Caltech Names Thomas F. Rosenbaum as New President

To: The Caltech Community

From: Fiona Harrison, Benjamin M. Rosen Professor of Physics and Astronomy, and Chair, Faculty Search Committee; and David Lee, Chair, Board of Trustees, and Chair, Trustee Selection Committee

Today it is our great privilege to announce the appointment of Thomas F. Rosenbaum as the ninth president of the California Institute of Technology.

Dr. Rosenbaum, 58, is currently the John T. Wilson Distinguished Service Professor of Physics at the University of Chicago, where he has served as the university's provost for the past seven years. As a distinguished physicist and expert on condensed matter physics, Dr. Rosenbaum has explored the quantum mechanical nature of materials, making major contributions to the understanding of matter near absolute zero, where such quantum mechanical effects dominate. His experiments in quantum phase transitions in matter are recognized as having played a key role in placing these transitions on a theoretical level equivalent to that which has been developed for classical systems.

But Dr. Rosenbaum's scientific achievements were not solely what captured and held the attention of those involved in the presidential search. We on the search committee were impressed by Dr. Rosenbaum's deep dedication, as Chicago's provost, to both undergraduate and graduate education—both critical parts of Caltech's mission. He has had responsibility for an unusually broad range of institutions and intellectual endeavors. Among his achievements as provost was the establishment of the Institute for Molecular Engineering in 2011, the University of Chicago's very first engineering program, in collaboration with Argonne National Lab.

We also believe that Dr. Rosenbaum's focus on strengthening the intellectual ties between the University of Chicago and Argonne National Lab will serve him well in furthering the Caltech-JPL relationship.

As provost, Dr. Rosenbaum was also instrumental in establishing collaborative educational programs serving communities around Chicago's Hyde Park campus, including the university's founding of a four-campus charter school that was originally designed to further fundamental research in education but which has also achieved extraordinary college placement results for disadvantaged Chicago youths.

This successful conclusion to our eight-month presidential search was result of the hard work of the nine-member Faculty Search Committee, chaired by Fiona Harrison, and the 10-member Trustee Selection Committee, chaired by David Lee. We are grateful both to the trustees and faculty on our two committees who made our job so very easy as well as to those faculty, students, staff, and alumni who provided us with input and wisdom as we scoured the country for just the right person for our Caltech.

"Tom embodies all the qualities the faculty committee hoped to find in our next president," Harrison says. "He is a first-rate scholar and someone who understands at a deep level the commitment to fundamental inquiry that characterizes Caltech. He is also the kind of ambitious leader who will develop the faculty's ideas into the sorts of innovative ventures that will maintain Caltech's position of prominence in the next generation of science and technology."

"The combination of deep management experience and visionary leadership Tom brings will serve Caltech extremely well in the coming years," Lee adds. "The Board is excited about collaborating closely with Tom to propel the Institute to new levels of scientific leadership."

"The Caltech community's palpable and deep commitment to the Institute came through in all my conversations, and it forms the basis for Caltech's and JPL's lasting impact," Dr. Rosenbaum says. "It will be a privilege to work closely with faculty, students, staff, and trustees to explore new opportunities, building on Caltech's storied accomplishments."

Dr. Rosenbaum received his bachelor's degree in physics with honors from Harvard University in 1977, and both an MA and PhD in physics from Princeton University in 1979 and 1982, respectively. He did research at Bell Laboratories and at IBM Watson Research Center before joining the University of Chicago's faculty in 1983. Dr. Rosenbaum directed the university's Materials Research Laboratory from 1991 to 1994 and its interdisciplinary James Franck Institute from 1995 to 2001 before serving as vice president for research and for Argonne National Laboratory from 2002 to 2006. He was named the university's provost in 2007. His honors include an Alfred P. Sloan Research Fellowship, a Presidential Young Investigator Award, and the William McMillan Award for "outstanding contributions to condensed matter physics." Dr. Rosenbaum is an elected fellow of the American Physical Society, the American Association for the Advancement of Science, and the American Academy of Arts and Sciences.

