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Another image of labor’s broken back: $48,887 in profit per employee!

This article via Yahoo news caught my attention: Five years into recovery, Dow Companies squeeze workers as investors thrive

I think this picture spells it out rather well.


Profit per employee

“As the chart shows, the 30 huge companies that comprise the Dow Jones Industrial Average have barely nudged their employee ranks higher…”

But this is even more astounding:

Over the past five years, total profits of the current Dow 30 members surged by more than 42% through the end of 2014, to nearly $320 billion. This has driven the average annual profit per employee up by more than 34% since 2009, to $48,887.

According to this CNN article from August, the median household income is $53,891.    That means these 30 companies are pocketing 90% of what an household earns.  That’s out the door, cash in the pocket 90% of what a household works all year to earn.  Now, I’m not sure, but I think that household income is pretax and I doubt they get to hid that $53,891 in some account out of reach of the tax man.  In fact, I’ll bet that household needs every bit of that money just to get through the year.

Well, the 30 are not hiding all of it:

Dividends paid by the Dow 30 are up better than 30% the past five years, according to FactSet.

Read the article.  The author does his best to explain this situation, but it’s seem more like excuses.  A grasping at straws to dismiss what we know has been an intentional drive to get to this point.  My interpretation of it is that these companies are now able to “grow” the pot of money without actually having to increase their sales.  True money from money… but, they are scared that this magic will leave them and then what?




What would Romney say? What would Obama say? What would you say?

I noticed that the notion of income inequality and consequences was described outside the box in this article in the NYT. Several ideas struck me about the article.  How people can work side by side with such little connection in their lives is instructive.  The sense of ‘commons’ is missing from the article could be instructive in high lighting how the two women see their obligations and options, but another follow up could help instruct  us.  We tend to act on our own perceived stories’ to determine these choices. :

But a friendship that evokes parity by day becomes a study of inequality at night and a testament to the way family structure deepens class divides. Ms. Faulkner is married and living on two paychecks, while Ms. Schairer is raising her children by herself. That gives the Faulkner family a profound advantage in income and nurturing time, and makes their children statistically more likely to finish college, find good jobs and form stable marriages.

The economic storms of recent years have raised concerns about growing inequality and questions about a core national faith, that even Americans of humble backgrounds have a good chance of getting ahead. Most of the discussion has focused on labor market forces like falling blue-collar wages and lavish Wall Street pay.

But striking changes in family structure have also broadened income gaps and posed new barriers to upward mobility.

The advantage of comparing is to personalize and give life to ‘trends’ in our social fabric. The disadvantage of using real examples is that readers may trivialize the significance of a trend by making pronouncements on individual morality and choices and not look at real trends. Often little is offered for the psychological reasons for choices other than “shoulda known better”. Individual choices are of course tremendously important, but fail to explain the much larger trends.

The significant growing necessity of having two paychecks to raise a family is mentioned, and also the type of jobs women tend to get at lower pay compounding the difficulty of making enough money. Also mentioned is Ronald Reagan’s earned income credit to help alleviate what could have been much more severe poverty. There was no mention of medicaid, and no mention of what state the two women lived in. Not mentioned is the profound decrease in the labor participation rate for male ‘blue collar’ workers and subsequent dislocations  (lower wages for men were given slight mention).

One important  thought is that a significant number of people have dropped out of the ‘middle class’.  

The Best Data on Middle Class Decline (Updated)

by Kenneth Thomas who writes The Middle Class Economist
(corrected author name)

The Best Data on Middle Class Decline (Updated)

The flurry of posts earlier this month on middle class decline (me, Lane Kenworthy, Matthew Yglesias, Kevin Drum) made me think some more about what the best way is to show what’s happened since the peak of real wages in the early 1970s. While in my opinion there is no perfect measure, there are a lot of choices to be made, and I argue below why real wages for production and non-supervisory workers, with an adjustment for non-wage compensation, is the best single measure.

Choice 1: Household/family vs. individual

While we all live in households or families, over the past 40 years, there has been a decline in persons per household (see Kenworthy) and an increase in incomes per household as women’s labor force participation has increased. The decline in persons per household means that a household needs less income than in the past to have a fixed per capita income. The increase in incomes per household has meant that households have had higher real income even as real individual income has fallen, as pointed out by commenter peggy_Boston in the comments thread of Drum’s article. To my mind, this is partly causal; that is, because real wages have fallen, families have had to have more incomes in order to maintain their living standards. Indeed, falling real wages have forced families to run up high levels of debt, with non-mortgage debt reaching 1/3 of family income by 2005. Therefore, I think individual data is the right choice here.

Choice 2: Median income vs. production and non-supervisory workers’ income

The median (middle value, with an equal number of observations above and below it) has big advantages over the arithmetic mean in trying to show the typical situation in a distribution of values. It is especially useful for income distributions, where the presence of very high incomes means that the mean is much higher than the median. In fact, the literature on “decoupling” (see Kenworthy above) demonstrates just how much this is the case. But I think that “production and non-supervisory workers” captures our intuition about who is in the middle class even better than the median does.

This series, in Table B-47 of the Economic Report of the President, is an average of the earnings of employed persons in private (non-government), non-agricultural jobs. It includes about 80% of the private workforce and 64% of the total non-agricultural workforce. Despite being an average, its exclusion of supervisory workers means that virtually all of the extremely high values that distort the mean of the entire workforce are eliminated. It is, essentially, the mean income of the bottom 80% of private workers. The biggest drawback to this dataset is that it does not include non-supervisory government workers, but I think that is outweighed by its broader coverage of the middle class than the pure median income (or middle quintile, as in Kenworthy’s post).

