Retail sales continue this year’s positive trend, suggest jobs market likely to improve as well

 

 - by New Deal democrat

As per usual, real retail sales is one of my favorite economic indicators, because it says so much about the health of the US consumer, and since consumption leads employment (noisily), also forecasts the trend in job creation.

Normally I don’t spend a lot of time on nominal retail sales, but this year that is more useful. That’s because the weekly Redbook index, which tracks nominal retail spending YoY, has been accelerating, up as much as 11% YoY (in fact this week it was 10.5% higher YoY). Here’s what the past five years of that index look like:

It was white hot in 2022, cratered in 2023, and has been accelerating back higher ever since, including this year.

But was it telling an accurate story? 

That’s where nominal retail sales come in. These were up 0.8% in September, and higher by 6.3% YoY. Here is what the YoY% changes in that metric look like over the past five years:

This is the exact same pattern as in the Redbook graph above. In other words, Redbook’s weekly updates have been telling us a true story (which is one reason why I track them every week as part of my Seeking Alpha weekly roundup of data).

But as useful as nominal information can be, the inflation adjusted data is more important. And since consumer inflation was higher by over 0.6% in September, real retail sales rounded to only a 0.1% gain. Still, note that there has been a sharp increase in real retail sales this year, although they remain lower than during the immediate post-pandemic Boom:

Note that this is telling a similar story to that of jobless claims that I just updated again this morning.

Although I won’t show the historical graph in this post, for about 70 years prior to the pandemic a decline in real retail sales YoY generally meant that a recession was close at hand. As you can see from the below graph, that wasn’t true for 2023-24. But YoY real retail sales have been positive, and improving, this year:

Further, real retail sales lead nonfarm payrolls (red in the above graph), albeit noisily. Sudden changes, such as caused by YoY comparisons with stimulus spending, take a longer time to get “digested” by the jobs market (a decent proxy is the 12 month average of the YoY% change in sales), but typically the lead/lag time is on the order of about 6 months. In that regard, here is the close-up of the last two years in the above YoY graph:

With the improvement in real retail sales this year, I expect the next few jobs reports to be positive, and perhaps more positive than we saw earlier this year.

So, to reiterate: like jobless claims, this is another positive for the economy.

Jobless claims continue near historic lows (yet again)

 

 - by New Deal democrat

Let’s take our regular weekly look at jobless claims. As per my periodic reminder, these are an excellent short leading indicator for the economy, particularly in conjunction with the other half of my “quick and dirty” forecast method, the YoY% change in stock prices.

These have been near historic lows much of this year, and continued in that vein this week. Initial claims rose 1,000 to 199,000, and the four week moving average rose 250 to 198,500. With the typical one week delay, continuing claims declined -4,000 to 1.710 million:

On the YoY% basis more important for forecasting purposes, initial claims were down -10.4%, the four week average down -11.7%, and continuing claims down -11.3%:

This metric continues to be very positive.

Since we’re still early in the month, I’ll dispense with what this means for the unemployment rate (but it certainly means I don’t expect the unemployment rate to increase). So here is the update on the “quick and dirty” forecast mentioned above. Note that since the metric for jobless claims is that they not be higher by more than +10% YoY, that line is inverted, and 10% added:

In contrast to the deteriorating real aggregate payrolls I discussed yesterday, this - like most current leading indicators - remains quite positive. To reiterate: when it comes to gauging the economy, leave your ideological predisposition at the door. In essence, the AI Boom (or bubble) is outweighing all the other economic determinants at the moment.

September CPI shows widespread movement *away* from Fed target, post-pandemic low in real nonsupervisory payroll growth

 

 - by New Deal democrat

After two benign months due to a temporary decline in energy prices this summer, the higher trend in inflation returned. And that continued in September, as prices (blue) rose 0.6%, and on a YoY% basis accelerated 0.3% to 3.7%. Core CPI excluding food and energy (red) also rose 0.3% for the second month in a row, rising from its post-pandemic YoY% low of 2.4% to 2.6%. Excluding shelter (gold), CPI rose 0.5%, but also increased 3.5% YoY:

Needless to say, the big culprit was energy prices, which rose 5.2% in September alone, and were up 20.4% YoY:

