Category: Labor Economics

Higher Minimum Wages Can Result in “Reduced Hours Worked”

(p. A17) Researchers who support raising the minimum wage often advocate a “close comparison”—using an area geographically nearby. The classic in this genre is the 1994 study of the fast-food industry by David Card and Alan Krueger. The minimum wage had been raised in New Jersey from $4.25 to $5.05, but had stayed flat in Pennsylvania. The two economists surveyed fast-food restaurants on either side of the state border and actually found sharp job gains in New Jersey.

I’m on record, in a 2000 paper, as arguing that the Card-Krueger study was based on flawed data. But other researchers using the “close comparison” method, such as Michael Reich at Berkeley, also have generally found that a higher minimum wage does not cause job losses. Those studies have fed into rosy policy reports saying that a $15 minimum wage would help workers with little downside.

Critics say these studies do not convincingly control for shocks to the low-skill labor market. Moreover, comparing across state borders is inherently difficult. Perhaps politicians in one state felt comfortable raising the minimum wage because the labor market there was already strong, while the other state was struggling. In that case, job losses from the higher minimum wage could be masked by the broader trend.

. . .

The dispute over methodology explains the importance of this summer’s research on Seattle’s minimum-wage experiment. The city’s wage floor, previously about $9.50 an hour, has been raised to $13 and is on its way to $15. A comprehensive study by academics at the University of Washington estimated that the higher minimum “reduced hours worked in low-wage jobs by around 9 percent.” Consequently, earnings for these employees actually dropped “by an average of $125 per month.”

What’s especially inconvenient for minimum-wage proponents is that the Seattle study used a “close comparison” method similar to the one they have favored for years. The authors of the study compared workers in Seattle with those in other metropolitan areas in Washington, like Olympia, Tacoma and Spokane.

For the full commentary, see:

David Neumark. “The $15 Minimum Wage Crowd Tries a Bait and Switch.” The Wall Street Journal (Thursday, Sept. 26, 2017): A17.

(Note: ellipsis added.)

(Note: the online version of the commentary has the date Sept. 25, 2017, and has the same title as the print version.)

Newmark’s comment on the Card and Krueger paper, mentioned above, is:

Neumark, David, and William L. Wascher. “Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania: Comment.” American Economic Review 90, no. 5 (Dec. 2000): 1362-96.

To Avoid “Misconduct” Starbucks Asks “That All Future Elections Be Conducted Fully in Person”

(p. B5) As the union drive at Starbucks stores accelerates, Starbucks has ratcheted up its efforts to push back on the campaign, asking on Monday [Sept. 15, 2022] that the National Labor Relations Board investigate allegations of misconduct during a union vote in the Kansas City area.

Starbucks, in a letter to the labor board, asked that the agency investigate reports by an N.L.R.B. employee that there was unfair coordination between the agency and the union, specifically that several employees were given special voting arrangements and that the N.L.R.B. provided confidential real-time election results to the union. The company asked that the agency suspend all elections until the allegations could be investigated. In addition, Starbucks asked that all future elections be conducted fully in person.

For the full story, see:

Emma Goldberg. “Citing Misconduct Claims, Starbucks Asks to Halt Union Elections.” The New York Times (Tuesday, August 16, 2022): B5.

(Note: bracketed date added.)

(Note: the online version has the date Aug. 15, 2022, and has the title “Starbucks Asks for a Suspension of Union Elections.”)

Covid-19 Health Effects Will Keep Reducing Labor Force

(p. A1) As the United States emerges from the pandemic, employers have been desperate to hire. But while demand for goods and services has rebounded, the supply of labor has fallen short, holding back the economy.

. . .

(p. A20) Morning Consult found in August [2022] that prime-age adults who aren’t working cited a variety of often overlapping reasons for not wanting jobs. In a monthly poll of 2,200 people, 40 percent said they believed that they wouldn’t be able to find a job with enough flexibility, while 38 percent were limited by family situations and personal obligations. But the biggest category, at 43 percent, was medical conditions.

Other data suggest some of that is due to long-term complications from Covid-19, although estimates of how many people have been knocked out of the work force by Covid range tremendously.