For the counterargument, that changes in composition of production & non-supervisory workers can cause distortions that the median wage is not subject to, see Dean Baker (p. 9).

Choice 3: Weekly vs. hourly
Baker mentions hourly earnings rates in some cases. As I discussed in the comments section of my March 11 post, the decline in hours worked per week (from 36.9 hours in 1972 to 33.6 hours in 2011) suggests to me that we need weekly, not hourly, wages.

Choice 4: Which inflation data to believe?
Shortly after President Clinton’s first election, I predicted to my students that, because his message of middle-class stagnation (“It’s the economy, stupid”) was dependent on how inflation was measured, that conservatives would soon attack the official Bureau of Labor Statistics inflation data. The issue is, if inflation is overstated, then the decline in real wages reported by the BLS could be overstated or even non-existent. Conversely, if BLS data understates inflation, then real wages have fallen even faster than shown in Table B-47.

Unfortunately, I did not publish this prediction, so you’ll have to take my word for it that I predicted the attack on inflation data that culminated in the Boskin Commission in 1995. I always took this to be a political attack rather than a scientific one. My attitude has always been that trade theory (i.e., the Stolper-Samuelson Theorem; see Ronald Rogowski’s great book Commerce and Coalitions for an explanation of this topic, which I intend to discuss in a later post) predicts that real wages in a relatively labor-scarce country like the United States will fall as trade expands, and the data shows that real wages indeed fell: so what reason do we have to question the data? In the end, though, the Commission concluded that inflation was being overstated by about 1.1 percentage points a year, and the BLS was mandated to adjust its methodology.
Barry Ritholtz takes an even more jaundiced view of the Boskin Commission than I do. Paul Krugman, on the other hand, is not convinced that inflation is now significantly underreported, citing the work of the Billion Prices Project. For the moment, I do not see reason enough to toss out the BLS data, despite the possibility that the Boskin Commission may have introduced distortions into it.
Choice 5: Wages vs. compensation

Martin Feldstein and other economists argue that it is not sufficient to look at wages alone, because the non-wage share of compensation has been growing over the past few decades. As I posted before, total employee compensation includes everyone from the CEO to the janitor, so it overlooks the fact that the top 1% have made almost all the gains from decades of economic growth. Nevertheless, it is clearly true that non-wage compensation has grown faster than wages, as we will see below. In fact, Yglesias suggests that the 2000s actually saw real compensation growth at the median, but it was all in the form of health insurance benefits. Of course, there is some debate over how much value actually comes from extra employer payments for health insurance, as Baker’s paper (p. 10) details

A different way to factor in compensation that I had seen before on the Economic Policy Institute’s website was explained to me in an email by Jared Bernstein and is documented in the footnote of his blog post here. It takes the ratio of total compensation to total wages, both of which are in National Income and Product Accounts Table 1.12 (you can set it to a wider range of years, as I did). Whereas he applies it to median wages, I apply it to Table B-47 and get the following results:

Year Weekly Real Earnings Comp/Wages Weekly Compensation
(1982-84 dollars) (1982-84 dollars)
1972 $341.83 1.14 $388.01
1975 $314.75 1.16 $366.63
1980 $290.86 1.20 $348.93
1985 $285.34 1.22 $347.10
1990 $271.12 1.21 $328.99
1995 $267.07 1.22 $326.23
2000 $284.79 1.20 $341.49
2005 $284.99 1.24 $352.87
2010 $297.67 1.24 $370.28
2011 $294.78 1.24 $365.77
Note: Last two columns rounded from spreadsheet calculations
Sources: Economic Report of the President 2012, Table B-47, National Income and Product Accounts, Table 1.12, and author’s calculations
By this measure, compensation in 2011 for most workers was still almost 6% below its 1972 peak. The advantage of this adjustment over Feldstein’s procedure is it strips out the wage inequality of the compensation data, although there is still some overstatement based on inequalities in non-wage compensation. Still, I think this gives us our most accurate picture of what’s happening to the bottom 80% of workers.

That is not to say that this is a perfect measure even with those caveats. It matters what is happening at the top, too. If high wage earners were seeing their income fall faster than middle-class workers, then inequality would be falling and we would probably object less to what would then look like the much-vaunted “shared sacrifice.” But of course, as Kenworthy notes, the share of the top 1% more than doubled from 1979 to 2007, from 8% to 17%. With inequality rising as it is, we now seem to be in danger of a consequent sharp shift of political power to the 1%, as MIT economist Daron Acemoglu told Think Progress’ Pat Garofolo.
I look forward to your comments, especially if I’ve gotten something wrong.
UPDATE: By way of comparison, here is Lane Kenworthy’s chart.

In it, you can see that by either median family income or 3rd quintile household income, incomes started rising shortly after 1980, whereas in my table compensation-adjusted real wages continued to fall until 1995. You can also see the divergence in median family income and Q3 household income between 2000 and 2007, as noted by Yglesias. Whereas the increase is made up entirely of nonwage compensation in the Q3 household income series, in my table at the individual level we have an increase made up partly of wages and partly of nonwage compensation.