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Two real economic consequences of the Trump presidency

Two real economic consequences of the Trump presidency

Next week we will be 1/3 of the way through Trump’s Presidential term. Last year I used to point out that it was really still Obama’s economy, as the GOP had failed to pass, nor Trump commence, any economic policy of consequence.

That is no longer the case.

In late December the GOP Congress passed and Trump signed their huge giveaway for the wealthy. Yesterday, Trump pulled out of the Iran nuclear deal. Both of these are going to have significant consequences for average Americans.

First, Trump’s election caused interest rates to spike. Wall Street guessed that there would be lots more business spending, meaning a stronger economy with higher inflation. As nothing much happened in 2017, interest rates settled back down somewhat.  But then in late December the tax bill was passed, and shortly thereafter interest rates spiked to five year highs:

Figure 1

As I write this, 10 year Treasury yields are back over 3%. More importantly, mortgage rates are also at 5 year highs:

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March JOLTS report: powerful further evidence of a taboo against rasing wages

March JOLTS report: powerful further evidence of a taboo against rasing wages

The March JOLTS report this morning is powerful further evidence that raising wages (or training new workers) has become a taboo.

Just about everyone thinks that, faced with a worker shortage, “rational” employers will offer higher wages to fill the empty skilled positions. This in turn will draw more marginal potential workers into open unskilled positions.

That’s the theory, anyway.

What is really happening — as so breathtakingly shown this morning — is that by and large employers will refuse to raise wages, and then complain about their unfilled job openings.

As Exhibit “A,” I give you job openings (blue) vs. actual hires (red) in this morning’s report:

As a refresher, unlike the jobs report, which tabulates the net gain or loss of hiring over firing, the JOLTS report breaks the labor market down into openings, hirings, firings, quits, and total separations.
Not only has hiring been flat for the last 10 months, but it was higher than today’s level in November 2015, January 2016, and January 2017. Meanwhile job openings have skyrocketed by 20% since January 2017, and 25% since the end of 2015!This can only be considered a “skills mismatch” for the wages you want to pay, and if you refuse to train workers without existing matching skills.

Incidentally, Paul Krugman may be ready to embrace the idea of a taboo against raising wages, although for now he is plumping for the “employers are afraid of getting stuck with a highly paid workforce when the next recession comes” hypothesis. The problem with that particular hypothesis, though, is that such skittish employers — a lot of them anyway — won’t bother to post new job openings, since they know they would need to raise wages to fill them. The big spike in openings in this morning’s report suggests instead that employers are refusing to get the message.

Turning to other noteworthy items in the report, as a general rule, historically hiring leads firing.  While the one big shortcoming of this report is that it has only covered one full business cycle, during that time hires have peaked and troughed before separations. This is manifest when we compare hiring (red) and total separations (blue) on a quarterly basis as it existed through the end of the third quarter of 2017:

Here is the monthly data through this morning’s report for the last several years:
The updated graph shows hiring last making a peak in October 2017.  Meanwhile separations actually peaked before then, in July of last year, with a clear downtrend since, another significant revision since last month. *if* both have made their expansion highs, needless to say that would be important.
Further, in the previous cycle, after hires stagnated, shortly thereafter involuntary separations began to rise, even as quits continued to rise for a short period of time as well:
[Note: above graph show quarterly data to smooth out noise]Here are voluntary quits vs. layoffs and discharges on a monthly basis for the last 2 years:

If hiring and total separations have indeed peaked for this cycle, based on the last cycle I would expect quits to continue to improve for a short while — and they have — before also beginning to decline. As a counterpoint to that, separations have approached their bottom, a very good sign.

And indeed, I don’t even see a yellow flag until hires and separations go negative YoY, as they did before well before the last recession, which they haven’t yet:

Two months from now when the YoY comparisons get much harder, if we haven’t established any new highs in hires and total separations, and they are at or below zero — which is a real possibility — then we may have confirmation of a late-cycle trend.

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The simple jobs and interest rates model generates a yellow flag

The simple jobs and interest rates model generates a yellow flag

Several months ago, I started toying with a simple model of interest rates and job growth.* Based on the historical evidence, I suggested that:

1. a YoY increase in the Fed funds rate equal to the YoY% change in job growth has in the past almost infallibly been correlated with a recession within roughly 12 months.

Figure 1

2. the YoY change in the Fed funds rate (inverted in the graph below) also does a very good job forecasting the *rate* of YoY change in payrolls 12 to 24 months out.

