Employment & Productivity

Light truck detailing with an insider

In our mid-November report, we noted that auto-industry expert Kim Hill pointed out at a recent conference that automobiles’ share of total sales had dropped five percentage points over the year, and that the average price had risen 3% over that same period, because of light trucks. You can see that on the graph below, and also the, we’d say, shocking fact that light trucks were about 15% of total sales in 1970 and are close to 70% today. We’d like to give Kim a hat-tip for pointing out that within this trend auto jobs in nine states were at risk, with four plants in Michigan, six between the Great Lakes and the Gulf Coast in danger, and plants in California and Kansas possibly targeted.

As we heard from a small percentage of those plants, we picked up the phone, and Kim immediately cut to the chase, highlighting two trends. First, “One of the ugly parts of this industry transformation is that you have a bunch of older workers who just don’t have the skills they need for the future.” Them’s harsh terms about “cutting out dead wood,” so they can hire the tech-savvy younger workers, and we all agree that that is a public policy issue.
Kim says that General Motors has been looking at the plant in Ontario for a long time, and they are going to take some PR lumps for that because Canada and Ontario governments helped out GM during bankruptcy.

Here in the U.S. they are contractually obliged with unions to give long leads when they are closing plants, so don’t pencil these layoffs into your forecasts yet. Kim thought there would be more shuffling of workers, and was surprised to hear about the outright closings, although he knew the risk was there. He also suspects that the two plants being scrutinized, one in Ohio and one in Michigan, will be whipsawed against each other, and the states will get involved in a kind of bribing process with lots of money on the table. As sales of sedans “fall off the table,” these shifts to truck-style products will continue.

Auto manufacturing multipliers are always a subject for debate, if you go in for that kind of thing, and you could drive a SUV through the range here. The Bureau of Economic Analysis puts a 2.87 on the auto industry, meaning $1.87 in spending for every direct dollar, but Kim says there are big differences if you look at regions or the entire nation. Regionally he and his colleagues can tell “the minute they get off the freeway” if a plant is thriving or wilting. “In Fort Wayne there make a ton of pickup trucks and small businesses are thriving, but for the last 10 years in Lordstown there are more and more empty parking lots.”

The auto-industry’s rule of thumb is that you’re safe if you take a multiplier of 7, that means 6 jobs for every direct job, for the industry overall. On the state level, that may fall to 4 or 5 because you are not picking up work generated outside the limited region, and if you look at the national level you can get up to a 10 multiplier for assembly plants because then you are picking up all the small suppliers and service firms throughout the country.

Plants at risk include those in Lansing, Michigan, assembling Camaros and Cadillacs; in Lake, Orion assembling Sonic and Bolt; in Georgetown, Kentucky assembling all sedans; in Fairfax, Kansas, making Malibus; in Chattanooga assembling small utility vehicles—as well as the Alabama Hyundai plant, and the Mississippi Blue Springs/Tupelo Corolla plant. More to come and not as sweet as Tupelo honey.

Many have reported that tariffs are a driving force in these plant closings, but Kim isn’t so sure. He didn’t refute our suggestion that tariffs may have been a deciding factor in the decision to shift employees between plants and outright closings, but he said there is too much in flux: many assembly plants might be able to absorb a 10% tariff but would choke on a 25% tariff, and it’s impossible to expect anyone to make a “massive industrial decision” without that information. It’s also very hard for decision makers to deal with “whimsical buyers driven by fuel prices.” Customers can turn on a dime, but manufacturers can’t. We’ll be featuring intermittent interviews with Kim Hill, so expect one in a few months when the effects of tariffs become clearer.

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Measuring the Platform

The “platform economy”—Uber etc.—is a lot smaller than people think it is. And workers would pay good money for better working conditions.

A lot of myths circulate about the contemporary labor market. One of the more durable is that we’re all day laborers now, working two temp jobs and driving an Uber on the side. As we showed back in June, BLS stats show that between 1.3% and 3.8% of all workers are contingent, depending on which definition you use, which are smaller shares than what prevailed in 1995 and 2005. In other words, hardly representative.

But what about what the BLS calls “electronically mediated employment,” platforms like Uber and TaskRabbit? Internet and barstool chatter would have you believe they’re ubiquitous—not as a way of hailing a ride but as a major form of employment. Data released by the BLS at the end of September challenges this story. In fact, such platforms account for just 1% of total employment. And over a fifth, or 22%, of such workers are in the transportation sector, more than four times that sector’s share of total employment. Take those away, and the electronically mediated account for just 0.8% of employment.