Joining the Caltech faculty will be Dr. Rosenbaum's spouse, Katherine T. Faber, the Walter P. Murphy Professor of Materials Science and Engineering at Northwestern University. Dr. Faber's research focuses on understanding stress fractures in ceramics, as well as on the fabrication of ceramic materials with controlled porosity, which are important as thermal and environmental barrier coatings for engine components. Dr. Faber is also the codirector of the Northwestern University-Art Institute of Chicago Center for Scientific Studies in the Arts (NU-ACCESS), which employs advanced materials science techniques for art history and restoration. Dr. Rosenbaum and Dr. Faber have two sons, Daniel, who graduated from the University of Chicago in 2012, and Michael, who is currently a junior there.

Dr. Rosenbaum will succeed Jean-Lou Chameau, who served the Institute from 2006 to 2013, and will take over the helm from interim president and provost Ed Stolper on July 1, 2014. The board, the search committee, and, indeed, the entire Institute owes Dr. Stolper a debt of gratitude for his unwavering commitment to Caltech, and for seamlessly continuing the Institute's forward momentum through his interim presidency.

As you meet Dr. Rosenbaum today and over the coming months, and learn more about his vision for Caltech's future, we believe that you will quickly come to see why he is so well suited to guide Caltech as we continue to pursue bold investigations in science and engineering, to ready the next generation of scientific and thought leaders, and to benefit humankind through research that is integrated with education.

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Caltech Named World's Top University in Times Higher Education Global Ranking

For the third year in a row, the California Institute of Technology has been rated the world's number one university in the Times Higher Education global ranking of the top 200 universities.

Harvard University, Oxford University, Stanford University, and the Massachusetts Institute of Technology round out the top five schools in the 2013–2014 rankings.

Times Higher Education compiled the listing using the same methodology as in the 2011–2012 and 2012–2013 surveys. Thirteen performance indicators representing research (worth 30 percent of a school's overall ranking score), teaching (30 percent), citations (30 percent), international outlook (which includes the total numbers of international students and faculty and the ratio of scholarly papers with international collaborators, 7.5 percent), and industry income (a measure of innovation, 2.5 percent) make up the data. The data were collected, analyzed, and verified by Thomson Reuters.

The Times Higher Education site has the full list of the world's top 400 schools and all of the performance indicators.

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Kathy Svitil
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Cause and Effect: An Interview with Frederick Eberhardt

Determining cause and effect is complex and fraught with difficulty, from our intuitive—but often mistaken—sense of the causes of events in our daily lives to the perils of structuring and interpreting scientific experimentation. One problem with teasing apart these relationships is that there are many cause-and-effect sequences that we can only observe; we cannot meaningfully intervene, which may make it more problematic to test causal relations. For example, we did not come to know that the gravitation of the moon causes Earth's tides by removing the moon to observe how Earth's tides would be affected by its absence. Other means of establishing causality were required.

More bedeviling for anyone seeking to find an accurate causal sequence is how often we observe things that look like causal relations but are only correlations—that is, variables that change (or seem to change) in relationship to one another but are not causally related. If you catch four colds this winter, you may recall that you went outside with wet hair before coming down with each one. This is a correlation. What you don't know—and what might require further reflection and experimentation—is whether the wet hair actually caused the cold.

Untangling causal relations and correlations is what Professor of Philosophy Frederick Eberhardt has come to Caltech to do. We recently spoke with him about how causal relations can be identified—and why they matter.

Why does causation matter?

Causal issues are everywhere. They're in policy, they're in medicine, they're in our basic sciences.

Can you give an example of a correlation that might not involve causation?

Let's take the example of eating ice cream and drowning. These two variables are correlated: when rates of ice cream consumption rise, so do cases of drowning. So we might wonder whether this is a causal relationship: Does eating ice cream cause drowning?

