For a half century, the most recession-proof story in mainstream journalism has been declaring that college degrees aren’t recession-proof. Every economic downturn produces headlines warning that diplomas have lost—or are losing—their value. “Two things about these stories have remained constant,” Kevin Carey, who currently directs the education policy program at New America, wrote in The New Republic in 2011. “They always feature an over-educated bartender, and they are always wrong.”  

The genre dates back at least to the 1970s, when the Harvard labor economist Richard Freeman warned in his book The Overeducated American that too many people were earning degrees and that their long-term wages would suffer. The New York Times splashed the argument across its front page in 1975: “After generations during which going to college was assumed to be a sure route to the better life, college-educated Americans are losing their economic advantage.” But within the decade, the opposite happened: The wage premium for graduates soared, and it has only gone up more ever since.  

Census Bureau data shows that households headed by a bachelor’s-degree holder earn a median income of $132,700, more than double the $58,410 for those led by someone with only a high school diploma. Over the past two decades, degree-holding households saw real incomes rise by 13 percent, while high school-only households saw virtually no rise. As Carey wrote again in The Atlantic in 2023, that hasn’t stopped the cycle of headlines and sad profiles every time the economic cycle slows down.  

Which brings us to this fall’s entrant. On September 15, The New York Times published a story with the headline “The Newest Face of Long-Term Unemployment? The College Educated.” As of August 2025, there were about 1.9 million Americans classified by the Bureau of Labor Statistics as “long-term unemployed”—roughly 26 percent of all jobless workers. (The BLS defines long-term unemployed as people who are jobless for 27 weeks or more.) A decade ago, only one in five of those classified as long-term unemployed had a college degree. The Times reports that today, it’s closer to one in three, or more than half a million people. Their stories are as affecting as ever: Sean Wittmeyer, profiled in the Times piece, has two master’s degrees, and said he can’t even get hired at his local board game store. “Anyone with a free subscription to Claude, ChatGPT, could do a decent amount of what I could do before,” he lamented.  

AI certainly can’t be what is preventing Wittmeyer from getting a retail job, but something real is happening. Job openings have fallen from 12.1 million in March 2022 to 7.2 million in July 2025. Despite recent cuts, interest rates remain high. Tariffs are sporadic and unpredictable. Federal agencies are being gutted. At the same time, employers are leaning into generative AI tools that automate exactly the kind of entry-level work that young people have historically used to get a foothold: research, drafting, data entry, analysis. OpenAI researchers have documented how ChatGPT can now perform more than 50 percent of tasks across 19 percent of all occupations. It’s the worst-case convergence—short-term economic chaos colliding with long-term technological change.  

The Burning Glass Institute, a nonprofit labor market analytics firm, warns that the bottom rung of the career ladder is eroding. Its July 2025 report found that one year after graduation, 52 percent of the class of 2023 were working in jobs that didn’t require a degree. The report describes a “flipped pyramid”: steady demand for experienced workers paired with shrinking opportunities for new graduates. SignalFire, a venture capital firm, similarly found that between 2019 and 2024, there was a 50 percent decline in new roles for people with less than one year of experience at top tech firms. In sales, design, HR, engineering, and legal departments, the old footholds are vanishing. Add to that a brutal job search process. “Tinderized,” as Annie Lowrey ​​described it in The Atlantic—résumés screened by AI without human input, cookie-cutter cover letters written by AI, and hundreds of applications are disappearing into the ether. It’s no wonder that the Sean Wittmeyers of the world are discouraged.  

So the Times is not wrong to notice the strain. But the narrow focus on college grads risks obscuring the bigger story. The unemployment rate for recent college graduates (4.8 percent in June) is trending upward, but it’s still lower than that of all workers ages 22 to 27 (7.4 percent). In reality, the broader economy is wobbling: August’s 4.3 percent unemployment rate was the highest since 2021. BLS revisions shaved nearly a million jobs off the books between March 2024 and March 2025, ending a 53-month growth streak. Immigrant labor supply has fallen by 1.5 million workers in six months, further contributing to slowdowns in manufacturing and construction, which then reverberate to fields like real estate and architecture. Federal workforce cuts are on pace to eliminate 300,000 jobs by year’s end. In sum: The labor market is cooling for everyone. The present numbers, while sobering, do not tell the story of a collapse in the value of a college degree.  

Demographically, the long-term unemployed still skew less educated, nonwhite, and disabled. The roughly half-million long-term unemployed degree holders constitute less than half a percent of the U.S. labor force. And while college grads do make up a bigger slice of that pool than before, their overall unemployment rate remains far lower than that of workers without a degree. New grads as a group always take a certain amount of time to gain traction. “We graduate a new class of degree holders every year, who typically take seven to nine months to find a job that aligns with their skills,” says Courtney Brown of the Lumina Foundation. In a job market with nearly half as many openings as there were less than three years ago, that ramp-up is simply taking longer, Brown told me.  

History backs this up. The class of 2010 entered the workforce amid the wreckage of the Great Recession, with unemployment above 9 percent and 45 percent of the unemployed classified as long-term unemployed. At the time, they were branded a “lost generation.” Yet within a decade, their cohort’s wage premium over nongraduates had climbed back up even above normal levels, approaching an all-time high. Underemployment spikes for cohorts graduating into weak economies; then it falls as they move into better jobs.  

“The [career] ladder isn’t broken—it’s just being replaced with something that looks a lot flatter,” ​​Heather Doshay, formerly of the venture capital firm SignalFire, told CNBC. Today’s first job might be more technical or specialized—but it’s not inaccessible. “When the internet and email came on the scene as common corporate required skills,” Doshay noted, “new grads were well positioned to become experts by using them in school, and the same absolutely applies here with how accessible AI is.” The key, she said, “will be in how new grads harness their capabilities to become experts so they are seen as desirable tech-savvy workers who are at the forefront of AI’s advances.”  

Wages tend to follow productivity, and the workers best positioned to harness new technologies like AI in today’s economy are, by and large, college graduates. That is one reason degrees continue to command a premium. When the Great Recession hit, millions of Americans lost their jobs, but college graduates were the most likely to be employed at the outset and least likely to be unemployed as the crisis went on.

Economists also caution against declaring AI a job killer just yet. Anders Humlum, an economist at the University of Chicago, points out that predictions about AI’s long-term labor market impact are still highly speculative. “We now have two and a half years of experience with generative AI chatbots diffusing widely throughout the economy,” Humlum told CNBC, and “these tools have not made a significant difference for employment or earnings in any occupation thus far.”  

