Sunday, September 24, 2017

A thought for Sunday: the most important issue in the 2016 election was . . .


 - by New Deal democrat

This is a post I've been meaning to write for several months. For a while after the election last year, there was a debate about whether the "economic anxiety" in the (white) working class was the most important factor vs. was it simply a matter of racism. The consensus has nearly settled on the narrative that racism was decisive, to the point where "economic anxiety" has become a taunt, and some who embrace identity politics actively disparage progressive economic issues.

I'm here to show you data that - in part - disputes that consensus. What was the most important issue in the 2016 presidential election?  The below data on that issue all comes from the Voter Study Group, from its survey published several months ago: "Insights from the 2016 Voter survey."  

In the below graphs, the potency of various issues are examined in terms of how well they lined up on a liberal/conservative or favorable/unfavorable axis, but for simplicity's sake it is pretty clear that they correlate with a vote for Clinton (left) or Trump (right).  The more vertical the line, the more decisive the factor, whereas a horizontal line means that the factor made essentially no difference in whether a vote was for one candidate or the other.  the 2016 results are in red, vs. the 2012 results in gray. What I've done is to delete the names of the nine factors they tested, so you won't be swayed by any pre-existing opinion you might have had about the factor.  Here they are:   



I'll give away one finding right away.  The most decisive factor, shown at the right of the lowermost column, is party affiliation. D's voted for Clinton. R's voted for Trump.

But after that, it's pretty clear that the close runner-up for most decisive factor in how people voted is the issue at the left of the middle column, which was ...



the economy!

That's right. The single most decisive factor in the 2016 vote was how people felt about the economy.

How can that be true?  After all, haven't we all heard that racism was dispositive?

The clue is in the difference in slope between the red and gray lines.  Even though the economy was the single most important issue in 2016, it was relatively *less* important than it was in 2012. Graphically it was less vertical in 2016 than 2012. And the difference disfavored democrats.  The economy was equally dispositive for conservatives, but less dispositive for liberals. Put another way, economic progressives voted less in lock-step on the economy in 2016 than they did in 2012.

And where did those votes go in 2016?  The three issues in the top column, and especially the issue at the top left.

But let's take them in reverse order.  The issue at the top right is nearly horizontal -- i.e., it made little difference to voters, but while it didn't motivate progressives at all, it did have a slight affect on conservative votes compared with 2012.  That issue is:



attitudes towards Muslims.

The issue at the top middle had some effect both in 2012, but moreso in 2016. It motivated both conservatives and progressives, but conservatives relatively more.  That issue is:



attitudes towards black people.  There more than anywhere is your racism, and while the issue did drive progressive voters to Clinton, it drove even more racist voters to Trump. 
   
This is an unfortunate dynamic for the left.  What it appears to mean is, both progressives and conservatives were motivated by the "Black Lives Matter" movement and protests against police violence. But while the protests may have convinced some progressives, they drove EVEN MORE CONSERVATIVES to harden, and act on, their racial views.  In other words, in electoral terms the protest movement was actually COUNTERproductive.

Finally, here is the social issue (top left among the nine) which most drove voter behavior in 2016 compared with 2012:



attitudes towards immigration. Note that, it too motivated both progressives and conservatives, and it too was more decisive in voting behavior on the right than on the left.

To get to the heart of the matter, it wasn't racism per se which drove the electoral college victory to Trump. It was Xenophobia, and anger in particular directed at illegal aliens. While probably about half of the Muslim immigrants to the US come from countries in the Middle East and are white, many also are from places like south Asia and are not white. Yet feelings about Muslims barely moved the needle.

Further, if it were racism per se which was most dispositive, we would expect to see a bigger correlation with feelings towards black people than feelings towards immigrants. Not only was that not the case, but the *reverse* was true.

In an article only a week after the election, Loren Collingwood wrote in the Washington Post that:
 I also found evidence consistent with the "racial threat" hypothesis. As shown by the orange dotted line in the graph, Trump’s vote was higher in counties where the number of Latinos has increased significantly since 2000. This suggests that some voters may have supported Trump as a way of expressing white identity in an increasingly diverse nation. 
... Trump also did better in counties experiencing a loss in manufacturing since 2000.
Here's her graph: 

It's worth noting that the unemployment rate among Latinos (I'm using men in the non-seasonal adjusted graph below) has declined further - from an admittedly higher peak -  in this expansion than that among whites:


At the height of the tech boom in 1999, male Latino unemployment was 1.3% higher than that of white males. In 2006 and again in June of this year, it was only 0.1% higher.

