Preventing discrimination and injustice in the workplace can save employers money, time, and damage to their reputation from potential lawsuits, said powerhouse feminist attorney Gloria Allred to a full house of Berkeley Haas students, faculty, and staff last Wednesday.
“Look for opportunities to make a difference for fairness and for change. I’m not saying there’s only one style or way to achieve it—you have to make a judgment call about the best way for you,” Allred said, after a student asked how to make change from within the corporate world. “Telling the truth matters. Saying nothing will do nothing but maintain the status quo:”
Allred, who has spent four decades fighting—and often winning—high-profile battles against discrimination, spoke in conversation with Kellie McElhaney, director of the Center for Equity, Gender, and Leadership. The event, which followed a Tuesday screening of the new documentary Seeing Allred, was part of the center’s AmpEquity Series.
Allred said those who decide to take action should think it through beforehand and, potentially, consult with a lawyer if they are in a vulnerable position. But, “it’s really in the interest of the corporation to get to the truth,” Allred said.
Allred mixed blunt warnings with advice and inspiration, at times showing her anger and frustration. She called the Kavanaugh hearings an “exercise in raw power” that lacked due process for everyone involved, and she warned students to be prepared for whatever comes their way in the workplace.
“This is not a downer—this is just a dose of reality for you,” Allred said. “Sexual harassment is going to be one of the biggest barriers you will face in coming up that corporate ladder and staying there. Or sex discrimination, race discrimination, discrimination based on sexual orientation. It’s out there. Think in advance how you’re going to deal with it because you will deal with it in some way.”
Allred urged students to live their values, noting—as Gloria Steinem said—that you can tell your values by your checkbook stubs.
“Think about your time as an investment. People are often more protective of their money than their time. You can earn more money, but you can’t earn more time,” she said.
“Decide what your priorities are. Everybody can make a difference in some way, usually more than one way,” she said. “Follow your heart. Everyone can make a difference.”
Watch Allred’s full talk:
When a Starbucks employee recently called the police on two black men who asked for a bathroom key but hadn’t yet ordered anything, it seemed a clear-cut case of racism leading directly to unfair treatment. Many outraged white customers publicly contrasted it with their years of hassle-free Starbucks pit stops.
But from a scientific perspective, making a direct connection between people’s biases and the degree to which they treat others differently is tricky. There are thousands of ways people stereotype different social groups—whether it’s assuming an Asian student is good at math or thinking an Irish colleague would make a good drinking buddy—and with so many variables, it’s incredibly challenging to trace how someone is treated to any one particular characteristic.
“There is a tendency for people to think of stereotypes, biases, and their effects as inherently subjective. Depending on where one is standing, the responses can range from ‘this is obvious’ to ‘don’t be a snowflake,’” said Berkeley Haas Assoc. Prof. Ming Hsu. “What we found is that these subjective beliefs can be quantified and studied in ways that we take for granted in other scientific disciplines.”
How do stereotypes influence behavior?
A new paper published today in the Proceedings of the National Academy of Sciences cuts to the heart of messy social interactions with a computational model to quantify and predict unequal treatment based on perceptions of warmth and competence. Hsu and post-doctoral researcher Adrianna C. Jenkins—now an assistant professor at the University of Pennsylvania—drew on social psychology and behavioral economics in a series of lab experiments and analyses of field work. (The paper was co-written by Berkeley researcher Pierre Karashchuk and Lusha Zhu of Peking University.)
“There’s been lots of work showing that people have stereotypes and that they treat members of different social groups differently,” said Jenkins, the paper’s lead author. “But there’s quite a bit we still don’t know about how stereotypes influence people’s behavior.”
It’s more than an academic issue: University admission officers, for example, have long struggled with how to fairly consider an applicant’s race, ethnicity, or other qualities that may have presented obstacles to success. How much weight should be given, for example, to the obstacles faced by African Americans compared with those faced by Central American immigrants or women?
While these are much larger questions, Hsu said the paper’s contribution is to improve how to quantify and compare different types of discrimination across different social groups—a common challenge facing applied researchers.
“What was so eye-opening is that we found that variations in how people are perceived translated quantitatively into differences in how they are treated,” said Hsu, who holds a dual appointment with UC Berkeley’s Helen Wills Neuroscience Institute and the Neuroeconomics Lab. “This was as true in laboratory studies where subjects decided how to divide a few dollars as it was in the real-world where employers decided whom to interview for a job.”