Universities are responding too—purchasing premium and university-specific services from companies ​​like OpenAI and Anthropic, offering hands-on AI courses, and transforming campuses into training grounds for a more digitally fluent workforce.  

So the education-to-employment conveyor belt might be noisier and slower than in the past, but it’s still moving. AI is reshaping the early stages of careers, not eliminating them entirely. A twenty-year-old can use AI to polish a cover letter, build a pitch deck, or practice job interviews. A designer can generate prototypes, a welder can simulate repairs. Many skills that used to require formal apprenticeship or classroom time are now teachable by machine. As Bruno V. Manno argued recently in the Monthly, AI raises the bar for demonstrated expertise—but it lowers the barrier to acquiring it.  

And if the short-term picture is cloudy, the long-term fundamentals point in the opposite direction. A new Georgetown University Center on Education and the Workforce report, Falling Behind, projects that by 2032 the U.S. will be short 5.25 million workers with postsecondary credentials, including 4.5 million with a bachelor’s degree or higher. Managers, teachers, nurses, engineers, accountants, and physicians are all on the shortage list. The culprits: Baby Boomer retirements, declining college enrollment and completion, and restrictive immigration policy. Far from being oversupplied with college graduates, the nation is on track for a severe shortage.  

Jobs demanding higher-order human skills—problem solving, communication, leadership—are likely to keep expanding, even in an AI-saturated economy. Those skills are exactly what college educations develop, and what AI cannot replace. That’s consistent with what we already see in the labor market. Even during today’s slowdown, degree holders earn far more, face lower unemployment, and enjoy better long-term prospects than their peers without diplomas. They live longer, are healthier, and are more likely to own homes.  

Why does the myth endure? Not because the reporting is false—the Times is right that more graduates are showing up among the long-term unemployed, and their stories deserve attention. What’s misleading is the leap from moment to meaning: the implication that the degree itself is losing value in the labor market. As Carey wrote almost 15 years ago, “People naturally tend to project current trends into the future, missing the up-and-down nature of the business cycle.” Today’s pain reflects two overlapping shocks: the economic whiplash of Trump’s second term, and AI tools that are rapidly automating the lowest rungs of white-collar work. Those forces make it harder for new graduates to get started—but history and data both show that the long-term premium on higher education is rising, not collapsing. 

Misreading cyclical pain as structural collapse has consequences. It erodes public confidence in higher education. In 2015, 57 percent of Americans said they had “a great deal or quite a lot of confidence” in higher ed. By 2024, that had fallen to 36 percent, while the share expressing little or no confidence more than tripled, to 32 percent. When students absorb the message that college isn’t worth it, whether because of rising costs, wokeness, or the rise of AI, they’re more likely to forgo it. That fuels a cycle that benefits no one: not the student’s long-term health and wages, not the economy that needs more educated workers, and not colleges that depend on enrollment. 

None of this diminishes the difficulty of Sean Wittmeyer’s job search. But it’s worth noting, as the Times buried at the end of its story, that he is now using his design skills to develop and sell board games. The college degree has endured for a reason. What we need isn’t fewer of them, but better-aligned ones: programs tailored to workforce demand, policies that boost affordability and completion, and institutions that help students translate education into opportunity. The bartender with a doctorate will always be good copy. But the degree remains the surest, sturdiest path to prosperity.  

The post No, College Degrees Aren’t Losing Their Value   appeared first on Washington Monthly.

As one of President Joe Biden’s top economic advisers, I frequently made my way out to the White House North Lawn to give interviews to the media about the state of the U.S. economy. Especially as the pandemic-induced recession faded in the rearview mirror, I was out there hundreds of times touting how the unemployment rate was at 50-year lows on the back of remarkably strong job growth. Inflation was falling and inflation-adjusted pay was rising.

And yet in every single interview, I got the same question: So why aren’t people feeling it? Why so much good data amid so many bad vibes?

In fact, the question was not hard to answer. It comes down to one word, a word that defines the dominant economic challenge with which American families have been struggling for years: affordability. Whether it’s housing, child care, health care, groceries, utilities, insurance, or other costs, significant numbers of Americans have found that these and other critical goods and services are either out of reach or so pricey that, after they’ve paid for them, they don’t have enough money left to even think about getting ahead.

This duality between the data and how people experience the economy is the subject of The Mismeasurement of America, by Gene Ludwig, a former comptroller of the currency during the Clinton administration. Focusing on unemployment, wages, inflation, and the growing economic distance between Americans at the top and the bottom of the income scale, Ludwig argues that the problem is that the numbers I was touting were, if not quite wrong, then “profoundly misleading.” He then develops his own set of numbers, which he argues better explain why people have long felt a lot worse about the economy than you’d glean from the government’s top-line statistics. While Ludwig is right that top-line numbers, all of which are broad averages, fail to present a full picture of how the different income classes are faring, that’s not a “mismeasurement” problem. It instead reflects the impossibility of encompassing in just a few numbers something as complex and disparate as the U.S. economy. A better title for his book might have been “The Incomplete Measurement of America.”

Ludwig’s critique of inflation statistics is particularly germane to the affordability crisis. The Consumer Price Index is an overall metric that averages out the changes in prices faced by 90 percent of the population. (The CPI does not include prices in extremely rural areas, farm households, and religious communities, among other exceptions.) Ludwig reasonably worries, however, that the average obscures important differences in inflation between income groups.

The Bureau of Labor Statistics, which publishes the CPI, has itself been looking into this and they find that from 2005 to 2024, prices rose 66 percent for those in the bottom fifth of the income scale but just 57 percent for those at the top. This disparity is a double disadvantage: Such households face both lower incomes and higher prices. Ludwig’s adjusted CPI, which he calls the “True Living Cost,” or TLC, captures this dynamic by significantly up-weighting in the index the goods and services that dominate the consumption basket of less-well-off households, including housing, health care, food, and child care.

While this is the right way to drill down on the affordability challenges facing low- and middle-income families today, Ludwig misses one of the more important positive price developments of our time. For technology goods, like computers and smartphones, the TLC registers large price increases while the CPI registers the opposite. The CPI has it right, reflecting a rare cost decline that’s actively making us better off. The BLS statisticians adjust for the fact that computers and cell phones are remarkably more powerful than they used to be. Decades ago, it would have cost millions of dollars for a computer to do what a $700 laptop can do today. Adjusted for quality, the cost of such technology has fallen sharply over the years, and this decline has improved consumer welfare. Yet the TLC appears to ignore these quality improvements and somehow has technology costs soaring over time.

