Behavioral Economics & Finance Archives | Haas News

Why Berkeley Haas leads in Bay Area investment banking

September 29, 2021| by Kim Girard

Rita Wiley, MBA 22, spent last summer interning at Piper Sandler’s San Francisco offices, taking in sweeping waterfront views from the 31st floor as she worked on healthcare investment deals with her team.

“On the first day, my managing director threw me into a live deal,” said Wiley, who spent a decade in project management with the U.S. Army before coming to Haas, where she was drawn to the work ethic and quick skill-building that investment banking demands. “I was given responsibility to run with projects.”

With that internship, Wiley joined a group of 14 Haas MBA students who worked as 2021 Summer Associate interns at Bay Area offices of investment banks. Now the top go-to business school for such hires, Haas typically nabs the largest—or over a 20%—share of the some-65 available IB Summer Associate slots each year. Internships, which are largely in either technology or healthcare investment banking, are critical because they lead to full-time positions at graduation with a very high return-offer rate relative to other industries.

“Haas produces world-class talent right here locally for the sought-after Bay Area offices, which focus largely on high-growth tech clients, and we perennially have the largest share of associates here at the global intersection of tech and finance,” said William Rindfuss, a member of the continuing professional faculty in finance who also manages financial services recruiting at Haas.

“Haas produces world-class talent right here locally for the sought-after Bay Area offices,” —William Rindfuss, who manages financial services recruiting at Haas.

Impressive alumni

Bill Rindfuss — William Rindfuss, who manages financial services recruiting at Haas.

Haas’ influence in investment banking grew for many reasons, including a strong finance faculty and curriculum, a Career Management Group (CMG) that’s well-connected to the top banks and supports students through the often intense recruiting process, and a powerful alumni network, Rindfuss said.

Importantly, those alumni show up for popular events like firm networking nights and the Investment Banking Speaker Series course, which recently featured Kate Claassen, MBA 07, head of West Coast Technology Investment Banking at Morgan Stanley, and will feature Nils Hellmer, MBA 15, an Executive Director at Goldman Sachs.

“Our alumni are so supportive and inspiring to the students,” said Rindfuss, a former J.P. Morgan banker, who has been at Haas since 2008. “You’ll find Haasies at all the top investment banks and we’re so grateful that they take the time to give back to the school and our students—while at the same time seeking new talent.”

Berkeley Haas’ investment banking network has grown over the decades, said Steve Etter, who teaches finance at Haas and is a founding partner at Greyrock Capital Group. Cal alumni helped build big investment banks of the 1970s and 1980s—banks like Montgomery Securities, Hambrecht & Quist, and Robertson Stephens, where alumni flocked. “Cal alumni helped build this West Coast community,” Etter said. “Then the Morgans and Goldmans started to build bigger West Coast presences. We now have senior (Cal) people across all the banks.”

Recruiting help from campus

Haas MBA students heading into full-time investment banking jobs: Rawool Sahu, (Moelis) Rita Wiley, (Piper Sandler) Alex Wong, and Adhithya Ravi. (Morgan Stanley) Photo: Jim Block

Berkeley Haas MBA students coveting jobs in investment banking compete with students from top programs including Wharton, Booth, and Columbia. The jobs are in demand because investment banking pays very well, with a standard $175,000 salary, a typical $50,000+ signing bonus, and year-end performance-based bonuses—all very strong compared to the average MBA graduate compensation, said Abby Scott, assistant dean of MBA Career Management and Corporate Partnerships.

“But the jobs not only pay well, they offer recent MBA hires some pretty amazing opportunities,” Scott said. “New MBA associates often become part of live deal teams working with high-profile clients in tech, healthcare, and other high-growth sectors.”

“But the jobs not only pay well, they offer recent MBA hires some pretty amazing opportunities,” —Asst. Dean Abby Scott.

MBAs typically commit to investment banking quickly as they have to start preparing for internship recruiting early. “For investment banking you have to know early on if you want to do it because an IB internship is pretty much a requirement for a full time offer,” said Wiley, who was among 13 finance students chosen as 2020 Finance Fellows, receiving partial scholarships, priority registration for finance courses, and mentorship.