And the bad news extended to shelter, which is 1/3rd of the entire index. It reversed its recent deceleration, rising 0.4% for the month, and 3.2% YoY (blue).  Of it’s two components, Owner’s equivalent rent rose 0.3% monthly and increased to 3.3% YoY, while actual rent of primary residence also rose 0.2% and was up 2.8% YoY:

There was other bad news as well. Electricity prices rose another 0.2%, and are higher by 20.4% YoY. Utility services did decline -0.3% for the month, but remained higher by 5.0% YoY. And computer hardware prices rose 1.4% for the month, and were higher by 9.7% YoY:

Motor vehicle maintenance and repair also continued to be a problem child, up 0.7% for the month and 5.8% YoY:

If there was a silver lining, it was that motor vehicle prices continued to be somnolent. New vehicle prices (red) rose 0.2% for the month, and were only higher 0.6% YoY, and while used vehicle prices (gold) rose 0.7% for the month, they remained lower YoY by -1.5%. The average for all motor vehicles (blue) was higher 0.5% monthly, but was unchanged YoY:

Finally, let’s update real nonsupervisory hourly wages (orange), which declined and real aggregate nonsupervisory payrolls (red), both of which declined -0.4% for the month. Both remain about -0.9% and -0.5% below their February and January peaks respectively:

Real wages are also down -0.4% YoY, but payrolls remain positive, up 0.5% YoY:

Recall that real aggregate nonsupervisory wages are an excellent short leading indicators for recession. Further, when they turn negative YoY, they have been a good coincident marker for a recession. The current situation remains almost sui generis. It is very rare for this metric to stay below peak for more than half a year without a recession occurring shortly thereafter. In fact, only three times in the past 60 years, for *1* month apiece in 1968, 1996, and 2011, have decelerating real aggregate nonsupervisory payrolls been higher this little YoY without a recession ensuing shortly thereafter:

In conclusion, this was a poor report for obvious reasons. Not only are oil and gas prices driving up the headline number, but the recent quietude in shelter prices appeared to reverse a little higher, and the AI-data center driven increases in electricity, water, and computers are still firmly in place. While my forte is forecasting rather than Fed-watching, it is difficult to see the Fed being comfortable with this widespread boomerang away from its 2% target.

The subpar equilibrium in existing home sales continues - for now

 

 - by New Deal democrat

To repeat my housing sector mantra for the umpteenth time, mortgage rates lead sales, which in turn lead prices, which finally lead inventory. 

And for the last three years, the market for existing homes has been rangebound, first in sales, then in prices, and finally this year in inventory as well, in what I have described several times as a “suboptimal equilibrium,” because the housing market as a whole continues to be unaffordable compared with any time outside of the housing bubble before the pandemic.

That continued in September, in which existing home sales rose a seasonally adjusted +1.5% monthly to 3.99 million annualized from a slightly downwardly revised August. Which continues to be well within its range of between 3.85 - 4.30 annualized for the past three+ years:

With rangebound sales, prices on a YoY basis have been relatively calm as well. These are not seasonally adjusted, so we look at them YoY. On that basis, since February of 2025 there has been no YoY comparison higher than 3.0%. in September the YoY comparison was +1.3%, as the median price of an existing home was $417,500, vs. $412,300 one year ago. Prices did  decline -10,200 vs. August on a non-seasonally adjusted basis, as they typically do after midyear:

As noted above, this year the most lagging metric, inventory, has also fallen in line - at least until this month, as the YoY% change in existing home inventories increased to 4.6%, the highest comparison since March. By contrast, last month it was down less than 1%. For context, as recently as last December it was up 7.9% YoY:

Unfortunately the above graph does not show the metric very well, but for the last year on a YoY basis inventory has consistently been about -500,000 less than it was a decade ago. Until this inventory shortage is taken care of, the housing market will continue to be tight, and largely unaffordable for new buyers.

To bring this discussion full circle, here is what mortgage rates (gray, right scale) look like in comparison with sales (blue, left scale):

As I wrote at the outset, mortgage rates lead sales, and with the recent increase in mortgage rates to the 7.50%-7.60% range, I fully expect both existing and new home sales, as well as housing permits and starts, to react to the downside over the next several months. So this recent subpar equilibrium may shortly be broken - unfortunately, to the downside.