For another example of how Ludwig offers an overreaching solution to a real measurement challenge, consider unemployment. Ludwig argues that instead of the 4.3 percent unemployment rate for August reported by the BLS, what he calls the TRU—the “True Rate of Unemployment”—is 24.7 percent. Anyone with even a passing familiarity with the history of unemployment in America will realize that Ludwig has either made a mistake or is aggressively redefining unemployment. The last time unemployment was that high was during the Great Depression.

Ludwig’s “unemployment” rate, however, includes a lot of people who are, in fact, working, both part-timers and low earners. His terminology is thus off, as is his critique of the current measurement system, which is clearly, transparently, and consistently measuring what it says it’s measuring. If you looked for a job and you didn’t find one, you’re unemployed. That simple and intuitive definition has revealed important information about labor market conditions for many decades.

But as Ludwig’s adjustments reveal, there were a lot more underemployed and underpaid people in the American labor force in August than 4.3 percent. That doesn’t make the official unemployment rate wrong or misleading. Though Donald Trump, who recently fired the commissioner of the BLS, might claim otherwise, our statistical agencies continue to rigorously churn out valid, reliable numbers. (Trump doesn’t like that they show the tariffs raising prices and cracks forming in the job market, but that’s actually a testament to their accuracy.) But Ludwig’s metric helps to bridge the gap between what the official jobless numbers say and the struggle that many working Americans go through every day.

Extracting from these weedy details, and recognizing that the current system is not mismeasuring America, Ludwig’s book provides an important bridge between good data and bad vibes. As he shows, in an economy where inequality has been on the rise for decades, where millions are underemployed, where poor people’s inflation rises faster than that of the rich, averages increasingly fail to tell the full economic story.

Of course, many authors, most notably Thomas Piketty in Capital in the Twenty-First Century, have made this point before. But by looking at the problem through the lens of jobs, hours worked, wages paid, the costs of housing (and utilities, such as electricity), child care, health care, and so on, Ludwig’s measurements help to shine a light on a policy agenda to address the affordability crisis. His underemployment rate would come down, for example, if we helped involuntary part-timers move to full-time schedules. (Ludwig would correctly note that such a change would not show up in a lower unemployment rate.) An affordability agenda, which Neale Mahoney and I describe in a new brief from the Stanford Institute for Economic Policy Research, would help make it easier for economically stretched families to afford housing (by making it easier and cheaper to build), child care (through targeted subsidies), and health care (reversing coverage cuts, Medicare buy-in) in ways that would directly feed into Ludwig’s alternate cost-of-living measure.

What we should take from this book, then, is not that America is mismeasured. It’s that the gap between what the top-line numbers report and how folks feel about their economic situation is, in part, a function of the increase in economic inequality, of how far they’ve fallen relative to the average. Should we want to better understand how America is really doing, we must dig deeper into the numbers.

The post Measuring the Vibecession appeared first on Washington Monthly.

As one of President Joe Biden’s top economic advisers, I frequently made my way out to the White House North Lawn to give interviews to the media about the state of the U.S. economy. Especially as the pandemic-induced recession faded in the rearview mirror, I was out there hundreds of times touting how the unemployment rate was at 50-year lows on the back of remarkably strong job growth. Inflation was falling and inflation-adjusted pay was rising.

And yet in every single interview, I got the same question: So why aren’t people feeling it? Why so much good data amid so many bad vibes?

In fact, the question was not hard to answer. It comes down to one word, a word that defines the dominant economic challenge with which American families have been struggling for years: affordability. Whether it’s housing, child care, health care, groceries, utilities, insurance, or other costs, significant numbers of Americans have found that these and other critical goods and services are either out of reach or so pricey that, after they’ve paid for them, they don’t have enough money left to even think about getting ahead.

This duality between the data and how people experience the economy is the subject of The Mismeasurement of America, by Gene Ludwig, a former comptroller of the currency during the Clinton administration. Focusing on unemployment, wages, inflation, and the growing economic distance between Americans at the top and the bottom of the income scale, Ludwig argues that the problem is that the numbers I was touting were, if not quite wrong, then “profoundly misleading.” He then develops his own set of numbers, which he argues better explain why people have long felt a lot worse about the economy than you’d glean from the government’s top-line statistics. While Ludwig is right that top-line numbers, all of which are broad averages, fail to present a full picture of how the different income classes are faring, that’s not a “mismeasurement” problem. It instead reflects the impossibility of encompassing in just a few numbers something as complex and disparate as the U.S. economy. A better title for his book might have been “The Incomplete Measurement of America.”

Ludwig’s critique of inflation statistics is particularly germane to the affordability crisis. The Consumer Price Index is an overall metric that averages out the changes in prices faced by 90 percent of the population. (The CPI does not include prices in extremely rural areas, farm households, and religious communities, among other exceptions.) Ludwig reasonably worries, however, that the average obscures important differences in inflation between income groups.

The Bureau of Labor Statistics, which publishes the CPI, has itself been looking into this and they find that from 2005 to 2024, prices rose 66 percent for those in the bottom fifth of the income scale but just 57 percent for those at the top. This disparity is a double disadvantage: Such households face both lower incomes and higher prices. Ludwig’s adjusted CPI, which he calls the “True Living Cost,” or TLC, captures this dynamic by significantly up-weighting in the index the goods and services that dominate the consumption basket of less-well-off households, including housing, health care, food, and child care.

While this is the right way to drill down on the affordability challenges facing low- and middle-income families today, Ludwig misses one of the more important positive price developments of our time. For technology goods, like computers and smartphones, the TLC registers large price increases while the CPI registers the opposite. The CPI has it right, reflecting a rare cost decline that’s actively making us better off. The BLS statisticians adjust for the fact that computers and cell phones are remarkably more powerful than they used to be. Decades ago, it would have cost millions of dollars for a computer to do what a $700 laptop can do today. Adjusted for quality, the cost of such technology has fallen sharply over the years, and this decline has improved consumer welfare. Yet the TLC appears to ignore these quality improvements and somehow has technology costs soaring over time.

