Posts Tagged ‘Unemployment’
“Statistics are like bikinis. What they reveal is suggestive, but what they conceal is vital.”*…
Former Comptroller of the Currency Eugene Ludwig argues that, at least insofar as many (maybe most) Americans are concerned, unemployment is higher, wages are lower, and growth is less robust than government statistics suggest…
Before the presidential election, many Democrats were puzzled by the seeming disconnect between “economic reality” as reflected in various government statistics and the public’s perceptions of the economy on the ground. Many in Washington bristled at the public’s failure to register how strong the economy really was. They charged that right-wing echo chambers were conning voters into believing entirely preposterous narratives about America’s decline.
What they rarely considered was whether something else might be responsible for the disconnect — whether, for instance, government statistics were fundamentally flawed. What if the numbers supporting the case for broad-based prosperity were themselves misrepresentations? What if, in fact, darker assessments of the economy were more authentically tethered to reality?
On some level, I relate to the underlying frustrations. Having served as comptroller of the currency during the 1990s, I‘ve spent substantial chunks of my career exploring the gaps between public perception and economic reality, particularly in the realm of finance. Many of the officials I’ve befriended and advised over the last quarter-century — members of the Federal Reserve, those running regulatory agencies, many leaders in Congress — have told me they consider it their responsibility to set public opinion aside and deal with the economy as it exists by the hard numbers. For them, government statistics are thought to be as reliable as solid facts.
In recent years, however, as my focus has broadened beyond finance to the economy as a whole, the disconnect between “hard” government numbers and popular perception has spurred me to question that faith. I’ve had the benefit of living in two realms that seem rarely to intersect — one as a Washington insider, the other as an adviser to lenders and investors across the country. Toggling between the two has led me to be increasingly skeptical that the government’s measurements properly capture the realities defining unemployment, wage growth and the strength of the economy as a whole.
These numbers have time and again suggested to many in Washington that unemployment is low, that wages are growing for middle America and that, to a greater or lesser degree, economic growth is lifting all boats year upon year. But when traveling the country, I’ve encountered something very different…
… Within the nation’s capital, this gap in perception has had profound implications. For decades, a small cohort of federal agencies have reported many of the same economic statistics, using fundamentally the same methodology or relying on the same sources, at the same appointed times. Rarely has anyone ever asked whether the figures they release hew to reality. Given my newfound skepticism, I decided several years ago to gather a team of researchers under the rubric of the Ludwig Institute for Shared Economic Prosperity to delve deeply into some of the most frequently cited headline statistics.
What we uncovered shocked us. The bottom line is that, for 20 years or more, including the months prior to the election, voter perception was more reflective of reality than the incumbent statistics. Our research revealed that the data collected by the various agencies is largely accurate. Moreover, the people staffing those agencies are talented and well-intentioned. But the filters used to compute the headline statistics are flawed. As a result, they paint a much rosier picture of reality than bears out on the ground.
Take, as a particularly egregious example, what is perhaps the most widely reported economic indicator: unemployment. Known to experts as the U-3, the number misleads in several ways. First, it counts as employed the millions of people who are unwillingly under-employed — that is, people who, for example, work only a few hours each week while searching for a full-time job. Second, it does not take into account many Americans who have been so discouraged that they are no longer trying to get a job. Finally, the prevailing statistic does not account for the meagerness of any individual’s income. Thus you could be homeless on the streets, making an intermittent income and functionally incapable of keeping your family fed, and the government would still count you as “employed.”
I don’t believe those who went into this past election taking pride in the unemployment numbers understood that the near-record low unemployment figures — the figure was a mere 4.2 percent in November — counted homeless people doing occasional work as “employed.” But the implications are powerful. If you filter the statistic to include as unemployed people who can’t find anything but part-time work or who make a poverty wage (roughly $25,000), the percentage is actually 23.7 percent. In other words, nearly one of every four workers is functionally unemployed in America today — hardly something to celebrate…
[Ludwig similarly analyzes data on wages, inflation, and GDP, finding them similarlly flawed…]
… Take all of these statistical discrepancies together. What we have here is a collection of economic indicators that all point in the same misleading direction. They all shroud the reality faced by middle- and lower-income households. The problem isn’t that some Americans didn’t come out ahead after four years of Bidenomics. Some did. It’s that, for the most part, those living in more modest circumstances have endured at least 20 years of setbacks, and the last four years did not turn things around enough for the lower 60 percent of American income earners.