 

A proposal for Project 2029: Medicare Advantage for All

 

 - by New Deal democrat

On this Indigenous Peoples/Columbus Day holiday, there is no new economic news, so let me roll out something I have been thinking about for quite a while; namely, how to migrate from out current patchwork health care insurance system to a better, universal system.

Such a migration is very popular. Just last week, the Kaiser Family Foundation reported that 66% of all Americans, including 72% of all self-identified Independents, favor some sort of national health care plan:

 

The question has always been, how to get there from here, given the many stakeholders with strong financial incentives under the current hodgepodge.

While many observers have issues with Medicare Advantage plans, they are very - and increasingly - popular among Medicare recipients. But they do have several advantages, including that a person enrolled knows up front how much is being paid for by the plan (rather than the uncertain “80%” coverage of regular Medicare). And over the long run, both types of plans seem to cost a similar amount, with the difference being that Medicare Advantage plans are better for relatively younger, healthier seniors, and regular Medicare better for seniors who have costly medical conditions.

(ADDENDUM: I also wanted to mention that other countries with very efficient and successful universal public health insurance programs, like France and Germany, rely upon private insurers to provide coverage).

Another advantage that “Medicare Advantage for All” would have over “Medicare for All” is that the potent medical insurance lobby would very much be in favor of its passage, removing one very big roadblock to it. And it could easily be employed promptly, since medical insurers already have plenty of experience handling and paying medical claims.

But one big question is, how would it be paid for? Especially if some sort of taxpayers’ revolt from an increased tax burden might be feared.

First of all, there should be no further concern about deficit spending for such a plan. If the GOP can blow a huge hole in the budget and run up $Trillions of debt for a tax giveaway to Billionaires, there is no point in arguing for fiscal prudence on the other side. On top of which, as I’ll lay out below “Medicare Advantage for All” ought to be able to pay for itself.

Here’s how my proposal would work.

1. Everybody not covered by existing Medicare, CHIPs benefits, or Veterans’ benefits, would qualify.

2. The plan would be funded by a FICA withholding tax. Similarly to income tax withholding, at the beginning of each year, every person employed would fill out a form listing the number of persons in their household. Full exemptions would be granted for every household member covered by any other type of medical insurance (including employer-sponsored medical coverage at least equivalent to either an Obamacare silver plan or a Medicare Advantage plan. FICA taxes for the program would be withheld from the person filing the form, as well as any dependent not so covered. In this way, most importantly anyone already covered by an employer’s plan would face no new taxes.

3. Employers with more than 50 employees and $5 million in gross sales would be required to pay their 50% share of the FICA withholding tax starting with the next fiscal quarter more than 60 days after the passage of the act.

4. Employees and smaller employers would not be required to pay their share of the FICA withholding tax until the first fiscal quarter more than one year after the passage of the act.

5. Which means, as per my opening comment, most of the initial year’s outlays for the program would be put right on the general national debt. After that, the FICA taxes would be designed to fund the annual costs of the program, just as FICA taxes have done for, e.g., Social Security and Medicare in the past.

6. Benefits under the act would begin to be paid the first fiscal quarter more than one year after passage of the act as well.

7. The year’s delay in employees’ having to pay the tax would give them a chance to bargain with their employer, formally or informally, about their pay; and if their employer refused to raise their pay to cover their share of the FICA withholding tax, it would give them a chance to find employment elsewhere at a higher rate of pay.

8. Any employer with over 100 employees or over $10 million in gross sales refusing to increase employee wages or salaries to cover their share new FICA taxes would be hit with an income tax surcharge of an equal amount.

9. Just like Medicare Advantage plans, people newly enrolled in the plan would have to compare various plans on offer. If they failed to choose one during the coverage window (the same window of time as with existing Medicare), they would be enrolled in a randomly chosen plan available in their area. Over several years, even lazy consumers who wound up with poorer plans would likely migrate to better plans recommended by relatives and/or friends.

10. The year’s delay in the beginning of payments of benefits would also allow insurers to develop their Medicare Advantage plans for the new influx of younger people (who on average would be in much better health than current Medicare enrollees).