Andrew Elliott, MBA 22, said he was “95% committed” to investment banking when he arrived at Haas after working in strategy and business development at Boeing. Elliott worked for six months with Abby Franklin, an investment banking industry specialist with the Haas Career Management Group (CMG), to better understand both the career progression and work-hour demands.

He applied to multiple firms, a few on his own and most through CMG. CMG’s on-campus recruiting resources—that covered everything from resume design to networking events and interviews—helped Elliott land a summer internship at Citi, where he had already connected with his peer advisor, Ryan Alders, MBA 20, an associate in technology investment banking at Citi. “When I first saw CMG’s requirements I was a little scared because they seemed so specific, but in the end, the process protected me because I ended up with a solid job offer,” said Elliott, who will start a full-time job at Citi this spring, after graduating early.

Christine Jan, who also worked closely with CMG, said she spent hours talking to Haas alumni at different investment banks about everything from deals to the nuts and bolts of jobs to personal life management advice before landing an offer.

With Franklin’s guidance, Jan reached out to Shilpi Saran, MBA 13, a vice president in technology investment banking at Morgan Stanley. “Shilpi got me interested,” said Jan, who grew up in Taiwan and worked in wealth management at UBS in Hong Kong before coming to Haas. “It’s a process. We have alumni who are performing exceptionally well and they draw us in.”

During recruitment, Jan also met UC Berkeley alumnus Michael Grimes, head of Global Technology Investment Banking for Morgan Stanley, who also founded Berkeley’s M.E.T. program, an undergraduate dual-degree program in business and engineering, and Michael Bausback, MBA 19, an associate in global tech investment banking. Jan committed to a summer internship in tech investment banking with them that led to a full-time job offer. (Jan will join Adhithya Ravi and Alex Wong, both MBA 22, who are also heading to Morgan Stanley Bay Area investment banking offices).

“I loved (the internship),” she said. “It was a deep dive into investment banking. I got to realize what it was and connect the dots to what I’ve done before, connecting my work in Asia and here. It was a great, overwhelming, inspiring experience.”

The boutique path

While bigger firms like Morgan Stanley, J.P. Morgan, and Goldman Sachs draw Haas students each year, a smaller firm like Moelis or Evercore can be a better fit for other students—many who say culture, regardless of size, influences where they end up.

Rawool Sahu, MBA 22, who shifted from a career in corporate financial planning and analysis to investment banking through Haas, will join Moelis, a boutique investment bank, in its thriving San Francisco office next July. (Moelis’ founder and CEO Ken Moelis just announced that the firm had raised pay for first-year analysts because “business is booming” and deal flow is rising.)

Sahu said there are benefits to joining a smaller firm. “Moelis has a smaller office on the West Coast and you get more time with the senior bankers here. At banks on the East Coast, that’s harder.” In a smaller office, he said, work also feels more focused. “Managing directors communicate more directly about what they want, so we don’t waste time. It makes things more efficient.”

At Moelis, Sahu joins a group of Haas alumni, including Adam Burgess, an investment banking associate from the class of 2020, “who helped me to make inroads in the West Coast office,” Sahu said.

“You can do this”

Adhithya Ravi, who will work at Morgan Stanley after graduating, is a peer advisor to first-year investment banking students at Haas.

With the 2023 MBA class now on campus, finance students are attending the Investment Banking Speaker Series—along with three networking events each week that connect them with bankers—and preparing for investment banking internship recruiting.

Ravi, who is co-president of the Haas Finance Club, said recruiting with investment banks was one of the most difficult experiences that he has gone through in his life, which is why he’s helping first-year students as one of three peer advisors.

This year, he said the Finance Club rolled out a new guide to everything a recruit will need to succeed, including a networking primer, study schedules, interview prep, and advice for finding a bank that’s a good internship fit. “I’m constantly reminding recruits to leverage those around them and support one another,” Ravi said. “Having a support group and people to prep with helped so much,” he said.

To prospective Haas investment banking students, Wiley offered encouragement. “I had an interest in finance on the personal side but never thought I would make a career out of it,” said Wiley, who accepted a job with Piper Sandler after graduation. “I’m a prime example that you can do this.”

How Robinhood’s trading app spurs investors’ herding instincts: Q&A with Prof. Odean

February 5, 2021|By Kathleen Pender

The Robinhood app displayed on a phone — Photo by: STRF/STAR MAX/IPx 2021

Last year, when Berkeley Haas finance professor Terrance Odean was researching why users of the popular trading app Robinhood tended to “herd” into a small number of stocks, he never imagined a situation like what unfolded last week with GameStop.

