A somewhat negative personal income and spending report for September

 

 - by New Deal democrat

As promised, let’s take a look at the second of this morning’s three significant data updates. As I typically note, along with the employment report, real income and spending are probably the most important monthly reports as to the health of the average American household. Earlier this year there had been a real split between the income and spending sides of that ledger, with the former looking recessionary and the latter very positive. Last month the negatives on the income side were revised away, due to incorporating the more comprehensive measures found in the QCEW (through the first quarter of this year) and income tax payments (through Q3).

This month the softness reasserted itself somewhat, as real incomes declined, while real spending was unchanged. Here’s the more detailed look.

Nominally income rose 0.2% in September, and nominal spending increased 0.5%. But after adjusting for the price deflator, which rose 0.5% as well, real income (blue) declined -0.3% and real spending was unchanged:

Real income less government transfers payments is one of the important coincidental indicators the NBER looks at in determining if the economy is expanding or in recession. Since even without government transfers real income was down, needless to say so was this metric as well, also by -0.3% for the month, although it too was higher 0.5% YoY:

Here is what both real incomes and spending look like YoY since the pandemic:

The former is up 0.5% YoY, which is weakly positive, while the latter is up 2.5%, a normal expansionary positive number.

As I’ve noted many times in the past, real spending on services frequently rises all the way through recessions. The leading indicator is real spending on goods (gold). Further, real spending on durable goods (red) historically tends to peak even before goods spending as a whole.  In September real spending on goods declined -0.3%, and real spending on durable goods declined a sharp -0.8%

But both remain higher YoY, the former by 2.5%, and the latter by 3.2%:

The difference between income and spending is saving. In September, the saving rate declined -0.2% to 3.6%. This is low historically, but not as low as the era of the housing bubble and in 2022:

Typically, as expansions go on, consumers become more and more risk-taking about spending, and the saving rate declines. An increase in the saving rate in the presence of price pressures is one of the signs of an imminent recession. Needless to say, whatever they are telling pollsters, in the aggregate consumers remain quite confident about spending, likely tilted towards those with AI-based stock market gains. 

Finally, this morning’s report also enables the update of real manufacturing and trade sales, one of the other important coincident markers used by the NBER to date recessions. These lag by one month. They were also flat in August, but their uptrend remains intact:

They are higher 2.5% YoY.

This was a slightly negative report. Real incomes declined, real spending was unchanged, and the goods component of that spending declined. Consumers in the aggregate dug into their savings to continue that spending. But the overall positive trend in these numbers remains intact. For me to change that opinion would require real spending on at least goods or durable goods to turn negative.

Jobless claims continue near 60 year lows; compelling evidence that the unemployment rate is headed under 4%

 

 - by New Deal democrat

As I wrote yesterday, this morning we got a deluge of significant data. I’ll write about personal income and spending later, and the details of Q3 GDP tomorrow. For now, suffice it to say that real GDP was very positive, up 3.4% annualized, and “core” GDP, a/k/a real final sales to domestic purchasers, was even more strongly positive, at 4.9% annualized.

But let me start out with my usual weekly update of jobless claims, which make up 1/2 of my “quick and dirty” forecast, along with stock prices. They have been excellent almost all this year, and this week was one of their “most excellent” of all. Initial claims declined another -1,000 to 194,000, and the four week moving average declined another -1,250 to 196,750. Any time either of these numbers are under 200,000, not only are they among the best since the pandemic, but among the best in the entire nearly 60 year history of the series. Meanwhile, continuing claims, with the typical one week delay, declined -21,000 to 1.701 million:

And the YoY% numbers got even better as well, with initial claims down -12.2%, the four week moving average down -13.2%, and continuing claims down -12.9%:

In short, if real GDP, one of the premier coincident indicators, is very positive, then jobless claims are telling us that should continue at least through this Quarter as well.

Finally, as we close out the month, let’s take a look at what jobless claims forecast for the unemployment rate (red) over the next few months:

The last time the monthly average of claims were this low, which was early in 2023, the unemployment rate in the immediate subsequent months, was several tenths of percent under 4%. The evidence is becoming stronger and stronger that that’s where the unemployment rate is heading between now and the end of the year.

 

The AI data center driven manufacturing rebound continues

 

 - by New Deal democrat

While we await tomorrow’s deluge of data (Q3 GDP, personal income and spending, and jobless claims) let’s take a look at the yesterday’s most recent update of manufacturer’s new durable and capital goods orders from yesterday.

This comes out twice a month, as a first estimate and then as a final number for each month. Yesterday’s report was the first estimate for September. And it continued the strong rebound we have seen for over a year.