To be fair, the prevailing indicators aren’t without merit. It is, for example, useful to know how the wages of full-time employees have evolved. The challenge, quite separate from any quibbling with the talented people working to tell the nation’s economic story, is to provide policymakers with a full picture of the reality faced by the bulk of the population. What we need is to find new ways to provide a more realistic picture of the nation’s underlying economic conditions on a monthly basis. The indicators my colleagues and I have constructed could serve as the basis for or inspiration for government-sponsored alternatives. Regardless, something needs to change.
This should not be a partisan issue — policymakers in both parties would benefit from gleaning a more accurate sense of what’s happening at the ground level of the American economy. In reality, both Democrats and Republicans were vulnerable to being snowed in the 2024 cycle — it just happened that the dissatisfaction during this particular cycle undermined the incumbent party.
In an age where faith in institutions of all sorts is in free fall, Americans are perpetually told, per a classic quote from former Sen. Daniel Patrick Moynihan, that while we may be entitled to our own opinions, we aren’t entitled to our own facts. That should be right, at least in the realm of economics. But the reality is that, if the prevailing indicators remain misleading, the facts don’t apply. We have it in our grasp to cut through the mirage that led Democrats astray in 2024. The question now is whether we will correct course…
On the need to revise our economic reference statistics: “Voters Were Right About the Economy. The Data Was Wrong.” from @LISEP_org in @POLITICOMag. Eminently worth reading in full.
More on (and more-current readings of) the suggested “revised metrics” at the Ludwig Institute for Shared Economic Prosperity.
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As we muse on measurement and meaning, we might recall that it was on this date in 1979 that The Cars released “Good Times Roll,” the third single from their eponymously-titled debut album.
“Economic problems have no sharp edges. They shade off imperceptibly into politics, sociology, and ethics. Indeed, it is hardly an exaggeration to say that the ultimate answer to every economic problem lies in some other field.”*…
The number of households that live above the poverty line but are barely scraping by is ticking higher…
Over time, higher costs and sluggish wage growth have left more Americans financially vulnerable, with many known as “ALICEs.”
Nearly 40 million families, or 29% of the population, fall in the category of ALICE — Asset Limited, Income Constrained, Employed — according to United Way’s United for ALICE program, which first coined the term to refer to households earning above the poverty line but less than what’s needed to get by.
That figure doesn’t include the 37.9 million Americans [individuals, as opposed to families as measured above] who live in poverty, comprising 11.5% of the total population, according to data from the U.S. Census Bureau.
“ALICE is the nation’s child-care workers, home health aides and cashiers heralded during the pandemic — those working low-wage jobs, with little or no savings and one emergency from poverty,” said Stephanie Hoopes, national director at United for ALICE…
Read on for an explanation of how high inflation and higher interest rates have aggravated what was already a problem: “29% of households have jobs but struggle to cover basic needs,” from @CNBC.
Apposite: “Millions of Americans are about to lose internet access, and Congress is to blame.”
(Image above: source)
***
As we knit a safety net, we might recall that, on this date in 2020, as a product of the COVID-19 recession, the U.S. unemployment rate to hit 14.9 percent, its worst rate since the Great Depression. Federal legislators enacted six major bills, centered on the American Rescue Plan and costing about $5.3 trillion, to help manage the pandemic and mitigate the economic burden on families and businesses. Those programs have now expired.
“Humanity is acquiring all the right technology for all the wrong reasons”*…
Further to yesterday’s post on the poverty created by manufacturing displacement, and in the wake of the sturm und drang occasioned by the coup at OpenAI, the estimable Rana Foroohar on the politics of AI…
… Consider that current politics in the developed world — from the rise of Donald Trump to the growth of far right and far left politics in Europe — stem in large part from disruptions to the industrial workforce due to technology and globalisation. The hollowing out of manufacturing work led to more populist and fractious politics, as countries tried (and often failed) to balance the needs of the global marketplace with those of voters.
