Are Earnings Rising or Stagnant? Published June, 2005 by Kash

This question is not as easy to answer as it may first appear. In working on various posts last week I came across an apparent contradiction in the official data on compensation: some series show it rising in real terms, while others show it barely able to keep up with inflation. This discrepancy was also noted by a few readers, who deserve credit for their sharp eyes.

So I thought I’d take a bit of time to sort out these conflicting data series for myself. Here’s what I found. (A warning and apology here: what follows is a relatively econ-geeky post about data details that many may find uninteresting… and I won’t be offended if you stop reading here.)

There are three major sources for time series data on earnings: “Hourly Compensation,” from the BLS’s Productivity and Costs (P&C) dataset; the Employment Cost Index (ECI), which provides compensation series broken into the two sub-categories of wage/salary earnings and benefits; and the “Average Hourly Earnings” provided in the monthly employment report as part of the Current Employment Statistics (CES). The following two charts show the behavior of these different series since 1990. All series express hourly compensation rates in real terms.

Note: all series are expressed in real (inflation-adjusted) terms using the PCE deflator.

What explains the sometimes substantial differences between these series? There are several factors that contribute to the discrepancies, but let me point out the most important ones. (For a more complete description of their differences see this paper by Joseph Meisenheimer in the May 2005 issue of the Monthly Labor Review.)

First of all, two of the series – the CES series and the “ECI: wages and salaries only” series – do not include benefits that workers receive. In the charts, those are the pink and green series. Comparing the two ECI series shows that in the past three years or so, a significant gap has opened up between workers’ take-home pay and the amount of compensation that employers are paying, including benefits. I would argue that this is directly attributable to the soaring cost of health insurance since about 2000. Even if workers’ pay has been rising in real terms, nearly all of the increases have been going to pay higher health insurance premiums.

Secondly, the different series include and exclude different types of income and different types of workers. The table below summarizes the different types of workers and income that each series excludes.

Finally, it should be noted that the ECI differs from the other series in that it comes from a survey that is intended to compare the wage rate in a particular job over time, not the wage rate of a person. (The sample is 35,000 specific jobs across the country.) In other words, the survey compares what each job in the sample pays at one point in time to what it used to pay earlier. Furthermore, in constructing the average wage rate across the economy, the ECI holds the number and types of jobs constant at the proportions in the base year (which I believe was just changed from the year 1990 to the year 2000). What this means is that the ECI will not accurately reflect how a change in the composition of jobs in the economy might affect average wages.

Each of the series thus has its own strengths and weaknesses, and there’s no right answer as to which series is best. They each tell us slightly different things, and the differences between them tell us still more. For example, the surge in the P&C measure during the period 1998-2001 probably reflects the large-scale adoption of payments through stock options. The divergence between the wage/salary series and the total compensation series reflects the growing burden of health insurance. And the recent rise of the P&C measure compared to the ECI measure may reflect higher rates of compensation growth in for-profits firms compared to non-profit firms, or large increases in the compensation of self-employed business owners, or a change in the composition of jobs in the economy that the ECI hasn’t caught up with.

A note about income inequality: to the degree that some of the excluded groups (in the table above) may have different levels of income than others, the differences between the series may also suggest something about changes in income inequality. A word of caution about that, however: if you want to find evidence of income inequality, I think there are much better measures (such as the Census Bureau’s income data) than these compensation measures. There is too much else going on in these series to be able to safely attribute anything on the charts above to changes in income inequality.

So what’s my answer to the title question of this post? Personally, if I had to choose just one series to use it would be the P&C series. In addition to being arguably the most complete series, it seems to have done the best job of matching my sense about how the economy has done over the past 20 years. When asked, I think that most people would agree that income growth was indeed much lower during 2002 and 2003 than it had been during the late 1990s; the P&C series bears that out, while the ECI series doesn’t. Meanwhile, the CES series excludes benefits, which I think are a major part of the story today.

But let me reiterate the point that I have made several times now: just because real compensation is rising, that doesn’t mean that people are better off, particularly if nearly all of the gains are just going to paying higher health insurance premiums. This data persuasively illustrates that nearly all of our real compensation gains today (and I do think we’re seeing them) are being eaten up by the monster that we call a health care system in the US. Until we address the profound inadequacies of our health care system, this trend will only get worse.

Kash

A NonReview of Yves Smith’s Econned, Plus Some Questions About Selling Books

I’ve been swamped – a lot of work at work, deadlines for my book (more on that below), and family issues to contend with so for the past few weeks I’ve been cooped up with zero downtime. Friday I managed to crawl out of my hole… at least for the time being. I remembered that Yves Smith’s book, Econned, was due out. Yves’ blog, Naked Capitalism is one of my daily reads and I’ve been looking forward to her take on the whole Great Recession.

Long story short, I visited two bookstores – both had sold out. I placed an order for the book at Barnes and Noble and was told it would be available this week.

All that is a good sign for Yves Smith, and I wish her well. But I was wondering… what can one do to make one’s book more likely to do well? Obviously, with a book coming out later this year – in August – its something I have an interest in knowing. (The book is already for sale at some online locations. Here’s the Amazon link to the book. As an FYI, given how little the bio of me is, there’s a surprising amount that’s incorrect.)