On a monthly basis, headline manufacturer’s new durable goods orders (blue) increased another 1.8%, while the less noisy core capital goods orders (red) increased 0.5%, to new post-pandemic high in the case of the less-noisy, more-signal latter:

On a YoY basis, the headline number increased 9.9%, and core capital goods orders increased a very sharp 13.5%:

What is interesting about the YoY comparison is that, if we use a paradigm that AI adoption will follow a typical “S” curve of exponential acceleration in growth followed by a similar exponential deceleration in growth” (note, we are talking about the second derivative here), then the fact that the core capital goods growth, while remaining very strong, may have reached peak acceleration at about 15%, then the first sign of the diminishment of the AI story may be near at hand (i.e., still strong growth, but decelerating to under 10% YoY).

Also interesting is that this inflection point of the second derivative may also be operative in the regional Fed new orders indexes that I updated last week. Here again is that graph:

This is noisier, so I look at the three month average, which remains close to its 3+ year peak.

The bottom line is that the AI-data center driven manufacturing rebound is very much intact at present. This suggests that consumer spending and goods-producing employment will also continue to be strong (in the case of the former) or rebounding (in the case of the latter). The inflationary expansion continues.

New home sales and repeat home prices may both have sung their ‘swan song’ for recent trends last month

 

 - by New Deal democrat

Last month I closed with “a reminder that the Fed’s interest rate hike and the similar increase in mortgage rates suggests that the recent equilibrium in the market is probably going to be yanked to the downside.” We have already seen that with mortgage applications, which have fallen to close to their 5 year lows. Next in line is sales, and only after that, with a lag, will be prices.

With that in mind, let’s take a look at this morning’s reports on new home sales and median prices, as well as repeat home sales as measured by both the FHFA and Case-Shiller indexes.

Let me start by repeating that new home sales are perhaps the most leading of all the housing sector metrics. But they suffer from being very volatile and heavily revised. So their three month moving average is more reliable as a signal.

In September sales (blue) declined -4,000 annualized to 676,000. But as the graph below shows, this remained close to the high point for this year, and was in the middle of the range for the past 3+ years:

The above graph also shows inventory (red). Although I won’t bother with the historical graph this month, sales have *always* led inventory, which tends to turn down much closer to a recession, and generally bottoms towards or even after the end of a recession. So the sideways to slightly higher trend this year would normally suggest a recovering housing market.

Prices are not seasonally adjusted, so are best measured YoY. And there, they have been in a sideways to slowly declining trend, which continued in September as the median price for a new home declined -1.0% for the month (dark blue), and -2.3% YoY. The below graph also shows the quarterly averages (light blue), which are down -1.0% YoY:

The trend in absolute numbers indicates a general decline in the past four years. Even more importantly, as shown in the graph below whicg deflates the median price of a new home by average weekly earnings, normed to 1 as of September, indicates that the “real” median price of a new home (dark blue) is down to its range in the 1990s and after the housing bust around the Great Recession. This contrasts with the “real” similarly deflated cost of existing homes as measured by the FHFA repeat sales index (orange), which while lower than several years ago, is still very high in historical terms:

Before I sum up, let’s turn to this morning’s other housing reports. Although they are not an infallible indicator (nothing ever is!),house prices are an important component of the economy, particularly as they affect the official CPI measure downstream, not to mention their importance to especially younger people in terms of the affordability of purchasing a new or existing home. And the repeat home sales indexes, by S&P Case Shiller and the FHFA, are the best indicator of prices in the 90% of the market that is existing home sales. same.

Since the beginning of this year, prices in both indexes have appeared to be firming, with the FHFA (red in the graphs below) as it often does slightly leading the Case-Shiller National Index (blue). That continued to be the case in this morning’s reports through August, with both reports indicating a seasonally adjusted monthly increase of 0.3% in prices. [Note: FRED has not yet updated the Case Shiller data]:

As per the above comment, earlier this year there had been something of a divergence showing in the YoY comparisons of the two national indexes, as the Case Shiller national index had increased less than 1% YoY, while the FHFA Index had accelerated to a 2.0% increase. But in the past several months, the Case Shiller index has followed suit. As of this morning’s report, the FHFA continued to be slightly “hotter” overall, with a 2.4% YoY increase, vs. 2.1% in the Case-Shiller Index.

It continues to be the case that it will take considerably more inventory on the market to bring existing homes down to just their average affordability compared with the past 30 years.