“It was like a supernova of herding events,” he said.

Shares in the moribund video-game retailer soared more than 400% over three days when a mob of investors—many congregating on the Reddit chat room WallStreetBets—coordinated to buy the stock en masse. It fell 44% the next day as Robinhood and other brokerage firms temporarily curbed new purchases of GameStop. Although trading has been restored, the stock has been mostly down but remains volatile. Tens of billions of dollars of market value have been created and erased.

Odean had been examining how Robinhood’s easy-to-use technology drives investor behavior and share prices. The Menlo Park company, founded in 2013, has built an enormous following, especially among young investors. It was “the first brokerage to offer commission-free trading on a convenient, simple, and engaging mobile app,” Odean wrote in a working paper he co-authored with three other finance professors.

Making trading fun

The Robinhood app makes investing fun and—critics say—addictive. New members get a free share of stock after they scratch off the image of a lottery ticket, and when they reach certain milestones, digital confetti rains down on their screen. Robinhood users can begin trading as soon as they open an account.

“Half of Robinhood users are first-time investors, who are unlikely to have developed their own clear criteria for buying a stock,” the paper says. “The app prominently displays lists of stocks in an environment relatively free of complex information. For example … Robinhood only provides five charting indicators, while TD Ameritrade provides 489.”

The app focuses attention on Robinhood’s 100 “Most Popular stocks,” and a narrower “Top Mover” list that shows which 20 stocks, throughout the day, have the biggest positive or negative percentage changes.

Using Robintrack, a database of the most popular stocks among Robinhood users from May 2018 until August 2020, the researchers compared trading by its users to other retail investors. They also looked at trading in “attention-grabbing” stocks on three days when Robinhood system outages prevented its users from trading.

They concluded that the simplicity of Robinhood’s app, combined with its users’ inexperience, made them more likely to herd, or pile into a smaller set of stocks, than other retail investors.

Short sellers took note

They also looked at what happened to a stock’s price when it was subject to a herding event or “extreme herding” event, the latter being days when the number of Robinhood users who own a stock grew by 1,000 users and 50% from the previous day. These stocks posted abnormally large gains on the day of herding—averaging 14% for a regular herding event and 42% for an extreme herding event. The next day, however, returns turned “significantly negative” and were still down—5% and 9%, respectively—after 20 days.

“While some Robinhood users undoubtedly made money, in our analysis, a greater number of them lost money,” Odean said.

The team also documented a “marked increase in short selling for stocks involved in Robinhood herding events,” a sign that some investors have been exploiting these “predictably negative returns” by placing bets that Robinhood favorites will fall. The paper’s co-authors are Brad Barber of UC Davis, Chris Schwarz of UC Irvine and Xing Huang of Washington University in St. Louis.

We asked Odean about Robinhood, GameStop and lessons to be learned from recent events.

Q: Did you ever dream there would be a herding event like GameStop?

A: It would be lovely to say I saw it coming, but no. What we are seeing with Robinhood is herding similar to what’s been documented in other situations, but previously the magnitudes have been much lower. We saw herding in the 1970s and 1980s, when people on Monday would buy stocks mentioned Friday evening on Louis Rukeyser’s Wall Street Week, a public-television show. Now what you have is a lot more investors having their attention funneled into what is often a small set of illiquid stocks and buying at the same time.

What’s surprising about GameStop was the extent to which people were writing (primarily on the Reddit chatroom WallStreetBets) about how we will all consciously do the same thing at the same time and thus possibly affect market prices. That aspect of the GameStop fiasco is not in our paper.

Is what you just described illegal?

I’m not an attorney but my understanding is, if two hedge funds started sending emails to each other saying if we both buy these stocks in large numbers on Tuesday, that will drive the price through the roof—that would probably be illegal.

I’m not sure what will happen with GameStop, but it’s a lot harder to make a case against millions of people spending small amounts of money than against a small number of sophisticated investors doing this with a lot of money.

I’m not sure what will happen with GameStop, but it’s a lot harder to make a case against millions of people spending small amounts of money than against a small number of sophisticated investors doing this with a lot of money.