For another example of how Ludwig offers an overreaching solution to a real measurement challenge, consider unemployment. Ludwig argues that instead of the 4.3 percent unemployment rate for August reported by the BLS, what he calls the TRU—the “True Rate of Unemployment”—is 24.7 percent. Anyone with even a passing familiarity with the history of unemployment in America will realize that Ludwig has either made a mistake or is aggressively redefining unemployment. The last time unemployment was that high was during the Great Depression.

Ludwig’s “unemployment” rate, however, includes a lot of people who are, in fact, working, both part-timers and low earners. His terminology is thus off, as is his critique of the current measurement system, which is clearly, transparently, and consistently measuring what it says it’s measuring. If you looked for a job and you didn’t find one, you’re unemployed. That simple and intuitive definition has revealed important information about labor market conditions for many decades.

But as Ludwig’s adjustments reveal, there were a lot more underemployed and underpaid people in the American labor force in August than 4.3 percent. That doesn’t make the official unemployment rate wrong or misleading. Though Donald Trump, who recently fired the commissioner of the BLS, might claim otherwise, our statistical agencies continue to rigorously churn out valid, reliable numbers. (Trump doesn’t like that they show the tariffs raising prices and cracks forming in the job market, but that’s actually a testament to their accuracy.) But Ludwig’s metric helps to bridge the gap between what the official jobless numbers say and the struggle that many working Americans go through every day.

Extracting from these weedy details, and recognizing that the current system is not mismeasuring America, Ludwig’s book provides an important bridge between good data and bad vibes. As he shows, in an economy where inequality has been on the rise for decades, where millions are underemployed, where poor people’s inflation rises faster than that of the rich, averages increasingly fail to tell the full economic story.

Of course, many authors, most notably Thomas Piketty in Capital in the Twenty-First Century, have made this point before. But by looking at the problem through the lens of jobs, hours worked, wages paid, the costs of housing (and utilities, such as electricity), child care, health care, and so on, Ludwig’s measurements help to shine a light on a policy agenda to address the affordability crisis. His underemployment rate would come down, for example, if we helped involuntary part-timers move to full-time schedules. (Ludwig would correctly note that such a change would not show up in a lower unemployment rate.) An affordability agenda, which Neale Mahoney and I describe in a new brief from the Stanford Institute for Economic Policy Research, would help make it easier for economically stretched families to afford housing (by making it easier and cheaper to build), child care (through targeted subsidies), and health care (reversing coverage cuts, Medicare buy-in) in ways that would directly feed into Ludwig’s alternate cost-of-living measure.

What we should take from this book, then, is not that America is mismeasured. It’s that the gap between what the top-line numbers report and how folks feel about their economic situation is, in part, a function of the increase in economic inequality, of how far they’ve fallen relative to the average. Should we want to better understand how America is really doing, we must dig deeper into the numbers.

The post Measuring the Vibecession appeared first on Washington Monthly.

For a half century, the most recession-proof story in mainstream journalism has been declaring that college degrees aren’t recession-proof. Every economic downturn produces headlines warning that diplomas have lost—or are losing—their value. “Two things about these stories have remained constant,” Kevin Carey, who currently directs the education policy program at New America, wrote in The New Republic in 2011. “They always feature an over-educated bartender, and they are always wrong.”  

The genre dates back at least to the 1970s, when the Harvard labor economist Richard Freeman warned in his book The Overeducated American that too many people were earning degrees and that their long-term wages would suffer. The New York Times splashed the argument across its front page in 1975: “After generations during which going to college was assumed to be a sure route to the better life, college-educated Americans are losing their economic advantage.” But within the decade, the opposite happened: The wage premium for graduates soared, and it has only gone up more ever since.  

Census Bureau data shows that households headed by a bachelor’s-degree holder earn a median income of $132,700, more than double the $58,410 for those led by someone with only a high school diploma. Over the past two decades, degree-holding households saw real incomes rise by 13 percent, while high school-only households saw virtually no rise. As Carey wrote again in The Atlantic in 2023, that hasn’t stopped the cycle of headlines and sad profiles every time the economic cycle slows down.  

Which brings us to this fall’s entrant. On September 15, The New York Times published a story with the headline “The Newest Face of Long-Term Unemployment? The College Educated.” As of August 2025, there were about 1.9 million Americans classified by the Bureau of Labor Statistics as “long-term unemployed”—roughly 26 percent of all jobless workers. (The BLS defines long-term unemployed as people who are jobless for 27 weeks or more.) A decade ago, only one in five of those classified as long-term unemployed had a college degree. The Times reports that today, it’s closer to one in three, or more than half a million people. Their stories are as affecting as ever: Sean Wittmeyer, profiled in the Times piece, has two master’s degrees, and said he can’t even get hired at his local board game store. “Anyone with a free subscription to Claude, ChatGPT, could do a decent amount of what I could do before,” he lamented.  

AI certainly can’t be what is preventing Wittmeyer from getting a retail job, but something real is happening. Job openings have fallen from 12.1 million in March 2022 to 7.2 million in July 2025. Despite recent cuts, interest rates remain high. Tariffs are sporadic and unpredictable. Federal agencies are being gutted. At the same time, employers are leaning into generative AI tools that automate exactly the kind of entry-level work that young people have historically used to get a foothold: research, drafting, data entry, analysis. OpenAI researchers have documented how ChatGPT can now perform more than 50 percent of tasks across 19 percent of all occupations. It’s the worst-case convergence—short-term economic chaos colliding with long-term technological change.  

The Burning Glass Institute, a nonprofit labor market analytics firm, warns that the bottom rung of the career ladder is eroding. Its July 2025 report found that one year after graduation, 52 percent of the class of 2023 were working in jobs that didn’t require a degree. The report describes a “flipped pyramid”: steady demand for experienced workers paired with shrinking opportunities for new graduates. SignalFire, a venture capital firm, similarly found that between 2019 and 2024, there was a 50 percent decline in new roles for people with less than one year of experience at top tech firms. In sales, design, HR, engineering, and legal departments, the old footholds are vanishing. Add to that a brutal job search process. “Tinderized,” as Annie Lowrey ​​described it in The Atlantic—résumés screened by AI without human input, cookie-cutter cover letters written by AI, and hundreds of applications are disappearing into the ether. It’s no wonder that the Sean Wittmeyers of the world are discouraged.  

