down from 546,000 net new jobs in October, and was well below Wall Street expectations (based on a survey of Wall Street firms by Dow Jones) that the figure for November would come to 573,000.  While it was noted that the unemployment rate also fell – to just 4.2% – the negative reaction contributed to a significant decline in the stock market that day, with the S&P 500 index, for example, down by over 2% at one point.

But the November jobs report was actually pretty solid.  In this post, we will look at what was reported and some factors to take into account when examining such figures.

B.  Monthly Job Gains in 2021

The chart at the top of this post shows the current BLS estimates of monthly net job growth this year, starting in February to cover the period of Biden’s presidency  The estimates are based on a survey of establishments by the BLS, that asks (along with much else) the number of employees on their payroll as of the middle week of each month.  Hence the January numbers would have been for before Biden’s January 20 inauguration.  The news reports following the release by the BLS of the November jobs report were often accompanied by charts such as this one, with the November figure showing a substantial reduction in the number of net new jobs compared to what was seen in earlier months.  The question of interest is whether this was significant.

A number of factors should be taken into account.  One is simply that there is substantial month to month variation, as seen in the chart.  This may be in part due to fluctuations in the economy, but may also be due to idiosyncratic factors (such as how the weather was in the week of the survey) and to statistical noise.  The figures are based on surveys, and surveys are never perfect.  Examined in context, the change in the November figure from the prior month is similar to the changes seen in other months this year.  Indeed, it was less than in several.

There will, however, always be limitations with any single estimate, and in part for this reason the BLS provides in its published document a few different estimates for employment growth. The measure shown in the chart at the top is rightly considered the best one.  It is based on a monthly survey (called the Current Employment Statistics, or CES, survey) of business and other establishments (including government entities as well as non-profits such as universities and hospitals) – whoever employs workers.  The sample size is huge:  144,000 different businesses and government entities, at almost 700,000 different worksites.   The BLS indicates this “sample” covers approximately one-third of all such jobs in the US.

The numbers are specifically for nonfarm payroll jobs, and hence exclude those employed on farms (which is now small in the US – about 1.4% of workers based on figures from other surveys) and more importantly the self-employed (about 6% of the labor force).  Given the large sample size, and also recognizing that those in the sample include not only small firms but also large entities employing thousands of workers, statistical noise is limited.  However, even with such a large sample size, the BLS states that the 90% confidence interval on the month to month changes in employment is +/- 110,000.  At the more commonly accepted 95% confidence interval it would be wider.

Finally, the figures for the prior two months in each report are preliminary and subject to change as more complete data comes in.  The November report, for example, indicated the estimate of net new jobs in October had been revised up by 15,000, and for September by 67,000.  And the October report last month indicated that its earlier estimate for September had been revised up by 118,000.  That is, the initial estimate for September had been 194,000 net new jobs, but this was revised up a month later to 312,000 net new jobs, and then revised again in the estimates published this month to 379,000.  Such revisions are routine, and one should expect that the initial estimate for November of 210,000 net new jobs will likely be revised in the coming months as more complete data becomes available.  While the revisions can in principle be positive or negative, in an expanding job market (as now) they are likely to be positive.  

The figures in the chart are also seasonally adjusted.  This is done via standard algorithms that estimate the normal annual pattern of employment changes in any given month based on historical data.  Employment growth is normally higher in certain months of the year (such as June, following the end of the school year) and normally lower in other months (such as January).  Analysts will therefore usually focus on the seasonally adjusted figures to see whether certain trends are developing outside of the normal seasonal fluctuations.

This is indeed appropriate.  However, it is also worth recognizing that due to Covid, with the resulting lockdowns, opening-ups, quite prudent changes in consumer behavior due to the health risks from Covid-19 even with all the protective measures taken that can be taken, and the truly historic fiscal relief measures provided through the government budget to support households in the light of all these disruptions, seasonal patterns this year (and last) are likely to be not at all similar to what they have been historically.  It is therefore of interest also to look at the underlying employment estimates, before the seasonal adjustment algorithms are run, to see what those numbers might be saying.

The next section will look at this, along with other measures of the change in employment.

C.  Alternative Measures, and Long-Term Limits on What Employment Growth Could Be

As noted, the BLS makes available in its monthly Employment Situation report several measures of how employment is estimated to have changed in the month, in addition to the one discussed above.  These additional measures should not be seen as better measures (at least in normal circumstances) than the seasonally adjusted measure based on the findings from the huge CES survey of establishments.  Rather, it is best to see them as supplementary measures, or alternative measures, that together help us understand what may be going on in terms of employment. There is always uncertainty in any individual measure, as they are all estimates.  It is better to look at several, to see what the overall story might be.