The book is – we think – a bit unique. We looked at a how a large number of issues – from abortion to crime to the economy – evolved over the length over each administration from Ike to GW. (In a few instances, where the data is reliable, we go back to Hoover.) And we let the data speak, as regular readers can imagine from the posts I’ve written. I’ll give you an example – my own political views, as one can imagine from the fact that I occasionally post at Angry Bear, are generally slightly left of center. And when this project started some years ago, I hewed closely to what one might term a slightly left of center view on crime, namely that the way to reduce crime is to focus more on rehabilitation. But the data shows that the Presidents under whom crime fell by the most were the ones who, once you account for demographics, put cops on the street, locked people up, and threw away the key. And that is precisely what we show.

I’m not sure I’m happy that the results on crime are what they are. Philosophically, I’d be a lot more comfortable being able to state that we should spend more time and effort and resources on rehabilitation relative to punishment, but the data shows what it shows. And my comfort level, frankly, is irrelevant, when it comes to determining what reduces crime. And the one thing my co-author and I agreed on from the start was that we would post the data (in a nice graphical format thanks to Nigel Holmes, a brilliant artist the publishing company hired to make our graphs look nice), whatever it showed.

Now, that is going to cause a major problem. See, on some issues, there doesn’t seem to be much of a relationship between a governing philosophy and outcomes. For instance, stock market performance seems to be unrelated to the president’s party, or even to how well the economy did. But (its not exactly a surprise to readers of this blog) on a lot of issues, particularly the economic ones, Democrats tend to outperform Republicans. And we think we’re able to nail the cause of this disparity. We also feel we’re able to do a good job of showing that the cause is related specifically to the occupant of the White House, as opposed to, say, Congress, God’s will, the public’s voting patterns, or whatever else.

And as regular readers know, stating that politicians that followed a certain policy produced better economic outcomes than politicians who followed the opposite policies seems to leads to uncomfortable conclusions for some people. As uncomfortable, for instance, as my epiphany on looking at the data on crime. But some people simply refuse to give up cherished beliefs. Its easier to attack the messenger. So though we call it like it is, and we call it for Republicans when Republicans have the better argument, I have zero doubt whatsoever that our book is going to labeled “liberal.” Which is a pity, because the book is not intended to cheerlead. In fact, its intended to poke and prod both sides into keeping what works from their side and giving up what doesn’t.

OK. So there it is. That’s what the book is about. How do we sell it? Anyone have concrete ideas? Bear in mind, this has to be something we can do. People always tell me to go on the Daily Show or some similar program. I don’t exactly have any media exposure (my co-author does), but I’d love to do it. However, there are a lot of people trying to go on TV to peddle their wares or their opinion. Heck, even people who know they’re going to get publicly humiliated by Jon Stewart show up with big smiles on their face. And my guess is that a lot of people think, like I do, that they have something unique that can change the world if word gets out. So what do I do from here?

A few minor steps I’ve taken…
1. I took out websites in my name and the book’s name. What should go on them at this time?
2. I took out twitter accounts in my name the book’s name. I’ve never used twitter before in my life. What do I do with these now?
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by cactus

In the paper they conclude that strong productivity was the main reason employment growth was weaker than the traditional relationship in Okum’s law implied.

Of course, we at Angry Bear have long known this because I have published this chart that shows that roughly before 1974 that a one percentage point growth in real GDP generated
a 0.3 percentage point growth in employment. This is what Okum’s law is based on. But during the era of low productivity growth, 1974 to 1995 a percentage point growth in real GDP generated almost a 0.5 percentage growth in employment. But since productivity growth
rebounded in 1995, every percent increase in real GPD was accompanied by almost a 0.9% gain in productivity so that employment barely rose 0.1% — a significantly lower rate than Okum thought.

The data in the chart is the long term trend and ignores the cyclical pattern in productivity where productivity growth peaks in a recession or early recovery period and slows as the expansion continues. That is why productivity growth has long been widely considered a leading indicator. It is also why you get patterns like in 2009 that the San Francisco Fed found and why we now seem to have jobless recoveries.

After an email exchange with Marshall Auerback, and thinking more about the cross-section of Europe, I now see a very scary trend emerging across Europe: the fight for exports.

To be sure, Latvia’s efforts are of note, as the acceleration in hourly labor costs dropped from a 22% pace spanning 2007-2008 to just 2.8% in the first three quarters of 2009 compared to the same period in 2008 (the Eurostat data are truncated at Q3 2009).

But look at the similar wage-cutting behavior occurring across the European Union, especially in the Eurozone hopefuls (Latvia, Lithuania, and Estonia are preparing to adopt the euro in coming years).

The battle for exports has begun. Compared to the same period in 2008, Q1-Q3 2009 annual hourly labor cost growth is down 4.9% in Lithuania, 0.8% in the U.K., and 0.5% in Estonia. In fact, every country across the 26 countries listed except Belgium, Germany, Greece, and Spain, saw the rate of hourly wage growth decrease since 2008. The currency is pegged, so the only mechanism to increase external competitiveness is through price (wages) declines. To be sure, this growth model cannot work for the Eurozone as a whole.