There's a big debate in philosophy over exactly what constitutes a causal relation.

To say one is the cause of the other, we presumably don't require that every time someone eats ice cream they go and drown. So it's only a weaker, probabilistic relation. But it may be more than just a probabilistic relation since, in this example, we think that there could be a common cause: such as good weather, which increases the probability of both ice cream consumption and drowning. If this is the case, it is the common cause that gives rise to the observed correlation. However, if we intervened to increase the consumption of ice cream while holding everything else fixed, and rates of drowning increased as well, then there would be good reason to think that we had identified a causal relation. So, a rather useful way to think about causal relations is that they support certain kinds of interventions.

Given how tricky it can be to establish causality in complex real-world systems, are there correlations for which you think a causal relationship is well established?

That smoking causes lung cancer is reasonably well established. This was not always obvious. Not every smoker died of lung cancer, right? Whether or not drinking red wine in reasonable amounts is related to less cardiovascular disease is not so clear yet. Climate change, of course, is another example. You see the debates about the causal relations involved in climate change and the extent to which we can establish them on the basis of the finite data that we have. Maybe we don't need to know the causes of climate change in order to predict what will happen, but it's crucial to know the causal relations in order to know whether your intervention is going to be efficacious.

Do you ever find it difficult to avoid confusing "causal" and "casual"?

It does happen, because, of course, spell checkers don't catch this. But I guess your fingers have a motor memory of what sequence the letters come in. Because of what I do, it's more likely that I will make a typo in an invitation to a party saying, "Please, it's causal clothing.

Are you planning to be the conscience of Caltech? Hovering over researchers' shoulders saying, "Not so fast!"

I think that's the risk of someone working in methodology, that they become the preacher. I don't want to be the preacher but rather get my hands dirty in the data as well. I try to develop algorithms that infer from one or many different data sets, the causal relations among the variables. These algorithms could prove useful to scientists attempting to ferret out the causal relations in their statistical data.

What attracted you to the position at Caltech?

If you ask other philosophers whether my work is philosophy, they might cringe a little bit and think that I fall more into a technical environment. I actually think these methodological questions about understanding the difference between causality and correlations are fundamentally philosophical problems. I think here at Caltech, this categorization of research topics just won't be an issue. I think people will hopefully see that what I do is relevant and that it matters to a lot of fields, and then who cares whether you call it "philosophy" or not? A lot of people write "interdisciplinarity" on their flag, but very few people do it. I am looking forward to working with some very bright students at Caltech who hopefully will share my disregard for disciplinary boundaries.

Will you be collaborating with other faculty at Caltech?

I hope to find other faculty and researchers here who in their own work have become interested in questions about causality and are keen to pursue those questions in collaborations, but projects like these will need time to develop.

Eberhardt was born in Guayaquil, Ecuador, because his parents—both biologists—were living on the Galápagos Islands. He grew up in Germany and received his B.Sc. in philosophy and mathematics from the London School of Economics before doing graduate work at Carnegie Mellon University, postdoctoral work at UC Berkeley and at Carnegie Mellon University, and taking on an assistant professorship at Washington University in St. Louis. He is joined in California by his wife, Minoli Ratnatunga, an economist at the Milken Institute in Santa Monica, and their young son, Gustav.

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Cynthia Eller
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Colin Camerer Named MacArthur Fellow

Colin Camerer, a behavioral economist at the California Institute of Technology whose work integrates psychology with economics experiments to understand how people behave when making decisions, has been named a MacArthur Fellow and awarded a five-year, $625,000 "no strings attached" grant. Each year, the John D. and Catherine T. MacArthur Foundation awards the unrestricted fellowships—popularly known as "genius grants"—to individuals who have shown "exceptional creativity in their work" and "manifest promise for important future advances," according to the foundation.

The MacArthur Foundation describes Camerer as a "pioneering economist whose research challenges assumptions about human behavior in the traditional models used by economists."

