Q&A: Teaching the business of Taylor Swift at Berkeley Haas

young woman with long curly dark hair
Miaad Madeline Bushala, BS 25, co-teaches a DeCal on Taylor Swift.

Miaad Madeline Bushala, BS 25, likes Taylor Swift’s music but doesn’t consider herself a die-hard “Swiftie.” What’s more intriguing to Bushala is Taylor Swift’s evolution as a business leader who continues to top the music industry.

Bushala is now tapping into how the 14-time Grammy winner built her fortune, co-teaching a DeCal at Berkeley Haas called “Artistry & Entrepreneurship: Taylor’s Version” with Sofia Mei Lendahl, a sophomore Data Science and Statistics double major. The pair were in their fourth week of teaching the 13-week class for the first time when Bushala talked to Haas News.

You came to this class with both a musical and a business background.

Indeed, I did. I was a vocalist in the Popular Music Conservatory at the Orange County School of the Arts (OCSA) alongside my brother who is a fantastic drummer and my biggest musical inspiration. I attended Grammy Camp twice for vocal performance, a camp where high school students across the nation learn from and collaborate with music professionals.

My business background comes from watching and helping my parents with their real estate business, and then of course all that I’ve learned since being a student at Haas.

What interested you most about Taylor from a business perspective?

I heard somebody say that “nothing about Taylor Swift is an accident,” and I truly do believe that. Particularly as a business student, Taylor’s story has been so fascinating to me. At the end of the day, her songs, albums, merchandise, tours, etc. are all products, and for a product to have a life of almost 20 years not only says something about Taylor’s brilliance as an artist, but as a  businesswoman. With that, I am interested in unraveling all those pieces about her and seeing what made her the success that she’s become.

I heard somebody say that “nothing about Taylor Swift is an accident,” and I truly do believe that.

How did you meet Crystal Haryanto, BA 23 (Economics, Cognitive Science, & Public Policy), who founded this class?

Crystal and I met through Lizzie Coyle, director of Major Gifts at Haas. Lizzie shared the excitement of the Taylor Swift course in the business school and I was encouraged to consider joining the team as the team was also seeking a business perspective. I was supposed to study abroad this semester in Spain, but this was my sign to stay and do something that I’d never done before.

As a business student, how did you help shape the class syllabus? 

I asked the hard questions—for every concept in our syllabus, I ensured that there was a viable link to business. We wanted students to view Taylor as an entrepreneur who differentiates herself within a market, manages customer acquisition and sustains customer loyalty, and impacts multiple economies. We wanted them to think about how, as future entrepreneurs and business leaders, to make their customers their biggest fans, like Taylor has done.

Taylor Swift
Taylor Swift attending the MTV Europe Music Awards 2022 in Dusseldorf. (Press Association via AP Images)

Can you give a few examples of how that plays out weekly in the class?

One of my ideas for our marketing unit was a deep dive into Taylor’s style evolution over her self-proclaimed eras, and how that has reinforced her principles of relatability and world building. While style was a more subtle signal that built up over time, I’ve also enjoyed speaking about her direct power moves. Last night, for instance, we discussed how Taylor negotiated her contract with AMC Theatres and took hold of the reins for the Eras Tour film project. She financed the film and received 57% of the movie profits. To me, that was her learning from the mistake she made when she was younger, when she signed over the masters to her music.

In business school, students study the importance of connection in building an authentic brand. How has Taylor become a master at that?

Taylor’s songwriting stands out on two primary levels. The first is that she puts her insecurities and struggles out there, emotionally stripping herself through art. The second is that she vividly weaves those vulnerabilities into stories. Unique structures, sonic devices, and figurative language add layered complexities to these stories that ensure that they are highly talked about among consumers as a hot commodity. These elements of songwriting craft also tailor each product to match the message it is sending, which strengthens its value to consumers. She’s able to create a dynamic, so people continue to feel like they can relate to her. She really knows her audience, and her songs cover every part of her ideal listener’s life.

What does Taylor teach us about how to lead?

Taylor’s grandmother, Marjorie, said it best: “Never be so kind, you forget to be clever / Never be so clever, you forget to be kind.”

Taylor shows us how to balance a good heart with strategic design. We bring it up in class—the bonuses that she gives her team and the ways that she gives back to the community. Philanthropy happens to also be a tax write off for her, but that isn’t a bad thing. I think people know when a brand is doing something that feels inauthentic, and that isn’t the case with Taylor.