Katie Bach, a Brookings Institution fellow, put the impact at two million to four million full-time workers, based on her interpretation of the Census Bureau’s Household Pulse Survey and other research. (The total affected may be larger, with many who suffer from long Covid reducing their hours rather than stopping work.) A Federal Reserve economist didn’t specify a number, but observed that even as Covid-related hospitalizations and deaths receded, the share of people saying they were not able to work because of illness or disability had remained elevated in Labor Department data after spiking in early 2021.

Another analysis, in a paper published by the National Bureau of Economic Research, found that people who’d taken a week off for health-related reasons in 2020 and 2021 were 7 percent less likely to be in the labor force a year later — which equates to about 500,000 workers.

Whatever the magnitude, the effects are likely to be significant and long-lasting. Vaccines provide imperfect protection against getting long Covid, studies suggest, and other post-viral diseases have proven difficult to recover from. “I certainly don’t think the worst is behind us,” Ms. Bach said.

For the full story, see:

Lydia DePillis. “Pool of Labor In U.S. Stays Bafflingly Low.” The New York Times (Saturday, September 13, 2022): A1 & A20.

(Note: ellipsis, and bracketed year, added.)

(Note: the online version has the date Sept. 12, 2022, and has the title “Who Are America’s Missing Workers?”)

The NBER paper mentioned above is:

Goda, Gopi Shah, and Evan J. Soltas. “The Impacts of Covid-19 Illnesses on Workers.” National Bureau of Economic Research Working Paper No. 30435, Sept. 2022.

NU President Carter May Earn $1.5 Million Per Year by 2023

(p. B1) LINCOLN — The University of Nebraska Board of Regents extended President Ted Carter’s contract by three years on Thursday, potentially keeping the university’s top leader in Nebraska through 2027.

Carter’s new contract, approved unanimously, also raises his base salary by 3% this year and adds a second deferred compensation package to incentivize the president to stay at NU.

In all, Carter’s total compensation could top $1.5 million beginning in 2023.

. . .

Regents also awarded Carter, a former superintendent of the U.S. Naval Academy, a $105,000 performance bonus for the (p. B1) 2021-22 academic year.

That amount is less than the $140,000 he was eligible to receive; Carter hit 89% of the benchmarks set for him by the board last year after first- to second-year retention numbers fell at several NU campuses.

For the full story, see:

CHRIS DUNKER, Lincoln Journal Star. “NU President Given Raise, Extension.” The Omaha World-Herald (Friday, August 12, 2022): B1-B2.

(Note: the online version of the story was updated Sept. 18, 2022, and has the title “Regents approve contract extension, pay raise for NU president.”)

Minorities, Disabled, Less-Educated, and Felons Are First Laid Off in a Recession

(p. A1) Black Americans have been hired much more rapidly in the wake of the pandemic shutdowns than after previous recessions. But as the Federal Reserve tries to soften the labor market in a bid to tame inflation, economists worry that Black workers will bear the brunt of a slowdown — and that without federal aid to cushion the blow, the impact could be severe.

Some 3.5 million Black workers lost or left their jobs in March and April 2020. In weeks, the unemployment rate for Black workers soared to 16.8 percent, the same as the peak after the 2008 financial crisis, while the rate for white workers topped out at 14.1 percent.

Since then, the U.S. economy has experienced one of its fastest rebounds ever, one that has extended to workers of all races. The Black unemployment rate was 6 percent last month, just above the record low of late 2019. And in government data collected since the 1990s, wages for Black workers are rising at their fastest pace ever.

Now policymakers at the Fed and in the White House face the challenge of fighting inflation without inducing a recession that would erode or reverse those workplace gains.

Decades of research has found that workers from racial and ethnic minorities — along with those with other barriers to employment, such as disabilities, criminal records or low levels of education — are among the first laid off during a downturn and the last hired during a recovery.

For the full story, see:

Talmon Joseph Smith and Ben Casselman. “Job Gains for Black Workers Could Reverse in a Downturn.” The New York Times (Wednesday, August 24, 2022): A1 & A14.

(Note: the online version of the story has the same date as the print version and has the title “What Will Happen to Black Workers’ Gains if There’s a Recession?”)

Current Labor Market Seems Robustly Redundant

In Openness to Creative Destruction, I argue for the possibility and desirability of a “robustly redundant labor market” in which workers can usually quickly find an equally good or better job when they lose their current job.