The model offers a way to establish a direct connection between widely held stereotypes and entrenched societal inequities. Kellie McElhaney, founding executive director of the Center for Equity, Gender and Leadership (EGAL), said this is the kind of fundamental research that informs the mission of the center, which aims to “develop equity fluent leaders who ignite and accelerate change.”
“This research continues to advance critical knowledge and solutions around the significant and negative impact of biases, and in particular, the consequences in the business world,” she said.
Rather than analyzing whether the stereotypes were justified, the researchers took stereotypes as a starting point and looked at how they translated into behavior with over 1,200 participants across five studies. In the first study involving the classic “Dictator Game,” where a player is given $10 and asked to decide how much of it to give to a counterpart, the researchers found that people gave widely disparate amounts based on just one piece of information about the recipient (i.e., occupation, ethnicity, nationality). For example, people on average gave $5.10 to recipients described as “homeless,” while those described as “lawyer” got a measly $1.70—even less than an “addict,” who got $1.90
To look at how stereotypes about the groups drove people’s choices to pay out differing amounts, the researchers drew on an established social psychology framework that categorizes all stereotypes along two dimensions: those that relate to a person’s warmth (or how nice they are seen to be), and those that relate to a person’s competence (or how intelligent they are seen to be). These ratings, they found, could be used to accurately predict how much money people distributed to different groups. For example, “Irish” people were perceived as warmer but slightly less competent than “British,” and received slightly more money on average.
“We found that people don’t just see certain groups as warmer or nicer, but if you’re warmer by X unit, you get Y dollars more,” Hsu said.
Specifically, the researchers found that disparate treatment results not just from how people perceive others, but how they see others relative to themselves. In allocating money to a partner viewed as very warm, people were reluctant to offer them less than half of the pot. Yet with a partner viewed as more competent, they were less willing to end up with a smaller share of the money than the other person. For example, people were ok with having less than an “elderly” counterpart, but not less than a “lawyer.”
Predicting job callbacks
It’s one thing to predict how people behave in carefully controlled laboratory experiments, but what about in the messy real world? To test whether their findings could be generalized to the field, Hsu and colleagues tested whether their model could predict treatment disparities in the context of two high-profile studies of discrimination. The first was a Canadian labor market study that found a huge variation in job callbacks based on the perceived race, gender, and ethnicity of the names on resumes. Hsu and colleagues found that the perceived warmth and competence of the applicants—the stereotype based solely on their names—could predict the likelihood that an applicant had gotten callbacks.
They tried it again with data from a U.S. study on how professors responded to mentorship requests from students with different ethnic names and found the same results.
“The way the human mind structures social information has specific, systemic, and powerful effects on how people value what happens to others,” the researchers wrote. “Social stereotypes are so powerful that it’s possible to predict treatment disparities based on just these two dimensions (warmth and competence).”
Hsu says the model’s predictive power could be useful in a wide range of applications, such as identifying patterns of discrimination across large populations or building an algorithm that can detect and rate racism or sexism across the internet—something these authors are deep at work on now.
“Our hope is that this scientific approach can provide a more rational, factual basis for discussions and policies on some of the most emotionally-fraught topics in today’s society,” Hsu said.
In Afghanistan, where fake or “ghost” workers siphon off government paychecks and some rural teachers get paid through bursars who carry bags of cash to remote areas, can mobile money reduce corruption in public payrolls?
In Sierra Leone, where just 10 percent of households own a TV and opposition parties are weak, can screenings of videotaped candidate debates at large public gatherings help increase voter knowledge and improve candidates’ accountability?
Of these and the myriad efforts to reform public institutions in the developing world, which ones are proving to be most effective?
That was the central question occupying the researchers, funders, and “public sector entrepreneurs” from across the globe who gathered at the Haas School this week to share knowledge and strategies on how to achieve positive institutional change in developing nations.
Professors Ernesto Dal Bó and Frederico Finan, both from the Business and Public Policy group at Haas, convened the three-day forum as part of the Economic Development and Institutions (EDI) initiative, a five-year, $19 million international effort funded by UK Aid from the UK Department for International Development and managed by Oxford Policy Management. The professors, working with Berkeley’s Center for Effective Global Action (CEGA), are overseeing $5.5 million in randomized control trials of institutional reform efforts throughout the world in order to build on what works.