Latvia’s model: drop wages to increase export income. Greece: drop wages to increase export income. France, Germany, Spain, Portugal, etc., etc. It’s impossible that the whole of the Eurozone will drop wages to increase export income. It’s especially bad for countries like Latvia or Hungary, where the lion’s-share of trade occurs withing the boundaries of Europe.

And what happens when export income does not provide the impetus for aggregate demand growth? Well, there’s not much left. Can’t devalue the currency (via printing money), and tax revenues will fall faster than a ten-pound weight: rising deficits; rising debt; rising debt service (via surging credit spreads). Sovereign default seems like a near-certainty somewhere in the Eurozone!

This article is crossposted at News N Economics

Rebecca Wilder

Steve Waldman

Dean Baker

To obamanate V. To open an argument absurdly excessive concessions to one’s opponents.

Obamanation gerund of To obamanate.
Obamanation present participle of to obamanate.

I offer this definition in defense of Obama. The word will be defined, and he’d better hope my definition is adopted.

There has been a scattering of stories about how China has slowed or stopped buying U.S. Treasuries. This story offers a possible explanation

LA Times: China’s investments in U.S. up sharply

Beijing is using its accumulation of billions of American dollars to step up its investments around the globe. In the last year, Chinese acquisitions in the U.S. have ranged from a relatively obscure theater in Branson, Mo., to stakes in such famous brands as Coca-Cola and Johnson & Johnson.

China’s huge stockpile of dollars stems in part from Americans’ enormous purchases of relatively inexpensive Chinese manufactured goods and the significantly smaller volume of U.S. exports to the Asian country.

By recycling much of its dollar trove over the years back to the United States with the purchase of U.S. government debt, China has in effect helped Washington finance its deficits.

Now, Beijing is branching out. The country’s direct investments overseas rose 6.5% in 2009 to $43.3 billion — despite a global slump in such investments — and could jump to $60 billion this year, Chinese state media reported last week.

Formal estimates of Chinese investments in the U.S. last year, excluding bond purchases, range from $3.9 billion — a figure put out by New York research firm Dealogic — to $6.4 billion, a number that comes from Derek Scissors, a Heritage Foundation research fellow who tracks China’s global transactions

I’ll let the econoBears explain the significance here, my flip summary would be “Why rent when you can own”. It certainly doesn’t indicate that the Chinese are expecting some terrific crash in the medium term.

The Federal Open Market Committee (FOMC) is making tough decisions right now. Its mandate, “to promote effectively the goals of maximum employment, stable prices, and moderate long-term interest rates”, is a seriously tall order given current economic conditions.

The unemployment rate sits at 9.7%, while prices have bounced back to 2.6% Y/Y in January. On the surface of it, inflation appears to be gaining some traction; but the big numbers are representative of base effects, and that is really all. The drag on prices remains very real.

But there is one little kink in the headline figures of unemployment that complicates an already complicated task: extended unemployment insurance. From the FOMC’s Jan. 26-27 minutes:

Though participants agreed there was considerable slack in resource utilization, their judgments about the degree of slack varied. The several extensions of emergency unemployment insurance benefits appeared to have raised the measured unemployment rate, relative to levels recorded in past downturns, by encouraging some who have lost their jobs to remain in the labor force. If that effect were large–some estimates suggested it could account for 1 percentage point or more of the increase in the unemployment rate during this recession–then the reported unemployment rate might be overstating the amount of slack in resource utilization relative to past periods of high unemployment.

Why would extended unemployment benefits increase the unemployment rate? In order to claim unemployment benefits, one must be “in the labor force”; and that means looking for work. Therefore, some workers who would otherwise be classified as “not in the labor force” remain in the work force as “unemployed”. Therefore, the current unemployment rate is elevated above the rate that would occur without the extended benefits. The Fed suggests this differential to be roughly 1% point.

I am in no way proposing that the extended benefits be rescinded; nor am I deluding myself into thinking that the labor market is anything short of awful. But Fed policy is calibrated to the non-inflation-generating level of the unemployment rate. And the current unemployment rate may be closer to the long-run level than the headline number suggests.

I have talked about this before (see this post) from another angle: the long-run level of unemployment may be a moving target right now, i.e., it’s likely rising. Therefore, if the long-run level of unemployment is rising and subsidies are masking the true level of the current unemployment rate, then we may very well get some inflation while the economy is still weak.

Of course, I do not believe that we are even near such a threshold level; but it does complicate an already complicated situation. A modified Taylor rule demonstrates the implications for policy.

The chart above illustrates the estimated Taylor Rule using the current unemployment rate (in blue line) versus one in which 1% point is shaved off the unemployment rate for every month since January 2008 (green line). The modified rule does suggest that the Fed policy rate is currently at (or now below) the prescribed rate.

Just some food for thought. Rebeca Wilder crossposted with Newsneconomics