So the Times is not wrong to notice the strain. But the narrow focus on college grads risks obscuring the bigger story. The unemployment rate for recent college graduates (4.8 percent in June) is trending upward, but it’s still lower than that of all workers ages 22 to 27 (7.4 percent). In reality, the broader economy is wobbling: August’s 4.3 percent unemployment rate was the highest since 2021. BLS revisions shaved nearly a million jobs off the books between March 2024 and March 2025, ending a 53-month growth streak. Immigrant labor supply has fallen by 1.5 million workers in six months, further contributing to slowdowns in manufacturing and construction, which then reverberate to fields like real estate and architecture. Federal workforce cuts are on pace to eliminate 300,000 jobs by year’s end. In sum: The labor market is cooling for everyone. The present numbers, while sobering, do not tell the story of a collapse in the value of a college degree.  

Demographically, the long-term unemployed still skew less educated, nonwhite, and disabled. The roughly half-million long-term unemployed degree holders constitute less than half a percent of the U.S. labor force. And while college grads do make up a bigger slice of that pool than before, their overall unemployment rate remains far lower than that of workers without a degree. New grads as a group always take a certain amount of time to gain traction. “We graduate a new class of degree holders every year, who typically take seven to nine months to find a job that aligns with their skills,” says Courtney Brown of the Lumina Foundation. In a job market with nearly half as many openings as there were less than three years ago, that ramp-up is simply taking longer, Brown told me.  

History backs this up. The class of 2010 entered the workforce amid the wreckage of the Great Recession, with unemployment above 9 percent and 45 percent of the unemployed classified as long-term unemployed. At the time, they were branded a “lost generation.” Yet within a decade, their cohort’s wage premium over nongraduates had climbed back up even above normal levels, approaching an all-time high. Underemployment spikes for cohorts graduating into weak economies; then it falls as they move into better jobs.  

“The [career] ladder isn’t broken—it’s just being replaced with something that looks a lot flatter,” ​​Heather Doshay, formerly of the venture capital firm SignalFire, told CNBC. Today’s first job might be more technical or specialized—but it’s not inaccessible. “When the internet and email came on the scene as common corporate required skills,” Doshay noted, “new grads were well positioned to become experts by using them in school, and the same absolutely applies here with how accessible AI is.” The key, she said, “will be in how new grads harness their capabilities to become experts so they are seen as desirable tech-savvy workers who are at the forefront of AI’s advances.”  

Wages tend to follow productivity, and the workers best positioned to harness new technologies like AI in today’s economy are, by and large, college graduates. That is one reason degrees continue to command a premium. When the Great Recession hit, millions of Americans lost their jobs, but college graduates were the most likely to be employed at the outset and least likely to be unemployed as the crisis went on.

Economists also caution against declaring AI a job killer just yet. Anders Humlum, an economist at the University of Chicago, points out that predictions about AI’s long-term labor market impact are still highly speculative. “We now have two and a half years of experience with generative AI chatbots diffusing widely throughout the economy,” Humlum told CNBC, and “these tools have not made a significant difference for employment or earnings in any occupation thus far.”  

Universities are responding too—purchasing premium and university-specific services from companies ​​like OpenAI and Anthropic, offering hands-on AI courses, and transforming campuses into training grounds for a more digitally fluent workforce.  

So the education-to-employment conveyor belt might be noisier and slower than in the past, but it’s still moving. AI is reshaping the early stages of careers, not eliminating them entirely. A twenty-year-old can use AI to polish a cover letter, build a pitch deck, or practice job interviews. A designer can generate prototypes, a welder can simulate repairs. Many skills that used to require formal apprenticeship or classroom time are now teachable by machine. As Bruno V. Manno argued recently in the Monthly, AI raises the bar for demonstrated expertise—but it lowers the barrier to acquiring it.  

And if the short-term picture is cloudy, the long-term fundamentals point in the opposite direction. A new Georgetown University Center on Education and the Workforce report, Falling Behind, projects that by 2032 the U.S. will be short 5.25 million workers with postsecondary credentials, including 4.5 million with a bachelor’s degree or higher. Managers, teachers, nurses, engineers, accountants, and physicians are all on the shortage list. The culprits: Baby Boomer retirements, declining college enrollment and completion, and restrictive immigration policy. Far from being oversupplied with college graduates, the nation is on track for a severe shortage.  

Jobs demanding higher-order human skills—problem solving, communication, leadership—are likely to keep expanding, even in an AI-saturated economy. Those skills are exactly what college educations develop, and what AI cannot replace. That’s consistent with what we already see in the labor market. Even during today’s slowdown, degree holders earn far more, face lower unemployment, and enjoy better long-term prospects than their peers without diplomas. They live longer, are healthier, and are more likely to own homes.  

Why does the myth endure? Not because the reporting is false—the Times is right that more graduates are showing up among the long-term unemployed, and their stories deserve attention. What’s misleading is the leap from moment to meaning: the implication that the degree itself is losing value in the labor market. As Carey wrote almost 15 years ago, “People naturally tend to project current trends into the future, missing the up-and-down nature of the business cycle.” Today’s pain reflects two overlapping shocks: the economic whiplash of Trump’s second term, and AI tools that are rapidly automating the lowest rungs of white-collar work. Those forces make it harder for new graduates to get started—but history and data both show that the long-term premium on higher education is rising, not collapsing. 

Misreading cyclical pain as structural collapse has consequences. It erodes public confidence in higher education. In 2015, 57 percent of Americans said they had “a great deal or quite a lot of confidence” in higher ed. By 2024, that had fallen to 36 percent, while the share expressing little or no confidence more than tripled, to 32 percent. When students absorb the message that college isn’t worth it, whether because of rising costs, wokeness, or the rise of AI, they’re more likely to forgo it. That fuels a cycle that benefits no one: not the student’s long-term health and wages, not the economy that needs more educated workers, and not colleges that depend on enrollment. 

None of this diminishes the difficulty of Sean Wittmeyer’s job search. But it’s worth noting, as the Times buried at the end of its story, that he is now using his design skills to develop and sell board games. The college degree has endured for a reason. What we need isn’t fewer of them, but better-aligned ones: programs tailored to workforce demand, policies that boost affordability and completion, and institutions that help students translate education into opportunity. The bartender with a doctorate will always be good copy. But the degree remains the surest, sturdiest path to prosperity.  

The post The College Degree Is Not Losing Value   appeared first on Washington Monthly.