Has Robinhood made investing too simple?

It has changed people’s behavior by making it simple. Robinhood’s mission statement is to democratize investing for all. Jack Bogle (founder of Vanguard Group) did that years ago. You can buy a Vanguard index fund, pay $4 a year for every $10,000 you have invested and have a well diversified, long-term investment in the market and the U.S. economy. That’s democratization. What Robinhood has done is make it easy to trade.

How does Robinhood make money?

Hand over fist. They sell their customer’s orders to market makers. If you want to sell, the market makers buy from you, and vice versa. When market makers take the other side of a trade, they face asymmetric information risk—the risk that they are trading with someone who knows more than they do. Market makers seem to think that when they trade with someone from Robinhood, they are not taking that risk. They think, if I always take the opposite side of the trade from the side Robinhood is on, I will make so much money I can pay Robinhood.

This is called “payment for order flow,” and it’s not new. Other retail brokerage firms also do it.

(In December 2020, the Securities and Exchange Commission charged Robinhood with failing to properly disclose its payments for order flow to customers and failing to seek the best terms for their trades. Robinhood paid $65 million to settle the changes without admitting or denying guilt.)

Should regulators outlaw this practice?

It’s complicated. Without payment for order flow, there won’t be commission-free trading. My concern is that investors are only aware of costs that are direct and explicit. Most investors are aware of commissions, but not payment for order flow. If investors mistakenly believe that zero commissions means free trading, they are likely to trade more actively and more speculatively. I believe that we should get rid of payment for order flow, but one has to be careful about the unintended consequences of well-intended regulations.

What is the most important lesson to take away from this GameStop event?

Retail investors whose trades are highly correlated—through forums such as WallStreetBets or other means—have more market power than many people on Wall Street expected.

Retail investors whose trades are highly correlated—through forums such as WallStreetBets or other means—have more market power than many people on Wall Street expected.

Why did Robinhood temporarily halt new purchases in Gamestock, AMC and other stocks subject to extreme volatility?

Depository Trust and Clearing Corporation (the clearing house for Robinhood’s trades) required Robinhood to put up more capital to ensure that Robinhood would make good on the trades it placed for its clients. Brokerages are required to use their own money as collateral while they wait for trades to clear. Robinhood’s clearing house increased its capital requirement because of the surge in orders in GameStop and some other stocks and because these stocks became hugely volatile. Robinhood reopened trading after it raised $3.4 billion in additional capital.

Traders allegedly targeted companies like GameStop because a large percentage of their shares had been sold short by hedge funds and others. This means the short sellers borrowed GameStop shares and sold them, hoping to buy them back later at a lower price and pocket the difference. When GameStop shares skyrocketed, hedge funds suffered massive losses when they had to buy the shares at higher prices, which put even more upward pressure on GameStop shares. Some traders are portraying short sellers as the “bad guys” and Robinhood traders as “good guys.” Are there really any good guys and bad guys here?

Financial economists believe that short selling plays a useful role in markets by enabling investors with negative information or opinions about a stock to influence prices and thus keep prices from being set only by investors with optimistic views. Short sellers do, however, sometimes behave badly by promoting negative rumors about companies after they’ve established their short positions. I have not read that this was a major problem with GameStop. I would say that people who intentionally manipulate stock prices qualify as bad guys. And Jack Bogle—who tried to make investing less expensive and safer—was a good guy.

Stock options worth more for women, senior managers, study finds

January 7, 2019| by Sam Zuckerman

Stock options worth more for women_berkeley haas study

A novel new way of determining the value of employee stock options has yielded some surprising insights: Options granted to woman and senior managers are worth more because they hold them longer. And options that vest annually rather than monthly are worth more for the same reason.

The new valuation method, which combines standard option theory with real-world observations of what employees actually do with their grants, gets at a knotty problem: Even though stock options are one of the most common forms of compensation, companies don’t really know how much granting options costs them.

Berkeley Haas Prof. Richard Stanton — Richard Stanton

“We’ve come up with a practical method of valuing stock options that takes into account actual behavior of employees,” says Richard Stanton, a Berkeley Haas professor of finance and real estate who holds the Kingsford Capital Management Chair in Business.