Since roughly 11 million, or 1/4 of the total Latino population, are illegals/undocumented workers, it is not difficult to imagine whites (and maybe some blacks) seething that illegals have taken some of their jobs, in a very long and still-incomplete recovery. Is that "economic anxiety" or racism or Xenophobia, or both?
A similar dynamic about the volume and nature of immigation, by the way, appears to be behind the big decline in the center left Social Democratic parties of Europe. 

Further, I wish I had kept the cite, but I recall reading stories of white working class voters who went to Trump rallies and participated in all of the chants, who supported him in part because they didn't take his racial rhetoric seriously.  They treated it as all part of the show. The distinction is worth emphasizing -- if I am a minority, I may not like a person who is willing to overlook that racial rhetoric, but it is different from a person who actually *agrees with* that racial rhetoric. More succinctly, if it comes down to whether you win or lose political power, you may be dead set against compromising with the latter, but what about the former?

I think there are three big lessons here for future elections: 
  1. Even if you want to embrace the importance of social issues, you simply cannot ignore the economy,  which remains the single most important issue to most voters. As I have pointed out a number of times, econometric models did a very good job in 2016 forecasting a narrow popular vote advantage for the incumbent party.
  2. Social issues should not be highlighted in ways which drive your supporters to the polls, but drive your opponents to the polls even more.
  3. While I unequivocally support a path to legalization, and ultimately citizenship, for DREAMers, it is crystal clear from the experiences in both the US an d Europe that progressive parties have to come to grips with reasonable restrictions on immigration, and enforcement of, immigration laws.

Saturday, September 23, 2017

Weekly Indicators for September 18 - 22 at XE.com


 - by New Deal democrat

My Weekly Indicators post is up at XE.com.

The biggest news was in purchase mortgage applications, hurricane adjusted jobless claims, and stock prices.

Friday, September 22, 2017

On August housing permits and starts, curb your enthusiasm


 - by New Deal democrat

Hurricanes Harvey and Irma together affected over 10% of the housing market at minimum. That's one of three good reasons to take the good permits number with a grain of salt.

This is a two part post I have up at XE.com.

Part 1 is here.
Part 2 is here.

Thursday, September 21, 2017

Hurricane adjusted initial jobless claims for the week of September 9: 229,000


 - by New Deal democrat

I am repeating an exercise I undertook in 2012 when Superstorm Sandy disrupted the initial claims data: estimating what the initial jobless claims would have been, but for the hurricanes.

In 2012 I created that adjustment by backing out the affected states (NY and NJ) from the non-seasonally adjusted data.  That gave me the number of initial claims filed in the other 48 states.  I compared that with the same metric one year earlier, and multiplied by the seasonal adjustment.

That gave me the number if the affected states had the same relative number of claims during the given week, as all of the unaffected states.  In 2012, it showed that Sandy was not masking any underlying weakness in the economy.

The state by state data is released with a one week delay.  So what follows is the analysis for the week of September 9, the number for which was reported one week ago and revised this week to 282,000. Last week I found the adjusted number for September 2 was 239,000.  Last week I only had to back out Texas, but this week I have also backed out Florida.

Here is the table for the Week of September 10 in 2016 vs. September 9 this year:

Metric                              2016                   2017
Seasonally adjusted:       258,000              282,000
Adjustment for total:       1.33                   1.33
Not seasonally adjusted:  193,291             212,284 
Florida claims:                 7,493                 4,773 (!!! - yes, a decline this year)
Texas claims:                   13,432               52,024                
NSA claims ex-TX+FL    202,008             155,487
TX+FL as % of total:       10.8%                   n/a
2017 w/ TX+FL adjustment:  n/a              172,280

In both 2016 and 2017 the weekly seasonal adjustment was 1.33. Multiplying the non-seasonally adjusted total of 172,280, gives us the hurricane-adjusted initial jobless claims number for the week of September 9, 2017 of 229,000.

The underlying national trend in initial jobless claims remains very positive.