Now consider that this past summer, the OECD warned that white-collar, skilled labour representing about a third of the workforce in the US and other rich countries is most at risk from disruption by AI. We are already seeing this happen in office work — with women and Asians particularly at risk since they hold a disproportionate amount of roles in question. As our colleague John Burn-Murdoch has charted [image above], online freelancers are especially vulnerable.
So, what happens when you add more than three times as many workers, in new subgroups, to the cauldron of angry white men that have seen their jobs automated or outsourced in recent decades? Nothing good. I’m always struck when CEOs like Elon Musk proclaim that we are headed towards a world without work as if this is a good thing. As academics like Angus Deaton and Anne Case have laid out for some time now, a world without work very often leads to “deaths of despair,” broken families, and all sorts of social and political ills.
Now, to be fair, Goldman Sachs has estimated that the productivity impact of AI could double the recent rate — mirroring the impact of the PC revolution. This would lead to major growth which could, if widely shared, do everything from cut child poverty to reduce our burgeoning deficit.
But that’s only if it’s shared. And the historical trend lines for technology aren’t good in that sense — technology often widens wealth disparities before labour movements and government regulation equalise things. (Think about the turn of the 20th century, up until the 1930s). But the depth and breadth of AI disruption may well cause unprecedented levels of global labour displacement and political unrest.
I am getting more and more worried that this is where we may be heading. Consider this new National Bureau of Economic Research working paper, which analyses why AI will be as transformative as the industrial revolution. It also predicts, however, that there is a very good chance that it lowers the labour share radically, even pushing it to zero, in lieu of policies that prevent this (the wonderful Daron Acemoglu and Simon Johnson make similar points, and lay out the history of such tech transformation in their book Power and Progress…
We can’t educate ourselves out of this problem fast enough (or perhaps at all). We also can’t count on universal basic income to fix everything, no matter how generous it could be, because people simply need work to function (as Freud said, it’s all about work and love). Economists and political scientists have been pondering the existential risks of AI — from nuclear war to a pandemic — for years. But I wonder if the real existential crisis isn’t a massive crisis of meaning, and the resulting politics of despair, as work is displaced faster than we can fix the problem…
Everyone’s worried about AI, but are we worried about the right thing? “The politics of AI,” from @RanaForoohar in @FT.
See also: Henry Farrell‘s “What OpenAI shares with Scientology” (“strange beliefs, fights over money, and bad science fiction”) and Dave Karpf‘s “On OpenAI: Let Them Fight.” (“It’s chaos… And that’s a good thing.”)
For a different point-of-view, see: “OpenAI and the Biggest Threat in the History of Humanity,” from Tomás Pueyo.
And for deep background, read Benjamin Labatut‘s remarkable The MANIAC.
* R. Buckminster Fuller
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As we equilibrate, we might recall that it was on this date in 1874 that electrical engineer, inventor, and physicist Ferdinand Braun published a paper in the Annalen der Physik und Chemie describing his discovery of the electrical rectifier effect, the original practical semiconductor device.
(Braun is better known for his contributions to the development of radio and television technology: he shared the 1909 Nobel Prize in Physics with Guglielmo Marconi “for their contributions to the development of wireless telegraphy” (Braun invented the crystal tuner and the phased-array antenna); was a founder of Telefunken, one of the pioneering communications and television companies; and (as the builder of the first cathode ray tube) has been called the “father of television” (shared with inventors like Paul Gottlieb Nipkow).