11. Since the program would be funded just like Social Security and existing Medicare, it should withstand any creative Court challenges (with the big caveat that nothing is beyond the majority of the current SCOTUS, but SCOTUS expansion should happen first before anything else anyway).

12. Over time, it’s likely that employers would find it easier and less expensive just to pay their employees’ FICA taxes to join the new Medicare Advantage plans rather than continue with the burdensome paperwork of their own private plans.

13. In addition to being funded by new FICA withholding taxes, the one year hole in the budget would be covered by rescinding the last 3 GOP tax giveaways to the wealthy in 3 stages. For individual taxpayers who earned over $500,000 and corporate taxpayers with gross sales or earnings over $10 million, the 2025 Big Bad Bust-out Bill’s tax cuts would be rescinded immediately. The similar but relatively smaller 2018 tax cuts would be rescinded in two years. And the 2012 extension of the 2002 Bush tax cuts would be rescinded in four years. Further, the rescission would be made retroactive for four years based on income declared then (note there is no “ex post facto” issue as to taxes, which can be made retroactive); and the taxpayers would be given years from the inception of each rescission to pay back the relevant taxes.

The end result would be that every American would be covered by medical insurance at least equal to either Medicare or an Obamacare silver program. Insurers, who suddenly would have a substantially larger pool of relatively healthy new customers, would also be happy. And to the extent necessary (which I doubt it would be), “Medicare Advantage for All” could be a stepping stone, via a subsequent public option if so passed, to “Medicare for All.”

Weekly Indicators for October 5 - 9 at Seeking Alpha

 

 - by New Deal democrat

My “Weekly Indicators” post is up at Seeking Alpha.

The paradigm that has been supreme for the last few months continues. On the one hand, there are soaring AI related stock prices fueling consumer spending. On the other hand, there are also sharply higher interest rates and gas prices. So far, AI has been ‘winning.’

As usual, clicking over and reading will bring you up to the virtual moment as to the state of the economy, and reward me a little bit for obtaining and organizing it all for you.

The US economy right now: AI vs. everything else

 

 - by New Deal democrat

Let’s wrap up this week of limited economic data by looking at perhaps the most prevalent theme about the state of the US economy right now: that it consists of basically 2 components, (1) AI and (2) everything else. This is a round up of a bunch of graphs I have seen in the past few weeks that have all circulated around this same point.

First of all, construction spending. While unfortunately FRED doesn’t separate out data center spending, some other writers have. Here’s a good graph from Steve Rattner showing how, when we take out AI data center construction spending, the entire remainder of construction spending has been declining since the middle of 2024:

Here’s a fuller breakdown from Prof. Jason Furman:

And Prof. Furman also points out that total CapEx investment is more concentrated now than at any point in the last 50 years:

This is showing up in stock market valuations:

The valuations of AI related companies are Booming. Everything else is moribund.

This is apparent in the advance-decline line. If share prices in more companies in, e.g., the S&P 500, increase on any given day vs. decline, the A-D line is positive. If the declining number of stocks outnumber advancing ones, the A-D line is negative:

Here is a longer term historical view of a similar, basically self-explanatory, metric:

The last time the number of outperforming stocks was this narrow was during the dotcom bubble at the end of the 1990’s.

Meanwhile borrowing costs are rising for lower rated corporate debt:

Here is a similar FRED graph that, in addition to Treasurys (purple), includes high rated AAA corporate debt (blue), lower rated but still investment grade BBB corporate debt (orange), vs. risky high yield CCC or lower corporate debt (red), all normed to “0” as of the lows in the bond market last October:

In general, the lower rated the debt, the more it blows out to the upside in the yield investors demand to buy that debt. This includes before and during recessions, but also during and after other scares, such as the Silicon Valley Bank collapse in March 2023.

Basically the US economy has put all its eggs in one basket, called AI. Earlier this week Paul Krugman wrote on his substack that "Massive spending on data centers is crowding out investment in everything else in the economy,” adding that "this isn't a hypothetical risk." And as I have written in the past several months, while the *software* aspect of AI may not be a bubble, i.e., the end result of AI may be a boon to human productivity, the *hardware* aspect, i.e., 10 or 20 different companies all making massive construction investments in plant and equipment, where only 1 or 2 companies are likely to survive as winners (much as in the 1990s all of the internet search companies withered except for the big winner, Google), almost certainly *is* a bubble. 