I think people know when a brand is doing something that feels inauthentic, and that isn’t the case with Taylor.

Taylor has so much power. How do you see her using it to uplift women’s voices, big and small?

Taylor has spoken extensively on how navigating the industry as a woman is different than as a man, which she writes about in “The Man” and “mad woman.”

She wears clothes from small, women-owned businesses, which have seen huge jumps in customers and traction.

But arguably one of the biggest ways that Taylor has amplified women’s voices is when she was a victim of sexual assault and ended up suing her assaulter for a symbolic one dollar. For many women, especially young fans, hearing a beloved figure speak so openly about that emotional damage not only acknowledges their pain, but also models speaking out against intolerable behavior that has become normalized in our society.

I have to ask about her dating Travis Kelce and what that has done for her brand.

The question should be what dating Taylor Swift has done for Travis Kelce’s brand. We’ll discuss her influence in the NFL in class and perhaps the perceptions that come with being in a high-profile relationship.

How much longer do you think that Taylor will continue reinventing herself as an artist? Do you think she will be like Madonna, touring in her 60s?

A lot of artists, once they feel like they’ve reached a certain point, go off the grid. I don’t quite know, but I know this: Taylor will always be a songwriter. She’s even said that she would consider writing songs for other people at some point. She cites songwriting as her lifeline, passion, and purpose—singing and performing are extensions of that.

Online images may be turning back the clock on gender bias, research finds

A paper published today in the journal Nature finds that online images show stronger gender biases than online texts. Researchers also found that bias is more psychologically potent in visual form than in writing.

An illustration of a hand holding a phone with a beam of light shining one a woman's face. A larger verison of her face is ampified in the background.
Image copyright Solène Delecourt

A picture is worth a thousand words, as the saying goes, and research has shown that the human brain does indeed better retain information from images than from text.

These days, we are taking in more visual content than ever as we peruse picture-packed news sites and social media platforms. And much of that visual content, according to new Berkeley Haas research, is reinforcing powerful gender stereotypes.

Through a series of experiments, observations, and the help of large language models, professors Douglas Guilbeault and Solène Delecourt found that female and male gender associations are more extreme among images retrieved on Google than within text from Google News. What’s more, while the text is slightly more focused on men than women, this bias is over four times stronger in images.

“Most of the previous research about bias on the internet has been focused on text, but we now have Google Images, TikTok, YouTube, Instagram—all kinds of content based on modalities besides text,” says Delecourt. “Our research suggests that the extent of bias online is much more widespread than previously shown.”

Not only is online gender bias more prevalent in images than in text, the study revealed, but such bias is more psychologically potent in visual form. Strikingly, in one experiment, study participants who looked at gender-biased images—as opposed to those reading gender-biased text—demonstrated significantly stronger biases even three days later.

As online worlds grow more and more visual, it’s important to understand the outsized potency of images, says Guilbeault, the lead author on the paper.

“We realized that this has implications for stereotypes—and no one had demonstrated that connection before,” Guilbeault says. “Images are a particularly sticky way for stereotypes to be communicated.”

The extent of bias–and its effects

To zero in on gender bias in online images, Guilbeault and Delecourt teamed up with co-authors Tasker Hull from Psiphon, Inc., a software company that develops censorship-navigation tools; doctoral researcher Bhargav Srinivasa Desikan of Switzerland’s École Polytechnique Fédérale de Lausanne (now at IPPR in London); Mark Chu from Columbia University; and Ethan Nadler from the University of Southern California. They designed a novel series of techniques to compare bias in images versus text, and to investigate its psychological impact in both mediums.

First, the researchers pulled 3,495 social categories—which included occupations like “doctor” and “carpenter” as well as social roles like “friend” and “neighbor”—from Wordnet, a large database of related words and concepts.

To calculate the gender balance within each category of images, the researchers retrieved the top hundred Google images corresponding to each category and recruited people to classify each human face by gender.

Measuring gender bias in online texts was a trickier proposition—though one perfectly suited for fast-evolving large-language models, which noted the frequency of each social category’s occurrence alongside references to gender in Google News text.

The researchers’ analysis revealed that gender associations were more extreme among the images than within the text. There were also far more images focused on men than women.