Wednesday, September 20, 2017

The asterisk in real median household income


 - by New Deal democrat

This is a follow-up to the post I wrote last week about the latest data on real median household income.

One of the things I notes is that "households" includes the millions that are composed of retirees, a burgeoning demographic due both to healthier longevities and the demographics of the Boomer generation.

This morning Jared Bernstein helpfully includes a graph of real median household income excluding those over age 65:



Households headed by working age adults did finally surpass their 2007 income, but were still 3.4% below the all-time highs of incomes of 2000.

But mainly I wanted to follow up on that break in the graph in 2013.  It was caused by a change in methodology by the Census Bureau.

Here's the graph I ran last week of real median household incomes at various quintiles and deciles:



So I was surprised a few days later to see another, more pessimistic graph floating around, purporting to show that only the top 20% of households had higher incomes than in 2000:



Note that this graph doesn't have any break. 

I traced the information back to its source, which turned out to be the Economic Policy Institute. And at the bottom of their article, I found a footnote explaining thus:



In other words, as best I can tell the E.P.I. simply took the 3.2% difference in the two methodologies in 2013 and projected it forward.

Now, let me state right up front that I don't know whether the data as represented by E.P.I. is correct or not.

But, neither does the E.P.I.

In fact, neither does anybody else, apparently including the Census Bureau itself.

That's because the Census Bureau hasn't provided data in any year since 2013 as to what the numbers would have been under their old methodology, so that we can form a basis of comparison.

By contrast, when the methodology for "real retail sales" was updated in the 1990s, the old data series continued to run for nearly 10 years, giving us an excellent basis for comparison, and confirming that the YoY changes were virtually identical, meaning that we can stitch the two series together confidently, giving us 70 years worth of data:



The Census Bureau didn't do that with real median household income, so there will *always* be a disconnect and a lack of ability to reliably and directly compare data from before 2013 with data afterward.  We'll always be guessing. 

This is a major problem for this important data series, and the Census Bureau should take steps, to the extent possible, to correct it.

Tuesday, September 19, 2017

Hurricane workarounds for industrial production and housing


 - by New Deal democrat

Hurricane Harvey has already affected some of the August data releases.  Irma has already started to affect some weekly releases, and will undoubtedly affect the September monthly releases.

I have already begun to adjust for the hurricanes in the case of initial jobless claims.  But what of the monthly data?

While there is nothing so timely and precise as backing out affected states from the initial jobless claims report, there are workarounds that can at least tell us if there has been any significant change in trend for both the industrial production and housing reports.

I will put up separate posts, but to cut to the chase, we can use the Regional Fed reports (minus Dallas, and adding the Chicago PMI) to give us a reasonable estimate of industrial production in the non-hurricane affected areas. Similarly, we can make use the regional breakdowns in the housing report by subtracting the South and determining the trend in the remaining 60% of the country outside of that census region.  I have already looked at this morning's housing report, and it turns out the effect is not what you would think!  I'll have that post up by tomorrow.

Unfortunately there is no regional or state-by-state breakdown of retail sales or regional consumption expenditures on any sort of timely basis, so we're kind of stuck there.

Saturday, September 16, 2017

Weekly Indicators for September 11 - 15 at XE.com


 - by New Deal democrat

My Weekly Indicators post is up at XE.com.

The effects of Hurricane Harvey have shown up in a number of data series, but the underlying trends are intact.

Friday, September 15, 2017

2.5 cheers for 2016's new high in real median household income!


 - by New Deal democrat

Given that I consider jobs and wages for average Americans my #1 focus, it's only fair that I write about this week's release of the real median household income for 2016, don't you think? 

A few years ago I wrote that real median household income was the most misused statistic in the entire econoblogosphere.  That's because: 

  • it is NOT a measure of real wages.  It includes all income -- things like pensions, dividends, and social security.
  • it includes ALL households, not just those headed by workers. A household of full time students is included.  Your 85 year old grandparents are included. A household where one or more persons is unemployed is included.  A household where one spouse stays home to raise the children is included.
  • it is subject to distortions from demographics.  In particular, since retirees tend to have only about half the income of households headed by wage or salary earners, as the percentage of households headed by retirees rises (due to both healthier longevities and Boomer retirements), downward pressure is placed on the median. Below is the graph of current US demographics, showing the barbell effect of young Millennials and old Boomers bracketing the smailler Gen X:



Another problem with the metric is that it is only reported once a year, and with a nine month delay to boot. So this week's data release tells us what household income was for the period of 9 to 21 months ago! Not exactly timely.