Following recent monthly jobs reports, officials in Donald Trump’s administration and their supporters have highlighted a remarkable increase in native-born employment. The Vice President, the Secretary of Labor, and the new nominee for Bureau of Labor Statistics (BLS) commissioner have all recently announced that there are two million more employed native-born Americans than a year ago.

It’s not just administration cheerleaders: Respected economists on the center-left and center-right have also charted and commented on these trends in native-born and foreign-born employment. And no wonder: immigration is a contentious topic that directly affects the economy. (Note: these figures are readily accessible in the monthly jobs report, and the historical series of native-born employment and foreign-born employment are easily downloadable on the Federal Reserve Economic Data (FRED) site.) 

However, agencies caution that these data are unsuitable for estimating and analyzing trends in the foreign-born and native-born populations. In fact, the “boom” in native-born employment is merely a statistical illusion caused by complex rules in how the data are compiled and population figures are calculated.  

The best way to gauge how native-born Americans are doing is to look at their unemployment rate. The native-born unemployment rate has gone up over the past year, while the foreign-born unemployment rate hasn’t. 

Before getting into the technical details, let’s pause to ask whether the supposed foreign-born and native-born employment trends pass the sniff test. The Current Population Survey (CPS) shows that the foreign-born population dropped by 2.2 million from January to July, and foreign-born employment by 1 million. That’s far different than a recent estimate by leading researchers that full-year 2025 net immigration could range from +115 thousand to -525 thousand. Furthermore, the CPS reports that the native-born adult population rose by 3 million from January to July, and native-born employment was up 2.5 million in those six months. How is that possible when population growth excluding immigration is typically over half a million annually? Was there a baby boom 16 years ago, now entering the workforce? Or a medical innovation that prevented any deaths this year? A moment’s thought says these swings are implausible. 

Admittedly, the Center for Immigration Studies, which has reported on some of these trends, correctly notes that the “CPS is the only up-to-date public data source that allows for analysis of the total foreign-born population.” However, even though CPS can be used to estimate the size of the foreign-born and native-born populations, it is not designed for that purpose, and you shouldn’t attempt it. Here’s why. 

There are three reasons why the CPS should not be used to estimate the population or employment of the native-born or foreign-born.  

First, the CPS has a small sample size. For example, the July 2025 estimate of foreign-born employment at 30.8 million has a “confidence interval” of plus or minus 720 thousand. In other words, there’s a 95 percent chance that foreign-born employment falls within a range of over 1.4 million around that 30.8 million estimate. That’s huge! Total annual immigration to the U.S. is usually less than that confidence interval. Unsurprisingly, the Census Bureau “routinely cautions against” using the CPS to estimate the foreign-born population. 

The second  reason is more technical—and damning: the annual CPS population adjustment. The CPS updates the survey each January to match the latest Census population estimates. The total population reported in the CPS sometimes jumps significantly up or down. In January 2025, the adjustment was substantial, adding 3.5 million people overall, which increased the number of adults by 2.9 million, employed people by 2.0 million, and native-born employed people by 1.2 million.  

Historical CPS data are not revised. Table A-7 of the July jobs report shows a 2 million increase in native-born employment between July 2024 and July 2025, but 1.2 million of that increase—more than half—is due to the population adjustment in January 2025. It’s not an apples-to-apples comparison.  

The third reason is the most important. Census population estimates serve as the “population controls” for the CPS. That means the total population reported each month in 2025 in the CPS equals the monthly population projections that the Census calculated in late 2024. These population controls predetermine not just the total population but also the population by age, sex, and race & ethnicity. That means we also already know that the CPS will report that there are, for instance, 5,308,938 Hispanic/Latino men age 25-34 in October 2025. 

In contrast, the native-born and foreign-born populations are not set by Census estimates. Instead, nativity (whether someone was born in the U.S. or elsewhere) depends on survey responses. However, the native-born and foreign-born populations must sum to the predetermined totals for the population and demographic groups, known as “population controls.” If foreign-born responses decrease for any reason, the survey’s sampling and weighting procedures will adjust the native-born population so that the total matches the population controls. 

Imagine an extreme thought experiment: suppose the entire foreign-born U.S. population vanished at the end of July: Tens of millions of people gone. What would that look like in the CPS? The reported foreign-born population would drop to zero. But because the total population is predetermined, the reported native-born population would swell to equal the predetermined population controls through sampling and weighting procedures.  

It’s plausible, though unverifiable, that the foreign-born population, as reported by the CPS, has fallen by some amount because of some mix of less immigration, more deportations, and declining survey response rates among fearful immigrants. That would cause the reported native-born population in the CPS to rise. 

If the foreign-born population decreases or their response rate declines, the reported native-born population would naturally appear larger in demographic categories with a higher proportion of immigrants. We should observe a greater increase in the reported native-born population among Hispanic/Latino men aged 25-34—a group with a high share of immigrants—compared to, for example, White women aged 65-74, a predominantly native-born group. 

Let’s examine the numbers. CPS reported that the native-born adult population increased from 222,243 thousand in January 2025 to 225,276 thousand in July 2025, a rise of 3 million people or 1.4 percent. This growth was disproportionately focused in demographic groups with a high share of non-citizen immigrants who are likely more hesitant to respond to surveys: Hispanics/Latinos aged 25 to 64 and Asian-Americans aged 25 to 44. (Older Asian immigrants are more likely to be naturalized citizens.) Analyzing CPS microdata, the native-born population in these high-immigrant demographic groups grew an implausibly high 5.9 percent between January and July, while the native-born population in all other groups increased by only 0.9 percent over the same period—a sixfold difference. 

One hypothesis about the decline in the foreign-born population and the increase in the native-born population doesn’t hold up: respondents aren’t changing their self-reported nativity status from foreign to native across the months they respond to the survey. In 2025, just 0.1 percent of respondents who said in their final month in the survey that they were native-born had responded in any previous month that they were foreign-born. This small share of respondents who switched from being foreign-born to claiming they were native-born is tiny compared to the reported growth in the native-born population. 

Therefore, the reported rise in the native-born population—year over year or since January—is due to population adjustment and population controls used in the CPS. The sharp decline in the foreign-born population is suspiciously large; the reality is likely a combination of a slowly growing or possibly slightly shrinking foreign-born population, along with decreasing response rates among foreign-born respondents. However, the significant jump in the native-born population is an artifact of survey sampling and weighting. It provides no real insight into the actual native-born American population, employment figures, or labor-market experience. 