New jobless claims continue near historical lows; plus the “quick and dirty” forecast, and an important comparison vs. long term unemployment

 

 - by New Deal democrat

Let’s take our regular weekly look at jobless claims. Plus, this week I want to make a statement about jobless claims vs. long term unemployment.

First, initial jobless claims declined -2,000 to 197,000. Aside from 2 weeks in 2018, the only time prior to the pandemic that initial claims were this low was all the way back in the 1960s. The four week moving average declined -2,500 to 198,000, also the lowest since the 1960s. And with the typical one week delay, continuing claims rose 17,000 to 1.716 million, in the lowest range since early 2023:

In the YoY% comparisons more important for forecasting purposes, initial claims were lower by 15.5%, the four week moving average lower by 13.0%, and continuing claims lower by 11.0%:

These YoY comparisons keep getting better, even in the face of very good numbers one year ago. This is very positive for the economy over the next few months.

Not only are jobless claims very positive, but the stock market (blue in the graph below), concentrated on AI-related gains, is higher by about 15% YoY. Thus the “quick and dirty” forecast model, which also included the four week average of jobless claims (inverted, +10%), remains very positive for the economy as well:

It’s early enough in the month that I can eschew a comparison with the unemployment rate, but last Friday I read a prominent reporter touting how long term unemployment was recessionary. This is simply not the case. So let’s compare YoY jobless claims with long term unemployment by 27 weeks or more (blue in the graph below):

There are two important things to notice about the above graph. The first is that, if new jobless claims lead the unemployment rate, they lead long term unemployment even more. Secondly, note that long term unemployment continues to rise even after a recession is over; i.e., early during the ensuing economic expansion. In other words, a rising long term unemployment number is consistent with both a recession and also a renewed upturn in the economy.

Another way to look at this is the ratio of long term unemployment to initial claims. Here’s the historical look:

Again, note two things about the above graph. First, just like the number of long term unemployed, the above ratio also continues to rise into the ensuing expansion for months after the recession is over. Secondly, note that there has been a long term secular trend of a higher ratio of long term unemployed vs. newly unemployed both at the troughs and the peaks of the comparison. This has been particularly true since the 1980s. In part this is likely due to the relative strength of employers vs. workers and the decline of unions since the Reagan era. It may also be due to workers adapting to the availability of long term unemployment benefits, especially as more and more spouses also work; i.e., the unemployed worker can afford to be choosier about what next offered position of employment to accept.

Now here is the post-pandemic view:

Just as with prior periods, the ratio peaked in the summer of 2021, more than a year into the post-pandemic Boom. There are ambiguous signs that it may be peaking again now, going on a year after the late 2025 “mini-recession.”

In short, whatever long term unemployment may suggest about the economy, new jobless claims get there first.

Last week’s major revisions to personal income: comparing the source data

 

 - by New Deal democrat

While we are waiting for new data releases to start back up, let me follow up on the surprise revisioins last week to personal income, that took real personal income for declining for over a year to an almost relentless rise. So shocking was this reversal that for the first time I wondered if the T—-p Administration had been successful interfering with economic reporting.  To give you an idea of just how large the revisions were. here is the YoY% change as originally reported (orange) vs. as revised (blue) of nominal personal income:

Once adjusted for inflation, the entire trend in *real* personal income changed from negative to positive:

Ultimately an answer came back from someone with impeccable credentials who pointed out that, so long as the revisions were in accord with the source data series giving rise to the revisions, they should be accepted.

So what do those data sources say? Let’s start with the Census Bureau’s note expalining where the revisions came from:

While I haven’t been able to track down all of these sources, there are two - the QCEW and income tax withholding receipts - which are readily available.

The QCEW is what the late financial analyst Jeff Miller called “the gold standard” of employment data, as it is the actual reporting by roughly 97% of all employers. Its biggest drawback is that it is not reported until almost 6 months after the close of any given Quarter, and it is subject to revisions until March of the ensuing year. I’ve reported on the employment side of this release for many years, but haven’t paid particular attention to the income side. 