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Gimme shelter Q1 2018 update: rents and house prices all at or near new extremes

Gimme shelter Q1 2018 update: rents and house prices all at or near new extremes

This post is a comprehensive update as to the cost of new and existing homes vs. renting, all measured compared with median household income. As such it is epistolary in length. So here is the TL:DR version:

  • as a multiple of median household income, new home prices are at an extreme beyond even the peak of the housing bubble, while existing home prices are about 5% under theirs
  • but unlike then, when apartment vacancies were high and rents cheap, now rents are *also* at an extreme as compared with median household income
  • even with their recent increase, interest rates are still lower now than during the housing bubble, so the median monthly mortgage payment adjusted for median household income is even still about 10% less than it was at the peak of the housing bubble
  • if the trends of rising prices and interest rates continue, at some point they will overcome the demographic tailwind of the large Millennial generation having reached typical home-buying age. At that point there may be another deflationary bust

Half a year ago I wrote a long post discussing “the real cost of shelter,” by which I meant not just the downpayment on a house, but the monthly carrying cost for a mortgage, and comparing both of those with median rent.

That comparison showed that, while the “real” cost of a house downpayment was at a new high, the “real” cost of median asking rent was even higher. By contrast, the monthly carrying cost of a mortgage was quite moderate. This meant that, if a buyer could find a way to put together a downpayment, home-owning was a bargain compared to renting.

As I’ll show below, six months of price and interest rate increases later, there is even more stress on both homebuyers and renters.

By way of a quick recap, I wrote six months ago that I had never seen a discussion of the relationship between the relative cost of homeownership vs. renting, particularly as a function of the household budget. The choice (or ability) to live in the residence one desires isn’t a matter of its cost by itself, but also the relative cost of the type of residence. What is the cost of a house compared with the cost of an apartment? How expensive are each of them compared with a household’s income? If both are too expensive, maybe the choice is made to live with mom and dad as an extended family.

So, here are the three relationships I’ll look at again in this post

1. the “real cost” of a downpayment on a house.
2. the “real cost of renting
3. the “real monthly carrying cost” of a mortgage

The best metric for calculating these “real” costs on a household is median household income

1. The “real cost” of a downpayment on a house

In order to generate the “real cost” of buying a house, the best way is to compare the median household income with the median house price.

One drawback is that the Census Bureau only publishes median household income annually in September — so there is as much as a 21 month lag. Here’s what the most recent data — through 2016! — looks like:

Figure 1

The good news is that Sentier Research published monthly estimates based on the Household Survey into 2017. The bad news is that they discontinued this service a year ago.

The renewed good news is that the website Political Calculations has picked up the mantle and continued to estimate the monthly change in median household income. Here’s what that looks like as of their most recent update through February:

Figure 2

After I engaged in some correspondence with them, last week they updated their metric on “real” house prices making use of their monthly median household income estimates (NOTE: here nominal values are used for both median income and median prices):


While they use new home sales for their median house prices, we get the same result if we use the FHFA house price index:

Figure 4

Meanwhile, the median price for an existing home, which peaked at $230,000 in summer 2005, has continued to appreciate at nearly 6% a year this year:

Figure 5

If that pace continues, by this summer the median price will be about $280,000, 22% above the bubble peak. Since nominal median household income has increased about 25% over that same period of time, they will be only aabout $7500, or about 3% below their “real” bubble peak.

In short, no matter how you measure, in real terms house prices are at or near their most expensive ever, even including the peak of the housing bubble.

So, why haven’t home sales rolled over? Part of the reason is the demographic tailwind I discussed last week. Because Millennials of peak first-home-buying age now number about 15% more than the Gen Xers of 2005, a build-up that has grown year after year for the last decade, it presumably takes even more financial stress to overcome that tailwind.

But there are two other reasons why home sales haven’t turned negative yet: the relative (un)attactiveness of renting, and the monthly carrying cost of mortgage payments. Let’s look at each of them in turn.

2. The “real cost” of renting

Here is the median asking monthly rent for an apartment in the US since 1995 (note: the series goes back to 1988):

Figure 6

In 1988 the median rent averged $343 per month. In the first quarter of this year it was $954.