The estimated change in employment in November (or, more precisely, the change in nonfarm payroll), based on figures from the CES survey of establishments, was 210,000 after seasonal adjustment.  But three alternative estimates for employment growth in November were far higher, as depicted in this chart:

In the CES estimate before the normal seasonal adjustment, the growth in net new jobs in November was 778,000.  This difference between the seasonally adjusted and non-seasonally adjusted figures is substantially greater than what one has normally seen for November.  Seasonal adjustment is complicated, but a simple average of the difference between the seasonally adjusted figures for November and the non-seasonally adjusted figures over the 20 years from 2000 to 2019, is 205,000.  But in November 2021 it was 568,000, suggesting something unusual.  If the November 2021 increase in the number of jobs was adjusted by 205,000 rather than the 568,000 estimated by the algorithms, then the “seasonally adjusted” change in the number of jobs would have been 573,000 (= 778,000 – 205,000).  This is exactly what the pre-release expectation was on Wall Street (as noted at the start of this post).  That it was exactly the same as the Wall Street forecast is just a coincidence, but the fact it was close at all might be significant.  It may be suggesting that the standard seasonal adjustment calculations, built from patterns historically seen for the month, might not have captured well the circumstances in this highly unusual year.

Quite separately, the BLS also has an employment measure from the monthly survey of households conducted by the US Census Bureau (with BLS input on what is asked), called the Current Population Survey (CPS).  This survey of a sample of 60,000 households is used by the BLS to determine how many are in the labor force (i.e. are working or are looking for work), whether they are employed (including self-employed and on farms), and thus the number unemployed (those in the labor force but not employed).  The BLS uses this to determine the unemployment rate, but to get to that they have to first estimate, based on this survey, how many are employed.

The November estimates based on the CPS of net new employment were 1,136,000 for the seasonally adjusted figure and 831,000 for the figure before seasonal adjustment.  Why the seasonal adjustment led to a reduction in the job growth estimate from the CPS while it led to an increase in the job growth estimate from the CES is not clear (seasonal adjustment is complicated), but in any case, both figures are relatively close to the 778,000 estimate from the CES estimate before seasonal adjustment.  And all three are all well above the 210,000 seasonally adjusted estimate from the CES that we normally focus on.  Together they suggest that the 210,000 estimate, while usually the most reliable one, might in this case be on the low side.

I have also included in the chart four figures for what I have termed the “long-term limits” on what monthly job growth might be for an economy at full employment.  I included them on the same chart so that one can easily recognize the relative scale.

For an economy at full employment (with unemployment at frictional levels), employment growth cannot exceed the growth of the adult population.  And indeed it will be less, as not all adults (defined by the BLS as all those in the population at age 18 and above) will be in the labor force – some will be retired, some will be students in college, some will have voluntarily left the labor force to raise children or provide care for others, and for other reasons.  Examining what these limits are for the US will provide a sense of what monthly employment growth might be, on average, in the coming years.

First, on population:  Population growth is relatively steady and predictable.  For the ten-year period from November 2011 to November 2021, it averaged 180,000 per month in the US.  It will be similar to this in the coming years, and it sets a (very) crude upper limit on what job growth could be in a steady state.  But one can see even from this figure that it will not be possible to sustain forever monthly net new job growth of even 200,000.  There will not be that many new adults available each month.

But 100% of the adult population are not in the labor force.  As noted, some will be retired, some students, and so on.  The labor force participation rate (LFPR) is the ratio of those who choose to be in the labor force (employed or looking for employment) to the adult population.  In the November CPS figures, that LFPR was 61.8%.  If one assumes that it will remain at that rate, then the monthly growth in the labor force will not be 180,000 (the growth in the adult population) but 61.8% of this, or 111,000.  And if one assumes that unemployment will be something steady, at say 4% at full employment, then potential employment growth would be even less, at 107,000.

The implication is that if the labor force participation rate remains where it is now, one should not be surprised to see monthly figures on job growth of no more than roughly 100,000.  This follows by simple arithmetic.  It could be higher for some period (but not forever) if the labor force participation rate rises from the current 61.8%.  This is possible, and perhaps even likely in the very near term, but probably not for long.  The LFPR in fact rose in the November BLS report to 61.8% from 61.6% in the prior month.  It normally changes only slowly over time.  The disruption that followed from Covid-19 led to relatively wide swings at first, with the LFPR falling from 63.4% in January 2020 to 60.2% in April 2020 with the lockdowns.  But by June 2020 it was back to 61.4% and since has fluctuated in a relatively narrow range before rising the 61.8% of November 2021.