Sticky images

The experimental phase of the study sought to illuminate the impacts that biases in online images have on internet users. The researchers asked 450 participants to use Google to search for apt descriptions of occupations relating to science, technology, and the arts. One group used Google News to find and upload textual descriptions; another group used Google Images to find and upload pictures of occupations. (A control group was assigned the same task with neutral categories like “apple” and “guitar.”)

After selecting their text- or image-based descriptions, the participants rated which gender they most associated with each occupation. Then they completed a test that asked them to quickly sort various words into gender categories. The test was administered again after three days.

The participants who worked with the images displayed much stronger gender associations compared to those in the text and control conditions—even three days later.

“This isn’t only about the frequency of gender bias online,” says Guilbeault. “Part of the story here is that there’s something very sticky, very potent about images’ representation of people that text just doesn’t have.”

Interestingly, when the researchers conducted their own online survey of public opinion—and when they looked at data on occupational gender distributions reported by the U.S. Bureau of Labor Statistics—they found that gender disparities were much less pronounced than in those reflected in Google images.

Opening doors to new research

Delecourt and Guilbeault say they hope their findings lead to a more serious grappling with the challenges posed by embedded bias in online images. After all, it’s relatively easy to tweak text to be as neutral as possible, whereas images of people inherently convey racial, gender, and other demographic information.

Guilbeault notes that other research has shown that gender biases in online text have decreased, but those findings may not reveal the whole story. “In images we actually still see very prevalent widespread gender bias,” he says. “That may be because we haven’t really focused on images in terms of this movement towards gender equality. But it could also be because it’s just harder to do that in images.”

Guilbeault and Delecourt are already at work on another project in this vein to examine gender-age bias online using many of the same techniques. “Part of the reason this paper is so exciting is that it opens the door to many, many other types of research—into age or race, or into other modalities, like video,” Delecourt says.

Watch a video explaining the research:

 

Read the paper:

“Online Images Amplify Gender Bias
Nature, February 14, 2024

Authors:

  • Douglas Guilbeault: Haas School of Business, University of California, Berkeley (corresponding author)
  • Solène Delecourt: Haas School of Business, University of California, Berkeley
  • Tasker Hull: Psiphon Inc.
  • Bhargav Srinivasa Desikan: Ecole Polytechnique Federale de Lausanne
  • Mark Chu: Columbia University
  • Ethan Nadler: University of Southern California

Contacts:

Douglas Guilbeault, corresponding author, [email protected]

Laura Counts, Berkeley Haas media relations: [email protected]

Nonstop Futility

Searching for a cheaper flight? There’s no secret trick.

Image of a plane crossing the sky with multicolored trails of other planes.Buy on a Tuesday. Search in your browser’s incognito mode. Use a VPN to pretend you live in Suriname.

“There are so many hacks out there for finding cheaper airline tickets,” says Assistant Professor Olivia Natan. “But our data shows many of these beliefs are wrong.”

Natan and colleagues from the University of Chicago, Yale, and the University of Texas at Austin looked deeply into how prices are set at a major U.S. airline. The system she found, which is representative of airlines worldwide, was strikingly at odds with what many economists would expect—and most consumers assume.

Substituting convenience for price

When people search websites like Google Flights or Kayak, a range of different flights from the same airline appear. Travelers tend to balance convenience and cost: The price of one flight might push people to select a slightly less convenient but cheaper flight.

“But airlines don’t consider this kind of substitution,” Natan says. They set the prices of seats on each individual flight on a given route separately, “even though changing the price on one flight will affect the way people think about all their options.”

A small menu of preset prices

Perhaps most surprisingly, airlines also don’t incorporate the prices of their competitors into their automated price-setting. This behavior, Natan explains, is the result of a specific pricing heuristic—or decision-making shortcut—that airlines use called Expected Marginal Seat Revenue-b. The use of this, the researchers show, results in another outcome that consumers may not expect.

Despite how it may appear when searching flights, airlines have a fixed and relatively small number of prices that they assign to tickets on each flight. Unlike other consumer sectors, where pricing can be adjusted down to the penny, airlines operate with large gaps between each possible price—sometimes upwards of $100. They may sell the first 30 economy tickets at the lowest price, then the next 30 tickets at the next possible price, and so on.