There were technical challenges
to evaluating the numbers, which were gathered as part of a supplement to the monthly Current Population Survey (CPS, the source of the household employment stats) for May 2017. Many respondents were apparently confused by this question into thinking they should answer “yes” if they drove to work or used a computer on the job:

Some people find short, IN-PERSON tasks or jobs through companies that connect them directly with customers using a website or mobile app. These companies also coordinate payment for the service through the app or website.

For example, using your own car to drive people from one place to another, delivering something, or doing someone’s household tasks or errands.

Does this describe ANY work (you/NAME) did LAST WEEK?

Since the BLS could compare responses to this question with respondents’ full answers to the CPS, they were able to discover a large number of false positives. For example, a banker, a cop, a professor, a motel desk clerk, a hairdresser, and a surgeon all answered “yes,” even though they shouldn’t have. The raw “yes” responses came to 3.3% of employment. But when the BLS recoded the answers to be consistent with the regular CPS questions, the share fell to 1.0%. For transparency’s sake, they report both sets of results. But given the rich comparative data provided by the standard CPS questions, the recodings look well-founded.

As the graph above shows, there were some variations by demographics and especially sector in the prevalence of platform employment. There was little gender difference. Blacks were somewhat more likely than others to be so employed. The share rose with education (and, although the graph doesn’t show these results, those with advanced degrees were more likely than those with bachelor’s only to do electronically mediated work). The biggest variations are by industrial sector, with almost no one in the goods-producing sectors or government working for an app. But 4.5% of workers in transportation and warehousing, 2.7% of those in professional and business services, and 2.3% of those in information were.

These are not large numbers, even in transportation.
They’re consistent with a new study from the JP Morgan Chase Institute, which is based on deposits into 39 million Chase checking accounts. It found 1.6% of the sample earning platform income in 2018Q1, up from 0.3% five years earlier. (If you’re the sensationalizing sort, you could say the share has quintupled, but it’s still quite small.) Two-thirds of that came from transportation. Over the course of a year, 4.5% of accounts showed some platform income, but most were for just a few months.

Strikingly, despite the growth in platform work in transportation, from close to 0 in 2013 to 1.0% of the sample in 2018Q1, average monthly earnings in transportation were down by more than half, “even among the highest earning and the most regularly engaged drivers.” Earnings from selling (presumably names like Etsy and eBay, though neither the BLS nor Chase names names) and space rental (presumably Airbnb and the like) were quite small, with under 0.5% of accounts showing such income in a recent month. In months when families participate in the platform economy, such earnings account for just over half the month’s income—but other sources of income are clearly necessary.

So, it looks like the platform economy can provide some income, but not enough to live on. And the steady influx of drivers into the likes of Uber and Lyft is driving down pay.

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Tax Contacts: “Where are those wages?”

As those who follow our work know, we have frequent, detailed discussions with senior revenue officials around the county on a regular basis. Withheld receipts are better tied to ordinary wages than are overall Personal Income Taxes, which include estimated payments on stock income and the like, and are out in front these days. Recently, when discussing growth in withheld receipts with our revenue contacts, we’ve been hearing from some: “Where are those wages we keep hearing about?

Maybe here: profits are up far more than wages in this cycle—almost three times as much. And that’s a real issue in our debt-laden economy, especially at the low end.

The two major factors of production, capital and labor, have enjoyed different rewards in this recovery/expansion. Graphed above are after-tax corporate profits and wage & salary payments by nonfinancial corporations, indexed so that the ending quarter of the recession, 2009Q2, is set to 100. (We use after-tax profits because those are what matter to shareholders, and because bookkeeping shenanigans at the end of 2017 and beginning of 2018 in anticipation of the tax cuts distort the numbers.)

Since mid-2009, nominal wages are up by 49%—but profits are up by 136%. (It’d be nice to present real measures but choosing the proper deflators would be a fatal challenge.) For a while, it looked as if profits had peaked in 2014, but they’ve made a healthy recovery since. And they got a splendid boost from the tax cuts.

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Earth to Kevin Hassett: If you use that wrench…

The other day, Kevin Hassett, chair of the Council of Economic Advisers, dismissed concerns about slow wage growth by saying that if you deflated average hourly earnings (AHE) by the index for personal consumption expenditures (PCE) rather than the consumer price index (CPI) earnings look a lot better over the last year. And, he added, it’s a mistake to look only at direct pay because a lot of raises are going into benefits. There are two problems with his argument: first, AHE have looked a lot better if you deflate them by PCE for most of the last three decades, and for second, benefits are running only slightly ahead of wages in the private sector, and rather behind overall.