Fortunately, there are several ways to get more timely data.

First of all, a decent back of the envelope estimate can be made by taking average hourly wages, which are reported monthly, multiplying by the number of hours worked, also indexed monthly, and dividing that by the entire population age 16 and over. It's an average, rather than a median, and it won't give you an exact number but will give you the overall trend.

Even better, Sentier services calculates an estimate of actual median household income monthly based on the Household Survey reported each month by the Census Bureau (that's the report that gives us, e.g., the unemployment rate). Doug Short has done excellent work putting this in graphic form each month.

Back before the big decline in gas prices had the result of driving real, inflation-adjusted wages to new highs, I would constantly read how real median household income showed that wages were actually declining. That was hogwash.  Now that real wages are at new multi-decade highs, there's a whole new round of hogwash!

But, enough background. Let's turn to the actual numbers.  

As you no doubt already know, real median household income at long last made a new all-time high in 2016, finally surpassing its previous highs in 2007 and 1999:



That is unadulterated good news.

Further, the official Census Bureau number was very much in line with Sentier's monthly reports for 2016. Here's Doug Short's aforementioned graph:



The average number for the 12 months of 2016 was higher than any previous year. This is the second year in a row that the very timely monthly reports by Sentier showed strong increases in real median household income, and were later confirmed by the official numbers. In other words, Sentier has a very trustworthy record and you should be paying attention if you care about this metric.

Digging a little deeper, here is how real median household income as broken down by quintiles, as well as the top and bottom 10%, since its previous 1999 peak (h/t Wall Street Journal):



The bottom two quintiles have still not made up all of the ground lost since 2000, although the top 50%-60% have.  On the contrary, the very top 10% have been doing extremely well (which has led to some earth-shaking political consequences on both the left and right).

Another legitimate caveat is that the Census Bureau changed its methodology 3 years ago, and regrettably has not published its results for both methodologies in order to create a baseline correlation for future use.  We know that three years ago, the change in methodology made the number *for that year* about 3.2% higher. Hence the break in the lines at that time period.  Is there a similar issue with regard to this year? Nobody knows for sure. But, yes, because of this we do have to put an asterisk next to the claim that 2016 was a new all-time high.

Yet another legitimate caveat is that real median household income for men only is still below its peak from the early 1970s (h/t Mike Shedlock):



All of the peaks since then, including the new peak for 2016, are in part because women entered the workforce, and thus the income of households where both spouses work has gotten higher.  But of course this is a real tradeoff if one of the spouses would prefer to stay home and raise the kids, but feels they have to work to make ends meet.

It is also perfectly fair to point out that the new highs in income last year don't do anything to erase the many years of lesser income in particular since the beginning of the Great Recession.  This means that median household *wealth* is still below what it would have been had we been at or near full employment for all of those years. In other words, the long-term well being of the median American household is still compromised.

Finally, it wouldn't be a true positive report without its very own batch of Doomer hogwash.  This year's hogwash is that the increase only happened because people had to work longer hours.  I'm not sure who originated it, but here are two links:  here and here, with the relevant quote:
[T]he Census Bureau data show that the bulk of the gains in real income in 2016 was explained by one factor: higher employment. In other words, hours worked rose but wages did not. The members of American median households are working harder at more jobs to finally get an increase in incomes.  
In other words, hIs logic runs: 
1. real median household income mainly rose because of more employment.
2. that means hours worked rose.
3. that means people were working more hours.
4. that means that household income really only increased because people had to work more hours for the same hourly pay.

Did you see what he did there?  He backed out the fact from line 1 when he got to line 3. Line 3 is true  in the aggregate, but he treated it as if it was true for most individuals in the set. The true line 3 is as follows:
3. that means that aggregate hours increased, due to unemployed people finding work, part-timers getting more hours, and some part-timers getting full-time employment.

Oh, that's a little different.

The bottom line is: 2.5 cheers for the new high in real median household income for 2016. That a majority of US households are earning more than that group ever did before is great news.  But, as evidenced by the last 15 years of this statistic, it by no means erases the long-term decline in the health of what used to be called the American middle class.