"I am thrilled to be honored by the foundation," says Camerer. "Their choice recognizes the importance and promise of using psychology, and now neuroscience, to do better economics."

"Colin's MacArthur Fellowship is well deserved," says Jonathan Katz, Kay Sugahara Professor of Social Sciences and Statistics and chair of the Division of the Humanities and Social Sciences. "He helped found the now-established field of behavioral economics, showing how fundamental understanding of human psychology can help improve our models of economic behavior, and he continues this exciting work by looking at the intersection of economics and neuroscience to open up the black box of economic decision making."

Behavioral economics, Camerer explains, combines the best ideas and methods from economics, psychology, and, most recently, neuroscience, to better understand choices people make. "The brain is computing an economic number—how much you like a new restaurant, whether a football team will win, whether a person is friend or foe," he explains. "We create theories that detail this neural computation, express it in math, and then predict what people do. When we eventually understand a lot more about the neural computations, we can help treat people with disorders—they're like broken software—make neural nudges to improve decisions, help companies organize work, and much more."

A key aspect of Camerer's work is his novel application of technologies such as electroencephalography and functional magnetic resonance imaging (fMRI) to economics experiments, positioning him as a leader in the emerging field of neuroeconomics. In recent work, he has used these and other instruments to probe the psychological underpinnings of financial bubble markets and Monday-morning quarterbacking (a phenomenon known as 20/20 hindsight bias) and to identify the brain regions that govern fear of the economic unknown.

Camerer already has some idea of what he'll do with the unrestricted funds. "I'll share with family, especially my sister who feeds poor people in Detroit," he says. "Then I'll push back against the science sequester by funding some really adventurous research, like replicating earlier studies—that's unglamorous and hard to fund, but it's crucial for really finding out where the science is rock solid—and then use the money as backup funding when necessary and prudent. For example, we have a grant that was highly rated by the National Science Foundation to do ongoing work on the neural basis of price bubbles, but it is in limbo due to the sequester cutbacks. So I will just start funding some of it to keep going."

Camerer received his bachelor's degree in 1976 from Johns Hopkins University; he earned his MBA in 1979 and a PhD in 1981, both from the University of Chicago. Following positions at Northwestern University, the University of Pennsylvania, and the University of Chicago, he joined the Caltech faculty as a visiting associate in 1993 and became the Rea A. and Lela G. Axline Professor of Business Economics in 1994. He has been the Robert Kirby Professor of Behavioral Economics since 2008.

Camerer, who is a fellow of the American Academy of Arts and Sciences and of the Econometric Society, becomes Caltech's 17th faculty member to be given a MacArthur Fellowship, joining recent awardees Sarkis Mazmanian (2012), John Dabiri (2010), and Alexei Kitaev (2008).

For more information on the 2013 MacArthur Fellows, visit the foundation website at www.macfound.org.

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Kathy Svitil
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What Causes Some to Participate in Bubble Markets?

Caltech research shows neural underpinnings of financially risky behavior

During financial bubbles, such as the one that centered around the U.S. housing market and triggered the Great Recession, some investors react differently than others. Some rush in, trying to "time" the market's rise and fall, while others play it safe and bow out. Ever wonder what accounts for such differences? New neuroeconomic research at the California Institute of Technology (Caltech) has found that the investors most likely to take a risk and fuel bubble markets are those with good "theory of mind" skills—those who are good at "putting themselves in others' shoes." They think the most about the motives behind prices and what other people in the market are likely to do next, but during bubble markets, that actually becomes risky behavior.

The finding is contrary to what some economists have suggested—that financial bubbles are driven by confusion or denial on the part of investors and traders.

"What we find is that the people who are most susceptible to bubbles are not just reckless traders getting caught up in a frenzy," says Colin Camerer, the Robert Kirby Professor of Behavioral Economics at Caltech. "Instead, when there are unusual patterns in trading activity, these people are actually thinking a lot about what it means, and they're deciding to jump in."