“Bureaucracy defends the status quo long past the time when the quo has lost its status”*…
… which is one of the reasons that they’re hard to update. Kevin Baker describes a 1998 visit to the IRS Atlanta Service Center and ponders its lessons…
… the first thing you’d notice would be the wires. They ran everywhere, and the building obviously hadn’t been constructed with them in mind. As you walked down a corridor, passing carts full of paper returns and rows of “tingle tables,” you would tread over those wires on a raised metal gangway. Each work area had an off-ramp, where both the wires and people would disembark…
… The desks were covered with dot matrix paper, cartons of files, and Sperry terminals glowing a dull monochromatic glow. These computers were linked to a mainframe in another room. Magnetic tapes from that mainframe, and from mainframes all over the country, would be airlifted to National Airport in Washington DC. From there, they’d be put on trucks to a West Virginia town of about 14,000 people called Martinsburg. There, they’d be loaded into a machine, the first version of which was known colloquially—and not entirely affectionately—as the “Martinsburg Monster.” This computer amounted to something like a national nerve center for the IRS. On it programs called the Individual Master File and the Business Master File processed the country’s tax records. These programs also organized much of the work. If there were a problem at Martinsburg, work across the IRS’s offices spanning the continent could and frequently did shut down.
Despite decades of attempts to kill it, The IRS’s Individual Master File, an almost sixty-year old accumulation of government Assembly Language, lives on. Part of this strange persistence can be pegged squarely on Congress’s well-documented history of starving the IRS for funding. But another part of it is that the Individual Master File has become so completely entangled in the life of the agency that modernizing it resembles delicate surgery more than a straightforward software upgrade. Job descriptions, work processes, collective bargaining agreements, administrative law, and technical infrastructure all coalesce together and interface with it, so that a seemingly technical task requires considerable sociological, historical, legal, and political knowledge.
In 2023, as it was in the 1980s, the IRS is a cyborg bureaucracy, an entangled mass of law, hardware, software, and clerical labor. It was among the first government agencies to embrace automatic data processing and large-scale digital computing. And it used these technologies to organize work, to make decisions, and to understand itself. In important ways, the lines between the digital shadow of the agency—its artificial bureaucracy—and its physical presence became difficult if not impossible to disentangle….
Baker is launching a new Substack, devoted to exploring precisely this kind tangle– and what it might portend…
This series, called Artificial Bureaucracy, is a long-term project looking at the history of government computing in the fifty-year period between 1945-1995. I think this is a timely subject. In the past several years, promoters and critics of artificial intelligence alike have talked up the possibility that decision-making and even governance itself may soon be handed over to sophisticated AI systems. What draws together both the dreams of boosters and the nightmares of critics is a deterministic orientation towards the future of technology, a conception of technology as autonomous and somehow beyond the possibility of control.
These visions mostly ignore the fact that the computerization of governance is a project at least seventy years in the making, and that project has never been determined, in the first instance or the last, primarily by “technological” factors. Like everything in government, the hardware and software systems that make up its artificial bureaucracy were and are subject to negotiation, conflict, administrative inertia, and the individual agency of its users.
Looking at government computing can also tell us something about AI. The historian of computing, Michael Mahoney has argued that studying the history of software is the process of learning how groups of people came to put their worlds in a machine. If this is right—and I think it is—our conceptions of “artificial intelligence” have an unwarranted individualistic bias; the proper way to understand machine intelligence isn’t by analogy to individual human knowledge and decision-making, but to methods of bureaucratic knowledge and action. If it is about anything, the story of AI is the story of bureaucracy. And if the future of governance is AI, then it makes sense to know something about its past…
Is bureaucracy the future of AI? Check it out the first post in Artificial Bureaucracy, from @kevinbaker@mastodon.social.
* Laurence J. Peter
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As we size up systems, we might recall that it was on this date in 1935 that President Franklin D. Roosevelt signed the Social Security Act. A key component of Roosevelt’s New Deal domestic program, the Act created both the Social Security program and insurance against unemployment.
“An imbalance between rich and poor is the oldest and most fatal ailment of all republics”*…
In a stark sign of the economic inequality that has marked the pandemic recession and recovery, Americans as a whole are now earning the same amount in wages and salaries that they did before the virus struck — even with nearly 9 million fewer people working.
The turnaround in total wages underscores how disproportionately America’s job losses have afflicted workers in lower-income occupations rather than in higher-paying industries, where employees have actually gained jobs as well as income since early last year.