Thursday, September 14, 2017

Hurricane adjusted initial claims for week of Sept. 2: 239,000


 - by New Deal democrat

Last week I promised I would repeat an exercise I first undertook in 2012 when Superstorm Sandy disrupted the initial claims data: estimating what the initial jobless claims would have been, but for the hurricane.

In 2012 I created that adjustment by backing out the affected states (NY and NJ) from the non-seasonally adjusted data.  That gave me the number of initial claims filed in the other 48 states.  I compared that with the same metric one year earlier, and multiplied by the seasonal adjustment.

What that does is give me the number if the affected states had the same relative number of claims during the given week, as all of the unaffected states.  In 2012, it showed that Sandy was not masking any underlying weakness in the economy.

The state by state data is released with a one week delay.  So what follows is the analysis for the week of September 2, the number for which was reported one week ago. This week I only had to back out Texas.  Next week I will undoubtedly have to back out Florida as well.

Here is the table for the Week of September 3 in 2016 vs. September 2 this year:

Metric                              2016                   2017
Seasonally adjusted:       257,000              298,000
Adjustment for total:       1.18%                1.19%
Not seasonally adjusted: 217,715              250,621 
Texas claims:                     15,707                63,788
NSA claims ex-TX           202,008              186,833
TX as % of total:              7.2%                   n/a
2017 w/ TX adjustment:  n/a                      201,405

If we use the 2016 weekly seasonal adjustment of 1.18% for the adjusted 201,405 total, this gives us ~238,000.

If we use the 2017 weekly seasonal adjustment of 1.19% for the adjusted 201,405 total, this gives us ~240,000.

Thus the hurricane-adjusted initial jobless claims number for the week of September 2, 2017 is 239,000.

The underlying national trend in initial jobless claims remains very positive.

Tuesday, September 12, 2017

More JOLTS hard data weakness in July


 - by New Deal democrat

I have been a dissenter about the JOLTS reports for over a year (although, perusing the intertoobs yesterday, it looks like a few more observers have joined the chorus). The typical commentator has focused on job openings (blue in the graph below), which have been trending higher strongly (as they did in yesterday's report for July): 



But openings are the one aspect of the report that are not "nard" data. They can just as easily be skewed by employers trolling for resumes, perhaps laying the groundwork for visas for cheap immigrant labor, or simply refusing to offer the wage or salary that would call forth enough actual applicants to hire. 


Hence the disconnect between "openings" and "hires," (red in the graph above), which have been barely above stagnant for the last year.  Here is the YoY trend for hires:




Thus I prefer to focus on the "hard" data series such as hires, quits, and layoff, where the story hasn't been nearly so strong.

Let me start by comparing hires to total separations (averaged quarterly to cut down on noise):





We only have one full business cycle to compare, but since the outset of the series at the start of the Millennium, the trend has been for hires to slightly lead separations. In the quarterly view, hires have been stagnant for going on 2 years.  Here is the monthly view of the last few years:




In the last three months, hires have picked up somewhat - although not to new hiighs, unlike separations, which *are* at new highs.

Let's further compare historical hires with voluntary quits and also layoffs and discharges. Here we see that in the last cycle, hires stagnated, and shortly thereafter involuntary separations began to rise, even as quits continued to rise for a short period of time as well:

 


Next, here is the current cycle, quarterly through June:



Significantly, even while quits have continued to rise, involuntary separations bottomed a year ago, and have risen on a quarterly basis ever since.  Here's the monthly view of the last several years: 



The recent surge in layofs and discharges is actually similar in scale to that just before the last recession.


In short, just like the slowly decelerating YoY change in payrolls:




JOLTS shows an employment situation that, while still positive, is slowly decaying.

Housing (un)affordability: an unholy triad


 - by New Deal democrat

What is the problem with the housing market?  Is it unaffordable house prices? Rents?  Maybe both!

Which leaves only one other alternative.

This post is up at XE.com.

Monday, September 11, 2017

The Chicago Fed revises its Adjusted Credit Conditions Index


 - by New Deal democrat


Last week the Chicago Fed announced backdated revisions to its Adjusted Financial Conditions Index. Since this changes their interpretation somewhat, I wanted to flesh this out.