Camerer is one of the principal investigators on a new paper describing the study and its results in the September 16 issue of the journal Neuron. The study was led by Benedetto De Martino, senior research fellow at Royal Holloway, University of London, while he was a postdoctoral scholar at Caltech.

An important message from the study, De Martino says, is that it shows "when we interact with complex modern institutions, like financial markets, the same neural computational mechanisms that have been extremely advantageous in our evolutionary history can turn against us, biasing our choices with potentially catastrophic effects." Indeed, theory of mind is typically considered a beneficial skill that can help an individual navigate everything from everyday social situations to emergency scenarios.

The findings center around two regions of the brain. One, called the ventromedial prefrontal cortex (vmPFC), can be thought of as "the brain's accountant" because it encodes value. The other, the dorsomedial prefrontal cortex (dmPFC), is strongly associated with theory of mind.

In the study, the researchers used functional magnetic resonance imaging (fMRI) to monitor blood flow in the brains of student participants as they interacted with replayed financial market experiments. Such blood flow is considered a proxy for brain activity. Each participant was given $60 and then served as an outside observer of a series of six trading sessions involving other traders; each trading session lasted 15 periods, and after each period the dividend for the traded asset decreased by $0.24. At various points during the trial, the students were asked to imagine that they were traders and to decide whether they would want to stick with their current holdings or buy or sell shares at the going price.

In half of the sessions, trading resulted in a bubble market in which the prices ended up significantly higher than the actual, or fundamental, value of the asset being traded. In the three other sessions, prices tracked fairly well with the fundamental value, and never exceeded it.

The researchers found that the formation of bubbles was linked to increased activity in the vmPFC, that "accounting" part of the brain that processes value judgments.

Next, they investigated the question whether the people who were more susceptible to participating in, or "riding," bubbles showed heightened activity in the same brain region. The answer? Yes—those who were willing to participate in the bubble market again displayed more activity in the vmPFC.

To further investigate the theory of mind connection, the researchers asked participants to take the well-known "mind in the eyes" test. The test challenges test takers to choose the word that best describes what various people are thinking or feeling, based solely on pictures of their eyes. The researchers found that study participants who scored highest on the test, and thus discerned the correct feelings most accurately, also showed stronger links between their portfolio values and activity in the dmPFC, one of the brain regions linked to theory of mind activity.

"The way we interpret this is that these people were thinking more about what was going on in the market and wondering why people were behaving the way they were," Camerer explains. "Normally, in everyday social encounters and in specialized professions, this kind of mind reading is useful to the individual. But in these markets, when prices are going crazy, these people think, 'Wow, I think I can figure these markets out. Let me buy and sell.' And that is usually going to contribute to the bubble's momentum and also cost them money."

One of the most innovative parts of the study involved using a new mathematical formula for detecting unusual activity in the trading market. Unlike normal markets in which the mathematical distribution of the arrival of "orders" (offers to buy or sell shares) follows a somewhat steady pattern, bubble markets display restlessness—with flurries of activity followed by lulls. The researchers looked to see if any brain regions showed signs of tracking this unusual distribution of orders during bubble markets. And they found a strong association with the dmPFC and vmPFC. Heightened activity in these prefrontal regions, the team suspects, is a sign that participants are more likely to ride the bubble market, perhaps because they subconsciously believe that there are insiders with extra information operating within the market.

Another of the paper's senior authors, Peter Bossaerts, completed the work at Caltech and is now at the University of Utah. He explains: "It's group illusion. When participants see the inconsistency in order flow, they think that there are people who know better in the marketplace and they make a game out of it. In reality, however, there is nothing to be gained because nobody knows better."

The research could eventually help in the design of better social and financial interventions to avoid the formation of bubbles in financial markets, as well as methods for individual traders and brokers to manage their trading better.