Here’s a comparison of yearly changes in the two inflation measures. In 88% of the months since 1990, the CPI came in above the PCE.

And here’s what AHE look like when you deflate them by the two measures. Since the all-private series only begins in 1964, and the all-worker series in 2006, we’ve chained nominal wages from those two series together with manufacturing (which go back to 1939) to produce a long-term measure. Using the CPI, real wages are 4% below their 1973 peak; using the PCE, they’re 18% above. We’ll leave the topic of which is the better measure for some other time. But any recent outperformance of real wages using the PCE rather than the PCI is a very old story.

Finally, benefits aren’t doing that great. Here’s the history from the Employment Cost Index (ECI) series. Overall compensation growth in the second quarter was at the high for the cycle—but it’s below early troughs, like 1987, 1995, and 2006. Benefit growth is only slightly above wage growth, and is nothing compared to the bulges seen from 1988–1993 and 2000–2005. A major reason for this is the deceleration in health costs. Employers’ health costs were up just 1.5% for the year ending in 2018Q2, a third the 2010 average of 4.8%, and less than a fifth the 2000–2006 average of 8.2%. Health insurance costs are now lagging overall medical inflation; they exceeded it in the early periods by a wide margin. That suggests employers are shifting more costs to employees.

By the way, here’s what the ECI looks like compared to AHE. We don’t recommend making a habit of using the ECI as “truth.” When we asked an economist at the Bureau of Labor Statistics some years ago what he thought of substituting the ECI for AHE, he said, “If you use that wrench, you’re going to strip that bolt.” Kevin Hassett may need to visit his favorite hardware store.

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State E&E = Job & Wage Growth Often Go Together

How have the states been doing on jobs and pay since the last business cycle peak? We’ve mapped some answers.

First E1, Employment: Between the last business cycle peak in December 2007 and July 2018, the most recent month available, the median state has seen a 5.3% increase in employment. At the top of the list is Utah, up 20.1%, with North Dakota and Texas close behind. Some of the bigger, richer states have done well, like California (up 10.8%) and New York (10.0%). So has Massachusetts, up 10.9%, a state that’s not thought of as a boomy place. At the bottom: Wyoming (-2.6%), West Virginia, (-1.1%) New Mexico (-0.8%), and Connecticut (-0.5%), who’ve all lost jobs over the last decade-plus. Also weak: Mississippi (+0.3%), Alabama (also +0.3%), Maine (+1.3%), Louisiana (+2.7%), and New Jersey (+2.8%). Of the ten states with the largest energy sectors, five (Louisiana, Alaska, New Mexico, West Virginia, and Wyoming) are clustered in the bottom quarter, and a sixth, Oklahoma, is at the median. Two are closer to the top, Texas and Colorado, but they’re generally more diversified economies than the ones at the bottom.

It’s interesting that while New York has done rather well, two of its neighboring states, Connecticut and New Jersey, haven’t. New York City accounted for 79% of the state’s employment gain over the period, nearly twice its share of the state job market. Were New York City a state, it would rank fifth in employment gains; New York State excluding the city would rank in the bottom third. This is a reversal of the trend of earlier decades when the urban core lagged its suburbs. For example, between 1990 and 2000, New York City’s employment gains were less than half that of the state outside the city.

Second E2, Earnings: There’s a huge variation in growth in average hourly earnings (AHE). At the top of the list, North Dakota, up 42.9% between December 2007 and July 2018. Since it ranked second in employment growth, its workers have done very well, a reflection of the fracking boom. South Dakota is in second place, up 38.9%; Oklahoma, third (34.7%); and Iowa, fourth (32.9%).

Four of the top ten states—South Dakota, Oklahoma, Montana, and West Virginia—are among the ten most energy-intensive. But other energy states did less well, with Texas (22.6%) just below the median of 23.9%, and Colorado (22.5%), Wyoming (21.7%), and Louisiana (also 21.7%) not far behind. California (25.0%) and New York (22.5%) are around the median. (There’s not much difference between New York City and State on earnings; the city’s AHE were up 24.7%.) Florida, Michigan, New Jersey, and Connecticut are all towards the bottom.

Texas is an interesting case. While it’s often touted as a jobs mecca, it’s not notable for high pay. That’s not to say that keeping pay down is necessarily good for employment. The correlation coefficient between employment and earnings growth between 2007 and 2018 is 0.37—not super-high, but still solidly positive. Job and wage growth often go together.

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