The Chicago Fed has a "Financial Conditions Index" which is self-explanatory, as well as several sub-indexes, one of which, the "leverage" subindex, it has identified as leading.  It also has an "Adjusted Financial Conditions Index," which is supposed to calibrate how loose or tight credit conditions are *relative to* background economic conditions --i.e., are financial conditions more or less tight than they have typically been given the data background.

Because the Adjusted Index appeared to track, and somewhat lead, the Senior Loan Officers Survey, and because it is reported weekly rather than quarterly, I report this Index every weekend.

The "updates" to the Index change its values considerably.  First of all, the new Adjusted Index is much less volatile, but also somewhat less leading:



Secondly, it no longer leads the un-adjusted index at all in terms of peaks or troughs, although it does appear to have higher (i.e., more tight) values in the several years leading up to recessions:



If we add +0.5 to the value of the updated Adjusted Index, and average it over a quarter, it does appear typically to lead the Senior Loan Officer Survey by one or two quarters, although note the exception from 2014-16:



With that modification (i.e., adding +0.5 to the Adjusted Index as the line between "loose" and "tight" credit conditions, I will continue to track it weekly as a long leading indicator of promise.

Saturday, September 9, 2017

Weekly Indicators for September 4 - 8 at XE.com


 - by New Deal democrat

My Weekly Indicators post is up at XE.com.

Harvey and Irma are going to wreak havoc with some of the numbes.

Friday, September 8, 2017

Are consumers on the cusp of rolling over?


 - by New Deal democrat

We can divide the long leading indicators into producer, consumer, and financial.

When we look at just the non-financial indicators, almost all of them are down.

This post is up at XE.com.

Thursday, September 7, 2017

A note on Hurricane Harvey and unemployment claims


 - by New Deal democrat

Initial jobless claims for last week were reported at 298,000 this morning, a jump of over 50,000 from recent levels.

As most people probably already know, this huge jump had everything to do with Hurricane Harvey shutting down southeastern Texas, including the entire 7 million Houston metro area. Undoubtedly, the effect will last for weeks.

Fortunately, if we want to know what jobless claims would be ex-Harvey, there is a way to figure that out.  Although I haven't felt the need to dwell on weekly claims for several years now, I'll start to calculate this again next week.

I did this before, in 2012, after Superstorm Sandy.  Here's how I described the process then
I wanted to try to find out how much of this morning's initial claims number was still due to Sandy. To do so, I checked the BLS breakdown of initial claims by states, which gives the unadjusted state-by-state initial claims numbers. I deducted NY and NJ, the two states most hit by Sandy, and compared the number as deducted with the unadjusted number minus NY and NJ this week one year ago. Since the seasonal adjustment should be almost identical, that should give me the "real" ex-Sandy initial claims number, assuming NY and NJ would, ex-Sandy, have layoffs at a similar rate to all the other states. 
To do the same thing for Harvey, I'll simply calculate the number for all states except Texas.  Because the state by state data is reported with a one week delay, that won't be until next week.

Of course, I might have to account for Irma and maybe even Jose in the next few weeks as well.  But, one bridge at a time . . . .

Tuesday, September 5, 2017

Comparing motor vehicle sales vs. real retail sales per capita


 - by New Deal democrat

I know, real clickbait-y headline, right? 

This week is about the lightest for economic data I've ever seen, with the discontinuance of the Labor Market Conditions Index, and JOLTS not due until Tuesday next week. So - hint - probably light posting.

But there are several trends that bear writing about, including the state of the consumer.  Consider this post a prequel to that broader subject.

In the past, I've identified motor vehicle sales and real retail sales per capita as somewhat long leading indicators. Motor vehicle sales can peak several years before a recession, and real retail sales per capita perhaps 12 months before, each with a lot of variation.  Of course, motor vehicle sales are a component of real retail sales, and have tended to "plateau" for lengthy periods in expansions, but is there any rhyme or reason as to which peaks first?  That's what I wanted to check.

Real retail sales data, in its current and prior iterations, goes back 70 years! That's a pretty rich monthly data source. Unfortunately, motor vehicle sales, by contrast, started to be reported in the late 1970s, and so includes only 5 complete business cycles. Thus any relationship has to be very lightly weighed. But it's still worth looking at.