“Airline tickets are sold through global distribution systems that make sure a travel agent in Wichita or Miami sees the same price you do on your computer,” Natan says. This system emerged from an industry alliance to facilitate inventory management. Other travel products, like hotel rooms, cruises, and car rentals, do the same. The downside is that airlines are relatively unresponsive to real-time changes in cost, as the next discrete fare is often a significant jump up.

Despite how it may appear when searching flights, airlines have a fixed and relatively small number of prices that they assign to tickets on each flight.

Lack of coordination across departments

One of the strangest discoveries from the research relates to the process airlines use to set their prices. To an economist, Natan explains, there is never a reason that firms would not raise prices if the increase assures an increase in revenue. But the set of possible prices chosen by the pricing team nearly always includes an option that is too low.

“We found they could make more money today by selling fewer tickets at higher prices and not foreclose future opportunities,” she says. “In practice, they choose the menu of prices without using their internal demand predictions.”

Interestingly, the revenue management team corrects much of this underpricing. Before tickets go on sale, this team makes demand forecasts that determine final prices. These forecasts are routinely inflated, reducing the number of underpriced tickets shown to consumers by roughly 60%.

“We find that these prices are a consequence of teams from different departments choosing the best pricing inputs when they are unable to coordinate,” Natan says. Or, airlines might not maximize short-term revenue to build customer loyalty or avoid regulatory scrutiny, she speculates.

Over the next several years, Natan says, airlines may start to adopt more dynamic pricing platforms, and non-business travelers may benefit from these changes. But for now, the hunt for a trick to find lower fares is largely futile. “What I can say is that prices do go up significantly 21, 14, and 7 days before a flight,” Natan says. “Just buy your ticket before then.”

Amid a replication crisis in social science research, six-year study validates open science methods

After a series of high-profile research findings failed to hold up to scrutiny, a replication crisis rocked the social-behavioral sciences and triggered a movement to make research methods more rigorous. A six-year effort to test these emerging methods, led by labs at UC Santa Barbara, UC Berkeley, Stanford, and the University of Virginia, has shown they can produce new and highly replicable findings. The paper, published in the journal Nature Human Behavior and co-authored by Berkeley Haas Professor Leif Nelson, is the strongest evidence to date that the methodological reform movement known as open science can lead to more reliable research results.

Illustration showing colorful silhouettes of people
Image: Robert Kneschke for Adobe Stock

Roughly two decades ago, a community-wide reckoning emerged concerning the credibility of published literature in the social-behavioral sciences, especially psychology. Several large-scale studies attempted to reproduce previously published findings to no avail or to a much lesser magnitude, sending the credibility of the findings—and future studies in social-behavioral sciences—into question.  

To confront this crisis, a handful of top experts in the field set out to test whether emerging research practices can produce more reliable results. Over six years, researchers at labs from UC Santa Barbara, UC Berkeley, Stanford University, and the University of Virginia discovered and replicated 16 novel findings with ostensibly gold-standard best practices, including pre-registration, large sample sizes, and replication fidelity. 

Their findings, published in the journal Nature Human Behaviour, suggest that with high rigor, high replicability is achievable. 

“The major finding is that when you follow current best practices in conducting and replicating online social-behavioral studies, you can accomplish high and generally stable replication rates,”said UC Santa Barbara Distinguished Professor Jonathan Schooler, director of UCSB’s META Lab and the Center for Mindfulness and Human Potential, and senior author of the paper.  

Their study’s replication findings were 97% the size of the original findings on average. By comparison, prior replication projects observed replication findings that were roughly 50%.

The paper’s principal investigators were John Protzko of UCSB’s META Lab and Central Connecticut State University, Jon Krosnick of Stanford’s Political Psychology Research Group, Leif Nelson at the Haas School of Business, UC Berkeley, and Brian Nosek, who is affiliated with the University of Virginia and is the Executive Director of the  Center for Open Science.

“There have been a lot of concerns over the past few years about the replicability of many sciences, but psychology was among the first fields to start systematically investigating the issue,” said lead author Protzko, who is a research associate to Schooler’s lab, where he was a postdoctoral scholar during the study. He is now an assistant professor of psychological science at Central Connecticut State University. 

The question, Protzko said, was whether past replication failures and declining effect sizes are inherently built into the scientific domains that have observed them. “For example, some have speculated that it is an inherent aspect of the scientific enterprise that newly discovered findings can become less replicable or smaller over time,” he said. 