(p. A6) . . . one characteristic of today’s economy is that job cuts at small startups and large companies have yet to dent the overall labor market. Labor demand is still historically strong, offering only faint signs of cooling. There are nearly two job openings for every unemployed person seeking work. That means many workers who are losing their jobs are quickly landing jobs. Some are even weighing multiple offers and accepting positions that pay more and better align with their skills.

. . .

Employers had 10.7 million unfilled jobs in June [2022], down from a record of 11.9 million in March, but still well above the 7 million job openings in February 2020 ahead of the pandemic, when the labor market was also booming.

Job-openings rates across industries are much higher than before the pandemic hit, suggesting companies still need workers even in sectors where company layoffs have been pronounced, such as technology, real estate, finance and insurance.

Longer periods of unemployment can allow job seekers more time to search for roles that match their skill sets, some economists say. But with job opportunities so abundant, many unemployed workers are finding jobs that suit them within a matter of weeks or even days.

For the full story see:

Sarah Chaney Cambon. “Laid-Off Employees Quickly Find New Jobs.” The Wall Street Journal (Thursday, Aug. 25, 2022): A1 & A6.

(Note: ellipses and bracketed year added.)

(Note: the online version of the story has the date August 24, 2022, and has the title “The Surprise in a Faltering Economy: Laid-Off Workers Are Quickly Finding Jobs.”)

My book mentioned above is:

Diamond, Arthur M., Jr. Openness to Creative Destruction: Sustaining Innovative Dynamism. New York: Oxford University Press, 2019.

Wittgenstein Center’s Scenario Has Global Population Peak in 2050 at 8.7 Billion

(p. A2) Since the 1960s, when the global number of people first hit three billion, it has taken a bit over a decade to cross each new billion-person milestone, and so it might seem natural to assume that nine billion humans and then 10 billion are, inexorably, just around the corner. That is exactly what the latest population projections from the U.N. and the U.S. Census Bureau have calculated.

. . .

The U.N.’s projections are the best known. But an alternate set of projections has been gaining attention in recent years, spearheaded by the demographer Wolfgang Lutz, under the auspices of the Wittgenstein Centre for Demography and Global Human Capital at the University of Vienna, of which Mr. Lutz is founding director.

. . .

“There’s two big questions,” Mr. Lutz explains, that determine whether his forecasts or the U.N.’s end up closer to the mark. “First, how rapidly fertility will decline in Africa…. The other question is China, and countries with very low fertility, if they will recover and how fast they will recover.”

. . .

The Wittgenstein forecasts, by contrast, look not only at historical patterns, but attempt to ask why birthrates rise and fall. A big factor, not formally included in the U.N.’s models, is education levels. Put simply: As people, especially women, have greater opportunities to pursue education, they have smaller families.

. . .

The U.N. projects Africa’s population will grow from 1.3 billion today to 3.9 billion by century’s end.

Once education is accounted for, Wittgenstein’s baseline scenario projects Africa’s population will rise to 2.9 billion during that time period. In another scenario from Wittgenstein, which it calls the “rapid development” scenario, the population of Africa will only reach 1.7 billion by century’s end.

Wittgenstein’s phrase “rapid development” is revealing: This isn’t a forecast of doom and decline, but rather one in which health and education simply improve, a world with better human well-being, lower mortality, and medium levels of immigration.

. . .

Wittgenstein’s rapid-development scenario has the global population topping out at 8.7 billion in 2050.

For the full commentary see:

Josh Zumbrun. “THE NUMBERS; As Population Nears 8 Billion, Some See Peak.” The Wall Street Journal (Tuesday, Aug. 13, 2022): A2.

(Note: ellipses added.)

(Note: the online version of the commentary has the date August 12, 2022, and has the title “THE NUMBERS; Global Population Is About to Hit 8 Billion—and Some Argue It Is Near Its Peak.”)

“Overzealous Environmentalism” Hurts Poor Poaching “Misunderstood Outcasts”

(p. 17) In the journalist Lyndsie Bourgon’s telling, . . ., the poachers are not quite villains. Instead, they are responding — if not justifiably then at least predictably — to a lack of economic opportunities and the perception that the rules governing forests are arbitrary and heavy-handed.

Bourgon puts herself in the poacher’s shoes, and the result is a refreshing and compassionate warning about the perils of well-intentioned but overzealous environmentalism.

. . .