Public sector entrepreneurs
The forum brought together the people behind these evidence-based reforms to share progress and challenges, spark new research, and build connections. Visitors include high-level officials from the Mexico City Labor Court, the Judiciary of Kenya Law Reform Commission, the Uganda Ministry of Lands, Housing and Urban Development, Pakistan’s Punjab Commission on the Status of Women, the City of Dakar tax authority, and others.
“Over a number of years here at Berkeley we have been devoted to the study of the institutional roots of economic development,” Dal Bó said in his opening remarks. “We have learned that when you scratch beneath the surface, you find that behind every successful institutional reform project is an individual who, in some part of a public organization, decided that he or she had had enough and that something needed to change. In every single case there is a figure that we like to call a ‘public sector entrepreneur,’ who is somehow combining resources to make something happen.”
30 studies underway
Launched two years ago, the EDI initiative has already allocated allocated $5.5 million in funding to 30 randomized control studies involving 80 researchers across 12 countries, Dal Bó said. They include academics, research institutions, and reform-minded public organizations working to increase government transparency, accountability, and other reforms to political and legal systems.
Randomized control trials are considered the gold standard in field research, reducing bias and providing data on which reforms actually make a difference. EDI is focusing on programs that work closely with local institutions and government, rather than efforts by outside groups alone that may be less sustainable. While there are many initiatives funding impact evaluations in the developing world, EDI has a broader goal, Dal Bó said.
“We want to go beyond the individual impact evaluations and create linkages to build more cohesive, generalizable knowledge,” said Dal Bó, the Philips Girgich Professor of Business and an expert on government corruption and reform, who holds a joint appointment in the Political Science Department. “The other thing we want to do is put the lens on these public sector entrepreneurs and endow these people with instruments that might be helpful.”
Frontiers of evidence-based policy
The forum included interactive sessions with leaders of the studies that are underway, discussions about the state of science and open policy questions, funding priorities, and presentations from the “frontiers of evidence-based policy.” Two of the presenters were professors Katherine Casey of Stanford’s Graduate School of Business, who conducted the study of citizen engagement and election reforms in Sierra Leone, and Michael Callen of UC San Diego’s Rady School of Management, who led the experiment on using mobile money to fight corruption in Afghanistan (which was not funded by EDI but presented as an example of a large-scale public sector experiment).
Callen worked with the Afghan Ministries of Finance, Labor, and Education and the Office of the President to register all workers and then test whether paying them through mobile money would reduce the substantial “leakage” of government funds. The program was successful enough that Office of the President and the Ministry of Finance are bringing it to scale with the goal of paying all public employees using mobile money.
“The evidence-based smart policy movement is creating innovations at a remarkable pace,” he said. “But for something like this to succeed it needs to be anchored in government so that innovators can hand it over to implementers.”
Dal Bó and Finan, who act as the scientific leads for EDI’s randomized control trial program, also presented on their own research on reform efforts in Mexico and Paraguay. Their experiments (not funded by EDI) showed how financial rewards, and mobile technology, can help with the recruiting and monitoring of frontline public service workers. In one study, they rolled out mobile phones to the government agents who support small-scale farmers in Paraguay. They found the phones improved their performance, allowing them to not only document their farm visits but also for their government supervisors to track and monitor their locations.
The EDI program also includes research that takes stock the evidence on specific issues, development of a new diagnostic tool, and in-depth case studies. Other partners include Belgium’s University of Namur, the Paris School of Economics, and consulting firm Aide a la Decision Economique.
Three new assistant professors have joined the Berkeley Haas faculty, with research interests that range from how financial news influences markets to the unintended consequences of mortgage market regulations to developing more accurate ways to predict consumer behavior.
Anastassia Fedyk and Matteo Benetton will join the Finance Group, while Giovanni Compiani will be part of the Marketing Group.
“We’re thrilled to have these three rising stars join us this year,” said Prof. Candace Yano, associate dean for academic affairs and chair of the faculty.
The three new faculty members have already won awards for their research and have published in top journals. As is customary, they will spend the fall semester working on their research and plan to begin teaching in the spring semester.
Assistant Professor Anastassia Fedyk, Finance
For Anastassia Fedyk, coming to Haas is a homecoming of sorts. Though she was born in Ukraine and moved to the United States at age 10, she spent her high school years in Berkeley while her mother earned her PhD in accounting at Haas.
“I really loved living here back in high school, so it was always a dream to move back,” says Fedyk. “And the fact that there are so many people here working in behavioral economics makes it a perfect fit with my work.”