Now, here is what it looks like in comparison with median household income:

Figure 7

If house prices have risen to new highs several times since the turn of the Millennium, so have apartment rents — almost relentlessly.
In percentage terms, in 1988, the median rent for an apartment was 14.5% of median household income. That rose to slightly over 16% in the mid 1990s before falling to the series’ low of 13.7% in 2000. It had risen to a record 18.4% of median household income in the 2nd quarter of 2017, the last available data when I first published this piece.
Since then, the situation has only gotten worse. In Q3 median asking rent was 18.7% of median household income. In Q4 it was 18.6%. And in the first quarter of 2018 it rose to 19.3%!
Note, by the way, that even if we make use of the metric of “rent of primary residence” from the monthly CPI report, which I think has been underestimating rent increases (because both Zumper and Rent Cafe, two private measures, are much more in accord with the surge in “median asking rent”), we see that rent increases have outpaced median household income, which over the same period of time has risen about 220% nominally:

Figure 8

So one very big difference between the present situation and that at the peak of the housing bubble is that renting was a *much* more attractive option 12 years ago than it is at present.

3. The “real monthly carrying cost” of a mortgage

A second big difference between the present and the housing bubble is that mortgage interest rates generally ranged between 5.5% and 7% then, but quickly fell below 5% in this expansion, all the way to a low of 3.3% in 2013:

Figure 9

Recently they have risen significantly.

With that in mind, let’s take a look at the monthly cost of living in a house. The below graph shows the median monthly mortgage payment for a house  (blue) compared with median household income (red). Median monthly mortgage payment is calculated by using the median house price and the 30 year mortgage rate for each quarter, and consulting an amortization table using those values. This is done by showing the percentage of median monthly income (1/12 of the annual) that one month’s mortgage payment consituted (note: I am assuming a 10% down payment, with 90% mortgaged to be consistent. Using a different down payment does not change the shape of the comparison at all, only the nominal values):
Figure 10

Last year, when I first posted this metric, the monthly payment for the median house wasn’t extreme at all, but rather very moderate in terms of the long term range.

  • Going back to 1988, the median mortgage payment was slightly over 40% of median monthly household income.
  • This fell back under 28% at the end of 1998 before rising to 32% in 2000.
  • After falling briefly, at the peak of the housing bubble in 2005 it had risen to 31.4%, and actually reached a secondary peak in Q2 of 2006 of just over 35% of median monthly income.
  • At the bottom of the bust at the end of 2011 it made a new low of 23%.
  • As of Q2 of last year, the median monthly mortgage payment was still less than 24% of median household income.
  • BUT, with the increase in both house prices of over 5% YoY, and the increase in mortgage interest rates to 4.28% as of Q1 2018, that has now risen to 29.5%

Mortgage payments for new buyers in 2018 and not nearly so moderate as they had been earlier in this expansion. But they are not yet at the extremes they were in 2005 and 2006.

4. Comparing rent and mortgage payments

In our final comparative graph, let’s see how median monthly rent compares with median monthly mortgage payment:

Figure 11

The overall trend in the last 30 years has been that monthly mortgage payments have fallen from over 3 times median rent to about 1.5 time median rent now. Put another way, even at the peak of the housing bubble, the monthly carrying cost of a house was about 2.3 times the median cost of renting an apartment. At the bottom of the bust, that fell to 1.4 times the cost to rent. For the last five years, monthly mortgage payments have hovered near 1.5 times the median asking rent.

What is particularly noteworthy is that *even with* the recent big increase in mortgage payments, rents have also increased so much so that the 1.5 ratio still holds.


By comparing the “real” cost of housing to renting, both in terms of down payments and monthly mortgage payments, we can make sense of some of the biggest trends in the market for shelter.

Record down payments are keeping an increasing number of prospective buyers, especially first time buyers, shut out of the market for buying a house. An enormous number are living in apartments instead. This explains both the multi-decade lows in the homeownership rate as well as the recent 30 year lows in the apartment vacancy rates, as a disproportionate number of adults are forced out of home ownership and into apartment dwelling.

But even with the recent increase in mortgage payments, in relative terms they are still lower than they were at the peak of the housing bubble, and a relative bargain compared with their historical multiple of rental payments. In short, if one can get past the down payment, home ownership still looks like the better choice.

Along with the demographic tailwind, the *relative* inexpensiveness of monthly mortgage payments vs. rental payments goes a long way towards explaining why single family home construction has continued to increase in the face of higher mortgage rates.

That being said, with increasing financial stress showing up across the board in the costs of both buying and renting, we can only expect to see even more involuntary extended family households and involuntary unrelated housemates. Further, *if* interest rates and housing costs increase much further — most importantly, if home builders continue to focus on only the most expensive segment of the market — at some point they will overwhelm the increased numbers of home-buying age Millennials who have been buoying up the market. Sales will turn down, followed by home values, leading to another deflationary bust.