The new approach is laid out in “Employee Stock Option Exercise and Firm Cost,” forthcoming in the Journal of Finance and co-authored by Berkeley Haas Prof. Nancy Wallace and New York University Assoc. Prof. Jennifer N. Carpenter. Their analysis also draws on behavioral economics, which considers the effects of psychology on financial decisions.

A behavioral economics approach

Among their original findings: Options awarded to women cost companies 2 to 4 percent more than those granted to men, who tend to exercise their options faster. And awards to the most senior employees cost 2 to 7 percent more than grants to their lower-ranking colleagues—again, because the execs hold onto them. In addition, options cost companies significantly more when they are set up to vest less frequently—that is, reach the threshold date when they become eligible to be exercised. A shift from an annual to a monthly vesting date reduces option value by as much as 16 percent because people exercise the options earlier and more often.

According to a recent survey by Meridian Compensation Partners, 42 percent of companies responding reported they awarded stock options to senior executives. And options represent more than 20 percent of CEO pay, according to one estimate. Options allow holders to buy a specific stock at a set price until a predetermined expiration date. The basic challenge in determining the cost of employee stock options is that their value depends on how long they are kept. In general, the longer they are held, the greater the cost to the company that issued them. Consequently, the key to valuing them is to predict accurately when they will be exercised. “How much the options are worth depends on what the employee is going to do with them,” Stanton notes.

A vast literature examines how to determine the value of stock options traded on exchanges. But employee stock options are a special breed with their own special characteristics. For that reason, the valuation methods originally developed for exchange-traded options are imprecise when applied to the options companies award their employees.

Standard option theory takes into account several factors to forecast when options will be cashed in. But it was largely developed through studies of exchange-traded options, making it out of whack for employee stock options for several reasons. For one, employee stock options can’t be traded on the market—the only way employees can dispose of them is to use them to buy the underlying stock. Second, they can only be used during a multi-year window that starts when they vest and ends when they expire. Third, employees can’t easily protect themselves from the risk of having so much of their wealth tied to their employer’s stock, since the only way to reduce the risk is to exercise the option, and that impacts its value.

New model factors in behavior and risk

To arrive at a more accurate way of estimating when employees would exercise stock options, Stanton, Carpenter, and Wallace, the Lisle and Roslyn Payne Chair in Real Estate Capital Markets, analyzed a unique set of data that included complete employee stock option histories awarded to some 290,000 employees from 1981 to 2009 at 88 publicly traded corporations. The dataset gave them an unprecedented fine-grained look at option-exercise behavior. The authors then constructed a mathematical model of exercise rates that took relevant factors from standard theory and added factors related to the riskiness of the options, based on portfolio theory, along with some additional behavioral factors and information on the terms governing options grants, along with characteristics of issuing companies and option holders.

Their findings included some surprises. For example, vesting frequency had an especially powerful effect on option cost. The obvious reason is that employees are able to exercise options earlier when they vest more frequently. But something else may be at work—employees receive an email when options vest, which may prompt them to pull the trigger. “When people’s attention is drawn to their holdings, they’re more likely to make a decision,” Stanton suggests. Similarly, men may exercise options earlier and more often than women because they are more confident making financial decisions. That finding is in line with influential work by Berkeley Haas Prof. Terrance Odean, who found that male investors trade more frequently than women—behavior that reduces their net returns.

But why do high-ranking employees hold their options longer than lower-ranking colleagues? One reason may simply be that they are wealthier and don’t need a stock options windfall to pay for a home renovation or an expensive vacation.

Almost ten years in the making, the research was funded by the Society of Actuaries in response to regulatory calls for improved employee stock option evaluation methods.

More from these researchers

Minority homebuyers face widespread lending discrimination

A decade after housing bust, mortgage industry is on shaky ground, experts warn

Nancy Wallace named chair of the Fed’s model validation council

A house of cards: Prof. Nancy Wallace warns of risk in real estate securities

Can racism, sexism, and other biases be quantified?

September 11, 2018| by Laura Counts

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?

Berkeley Haas Assoc Prof Ming Hsu — *Ming Hsu*

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?

Eye-opening findings

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).”

Future applications

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.