. . . she regards the history of the American conservation movement with something approaching scorn. It was hatched, she writes, to serve the whims of wealthy urban vacationers who wanted access to lands unspoiled by their longtime inhabitants. National parks were conceived as vehicles to resist “any attempt to turn to utilitarian purposes the resources represented by the forest,” as one booster put it.

At times, the motives were even less pure. Bourgon describes how ultrarich environmentalists in the early 1900s saw conservation — and in particular the protection of California’s redwoods — “as part of a mission to enshrine a white, masculine dominance over the wilderness.” Some conservationists, she notes, were “eugenicists who saw parallels between environmental destruction and the decline of Nordic supremacy.”

. . .

This is the backdrop for Bourgon’s depiction of “tree thieves” as misunderstood outcasts. “I have begun to see the act of timber poaching as not simply a dramatic environmental crime, but something deeper — an act to reclaim one’s place in a rapidly changing world,” she writes, tracing that desire back to 16th-century England, where poachers in royal forests were celebrated as folk heroes.

Bourgon immersed herself with a small handful of these men in the Northwest, and a picture emerges of a fractious band of down-on-their-luck crooks. A number abuse drugs. The poachers acknowledge that what they’re doing is illegal, but they frame it as principled, akin to stealing a loaf of bread to feed their families.

. . .

On the one hand, unemployed loggers and others who are suffering economically because of stringent enforcement of conservation laws are facing poverty. On the other hand, the damage that poachers are inflicting on forests appears to be, in the grand scheme of things, modest.

For the full review, see:

David Enrich. “No Clear-Cut Villains.” The New York Times Book Review (Sunday, July 24, 2022): 17.

(Note: ellipses added.)

(Note: the online version of the review has the date June [sic] 21, 2022, and has the title “When It Comes to Timber Theft, There Are No Clear-Cut Villains.” Where the online version has “misunderstood poacher’s” [sic], the print version quoted above has “misunderstood outcasts.”)

The book under review is:

Bourgon, Lyndsie. Tree Thieves: Crime and Survival in North America’s Woods. New York: Little, Brown Spark, 2022.

A.I. Cannot Learn What 4-Year-Old Learns From Trial-And-Error Experiments

(p. C3) A few weeks ago a Google engineer got a lot of attention for a dramatic claim: He said that the company’s LaMDA system, an example of what’s known in artificial intelligence as a large language model, had become a sentient, intelligent being.

Large language models like LaMDA or San Francisco-based Open AI’s rival GPT-3 are remarkably good at generating coherent, convincing writing and conversations—convincing enough to fool the engineer. But they use a relatively simple technique to do it: The models see the first part of a text that someone has written and then try to predict which words are likely to come next. If a powerful computer does this billions of times with billions of texts generated by millions of people, the system can eventually produce a grammatical and plausible continuation to a new prompt or a question.

. . .

In what’s known as the classic “Turing test,” Alan Turing in 1950 suggested that if you couldn’t tell the difference in a typed conversation between a person and a computer, the computer might qualify as intelligent. Large language models are getting close. But Turing also proposed a more stringent test: For true intelligence, a computer should not only be able to talk about the world like a human adult—it should be able to learn about the world like a human child.

In my lab we created a new online environment to implement this second Turing test—an equal playing field for children and AI systems. We showed 4-year-olds on-screen machines that would light up when you put some combinations of virtual blocks on them but not others; different machines worked in different ways. The children had to figure out how the machines worked and say what to do to make them light up. The 4-year-olds experimented, and after a few trials they got the right answer. Then we gave state-of-the-art AI systems, including GPT-3 and other large language models, the same problem. The language models got a script that described each event the children saw and then we asked them to answer the same questions we asked the kids.

We thought the AI systems might be able to extract the right answer to this simple problem from all those billions of earlier words. But nobody in those giant text databases had seen our virtual colored-block machines before. In fact, GPT-3 bombed. Some other recent experiments had similar results. GPT-3, for all its articulate speech, can’t seem to solve cause-and-effect problems.

If you want to solve a new problem, googling it or going to the library may be a first step. But ultimately you have to experiment, the way the children did. GPT-3 can tell you what the most likely outcome of a story will be. But innovation, even for 4-year-olds, depends on the surprising and unexpected—on discovering unlikely outcomes, not predictable ones.

For the full commentary see:

Alison Gopnik. “What AI Still Doesn’t Know How To Do.” The Wall Street Journal (Saturday, July 16, 2022): C3.