Both can be noisy on a month to month basis, so I have averaged each quarterly. Below are real retail sales per capita (blue, left scale), and motor vehicle sales (red, right scale) divided over the last 40 years:




On a quarterly basis, in the last 5 business cycles, real retail sales per capita have never peaked before motor vehicle sales. Both peaked together twice, and twice motor vehicle sales peaked two quarters before.  In one case (the 1980s), motor vehicle sales peaked about 3 years before real retail sales per capita!

Here's a look at the monthly data for the last few years through July (so the 16.1 million August motor vehicle sales number isn't included):


If motor vehicle sales have made their peak for this business cycle (I think they have), that at least is consistent with the last five cycles. Should the three month moving average of real retail sales per capita decline for several months, I would consider that of more significant importance now (vs. earlier in this cycle) concerning the state of the consumer.

Monday, September 4, 2017

The single most important fact this Labor Day


 - by New Deal democrat

On Labor Day, highlighting the single most important secular problem in the US economy:



If there is a silver lining, it is that the hemorrhaging has stopped since the end of the last recession.

But we are long past the point where we need another corporate tax cut. We desperately need to increase Labor's share of our $17 Trillion economy.

Happy Labor Day!

-----

On a lighter note, in honor of Labor Day's end of summer cookouts, here is my nomination for best hot dog anywhere in the USA, from my hometown Niagara Frontier. Ted's Hot Dogs:




Charcoal grilled and properly blackened and made with high quality Sahlens weiners, not like those wussy boiled downstate NY abominations, or the salad-ified Chicago messes.

If you visit the Falls, after your obligatory stop for the original chicken wings, make sure you sample these hot dogs (and stop for some Beef on Weck as well).

Saturday, September 2, 2017

Weekly Indicators for August 28 - September 1 at XE.com


 - by New Deal democrat

My Weekly Indicator column is up at XE.com.

Interest rates have improved, while there are several cracks in transport.

Friday, September 1, 2017

The August jobs report smacked of late cycle deceleration


 - by New Deal democrat

As promised, here is my abbreviated and late take on this morning's employment report.

While the additions to temporary positions (a leading indicator for jobs overall), and construction, and manufacturing jobs were welcome, this report sure looked like late cycle deceleration.

The YoY% growth in jobs - a very un-noisy metric - declined again slightly:



The number of people not in the labor force who want a job shot back up:



Those who are involuntarily part-time went sideways:



On the (relatively) bright side, when we adjust both of these metrics by the working age population, the comparisons with the last two expansions aren't quite so weak:




Finally, what on earth is it going to take to get wage growth for nonsupervisory workers?



And, although I won't bother showing the graph, we didn't make any progress on either the unemployment or underemployment rate.

So while the good news is, I still don't see any actual downturn anywhere near in time, this employment report was another sign of late cycle deceleration.

Housekeeping note on the employment report.


 - by New Deal democrat

I will be running an errand when the employment report comes out at 8:30.

I will put something up at about 10:30 to 11 eastern time. It will be a little truncated, but I will hit the high (or low) points, and try to highlight a few things that are overlooked in other commentators' posts.

Thursday, August 31, 2017

Trickle-down, with the emphasis on "trickle"

Since the turn of the Millennium, a torrent of corporate tax cuts has resulted in a trickle of investment growth.
 - by New Deal democrat
This morning Dean Baker objects to:
the argument ... that reducing corporate taxes will lead to more investment and thereby greater wage growth in the future. The data from the last seventy years show there is no relationship between aggregate profits and investment.

As can be seen, there is no evidence that higher corporate profits are associated with an increase in investment. In fact, the peak investment share of GDP was reached in the early 1980s when the after-tax profit share was near its post war low. Investment hit a second peak in 2000, even as the profit share was falling through the second half of the decade. The profit share rose sharply in the 2000s, even as the investment share stagnated. In short, you need a pretty good imagination to look at this data and think that increasing after-tax profits will somehow cause firms to invest more
I was a little puzzled why Dean didn't differently scale the two series so it would be easier to see any leading/lagging relationship.  Further, since corporate profits are a long leading indicator, and nonresidential fixed investment is more of a coincident indicator, I was pretty sure that there would be a correlation.