Meet the faculty: Haas welcomes three rising academic stars

August 20, 2018| by Laura Counts

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

Berkeley Haas Asst. Prof. Anastassia Fedyk — *Asst. Prof. Anastassia Fedyk*

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

Berkeley Haas Asst. Prof. Matteo Benetton — *Asst. Prof. Matteo Benetton*

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

Berkeley Haas Asst. Prof. Giovanni Compiani — *Asst. Prof. Giovanni Compiani*

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.

Assoc. Prof. Kolstad honored as top health economics researcher under 40

May 1, 2018| by Laura Counts

Assoc. Prof. Jonathan Kolstad_Berkeley Haas — *Assoc. Prof. Jonathan Kolstad*

Assoc. Prof. Jonathan Kolstad has received the top award from the American Society of Health Economists for researchers under age 40 who have made the most significant contributions to the field of health economics.

He shares the 2018 ASHEcon Medal with his collaborator, Assoc. Prof. Benjamin Handel of Berkeley’s Economics Department.

Kolstad said he’s honored to be recognized, relatively early in his career, for a larger contribution than just one paper, and for an ongoing collaboration.

“The fact that this was given jointly to Ben Handel and myself reflects an appreciation for some of the new avenues we’ve taken in health economics,” he said. “Much of our joint work has brought new data to bear on old problems that have really different implications when you get into how people actually behave, not just how we assume they behave. ”

Drawing on big data and behavioral economics

Kolstad’s research focuses on the intersection of health economics and public economics, and his work with Handel has also combined approaches from industrial organizations as well as behavioral economics. Their interdisciplinary, cross-departmental collaboration reflects the strength of health economics at UC Berkeley.

“We are very happy to have (Kolstad) at Haas, and we’re pleased by how he is helping to build interest in healthcare economics at Haas and across the Berkeley campus,” said Prof. Candi Yano, associate dean for academic affairs and chair of the faculty.

Recently, Kolstad and Handel have been working with a massive trove of health data on the entire population of the State of Utah over a long time period. The richness of the data has allowed them to analyze the different outcomes from different health insurers and health plans.

“We’re finding very large effects and big differences,” Kolstad said. “Simply changing insurers at the same employer—something most people encounter with some frequency—has huge effects not only on how much is spent on your health care, but also on how your healthcare is delivered.”

The researchers are now looking at what employers look for in choosing insurers and health plans, to answer the question of whether competition actually leads to “productive innovation”—i.e, improving care and lowering costs.

Data partnerships

*Assoc. Prof. Benjamin Handel, Berkeley Economics*

Kolstad and Handel are also working on partnerships with a number of private companies, from digital health to employers and health care providers, to leverage their data for new research. “This is a particularly exciting area,” he says. “Collaboration between academics and private firms, particularly technology companies, is driving a lot of new findings. We hope to make similar strides on big health care questions.”

Since arriving at Haas from Wharton in 2015, Kolstad has brought his expertise with big data into the MBA curriculum, including developing a new “Big Data and Better Decisions” course that he co-taught with Prof. Paul Gertler this spring. Earlier this year, he was honored as a “40 Under 40” business leader by the San Francisco Business Times for his work as a cutting edge researcher, teacher, and entrepreneur. He founded a startup, Picwell, which now provides more than 1 million personalized insurance recommendations per year.

He said he’s excited by the practical applications of his academic work. “We all deal with our health, and the policies and products in the industry affect our everyday lives. The recognition for this work and its importance to the field will hopefully continue to push health economics more in this direction.”

Hawk or dove? For central bankers, birth year influences outlook

March 26, 2018| by Sam Zuckerman

Federal Reserve policymakers are among the best informed and most knowledgeable experts on the economy, and their decisions on interest rates are supposed to be based on exhaustive analysis of data. But Ulrike Malmendier, the Edward J. and Mollie Arnold Professor of Finance at Haas, believes something else may also be at work: the personal experiences of inflation that Fed decision makers have had over their lifetimes.

In a working paper coauthored with Stefan Nagel of the University of Chicago and Zhen Yan of the University of Michigan, “The Making of Hawks and Doves,” Malmendier offers evidence that Fed policymakers’ lifetime experiences with rising prices help shape their projections of future inflation, influence their votes on monetary policy, and color the tone of their speeches. If they lived as adults through periods of high inflation, such as the 1970s, they tend to be much more leery of runaway prices than if they came of age during later decades, when inflation was largely under control. In short, lifetime inflation experience is important in determining whether members of the Fed’s policy body, the Federal Open Market Committee (FOMC), are “hawks” or “doves”—that is, whether they emphasize keeping prices in check or also give high priority to fostering economic growth and employment.