The researchers decided to perform new studies using emerging best practices in open science—and then to replicate them with an innovative design in which they committed to replicating the initial studies regardless of outcome.

“It is important to test the replicability of all outcomes,” said Nelson, the Ewald T. Grether Professor in Business Administration & Marketing at the Haas School of Business, UC Berkeley. Scientists and scientific journals will always prioritize emphasizing newly confirmed hypotheses, but consumers of science care just as much about the hypotheses that were not confirmed. We should care about the replicability of both outcomes.”

Replicating 16 new discoveries

Over the course of six years, research teams at each lab developed studies which were then replicated  by all of the other labs. In total, the coalition discovered 16 new phenomena and replicated each of them four times involving 120,000 participants.

Across the board, the project revealed extremely high replicability rates of their social-behavioral findings, and no statistically significant evidence of decline over repeated replications. Given the sample sizes and effect sizes, the observed replicability rate of 86%, based on statistical significance, could not have been any higher, the researchers pointed out.  

They also ran several follow-up surveys to test the novelty of their discoveries. “It would not be particularly interesting to discover that it is easy to replicate completely obvious findings,” Schooler said. “But our studies were comparable in their surprise factor to studies that have been difficult to replicate in the past. Untrained judges who were given summaries of the two conditions in each of our studies and a comparable set of two-condition studies from a prior replication effort found it similarly difficult to predict the direction of our findings relative to the earlier ones.” 

Indeed, many of the newly discovered findings have already been independently published in high-quality journals.

Because each research lab developed its own studies, they came from a variety of social, behavioral, and psychological fields such as marketing, political psychology, prejudice, and decision making. They all involved human subjects and adhered to certain constraints, such as not using deception. “We really built into the process that the individual labs would act independently,” Protzko said. “They would go about their sort of normal topics they were interested in and how they would run their studies.”  

Collectively, their meta-scientific investigation provides evidence that low replicability and declining effects are not inevitable, and that rigor-enhancing practices can lead to very high replication rates. Even so, identifying which practices work best will take further study. This study’s “kitchen sink” approach—using multiple rigor-enhancing practices at once—didn’t isolate any individual practice’s effect. 

The additional investigators on the study are Jordan Axt (Department of Psychology, McGill University, Montreal, Canada); Matt Berent (Matt Berent Consulting); Nicholas Buttrick (Department of Psychology, University of Wisconsin-Madison), Matthew DeBell (Institute for Research in Social Sciences, Stanford University), Charles R. Ebersole (Department of Psychology, University of Virginia), Sebastian Lundmark (The SOM Institute, University of Gothenburg, Sweden); Bo MacInnis (Department of Communication, Stanford University), Michael O’Donnell, (McDonough School of Business, Georgetown University); Hannah Perfecto (Olin School of Business, Washington University in St. Louis); James E. Pustejovsky (Educational Psychology Department, University of Wisconsin-Madison); Scott S. Roeder (Darla Moore School of Business, University of South Carolina); and Jan Walleczek (Phenoscience Laboratories, Berlin, Germany).

Research shows how airline pricing really works

A new paper co-authored by Olivia Natan of Berkeley Haas and published in The Quarterly Journal of Economics peers into the black box of airline pricing and finds some surprises.

A woman searches for a plane ticket on a laptop and phone at at the same time.
Photo: Fabio Principe/iStock

Buy your ticket on a Tuesday. Search in your browser’s incognito mode. Use a VPN to pretend you live in Suriname.

“There are so many hacks out there for finding cheaper airline tickets,” says Olivia Natan, an assistant professor of marketing at the Haas School of Business. “But our data shows many of these beliefs are wrong.”

With four colleagues—Ali Hortaçsu and Timothy Schwieg from the University of Chicago, Kevin Williams from Yale, and Hayden Parsley from the University of Texas at Austin—Natan looked deeply into the structure and processes behind how prices are set at a major U.S. airline. The system that she found, which is representative of airlines around the world, was strikingly at odds with what many economists would expect—and most consumers assume.

“We initially didn’t know how to rationalize the things we were seeing,” she says.

Substituting convenience for price

Consider fruit jam at the grocery store. Consumers have many options. If a company raises the price on its strawberry jam, one might fairly assume that this would affect sales of both strawberry and neighboring raspberry jam, since consumers can substitute one for another.