Knowing early on that she wanted to become a research economist, Fedyk majored in math at Princeton and did a two-year stint doing research at Goldman Sachs before heading to Harvard University to earn her PhD in business economics.
Her work spans finance and behavioral economics, and she has pursued three main research threads so far. The first focuses on financial news and how it translates into prices and trading volume in the markets. She’s looked at trading around news events and how the news is presented. “For example, if the news is printed on the front page that will prompt a much faster price response than if it’s less prominent,” she said. Or, when two old news stories are reprinted together, they are perceived as a new piece of information.
Her second line of research centers on present bias and procrastination. She’s found that although people fail to recognize these tendencies in themselves—and really do believe they’ll follow through on their plans for a new gym routine or diet—they easily recognize them in others.
Fedyk’s third line of inquiry looks at how employees’ skills relate to companies’ performance, working with a large dataset of resumes from a startup that collects public profiles. She has found that companies with an unusually high focus on sales-oriented skills tend to outperform, while companies that are heavy on administrative and bureaucratic personnel tend to do worse.
She will be teaching core finance in the evening & weekend MBA program.
Assistant Professor Matteo Benetton, Finance
Matteo Benetton also feels a kinship with Berkeley, although he had only spent three days here interviewing before moving 5,500 miles this month from the U.K, where he completed his PhD at the London School of Economics.
“The vast majority of Italian economists study at Bocconi, which is a private university, but I went to the University of Pisa’s Sant’Anna School of Advanced Studies, which is public,” said Benetton, who originally hails from Treviso near Venice. “I love the idea of a high-quality public university, and the research mindset that goes with that. That’s something I value a lot. Plus, after six years in London I’m looking forward to some sunshine.”
Benetton, whose work centers on the intersection between competition in the lending market, mortgage product design, and regulation, says he was excited to find so many faculty at Haas who share his interests, both in the Finance and Real Estate groups.
Benetton’s research has shown that some banking regulations put in place after the global financial crisis have had unintended consequences, giving more advantages to big banks over smaller banks. “The regulation can actually distort competition, and increase market concentration,” he said. In one paper, Benetton recommended that regulations apply evenly to big banks and smaller lenders, to prevent established banks from gaining additional advantages.
He has also researched how innovative mortgage product design can benefit consumers and prevent the buildup of risk in the housing market. He’s looked at shared-equity mortgages, in which a government or bank lender provides a homebuyer with part of the down payment but takes some of the equity. These profit-sharing contracts can reduce risk, but homebuyers who expect prices to go up tend to avoid the since they don’t want to share the gains.
While much of his work has been focused on Europe, with his new proximity to Silicon Valley Benetton says he’s interested in exploring how fintech is changing banking and payment systems, as well as branching out into household finance.
Benetton will be finishing up a research project this fall and will begin teaching finance in the undergraduate program in January.
Assistant Professor Giovanni Compiani, Marketing
Giovanni Compiani is also a native of Italy, who comes to Haas via Yale University, where he earned a PhD in economics. He’s looking forward to opportunities for working across disciplines at Berkeley, and also to the proximity to Silicon Valley and its trove of consumer data.
“Being at a business school and at Berkeley in particular, there’s a more question-oriented approach—rather than a focus on methods it’s about ‘What real-world question do we want to address?’”, Compiani said. “At Yale, I acquired a rich set of econometrics and structural methods tools which I now look forward to applying. There are so many relevant topics in the digital economy, and at Berkeley an economist can work with a computer scientist and say something very meaningful and interesting.”
Compiani grew up in Bologna before studying economics at Italy’s prestigious Bocconi University in Milan. He completed part of his master’s at Yale and returned for his doctorate.
He has focused much of his research so far on consumer behavior, building a model that gives more flexibility than established models allow for in predicting consumer reactions to price changes. “Let’s say a tax is levied on a supermarket. The market could lower the price of products to keep the final price to consumers unchanged, or they could pass on the full increase to consumers. The best strategy depends on knowing how consumers react,” he said. “This model relaxes certain strict assumptions typically made for ease of programming, and thus delivers more robust results.”
Compiani is also investigating patterns of how consumers search across different product characteristics, such as price. “Understanding these patterns has implications both for policy and for firm strategy,” he said.
With the possibility of increased access to data sources from Silicon Valley companies, Compiani is interested in exploring new lines of research on how concerns about data privacy influence consumer behavior.
He will begin teaching marketing analytics in the undergraduate program in the spring.