“Our central hypothesis is that FOMC members’ voting decisions are influenced by the inflation experiences they have accumulated during their lifetimes,” Malmendier and her coauthors conclude. “When forming beliefs about future inflation, people overweight realizations of past inflation that they have experienced in their lives so far.”

Behavioral economics lens

The study has been hailed as a landmark analysis of the policymaking process using the principles of behavioral economics, a field of study with deep roots at UC Berkeley that takes insights from psychology and has introduced ideas such as irrationality, emotion, and force of habit into economic research. The paper “is the first to provide evidence of the impact of personal experience on the decisions and expectations of central bankers,” economist Daniela Bergmann wrote in Chicago Policy Review.

Malmendier, who holds joint appointments at Haas and in UC Berkeley’s Economics Department, is a rising star in behavioral economics and a past winner of the American Finance Association’s Fisher Black Prize, awarded every second year to a leading finance scholar under 40. Along with Economics Prof. Stefano DellaVigna, Malmendier co-founded the Initiative for Behavioral Economics and Finance at UC Berkeley. In previous work, Malmendier and Nagel have explored other ways personal experience affects economic behavior, such as how willing investors are to take risks. They concluded that appetite for risk in the stock and bond markets depends on how those markets have performed over an investor’s lifetime, challenging the conventional notion that investors act rationally to maximize gains.

Going against the tide

The paper on Fed policymakers also goes against the tide. Standard economic analysis holds that FOMC members’ inflation expectations and votes on policy reflect objective information on how the economy is performing. If that were the case though, each FOMC member would take the same policy position, since all of them have access to the same information. “We’re trying to understand why these experts have very different views,” Malmendier explains. “We think the inflation experience they have had in their lifetimes is an important reason why some people are optimistic and some pessimistic” about rising prices.

In the paper, Malmendier and her coauthors implemented a new model of experience-based learning, which holds that Fed policymakers forecast inflation based on how prices have behaved up to the time of an FOMC meeting. The researchers then applied statistical analysis to economic data to create an econometric model that incorporates lifetime inflation experience to forecast each FOMC member’s voting behavior. They controlled for changing attitudes by age, as well as political party affiliation and academic background in economics (i.e., whether the members held a PhD in the field). When the authors compared their experience-based forecasts with members’ actual voting behavior from March 1951 to January 2014, they found that those with more inflation experience were more likely to have hawkish voting patterns. The effect was striking: An FOMC member had an above-average experience with inflation (according to the experience-based forecast) was one-third more likely to take a hawkish stance that went against the committee majority, and also one-third less likely to take a dovish stance.

Speech analysis

They also looked at whether FOMC members’ attitudes about monetary policy could be detected in their speeches. When they performed a linguistic analysis of FOMC members’ public statements, they found that those with higher experience-based inflation forecasts used more hawkish language. In addition, they were more likely to issue higher inflation projections than internal Fed staff forecasts that had been derived from rigorous data analysis.

The authors’ most striking finding was that FOMC members’ personal experience with inflation is a key determinant of Fed policy. Specifically, the interest rate targets set at FOMC meetings—the Fed’s most important policy decisions—have often strayed from levels suggested by Fed staff and tilted toward the subjective forecasts of FOMC members. Malmendier and her coauthors estimate that, throughout most of the 2000s, the Fed’s interest rate targets would have been 0.50 to 1 percentage point lower if policy had been based exclusively on staff forecasts.

One of the implications of this research is that age matters when choosing Fed policymakers since experience of inflation differs largely according to date of birth. It’s a point The New York Times noted in 2014 when it pointed out that inflation had averaged 3.8 percent during the adult life of Charles Plosser, one of the FOMC’s most prominent hawks, but only 2.5 percent during the adult life of Narayana Kocherlakota, one of its most outspoken doves.

Malmendier’s work suggests that the times a person has lived through may someday be considered in the selection of central bank policymakers. “Our results add a twist to the practical notion that the choice of a policy maker can have a long-lasting impact on policy outcomes,” the paper concludes. “To predict a policy maker’s leanings, it is helpful to look at the person’s prior lifetime experiences.”

