This morning the Bureau of Labor Statistics reported that 701,000 jobs disappeared in March. Economists had been expecting about a third that number. Hardest hit were bars and restaurants, accounting for 60% of the loss. Also hit hard: retail, temp work, and, shockingly, health care.
One reason job loss expectations were relatively low was that the survey of employers on which the count is based is done during the week containing the 12th—in this case, between March 8 and 14. (No one is expecting anything but a torrent of bad news in the coming weeks and months.) As the graph below shows, survey week came before the surge in applications for unemployment insurance from 282,000 in the week ending the 14th (survey week) to 3.3 million the following week and 6.6 million during the week ending the 28th. It also came before the wave of stay-in-place orders, which began on March 20. Within a week, 20 states and 4 cities issued such orders. (There’s a helpful timeline here.) It’s striking that employers began shedding workers ahead of the closures, not a good portent for the April numbers.
Expectations are that the unemployment rate, which rose 0.9 to 4.4%, will rise by at least 10 points and possibly 20 or more over the next month or two. The broad measure of unemployment, U-6, which accounts for discouraged workers (those who’ve given up the job search as hopeless but have looked in the past year) and people working part-time who’d like full-time work, rose 1.7 point to 8.7%. There is just no precedent for this rate of job loss.
The monthly surveys of households, on which the official unemployment rates are based, began in 1948, so we don’t have good stats for the slide into the Great Depression. We do have highly unofficial monthly estimates of the unemployment rate assembled by the predecessor of today’s Conference Board, available from the National Bureau of Economic Research. Those are graphed below. At the time of the great stock market crash, October 1929, the jobless rate was 2.3%. A year later it was 9.0%. It took over two years to break 20%, finally peaking at 25.6% in May 1933. By some forecasts we’ll be there before summer.
Goldman Sachs attracted a lot of attention with its forecast that US GDP will be off 34% in the second quarter of this year. That is a very big number. It’s three-and-a-half times the worst quarter in US economic history since quarterly GDP stats began in 1947. (That quarter, by the way, was the first of 1958, the onset of a sharp recession, which featured, among other things, an “Asian flu.”) Here’s a little perspective on that number.
That 34% figure is annualized, meaning it’s what the total decline would amount to if the quarter’s rate were sustained for a full year. A 34% annualized decline works out to a 9.9% decline for the quarter alone.* Big, but at least it’s not a third.
Unless you’re a connoisseur of these things, though, you probably don’t know that we never fully recovered from the 2008–2009 recession. That point is made in the graph below. The line marked “trend” is based on the 2.1% average growth rate from 1970 to 2007, the year just before the Great Recession hit. The “actual” line is, as the name suggests, reported GDP per capita. The Goldman Sachs estimate for the second quarter is marked with the dot. If something like that forecast comes to pass, we will have undone the entire 2009–2019 recover/expansion cycle in a matter of months.
Note how from 1970 to 2007, the actual line bounces around the trend, rising above it in expansions (peaking around 1990 and 2000, for example), and falling below in recessions (like 1975 and 1982). Actual never strayed far from the trend—until taking a sharp tumble in 2008 and 2009, from which it never really recovered. Since 2009, the growth rate has averaged 1.6%. Last year, which Trump touted as the greatest economy ever, it managed to get back to the pre-2008 average of 2.1%, an average that includes two deep recessions (1973–1975 and 1981–1982).
At the end of 2019, actual was 13% below trend. At the end of the 2008–2009 recession it was 9% below trend. Remarkably, despite a decade-long expansion, it fell further below trend in well over half the quarters since the Great Recession ended. The gap is now equal to $10,200 per person—a permanent loss of income, as economists say. That doesn’t translate literally into a loss of $10,000 in personal income; there are lot of other things in GDP, like investment. And gains in personal income have been concentrated in the upper brackets for several decades, so that doesn’t mean the average American is $10,000 poorer than they would be had the economy recovered normally after 2009. It does mean we have a lot less in the way material resources than we should. And it suggested there were serious pathologies underlying a superficial and often strange “prosperity.”
That’s all gone now. Regardless of the exact number, we have almost certainly entered a very sharp downturn, one that could rival or exceed that of the early 1930s, though at a much faster tempo. We could experience in months what took three or four years to unfold after the 1929 stock market crash.
Goldman is expecting a rapid recovery later in the year. I find that hard to believe. A shock like covid-19 isn’t easily recovered from. Even if we find our footing in two or three quarters, we’ll probably see another permanent income loss, unless we undergo some serious structural reforms.
Yes, GDP is a flawed measure of material well-being. It says nothing about what the economy produces, at what human and ecological cost, or how it’s distributed. But GDP is a useful shorthand for the principles around which our society is organized. This analysis helps explain why things have felt so unsatisfying despite cheerful economic headlines for the last five or seven years. And it’s only going to get worse, and probably a lot worse.