In February 2020, Americans earned $9.66 trillion in wages and salaries, at a seasonally adjusted annual rate, according to the Commerce Department data. By April, after the virus had flattened the U.S. economy, that figure had shrunk by 10%. It then gradually recovered before reaching $9.67 trillion in December, the latest period for which data is available.
Those dollar figures include only wages and salaries that people earned from jobs. They don’t include money that tens of millions of Americans have received from unemployment benefits or the Social Security and other aid that goes to many other households. The figures also don’t include investment income…
The figures document that the vanished earnings from 8.9 million Americans who have lost jobs to the pandemic remain less than the combined salaries of new hires and the pay raises that the 150 million Americans who have kept their jobs have received.
The job cuts resulting from the pandemic recession have fallen heavily on lower-income workers across the service sector— from restaurants and hotels to retail stores and entertainment venues. By contrast, tens of millions of higher-income Americans, especially those able to work from home, have managed to keep or acquire jobs and continue to receive pay increases.
“We’ve never seen anything like that before,” said Richard Deitz, a senior economist at the Federal Reserve Bank of New York, referring to the concentration of job losses. “It’s a totally different kind of downturn than we’ve experienced in modern times.”
The figures also underscore the unusually accelerated nature of this recession. As a whole, both the job losses that struck early last spring and the initial rebound in hiring that followed have happened much faster than they did in previous recessions and recoveries. After the Great Recession, for example, it took nearly 2 1/2 years for wages and salaries to regain their pre-recession levels…
One reason why the job losses have had relatively little impact on the nation’s total pay is that so many of the affected employees worked part time. The average work week in the industry that includes hotels, restaurants and bars is just below 26 hours. That’s the shortest such figure among 13 major industries tracked by the government. The next shortest is retail, at about 31 hours. The average for all industries is nearly 35 hours.
The recovery in wages and salaries helps explain why some states haven’t suffered as sharp a drop in tax revenue as many had feared. That is especially true for states that rely on progressive taxes that fall more heavily on the rich. California, for example, said last month that it has a $15 billion budget surplus. Yet many cities are still struggling, and local transit agencies, such as New York City’s subway, have been hammered by the pandemic.
The wage and salary data also helps explain the steady gains in the stock market, which have been led by high-tech companies whose products are being heavily purchased and used by higher-income Americans, such as Apple iPads, Peloton bikes, or Amazon’s online shopping.
This week, the New York Fed released research that underscored how focused the job losses have been. For people making less than $30,000 a year, employment has fallen 14% as of December. For those earning more than $85,000, it has actually risen slightly. For those in-between, employment has fallen 4%…
Some companies have cut wages in this recession, but on the whole the many millions of Americans fortunate enough to keep their jobs have generally received pay raises at largely pre-recession rates. Some of those income gains likely reflect cost-of-living raises; the Commerce Department’s wage and salary data isn’t adjusted for inflation…
Truman Bewley, a retired Yale University economist who wrote a book about the concept of sticky wages, said that most companies have a key core of workers they rely on through hard times and are reluctant to cut pay for them.
And there’s another reason, Bewley said, why many companies cut jobs instead of pay. While researching his book, he said a factory manager told him why his company did so: “It gets the misery out the door.”
More at: “Sign of inequality: US salaries recover even as jobs haven’t.”
See also “More Than 33 Million Americans Have Filed for Unemployment During Coronavirus Pandemic.” source of the image above.
And to compare the U.S. to other countries, try this nifty interactive visualization.
* Plutarch
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As we examine equity, we might send foundational birthday greetings to Pierre le Pesant, sieur de Boisguilbert; he was born on this date in 1646. A French lawmaker and a Jansenist, he is best remembered as one of the inventors of the notion of an economic market– he championed free trade in opposition to Colbert‘s mercantilist views (which generated government revenues through duties and tariffs).
But he is also noteworthy as the champion of a single tax on each citizen (in lieu of all tariffs, customs, and other trade-related fees) that in some ways presaged Henry George‘s proposals.
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