To take a better look, I compared the YoY% changes in each, so that they would scale more equally.  Here's what that looks like divided into 1948-86, and 1986-present:




Sure enough, there is a leading/lagging relationship between the two. That doesn't mean that an increase in corporate profits *causes* more investment, it just means there is a correlation with a lag.

But also notice that, in the post-WW2 era, the two series move in similar scales: a 40% increase in profits tends to lead to something close to a 40% increase in investment.  From the 1980s to the present, a 40% increase in profits leads to a much smaller increase in investment on the order of 10%.

In other words, even if we take the strong case, and assume there is a causative relationship, when we scale the two series more equally, we see that there is a big difference between the post-WW2 era, and the era that began with Ronald Reagan's presidency:




Simply put, particularly since the turn of the Millennium, a torrential increase in corporate profits only leads to a teaspoonful of investment.

The same is true of wage growth. Since wage growth is pro-cyclical, it tends to peak at the end of expansions, well after corporate profits peak.  So there is a leading/lagging relationship on a *cyclical* basis. But *secularly,* corporate profits have increased while wage growth has gradually deflated:



At this stage of the economic expansion, under counter-cyclical policy, if anything we should be trying to run a fiscal surplus. As we have seen above, a corporate tax cut now will do next to nothing for ordinary Americans, and will recklessly blow out the budget at the exact wrong time.

Bottom line: we don't need even more profits for corporations.  We need to increase the share of wage growth relative to corporate profit growth.

Wednesday, August 30, 2017

A Quick update on Bonddad


 - by New Deal democrat

I had a long conversation with Hale Stewart this morning.

He says he has been incredibly lucky. He, his spousal unit, and his pooches are all fine.  They have had no flooding at all.

On the other hand, he says that metro Houston in general is a complete mess. It sounds like, once the water has finally receded, Houston 2017 might resemble New Orleans 2005.

Tuesday, August 29, 2017

Comparing the 2014 and 2017 housing slowdowns


 - by New Deal democrat

We  had an interest rate spike late last year similar to the spike in mid-2013.  In 2014 the resulting housing slowdown resolved positively.  Will it do so again this year?

This post is up at XE.com.

Monday, August 28, 2017

Notes on Harvey: if Karma could bring her litter to visit the Texas GOP



 - by New Deal democrat

First of all, as many of you already know, the M.I.A. proprietor of this here blog, Hale Stewart, resides in the Houston area.  I traded messages with him on Saturday, and as of then, he was doing OK.

Secondly, when Superstorm Sandy hit New Jersey and New York, Texas Republicans were prominent among those who opposed aid.  Ultimately aid was provided -- but not until 75 days after the storm. 

There were two Sandy-related aid bills.

The first bill granted FEMA a $9.7 billion increase to borrow for the National Flood Insurance Program. It passed the Senate on a voice vote, but the following Texas GOP Members of Congress voted against the aid:

Mike Conaway (Midland) 
Bill Flores (Bryan)
Louie Gohmert (Tyler)
Kenny Marchant (Coppell)
Mac Thornberry (Clarendon)
Randy Weber (Pearland)
Roger Williams (Austin)

The second bill provided $17 billion emergency funding to the victims and to affected NY and NJ communities.  Both Texas Senators Ted Cruz and John Cornyn voted agains the bill.  In addition to all of the above Representatives, the following Texas GOPers also voted against this aid:

Ted Poe (Humble)
Sam Johnson (Plano)
John Ratcliffe (Heath)
Jeb Hensarling (Dallas)
Joe Barton (Arlington)
Kevin Brady (The Woodlands)
Michael McCaul (West Lake Hills)
Kay Granger (Fort Worth)
Lamar Smith (San Antonio)
Pete Olson (Sugarland)
Michael Burgess (Lewisville)
Blake Farenthold (Corpus Christi)
John Carter (Round Rock)
Pete Sessions (Dallas)

Now that it is Texas suffering a catastrophe, of course some of these same politicians will be at the front of the line braying for help. While with the GOP in control of the entire federal government, Karma will not be paying a visit with her litter, in a just world aid would be provided immediately -- on the same day they all visit NY and NJ, apologize, and abjectly beg forgiveness.

Of course, the "better angels" will prevail this time. But rest assured, the next time a disaster befalls anywhere in the Northeast, these same Texas politicians will once again vote against aid. In the meantime, above is the Roll Call of Shame for posterity.