*Normally, you can annualize a quarterly rate by just multiplying by 4, or “quarterize” an annual rate by dividing by 4. Such approximations are close enough with the small percentages associated with the ups and downs of US GDP. When the numbers get large, however, that trick doesn’t work because of compounding. The formula to compute the real quarterly rate from the annual one is ((1+-0.34)^(1/4))-1, which yields -9.9. Or, if you want to annualize -9.9, it’s ((1+-9.9)^4)-1, which yields -0.34. For simplicity’s sake I’ve omitted the percent sign.
Just added to my radio archive (click on date for link):
March 19, 2020 David Himmelstein of Physicians for a National Health Program and CUNY on how US health policy got us to this desperate pass • Helen Yaffe on Cuban interferon and COVID-19, and the country’s biotech industry and health system (YUP article here)
I’m going to be posting a series of commentaries on the current crisis. Here’s a quick first
It’s odd to see Democrats like Pelosi and Schumer objecting to Republican schemes to send everyone a check for $1,000, maybe two. Of course, one- or two-off checks for $1,000 won’t pay many of the the bills for very long. But talk of means-testing right now looks mean, cheap, and politically suicidal.
Schumer says that rather than write checks, we should expand unemployment insurance (UI) benefits. It would have to be some expansion. Benefits are low, of short duration, and available to a smaller share of the unemployed than in the past.
Right now, the average UI check is $372 a week and the average duration of benefits is just under 15 weeks. That works out to a total of $5,515. While well above $0, it still won’t take you very far. During the worst months of the last crisis, in early 2010, the average check was $307 and the duration of benefits 20 weeks, for a total of $6,236. That’s about a tenth the average household’s yearly income ($63,179).
And the share of the unemployed drawing benefits has declined over the decades. Now, less than a third of the unemployed are drawing benefits. (Those are known as “continuing claims,” in the jargon). In the 1970s it was around 40%, sometimes as high as 50%. The unemployed include people who’ve quit their jobs voluntarily, or are just entering or reentering the workforce. If you take them out and compare continuing claims to the number of job losers among the unemployed, the numbers are higher, but still dispiriting: not quite two-thirds. It was actually lower in the aftermath of the 2008–2009 crisis, just over 50%. In the 1970s, it was between 90% and 110% (!). It’s all in the graph below.
One wonders what sort of expansion Schumer has in mind, but it would have to be a very serious expansion to be of serious help in the coming months. In the meanwhile, don’t complain about $1,000 checks.
Just added to my radio archive (click on date for link):
March 5, 2020 Andrew Bacevich, historian and president of the Quincy Institute, on the history and structure of the US permanent war mobilization (Harper’s article, The Age of Illusions) • Chris Brooks on the UAW bribery/embezzlement scandal (articles: ITT, Intercept)
You can hardly look at Twitter without reading something about the impending AI revolution: robots are coming for your job. I’m a skeptic. By that I don’t mean to argue that IT and AI and all the other abbreviations and acronyms aren’t changing our world profoundly. They are. Tech affects everything—work, play, love, politics, art, all of it. But the maximalist version, where robots, equipped with artificial intelligence, are going to replace human workers, is way over done. No doubt they will replace some. But not all.
Back in 1987, ancient history in tech time, the economist Robert Solow observed, “You can see the computer age everywhere but in the productivity statistics.” That observation achieved cliché status, but unlike many of that breed, it was true. Productivity—measured as the dollar value of the output per hour of work, adjusted for inflation—had fell below its long-term average in the mid-1970s, one of many signs of the end of the post-World War II Golden Age, and would say there for 20 years. (See the graph below. Trend productivity in the graph is computed with a Hodrick–Prescott filter.)
Then, around 1995, productivity accelerated with the commercialization of the internet and the dot.com boom, which came with a surge in corporate investment in IT. Solow’s quip was retired, and the dawn of a new era was pronounced. Curiously, that productivity acceleration was a time of low unemployment and rising real wages—unlike the present, when unemployment is low but wage growth sucks. So by that precedent, there’s no reason to associate a productivity acceleration with job loss.
That new era lasted only about ten years. Productivity fell back into a slump, reaching all-time lows from 2014 to 2016. It’s picked up some since, but trend productivity growth is at levels comparable to the productivity slump of the late 1970s, 1980s, and early 1990s. So, we’re back in the land of Solow’s quip: robots aren’t visible in the productivity stats.
Here’s another way to look at it. Historically, it took just over 2% of GDP growth to generate a 1% increase in employment. For most of the last decade, employment growth has outstripped that historical norm. Lately the US economy has added almost 40,000 jobs a month more than GDP growth would suggest. That compares to an average gain lately of around 200,000. In other words, one out of every five jobs being produced in the US today wouldn’t be here if normal relationships between growth and employment were still holding sway. (See the graph below.)
GDP growth—which has been slow by historical standards—has also been producing larger declines in unemployment than you’d expect if old relationships were still in effect. If the robots were moving in, you’d expect just the opposite—job growth badly lagging economic growth, unemployment stickier than it has been. But these things are just not happening.
Maybe they will, though we’ve heard panicked tales of disappearing human workers since the onset of capitalism. Cries of alarm like “the robots are coming!” undermine the confidence of the working class and make people more grateful for whatever crap the system feeds them than they should be. Economic life is hard enough as it is without promoting mechanical competitors.