The same can happen with plane tickets: When people visit a website such as Google Flights or Kayak and search for a ticket, a wide range of different flights from the same airline appear. Travelers tend to make selections that balance convenience and price: The price of one flight might push people to select a slightly less convenient but cheaper flight.

“But the systems airlines use don’t consider this kind of substitution,” Natan says.  They set the prices of seats on each individual flight on a given route separately, “even though changing the price on one flight will affect the way people think about all their options.”

A small menu of pre-set prices

Perhaps most surprisingly, airlines also don’t directly incorporate the prices of their competitors in their automated price-setting. Typically, if one airline cut its prices, one would expect other firms to do the same. If they don’t, this dampens the benefits of a competitive market.

Setting prices of each product separately without considering substitution, Natan explains, is the result of a specific pricing heuristic—or decision-making shortcut—that airlines use called Expected Marginal Seat Revenue-b, or EMSRb. This shortcut is widely used because it is fast enough to set prices for hundreds of thousands of flights daily, and it allows airlines to reserve some seats to sell at higher prices.

The use of EMSRb, the researchers show, results in another outcome that consumers may not expect. Despite how it may appear when looking for flights, airlines have a fixed and relatively small number of prices that they assign to tickets on each flight. Unlike other consumer sectors, where pricing can be adjusted and targeted down to the penny, airlines operate with large gaps between each possible price—sometimes upwards of $100. They may sell the first 30 economy tickets at the lowest price, and then the next 30 tickets at the next possible price, and so on.

“Airline tickets are sold through global distribution systems that make sure a travel agent in Wichita or Miami sees the same price as you do on your computer at home,” Natan says. This system emerged from an industry alliance to facilitate inventory management across many channels. Other businesses in the travel sector, such as hotel rooms, cruises, trains, and car rentals do the same.

The downside is that airline ticket prices are relatively unresponsive to real-time changes in opportunity costs, as the next discrete fare is often a significant jump up. The researchers found that even if the airline would like to increase the price by $100—half the price of an average one-way ticket—they only do so about 20% of the time, since no fare is available at that price.

Today, airlines are starting to experiment with what’s known as “continuous revenue management,” which would, for instance, assign 100 different prices to a flight with 100 seats. “That would make pricing significantly more variable,” Natan says, “but even that would not be the kind of targeting that many consumers assume airlines use.”

Lack of coordination across departments

One of the strangest discoveries from the research relates to the process airlines use to set their prices. To an economist, Natan explained, there is never a reason that firms would not raise prices if the increase assures an increase in revenue. But the set of possible prices chosen by the pricing team nearly always includes an option which is too low, even by their internal estimates.

The pricing team’s work is made difficult by having to choose an entire menu of discrete prices, “but we found they could make more money today by selling fewer tickets at higher prices and not foreclose future opportunities. In practice, they choose the menu of prices without using their internal demand predictions,” Natan says.

Interestingly, the revenue management team corrects much of this underpricing before it ever reaches consumers. After prices are filed and before tickets go on sale, this team makes demand forecasts that determine final prices. These forecasts are routinely inflated, reducing the number of underpriced tickets shown to consumers by roughly 60%.

“We find that these prices are a consequence of teams from different departments choosing the best pricing inputs when they are unable to  coordinate,” Natan says “This may result in lower revenue, but in practice our solution, which sells fewer tickets at higher prices, could not be implemented. ” Two other possibilities as to why airlines don’t only focus on short-term revenue, she speculated, are either to build customer loyalty or to avoid regulatory scrutiny.

Over the next several years, Natan says, airlines may start to adopt more dynamic pricing platforms, and non-business travelers may benefit from these changes. But for now, the hunt for an undiscovered trick to find lower fares is largely futile. What is clear is that it’s wise not to wait until the last minute. “What I can say is that prices do go up significantly 21, 14, and seven days before a flight,” Natan says. “Just buy your ticket before then.”

Note: This article has been updated from the original version published October 4, 2023.

Read the full paper:

Organizational Structure and Pricing: Evidence from a Large U.S. Airline
By Ali Hortaçsu, Olivia Natan, Hayden Parsley, Timothy Schwieg, and Kevin Williams
The Quarterly Journal of Economics, Sept. 27, 2023