In any event, as per usual the data lags by half a year. Additionally it is not seassonally adjusted, so the only valid measure is YoY. To cut to the chase, here is the post-pandemic YoY quarterly record of aggregate wages:

While I can’t show you a graph, I also went back and calculated the full quarterly change in withholding income taxes paid YoY from the Treasury’s “Daily Treasury Statement.” There are very volatile and noisy on a daily, weekly, and even to some extent monthly basis, but by the time you take the entire 13 weeks that constitute a Quarter, the vast majority of the noise has been ironed out.

With that explanation done, below is a list showing the revised YoY% change in nominal personal income beginning with the 4th Quarter of last year, and ending with the first two months of Q3 of this year from the personal income releases vs. the entire third quarter for withholding tax payments. Note that since the QCEW has only been reported through Q1 of this year, there are no subsequent comparisons for that metric:

Quarter  //  P. I. (O) //  P. I. (R)  //  QCEW  //  D.T.S.

Q4 ‘25   //  +4.4%  //   +4.8%      //  +4.2%  //  +4.6%

Q1  ‘26  //  +3.6%   //   +4.6%      //   +3.9% //  +5.0%

Q2  ‘26  //  +3.5%  //   +4.4%      //  n/a        //  +1.9%

Q3  ‘26  //  +3.8%*  //   +4.4%*    //  n/a      //  +5.6%

(O) = original; (R) = revised

*average of first two months of quarter

For the entire period through August, the originally personal income averaged +3.82%. As revised it averaged +4.55%. For the entire fiscal year ending in September, YoY withholding tax payments averaged 4.3%, much closer to the revised income data than the original. for the first two quarters of the fiscal year, however, the QCEW is much closer to the original income data than the revisions (although note that the QCEW explicitly only covers wages, whereas the D.T.S. includes estimated tax payments which of course cover all sources of income, not just wages).

The QCEW of the 2nd quarter of this year should be reported next month. At that point we will have a better idea of how well that data tracks the revisions to personal income.

In any event, given the major revisions to the personal income data, going forward I will not just pay attention to the employment data in the QCEW, but also the wage data; and I will also report on the 13 week/quarterly average of withholding payments.

 < sigh > more work. For some reason I keep thinking of this old “Far Side” cartoon:

September vehicle sales send mixed message

 

 - by New Deal democrat

One piece of economic data that got reported late last week that is worth following up on is the monthly tally of heavy truck (red) and car sales (blue, right scale):

Both of these are leading indicators, but heavy truck sales are less noisy, and generally signal first (although, like the unemployment rate, they lag significantly coming out of recessions).

In any event, in September car sales were 16.0 million annualized, while heavy truck sales declined sharply in the month to 396,000. Car sales were therefore right in the middle of their range over the last three years, while truck sales are back down into recessionary territory (more than -10% from their recent peak) for the second month in a row. Here’s the zoomed in post-pandemic view that shows the situation a little more clearly:

Without confirmation from car sales, truck sales are not forecasting an imminent recession, but count this as a negative indicator.

Leading indicators from the Setpember employment report continue positive trends

 

 - by New Deal democrat

We’ve entered our post-employment report lull in new economic data, so let’s take a further look at the leading indicators contained in that report. Generally speaking, this includes the more cyclical sectors like construction and manufacturing, and goods production in general; real aggregate nonsupervisory payrolls; and, during expansions leading up to recessions, the unemployment rate (vs. immediately after recessions, when they lag).

Let me start with the last metric first. Almost every week I write that initial jobless claims lead the unemployment rate. Recently I’ve been writing that new jobless claims forecast further downward pressure on the unemployment rate, to the point of declining below 4.0%. Well, in Friday’s report the rate rose 0.1% to 4.2%. So is the forecast busted? 

Hardly. That’s because when we take the raw numbers going into that rate, and extend them another decimal point, they only went up 0.03% from 4.14% to 4.17%, as shown in dark red in the graph below. The lighter, thin orange line is the “official” employment rate, vs. the four week average of initial claims (purple, right scale):

The unemployment rate has drifted higher from its low in July, but the downward trend is intact. There is every reason to expect the unemployment rate to decline further over the next several months.