Both of this morning’s reports discussed above may have been the last for the current trends. Higher mortgage rates have badly hit mortgage applications, and can be expected to his sales and permits for construction within a month or two. Prices will only react after that, and the inventory of new homes in particular can be expected to increase again. If there is a silver lining, it is that builders have been steadily making their new homes for sale more affordable as a multiple of average earnings.

‘Level two’ chaotic systems, polling, and election results

 

 - by New Deal democrat

There’s no important economic data today, so let me post something that I meant to write about over the weekend before I was distracted by real life.

In his book “Sapiens,” Yuval Noah Harari writes that 

[M]any people [ ] prefer history to be deterministic. Determinism is appealing because it implies that our world and our beliefs are a natural and inevitable product of history….

[But h]istory cannot be explained deterministically and it cannot be predicted because it is chaotic…. [H]istory is what is called a ‘level two’ chaotic system. Chaotic systems come in two shapes. Level one chaos is chaos that does not react to predictions about it. The weather, for example, is a level one chaotic system….

Level two chaos is chaos that reacts to predictions about it, and therefore can never be predicted accurately. Markets, for example, are a level two chaotic system…. [because the better the history of a forecasting system, the more it will become a ‘nowcast,’ as people front-run the prediction].

Politics, too, is a second-order chaotic system…. Imagine … some political scientist in association with a computer wizard have developed an infallible algorithm [that predicts the political future. A politician on the losing end of that prediction, for example, would take pre-emptive measures to ensure that the prediction does not come to pass….]

(Sapiens, pp. 239-241)

This is exactly what happens with political polling, and the fate of poll aggregators is a case in point. Nate Silver was initially very successful. But soon, players with other interests reacted to his system. First, and with increasing frequency, partisan pollsters ‘flooded the zone’ with junk polls, forcing him to weigh pollsters by accuracy, and even to develop a slew of alternate and inconsistent forecasting systems. But those junk polls also influenced voters to decide that either a race was competitive, or that one candidate was sure to win or lose. And now we have seen the rise of outright fraudulent polling, to the same end.

The net result has been that these poll aggregations have been increasingly off-target. For example, Sam Wang famously said in 2016 that “It is totally over. If Trump wins more than 240 electoral votes, I will eat a bug.” (and to his credit, he ate a honey-dipped cricket on CNN four days after the election. 

What happened in 2016, essentially, was that “everyone knew” Hillary Clinton was going to win. And because “everyone knew” that, some voters felt free to stay home. Others felt free to cast a protest vote for Trump. Clinton herself felt free not to campaign in the “safe” upper Midwestern States. And most notoriously, FBI Director James Comey felt free to hold a press conference announcing a renewal of a criminal investigation into Clinton while early voting was already underway!

Now in 2026 we are being told that Democrats are heavily favored to take the House, and more likely than not to take the Senate. We are being told that early turnout is heavily in favor of Democrats, and that especially Hispanic voters are turning out in those areas.

But we are not just the passive recipients of these messages. We should fully expect that both potential voters and likely non-voters are going to *react* to that message as well. For example, might some Democratic voters in swing States relax? Will GOP operatives flood likely GOP voters’ mailboxes and social media feeds with horror stories about the big early Democratic turnout, thus driving more tenuous GOP voters to the polls to counter that early trend? Or conversely might a significant chunk of the public decide that they want to show up to be on the winning side, or turn a wave into a tsunami? 

We don’t know. But what we *should* know is that the very act of publicizing all these polls and early turnout models is going to significantly affect the ultimate result. Ask Brazil, where reporting and polling after the first round of balloting that Bolsonaro was almost sure to be elected drove a massive outpouring of votes for Lula.

For my part, I am hopeful. But I am thoroughly discounting all of these polls and dissections of early voting.

A century ago, early industrial psychologists ran a study of factory workers. They found that, e.g., increasing the light on the factory floor made the workers more productive. But it turned out that, more than anything else, it was the act of *observing* the workers that was the chief reason that the altered their behavior. Because, as a fan of Star Trek, to put Harari’s observation in Ferengi terms, “Hoo-mans are a clever species. When you observe the hoo-mans, they always observe back.”

Weekly Indicators for October 19 - 23 at Seeking Alpha

 

 - by New Deal democrat

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

While the usual recent troika of stock market valuations, low initial jobless claims, and strong consumer spending are holding up the short leading and coincident forecasting time frames, enough deterioration has occurred in the long leading time frame to turn that neutral.  This doesn’t mean that the economy ‘will’ stall in the next 12 months or so, but it does mean that the conditions are in place for a stall to be a significant possibility.

As usual, clicking over and reading will bring you up to the virtual moment as to the state of the economy, and reward me with a penny or two in my pocket for gathering and organizing the information for you.