Here’s What We DO Know about Immigration and Nativity from the Jobs Report 

Luckily, the jobs report shows how native-born and foreign-born people are doing in the labor market. For the foreign-born, unemployment was 4.1 percent in July 2025, down from 4.7 percent in July 2024. For the native-born, it was 4.7 percent in July 2025, slightly higher than 4.5 percent in July 2024. 

Like everything in the CPS, the unemployment rate is based on a small sample, so it’s always good to average over several months to smooth out volatility and compare the same months in previous years to eliminate seasonal patterns. Comparing the six-month average from February to July 2025 with that of February to July 2024: the foreign-born unemployment rate was 4.1 percent in both years, and the native-born unemployment rate increased from 4.0 percent in 2024 to 4.3 percent in 2025. Native-born workers are faring worse in the labor market this year than they did last year, before the end of the immigration surge in summer 2024. 

But what about those new 2 million employed native-born Americans in the past year? Look at that table again. The 2 million increase in native-born employment represents a 1.5 percent rise. However, the number of unemployed native-born Americans grew at a faster rate, by 6.1 percent. When quirks in the CPS population adjustment and population controls methods inflate the population for groups like the native-born, they inflate everything: not just the number employed but also the number unemployed and not in the labor force.  

The unemployment rate is the most reliable information the CPS provides about both native- and foreign-born populations. Ignore population and employment levels: they can be misleading. 

The other part of the jobs report—the payroll survey—provides a different perspective on how immigration influences the labor market. Employers are not asked about the citizenship or birthplace of their workers, but industries vary greatly in how many of their employees are immigrants. Using an algorithm developed by economist George Borjas, I estimated the share of unauthorized immigrants in different industries based on American Community Survey data and compared the monthly job growth in high unauthorized-immigrant industries with that in the rest of the private sector. 

Job growth in high-unauthorized-immigrant industries started lagging other industries after the immigration surge ended in mid-2024 and has been flat since the start of 2025. Job growth in other industries has also slowed, but less so. The end of the immigration surge coincided with a slowdown in the immigrant workforce and the growth rate of industries that rely more on immigrants.  

If Charting Native-Born Employment Levels Is a Crime, Are the Statistical Agencies Accomplices? 

No. The Census warns against using the CPS to estimate the size of the foreign-born and native-born populations, and BLS discourages users from comparing data across years. Ignore their warnings at your peril. 

The post No, Native-Born Employment Has Not Soared  appeared first on Washington Monthly.

The Bureau of Labor Statistics (BLS) surprised the markets and most economists Friday with an announcement that the unemployment rate fell from 14.7 percent in April to 13.3 percent in May. President Donald Trump had the temerity to boast that George Floyd, the unarmed black man killed by a white police officer in Minneapolis, was “looking down from heaven” to admire those numbers. “This is a great day for him,” Trump said in the Rose Garden. “This is a great day for everybody.”

Beyond the president’s remarkable and offensive invocation of Floyd, there is good reason to be skeptical of his administration’s latest report.

BLS asserts that 20,935,000 Americans were unemployed in May, attributing the decline to employers adding 2,509,000 jobs in May as states allowed “a limited resumption of economic activity.” But it’s not that simple. The unexpected decline in the jobless rate is based on a survey of businesses and households conducted over the week of May 16th, and BLS has also reported that 29,965,415 Americans received unemployment insurance benefits in the same week.  That’s a gap of 8,980,415 people, enough to raise the May jobless rate 5.7 percentage points to 19.0 percent and much closer to economists’ expectations.

How did the Labor Department come up with such a low figure?  Part of it is the Payroll Protection Program: The BLS counted anyone who employers say were still being paid as employed “even if they were not actually at their jobs.”  Part of it involves how the BLS treats the many millions of people now on furlough and not being paid. They are considered “unemployed on temporary layoff.”  But if BLS expects them to return to their old jobs, based on the survey, they do not count among the unemployed.

Those judgments are left to the BLS’s discretion, and the agency does not issue any data on those decisions. Yet a recent analysis from the Becker Friedman Institute at the University of Chicago estimated that 42 percent of people furloughed by the COVID-19 crisis will never get their old jobs back, and only 30 percent of those laid off will land new jobs later this year. With 30 million people receiving unemployment benefits, that analysis is more consistent with unemployment at 19.0 percent today than 13.3 percent.  BLS itself acknowledges in its May report that counting those on furlough as unemployed would raise its official rate to 16.3 percent.

Finally, part of the 9 million-person discrepancy may involve how BLS decides whether a person who is not working is still part of the labor force. If you are out of work but didn’t look for a job over the previous four weeks, or couldn’t work for family reasons such as caring for children who are no longer in school, BLS says you are out of the labor force.  If you’re not in the labor force, you’re not unemployed.

Again, it is BLS’s judgment call—and BLS clearly has decided that millions of people who lost their jobs because of COVID-19 shutdowns do not count as unemployed. In May 2019, BLS reported that 96,207,000 working-age Americans were not in the labor force; today, BLS reported that a year later, that number had jumped by 5,865,000 to 102,072,000.  For reference, the BLS found that 95,636,000 working-age Americans were not in the labor force in 2019, down 80,000 from 2018. Those 5,865,000 people could explain nearly two-thirds of the 9 million-person gap between those receiving unemployment benefits and those counted as unemployed.

Sometimes, unexpected events produce wildly inaccurate results from computer models that assume the unexpected won’t happen. Perhaps there is a glitch in the BLS unemployment model that couldn’t accommodate disruptions from the COVID black swan. We also have seen the Trump administration interfere with scientific analysis in other areas, such as when it directed what models the U.S. Geological Survey could use for the mandated National Climate Assessment. It would be unprecedented for the White House to pressure the Labor Department to produce a jobless report that serves Donald Trump’s needs and desires.  But unlike the May unemployment report, it would not surprise anyone.

The post No, the Unemployment Rate Didn’t Really Drop in May appeared first on Washington Monthly.

April’s 14.7 percent unemployment rate, announced by the Labor Department last Friday, is awful by any standard. The official tally shows that unemployment increased by 15,938,000 people last month—to 23,078,000 overall—resulting in the highest jobless rate since the Great Depression.