[Special thanks to Mike Kimel for preparing the customized comparative graphs used in this article.]

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March 2018 personal income and spending

March 2018 personal income and spending

Programming note: I’ve been working on a mega-post about housing, that is now complete except for a few graphs. So, please excuse the brevity otherwise.

March 2018 real personal income and spending were both positive. So far, so good.

The personal saving rate fell slightly:

Again, this is consistent with a late cycle dynamic where consumers are more stretched than they were earlier in the expansion.

Real personal spending continues to outstrip real retail sales (quarterly to reduce noise, through Q1 in the graph below):

This is also a typical late cycle dynamic (a relationship that holds for 10 of the last 11 expansions).  But since neither shows signs of significant declines, there is no imminent danger of a downturn.

As has been the case for the last several years.

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Don’t sweat the Q3 2017 job losses

 by New Deal democrat

Don’t sweat the Q3 2017 job losses

As an initial matter, this is a good time to remind you that the data is the data is the data. It’s not partisan. I’ve seen some of the same people who were touting “It’s still Obama’s economy” all last year (and I agree with that) now suddenly saying that the Q3 BED job losses show that “the Trump/GOP economy is tanking” No, they don’t.
The big flashing red neon sign is in this state by state map (h/t Bloomberg):

While job losses in Michigan and Ohio might not be so unexpected, for major job losses to happen in Florida sticks out in the data like a sore thumb.

Yesterday the BLS issued its report on Q3 2017 Business Employment Dynamics. This has gotten some notice because, for the first time in 7 years, it showed a net loss last summer of -140,000 jobs.
While hurricanes and wildfires occur every summer, last year was a particularly bad one.  And a look at the three states most directly involved — Florida, Texas, and California — tells us exactly what happened. The BLS appended a note expressly stating that they did not adjust for this.
Here’s a chart of the net job gains and losses over the last 5 quarters for each of the 3 affected states. The last line is the net change compared with the previous quarter:
Quarter   FL          TX       CA
Q3 2016  112.9     76.2   110.0
Q4           42.0       50.1    70.0
Q1 2017  35.9       61.0    90.3
Q2           37.8       48.9    45.3
Q3          (-133.5)   16.0    24.3
NET        (-171.3)   (-32.9) (-21.0)
The net loss of -171,300 jobs in Florida alone compared with the previous quarter exceeds the net nationwide loss of -140,000.  Add in the other two states affected by unusually severe disasters and you get a net loss of -224,200 jobs.
Does anyone seriously think the Florida economy suddenly went to hell in Q3 of last year in any cyclical manner? Of course it didn’t.
So I’m not putting too much stock in this report.
By the way, remember that initial claims shot through the roof for a month after the hurricanes:
This morning they made a new 48 year low, at 209,000. Wow!
When The End is really Near, I’ll tell you. If my systems are right, hopefully about a year in advance. If the economy is left to its own devices, The End is not Near now.

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Q1 2018 GDP downshifts slightly; long leading indicators mixed

 by New Deal democrat

Q1 2018 GDP downshifts slightly; long leading indicators mixed

This morning’s preliminary reading of Q1 2018 GDP at +2.3%, down from the previous quarter’s +2.9%, was generally in line with forecasts.  As usual, my attention is focused less on where we *are* than where we *will be* in the months and qatter will not be released until the second or third revision of the report, I make use of proprietors’ income as a more timely if less reliable placeholder.
So let’s take a luarters ahead.
There are two leading components of the GDP report: real private residential investment and corporate profits. Because the look at each.
Real private residential fixed investment was flat (blue). Measured by the more precise method of its share of the GDP as a whole (red), residential investment actually declined:
According to Prof. Edward Leamer, this typically peaks about 7 quarters before the onset of a recession. As it has not made a new high since four quarters ago, and must be considered a signficant leading indicator of recession at this point.

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Demographics, housing, and the economy

Demographics, housing, and the economy

Way back during the Great Recession, I first noted that demographics were about to become a tailwind for the housing market. The argument, in its simplest terms, is that the median age of first time home buyers is about 30, and the nadir of the “baby bust” was 1973-76. That means that the demographic nadir of the population of first time home buyers who ultimately drive the market (since everybody else just moves up from one house to another) was in the 2003-06 period.