(Note: ellipsis added.)

(Note: the online version of the commentary has the date July 15, 2022, and has the same title as the print version.)

A.I. Remains Useful Mainly for “Uncinematic Back-Office Logistics”

(p. B4) After years of companies emphasizing the potential of artificial intelligence, researchers say it is now time to reset expectations.

With recent leaps in the technology, companies have developed more systems that can produce seemingly humanlike conversation, poetry and images. Yet AI ethicists and researchers warn that some businesses are exaggerating the capabilities—hype that they say is brewing widespread misunderstanding and distorting policy makers’ views of the power and fallibility of such technology.

“We’re out of balance,” says Oren Etzioni, chief executive of the Allen Institute for Artificial Intelligence, a Seattle-based research nonprofit.

. . .

The belief that AI is becoming—or could ever become—conscious remains on the fringes in the broader scientific community, researchers say.

In reality, artificial intelligence encompasses a range of techniques that largely remain useful for a range of uncinematic back-office logistics like processing data from users to better target them with ads, content and product recommendations.

. . .

The gap between perception and reality isn’t new. Mr. Etzioni and others pointed to the marketing around Watson, the AI system from International Business Machines Corp. that became widely known after besting humans on the quiz show “Jeopardy.” After a decade and billions of dollars in investment, the company said last year it was exploring the sale of Watson Health, a unit whose marquee product was supposed to help doctors diagnose and cure cancer.

. . .

Elizabeth Kumar, a computer-science doctoral student at Brown University who studies AI policy, says the perception gap has crept into policy documents. Recent local, federal and international regulations and regulatory proposals have sought to address the potential of AI systems to discriminate, manipulate or otherwise cause harm in ways that assume a system is highly competent. They have largely left out the possibility of harm from such AI systems’ simply not working, which is more likely, she says.

For the full story see:

Karen Hao and Miles Kruppa. “AI Hype Doesn’t Match Reality.” The Wall Street Journal (Thursday, June 30, 2022): B4.

(Note: ellipses added.)

(Note: the online version of the story was updated July 5, 2022, and has the title “Tech Giants Pour Billions Into AI, but Hype Doesn’t Always Match Reality.”)

Brynjolfsson Made “Long Bet” with Gordon that A.I. Will Increase Productivity

(p. B1) For years, it has been an article of faith in corporate America that cloud computing and artificial intelligence will fuel a surge in wealth-generating productivity. That belief has inspired a flood of venture funding and company spending. And the payoff, proponents insist, will not be confined to a small group of tech giants but will spread across the economy.

It hasn’t happened yet.

Productivity, which is defined as the value of goods and services produced per hour of work, fell sharply in the first quarter this year, the government reported this month. The quarterly numbers are often volatile, but the report seemed to dash earlier hopes that a productivity revival was finally underway, helped by accelerated investment in digital technologies during the pandemic.

The growth in productivity since the pandemic hit now stands at about 1 percent annually, in line with the meager rate since 2010 — and far below the last stretch of robust improvement, from 1996 to 2004, when productivity grew more than 3 percent a year.

. . .

(p. B6) The current productivity puzzle is the subject of spirited debate among economists. Robert J. Gordon, an economist at Northwestern University, is the leading skeptic. Today’s artificial intelligence, he says, is mainly a technology of pattern recognition, poring through vast troves of words, images and numbers. Its feats, according to Mr. Gordon, are “impressive but not transformational” in the way that electricity and the internal combustion engine were.

Erik Brynjolfsson, director of Stanford University’s Digital Economy Lab, is the leader of the optimists’ camp. He confesses to being somewhat disappointed that the productivity pickup is not yet evident, but is convinced it is only a matter of time.

“Real change is happening — a tidal wave of transformation is underway,” Mr. Brynjolfsson said. “We’re seeing more and more facts on the ground.”

It will probably be years before there is a definitive answer to the productivity debate. Mr. Brynjolfsson and Mr. Gordon made a “long bet” last year, with the winner determined at the end of 2029.

For the full story see:

Steve Lohr. “Why Isn’t A.I. Increasing Productivity?” The New York Times (Wednesday, May 25, 2022): B1 & B6.

(Note: ellipsis added.)

(Note: the online version of the story was updated May 27, 2022, and has the title “Why Isn’t New Technology Making Us More Productive?”)