As depressing as that may be, it’s not the full story. The Labor Department also reported Friday that the number of employed Americans fell by 22,369,000 people in April. If you reconcile the gap between 22,369,000 and 15,938,000, you’ll find that the real unemployment rate is much worse. The actual unemployment rate for April was at least 18.6 percent.

The erroneous reporting is not part of a conspiracy. The Census Bureau collects the data as part of its monthly Current Population Survey; the Bureau of Labor Statistics (BLS) then analyzes the findings.  But when layoffs skyrocket suddenly—as they have since the COVID-19 Pandemic took off—the survey’s categories and the terms the BLS uses to interpret the results produce a huge underestimate of real unemployment.

One major issue involves how the Census survey and BLS analysts count people who were furloughed from their jobs in April. Normally, the BLS rules say that anyone laid off temporarily does not count as unemployed. In March, BLS modified that rule by holding that individuals working for a business that was closed by the pandemic could be counted as either on temporary furlough or unemployed. Workers are therefore categorized based on how they described their work situation to the Census surveyors.  Publicly, BLS would like to have it both ways:  It reported that 18,063,000 Americans were “unemployed on temporary layoff” in April without saying how many of them it counted as unemployed.

We can make a reasonable estimate.  A recent Washington Post poll found that 77 percent of people laid off recently expect to return to their jobs, so they probably were not counted as unemployed under the current BLS rule.  Based on this finding, the BLS counted the other 23 percent—4,154,490 of those now furloughed—as unemployed.

Yet many of the other 13,085,510 furloughed workers who expect to get their old jobs back will be disappointed. A new study from the University of Chicago projects that 42 percent of recent layoffs will be permanent. Those findings suggest that 42 percent of the 18,063,000 workers furloughed in April—7,586,460 rather than 4,154,490—actually were laid off permanently. If that’s correct, BLS should add another 3,431,970 Americans to those officially counted as unemployed last month.

Another big problem with the April unemployment report involves how BLS decides who has left the labor force. Anyone not working who tells the Census surveyor that they were not “available” to take a new job or did not actively try to find one during the preceding four weeks is not considered to be part of the labor force, and therefore does not count as unemployed. Most months, the size of the labor force changes little, because new people entering it largely offset new retirees, people with new disabilities, and those who simply stop working. In February, the labor force shrank by 60,000 people.

The pandemic has changed that: BLS calculates that the labor force contracted by an astounding 6,432,000 people in April, including 4,252,000 Americans who wanted to work. As with those on furlough, the huge and abrupt labor market changes driven by the pandemic overwhelm BLS’s normal categories; and many of those seen as dropping out of the labor force should be counted as unemployed.

In fact, millions of Americans were not “available” for work in April because they were caring for children whose schools were closed—and millions of people didn’t look for new jobs because the avalanche of layoffs made a job search pointless. They fit a textbook definition of individuals whom the BLS excludes from the ranks of the labor force, and so do not count as unemployed. BLS further notes that 23 percent of those excluded from the labor force are  “marginally attached,” meaning they want a job but didn’t look for one, most likely because they have family or health issues or don’t believe any jobs are available. At a minimum, 23 percent of the 6,432,000 people newly excluded from the labor force in April also should be added to the list of the unemployed.

Finally, the Census survey asked people about their job status–during the course of one week—from April 12 to April 19. This technicality usually doesn’t matter much, because unemployment normally changes little in any month, much less in its last week. Again, the pandemic changed that.  We know that during the week following April 1, nearly 3.5 million more Americans filed for unemployment benefits.

Add up these three changes, and unemployment in April increased by at least 6,075,399 more than the 15,938,000 officially reported by BLS, jumping by 22,013,399 to a total of 29,153,399 Americans, for a real unemployment rate of at least 18.6 percent.

Throughout this pandemic, President Trump has tried to gaslight the American people by denying, wishing away, and minimalizing the COVID-19 threat and its mounting spread. Failing at this, his administration now insists that an economic recovery is right around the corner. Like the virus, however, Trump’s PR campaign is already colliding with a reality plainly and painfully evident to anyone willing to look at it.

The post The Real Unemployment Rate Is Worse Than Trump Will Tell Us appeared first on Washington Monthly.

The Bureau of Labor Statistics released their June report this morning with the news that the economy added 213,000 jobs last month. The unemployment rate ticked up to 4 percent as more people entered the job market. Here’s how the First Daughter responded:

Since election day, the American economy has added 3.7 million jobs!
601,000 more Americans entered the labor force.
June #JobsReport beat forecasts and added 213,000 jobs. @POTUS’s Economic Agenda is clearly working + creating opportunities for ALL Americans. ??

— Ivanka Trump (@IvankaTrump) July 6, 2018

In a further attempt to politicize the news, a headline at the Washington Examiner reads: “Dems blast booming jobs report, Trump worker agenda, ‘reckless.’” That is based on statements released by Minority Leader Nancy Pelosi and DNC Chair Tom Perez. The “Trump worker agenda” that these two Democratic leaders called reckless specifically addressed the president’s trade wars, tax cuts for the wealthy and the latest union-busting Supreme Court decision.

But here’s the part of the jobs report that we should all be focused on right now:

Wage growth stayed at 2.7 percent, the same pace as last month, and the average since last December. It is also worth noting that inflation is now growing at about the same rate as wages, so, in one of the less impressive aspects of the current job market recovery, real hourly pay is flat.

Republicans can crow all they want about jobs, but as long as real hourly pay is flat, the current economic agenda isn’t working or creating opportunity for all Americans.

When Barack Obama was inaugurated in 2009, the economy was losing about 800,000 jobs a month due to the Great Recession. At that point, a singular focus on creating jobs was necessary. That is no longer the case. A certain base level of job creation is necessary to keep the economy strong, but that is a maintenance issue. The real problem right now is wages. The fact that, when combined with inflation, real hourly pay is flat indicates that workers can’t get ahead. Too many people are stuck in jobs that don’t pay a living wage and they’re not making any headway, even as the economic expansion that began in June 2009 enters its tenth year.

It’s true that Democrats have a lot of ideas about how to improve the economy and reduce income inequality. But the fastest and easiest first thing on the agenda needs to be an increase in the minimum wage. That is something everyone to the left of the current extremists in charge of our government can agree on. It is beyond time to put living wages at the top of the Democratic agenda.

The post Democrats Need to Pivot From Jobs and Focus on Wages appeared first on Washington Monthly.