UC Berkeley to Celebrate 30th Anniversary of Behavioral Economics

May 8, 2017| by Kim Girard

Economics Prof. Stefano DellaVigna and Finance Prof. Ulrike Malmendier, co-directors of the UC Berkeley Initiative for Behavioral Economics & Finance

In spring of 1987, two professors got together from the UC Berkeley economics and psychology departments to teach a new cross-disciplinary class on behavioral economics. The professors, George Akerlof and Daniel Kahneman, went on to win Nobel Prizes for their pioneering work.

On May 20, top economists from around the world—including several Berkeley-Haas thought leaders—will gather to celebrate the 30-year anniversary of behavioral economics at UC Berkeley. The one-day event at the Haas School is by invite only. It will examine the past, present, and future of behavioral economics, which relies on psychological insights into human behavior to explain economic decision-making.

Ulrike Malmendier, the Edward J. and Mollie Arnold professor of finance at Berkeley-Haas and a 2017 Guggenheim Fellow, and Stefano DellaVigna, the Daniel E. Koshland, Sr. Distinguished Professor of Economics, who recently won the American Economic Association’s 2017 award for best paper in applied economics, are the event co-organizers.

Malmendier and DellaVigna (both pictured) are co-directors of the Initiative in Behavioral Finance and Economics at Berkeley. “It is just incredible to have George and Danny back to commemorate the 30^th anniversary of that landmark PhD class,” DellaVigna said. “This is a great occasion to celebrate how deep the roots of behavioral economics are at Berkeley. So many thought leaders in our field emerged here and this is an occasion for us to celebrate that fact.”

“The Berkeley Reformation”

In 2015, Bloomberg columnist Noah Smith described what sets UC Berkeley’s approach apart.

“Their research has taken economics in new directions, in terms of both methods and subject matter,” he said. “It wouldn’t be an exaggeration to say that the Chicago School has been replaced in prominence and influence by what I like to call the Berkeley Reformation.”

UC Berkeley’s influence on the field runs deep. Many of the world’s most influential economists spending time on campus as students or professors. Other well-known UC Berkeley economists include David Romer, a pioneer of New Keynesian business theory, and Maurice Obstfeld, the International Monetary Fund’s chief economist.

A few highlights from the celebration:

A kickoff with Nobel Laureate and UC Berkeley Prof. Dan McFadden. McFadden invented discrete choice models, which are used to predict consumer choices between two or more alternatives.
LA Dodgers general manager Farhan Zaidi, who will speak on Behavioral Economics on the Field. Zaidi, who earned a doctorate in behavioral economics at UC Berkeley, previously worked with the Oakland Athletics’ Billy Beane. The Athletics’ “Moneyball” team “defied its low payroll to reach the playoffs in three consecutive seasons with a roster bearing Zaidi’s fingerprints,” according to an article featuring Zaidi in the LA Times.
George Akerlof, the Daniel E. Koshland Sr. Distinguished Professor Emeritus of Economics at UC Berkeley, and psychology Prof. Daniel Kahneman, both Nobel Laureates, will give a talk titled Back to 1987: Some Ideas for the Future. Akerlof pioneered the economics of asymmetric information in the 1970s, which identified ways that markets could fail. Kahneman, the Eugene Higgins Professor of Psychology Emeritus at Princeton University’s Woodrow Wilson School, wrote the global bestseller Thinking, Fast and Slow, which was influential in both psychology and economics.
A panel on Becoming Behavioral Economists at Berkeley will include a group of professors who spent developmental years on campus. The group includes Saurabh Bhargava (Carnegie Mellon University), Zack Grossman (UC Santa Barbara), Devin Pope (University of Chicago), Gautam Rao (Harvard University), Paige Skiba (Vanderbilt),and Justin Sydnor (University of Wisconsin).
A roundtable on Behavioral Economics: The Next 30 Years, led by long-time UC Berkeley Professor—now at Harvard University—Matthew Rabin. The discussion includes faculty who are currently at Berkeley, such as Shachar Kariv, chair of the Economics Department, and Terrance Odean, a leader in the behavioral finance field, and others who have been faculty or PhD students at Berkeley, including Botond Koszegi (Central European University) and Ted O’Donoghue (Cornell).

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Tag: Behavioral Economics & Finance