What no one knows is what will happen to the LFPR now.  It might rise a bit more, but the long term trend has been downward.  It peaked in the year 2000, with a steady increase up until then following from a rising participation rate of women in the labor force.  But since 2000 the participation rate for women has moved down, paralleling (but about 20% below) the slow downward trend seen for men since the mid-1950s.  (The factors behind this are discussed in some detail in this earlier blog post.)  It is due to this downward trend over the period of 2011 to 2021 that actual labor force growth over this period was just 67,000 per month (as depicted in the chart above) even though adult population growth was 180,000 per month over this same period.

The current 61.8% LFPR is in fact close to what a simple extrapolation of the trend since 2000 suggests it would be in November 2021.  While the LFPR has behaved unusually since 2016 (when it flattened out for several years and indeed then rose a bit until the start of 2020, before collapsing and then partially recovering in the spring of 2020 due to the Covid-19 crisis), it is now back roughly to what one would find by a simple extrapolation of the trend since the year 2000.

There may well be surprises in what now happens to labor force participation.  After the disruptions of the Covid-19 crisis, it may never revert to where it was just before the crisis.  Those who retired early may mostly choose to stay retired.  And many of those in low-paying jobs, particularly in cases of one spouse in a couple with young children, may have discovered during the Covid-19 crisis that one spouse dropping out of the labor force is not all that costly, and in a two-earner household they may be able to manage financially.

There is therefore a substantial degree of uncertainty on what will now happen to the LFPR.  If it goes up, with a substantial number of adults re-entering the labor force, there will be a transition period when the labor force (and hence the number employed) could rise by significantly more than the 107,000 per month that one would see at a constant LFPR.  Monthly changes in employment during this transition period could be substantial.  For example (and again, this is simple arithmetic), if the LFPR were to increase from the current 61.8% by one percentage point to 62.8% (which would put it back to where it was in much of 2016 through 2018), then the number in the labor force would increase by 2.5 million over what would follow from regular population growth.  Possible employment growth would be about the same 2.5 million if unemployment stays where it is now.  Thus there could be a transition period of five months during which employment could potentially grow by 600,000 per month (a fifth of the extra 2.5 million in the labor force under this scenario, on top of about 100,000 per month from natural population growth).  Or the transition period could be shorter or longer depending on the number of new jobs each month.

But the point is that even if the LFPR should rise, the impact would be a transitory one, after which one should expect employment growth each month of no more than 100,000 or so.  And as noted before, the trend over the last 20 years has been that the LFPR has been moving downward, not upward.

D.  Conclusion

The November jobs report was interpreted by many as disappointing, as the estimated number of net new jobs (based on the estimate normally used – and rightly so) was 210,000.  This was seen as low, and the stock market fell.  However, the report was in fact a pretty strong one, and analysts may have recognized this once they started to look at it more closely.  While one never knows with any certainty why the stock market moves as it does (and there will always be other factors as well), the S&P 500, after falling by over 2% at one point on December 3, started to recover partially by the end of the day.  And it then rose strongly on the next two trading days.

There are reasons to believe the estimate of 210,000 net new jobs in November may have been low.  Seasonal adjustment factors mattered more than normally, and other measures of job growth were significantly higher.  But even at 210,000, analysts need to recognize that as the economy returns to more normal conditions, monthly job growth will likely be a good deal less than that.  While monthly job growth during Biden’s presidency from February to November has so far averaged over a half-million per month (588,000 per month to be more precise), this was only possible because the unemployment rate could come down.  But unemployment is now low – it reached 4.2% in November – and cannot go much lower.  If the labor force participation rate stays where it is now, possible employment growth will only be around 107,000 per month.  If the LFPR rises, then this could go up for some transition period, but that transition period is limited in time and when it is over employment growth will then have to revert to something close to 100,000.

What is more likely is that the LFPR will now return to the longer-term trend seen since it reached its peak in the year 2000, and will fall slowly over time.  Monthly employment growth would then be less, at something less than 100,000 per month (where how much less depends on the pace at which the LFPR falls).

Expectations have to be reset.  Other than during a transition period should the labor force participation rate rise above where it is now, monthly net new jobs growth of 100,000 per month or so is likely to be the limit of what one will see.  But that would be a good performance in an economy that remains at full employment.  Only if unemployment shoots up due to some future downturn could one then see – during a recovery from that downturn – something more.