Yesterday I started looking into quantifying that tailwind. Without getting into too much detail, my suspicion is that it has amounted to an increase in the pool of potential first buyers on the order of roughly 250,000 households per year since 2010 — i.e., the increase of each year over the year previous, continuing year after year. That’s just a back of the envelope approximation.

Lo and behold, Bill McBride a/k/a Calculated Risk posted on a similar subject yesterday, opining that the demographic tailwind was likely to continue for years for both housing and the economy generally, concluding that “My view is this is positive for both housing and the economy, especially in the 2020s. “Then Mike Shedlock a/k/a Mish responded with regard to housing, opining that “On the surface, the demographic trends may appear neutral or slightly favorable…. [but] For now, and the next five years, attitudes and affordability are the key issues. They far outweigh any potential demographic benefit, if any.”
Who’s got the better argument? Because historically we’ve been around this block before, in a pretty big way. You may have heard of it: it was something called the “baby boom.”
In my opinion that history gives us a pretty definitive answer.
Let’s start with the demographic history. Here’s a graph of live births for each year since 1900:

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The consumer edges closer to the precipice

The consumer edges closer to the precipice

In addition to my “long leading/short leading” model adapted from the work of Profs. Geoffrey Moore and Edward Leamer, and the “high frequency” weekly variation on the same, I also have several “alternate” recession forecasting models. The most noteworthy model is really a consumer nowcast. It turns on consumers running out of options to to continue increasing purchases (i.e., no interest rate financing, no wage real wage increases, and no increasing assets to cash in). When that happens, and consumers turn more cautious by saving more, a recession begins.
I first posted the model 10 years ago under the title, “Are Hard Times Near?  The great decline in interest rates is ending.”  The history is straightforward.  Since the 1970s, real average hourly earnings had declined.  Average Americans coped by spouses entering the workforce, by borrowing against appreciating assets, and by refinancing as interest rates declined.
By 1995 the spousal avenue peaked.  Borrowing against stock prices ended in 2000.  Borrowing against home equity ended in 2006.  When interest rates failed to make new lows, the consumer was tapped out, and began to curtail purchases.  A recession began – and its effects lingered for a long time. “Hard Times” had indeed begun.
What does the consumer model show now? I haven’t updated it in about two years, and there have been noteworthy developments. Let’s take a look.
Real hourly wages haven’t increased since last July, are up only 0.1% YoY and barely more in the past two years:
According to Ironman at Political Calculations, real median household income has declined slightly  for nearly two years:

Mortgage rates haven’t made a new low since 2013, and if anything are trending up, on the verge of breaking a 30 year trendline:

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Higher wage growth for job switchers: more evidence of a taboo against raising wages?

Higher wage growth for job switchers: more evidence of a taboo against raising wages?

Yesterday the Atlanta Fed published a note touting the wage growth for those who quit their jobs and transfer to a different line of work, writing that:

Although wages haven’t been rising faster for the median individual, they have been for those who switch jobs. This distinction is important because the wage growth of job-switchers tends to be a better cyclical indicator than overall wage growth. In particular, the median wage growth of people who change industry or occupation tends to rise more rapidly as the labor market tightens.

The following graph was posted in support of this point:
Essentially the Atlanta Fed is highlighting the orange line as a “better cyclical indicator.”
Is it? There’s no doubt that wage growth among job switches declined first in the last two expansions. But I would want to see a much longer record before being that confident.
Because what I see in the above graph is a decline among job keepers (the green line) that is only matched by those declines presaging the onset of the last two recessions. Meanwhile the orange line, while still rising, has flattened.
In fact I think the Atlanta Fed’s graph mainly shows evidence of what I highlighted last week as an emerging “taboo” against raising wages — i.e., a stubborn refusal to raise wages even if it would lead to even higher output and gross profits for a net gain.
Once again the JOLTS data gives us a good proxy.  If wage growth is increasing at a “normal” rate compared with previous expansions, there shouldn’t be an inordinate need to change jobs in order to get a raise, i.e., a rate higher than previous expansions. Thus the ratio of job changers who quit vs. the number of actual hires should be equivalent to similar stages in those expansions. If, on the other hand, employers have become inordinately stingy, quitting is almost essential to get ahead, in which case the ratio of quits to hires should be higher than normal.
Here is what the data shows:
For the last several years, Quits have been in the range of 58%-60% of hires, the highest since 2001, and specifically higher than the 56%-58% peak of the last expansion.
In other words, it looks like what the Atlanta Fed’s graph is showing is that employees are reacting to the taboo against raising wages by quitting their jobs and moving to employers in fields that are already paying more.

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