Next, let’s look at the leading employment sectors. These include manufacturing (gold), residential construction (red, right scale), and goods production as a whole (blue). Also included is nonresidential construction, which includes construction on AI data centers (purple, right scale). All four lines are nomred to 100 as of just before the pandemic:

With the exception of residential construction, the trend line in all of these sectors is up. Even residential construction employment appears to have made a temporary bottom at least in July.

Another leading subsector is trucking employment. This too appears to have bottomed at the beginning of this year and has trended higher since:

Average hours worked in manufacturing is also an “official” leading indicator from the employment report. That increased 0.2 hours in the report to 42.0 hours, not just the highest number since the pandemic, but one of the highest numbers in the entire past 80 years:

Only one month in the 1990s was equal to this number, and most of 2014 and 2018 had higher numbers. In other words, the manufacturing sector is running “hot,” likely in main part due to AI data center related employment. I should point out that the secular increase over the decades probably has much to do with the tilting of the balance of power towards employers vs. employees as part of the general decline of unions that began with Ronald Regan’s presidency. In other words, rather than hire more employees, employers simply work their existing employees harder.

Finally, let’s take a look at real aggregate nonsupervisory payrolls. 

To begin with, average hourly earnings on a YoY basis are only equal to the inflation rate:

If workers are taking home more money in real terms, it would have to be via an increase in hours. So here is the long term historical view of aggregate nonsupervisory hours:

Note this is in log scale to better show the earlier historical data; and also note that with population increase we would expect hours to increase as well. Anyway, what I wanted to point out is that this is generally a coincident indicator, flattening out and peaking within several months before or after the onset of recessions.

Now here is the same data from the past 3.5 years:

Note that since May the number of hours worked has been all but flat. This indicates profound weakness, but such pauses have also occurred in economic slowdowns that have not resulted in recessions, such as in 1966, 1995, and 2016. 

Total hours * wages = aggregate payrolls. Then we adjust for inflation for the “real” number. Here is what they look like for the past 3.5 years, also normed to 100 as of just before the pandemic (ending with August, because September inflation hasn’t been reported yet):

As of August, real nonsupervisory payrolls were up only 0.1% in the 9 months since last November.

Further, the Cleveland Fed estimates that September inflation is likely to come in at +0.5%. So here are the last 12 months of the monthly changes in nominal aggregate nonsupervisory payrolls (blue) and inflation (red):

Last September, both payrolls and inflation rose 0.3%. With payrolls only rising 0.2% in September, if the Cleveland Fed’s estimate proves correct, real nonsupervisory payrolls will decline -0.3%. If that happens, real nonsupervisory payrolls will only be up about 0.65% YoY, the lowest since the pandemic, as shown in the below graph which subtracts -0.65% to show the likely September value at the “0” line:

Not only that, but in the past 60 years YoY increases of 0.65% or less have only occurred in 4 months without having indicated an oncoming or existing recession: once in 1968, once in 1995, and twice in 2011:

We’ll have problems calculating this over the next several months because of the blank October value last year due to the government shutdown, but since CPI only increased 0.3% last November over last September, that averages only 0.15% each month. Should the oil shock from the Iran war continue, it is at least possible that there could be *no* YoY increase in real aggregate nonsupervisory payrolls by December, which would be a strong coincident indicator of recession.

With one important caveat: pace last week’s major positive revisions to personal income, keep in mind that employees’ earnings will be subject to benchmark revisions next February based on the QCEW. And one very good proxy we have for that is withholding tax payments. While those are extremely noisy on a weekly or even monthly basis, once we use the entire past 3 months, they become much less noisy. And for the three month period of July through September, withholding tax payments were higher 5.6% YoY (not shown). vs. 4.2% for aggregate payrolls (blue in the graph below):

This suggests that the last few months, at least, of aggregate nonsupervisory payrolls could be revised higher in the benchmarking process early next year.

Here’s the conclusion: with one important exception - real aggregate nonsupervisory payrolls - all of the other leading indicators contained in the employment report were either positive (e.g., manufacturing and construction indicators) or at least consistent with an ongoing positive trend (the unemployment rate). 

Additionally: as I cautioned last month, leave your ideological priors at the door before evaluating the data. The US economy is extremely resilient, and so far it has found work-arounds for the incompetence and irrationality coming out of Washington.