The Neuron paper is titled "In the Mind of the Market: Theory of Mind Biases Value Computation During Financial Bubbles." Along with Camerer, De Martino, and Bossaerts, additional Caltech coauthors are John O'Doherty, professor of psychology, and Debajyoti Ray, a graduate student in Computation and Neural Systems. The work was supported by a Sir Henry Wellcome Postdoctoral Fellowship, the Betty and Gordon Moore Foundation, and the Lipper Family Foundation.

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Kimm Fesenmaier
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Caltech to Offer Online Courses through edX

To expand its involvement in online learning, the California Institute of Technology will offer courses through the online education platform edX beginning this October.

The edX course platform is an online learning initiative launched in 2012 by founding partners Harvard University and the Massachusetts Institute of Technology (MIT). Caltech's rigorous online course offerings will join those of 28 other prestigious colleges and universities in the edX platform's "xConsortium."

This new partnership with edX comes one year after Caltech offered three courses through the online learning platform Coursera in fall 2012. The Institute will now offer courses through both platforms.

"Coursera and edX have some foundational differences which are of interest to the faculty," says Cassandra Horii, director of teaching and learning programs at Caltech. Both organizations offer their courses at no cost to participating students; edX, however, operates as a nonprofit and plans to partner with only a small number of institutions, whereas Coursera—a for-profit, self-described "social entrepreneurship company"—partners with many institutions and state university systems.

The two platforms also emphasize different learning strategies, says Horii. "Coursera has a strong organizational principle built around lectures, so a lot of the interactivity is tied right into the video," she says. Though edX still enables the use of video lectures, a student can customize when he or she would like to take quizzes and use learning resources. In addition, edX allows faculty to embed a variety of learning materials—like textbook chapters, discussions, diagrams, and tables—directly into the platform's layout.

In the future, data collected from both platforms could provide valuable information about how students best learn certain material, especially in the sciences. "Caltech occupies this advanced, really rigorous scientific education space, and in general our interest in these online courses is to maintain that rigor and quality," Horii says. "So, with these learning data, we have some potential contributions to make to the general understanding of learning in this niche that we occupy."

Even before joining edX and Coursera, Caltech had already become an example in the growing trend of Massive Open Online Courses (MOOCs). Yaser Abu-Mostafa, professor of electrical engineering and computer science, developed his own MOOC on machine learning, called "Learning from Data," and offered it on YouTube and iTunes U beginning in April 2012.

Since its debut, Abu-Mostafa's MOOC has reached more than 200,000 participants, and it received mention in the NMC Horizon Report: 2013 Higher Education Edition—the latest edition of an annual report highlighting important trends in higher education. The course will be offered again in fall 2013 on iTunes U, and is now also open for enrollment in edX.

Although Caltech is now actively exploring several outlets for online learning, the Institute's commitment to educational outreach is not a recent phenomenon. In the early 1960s, Caltech physicist Richard Feynman reorganized the Institute's introductory physics course, incorporating contemporary research topics and making the course more engaging for students. His lectures were recorded and eventually incorporated into a widely popular physics book, The Feynman Lectures on Physics, which has sold millions of copies in a dozen languages.

Continuing in the tradition set by Feynman, the MOOCs at Caltech seek to provide a high-quality learning environment that is rigorous but accessible. "No dumbing down of courses for popular consumption . . . no talking over people's heads either; at Caltech, we explain things well because we understand them well," adds Abu-Mostafa.

More information on Caltech's online learning opportunities is available on the Online Education website.

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Friday, October 4, 2013

Undergraduate Teaching Assistant Orientation

Thursday, September 26, 2013

Graduate TA Orientation & Teaching Conference

Psychology Influences Markets

When it comes to economics versus psychology, score one for psychology.

Economists argue that markets usually reflect rational behavior—that is, the dominant players in a market, such as the hedge-fund managers who make billions of dollars' worth of trades, almost always make well-informed and objective decisions. Psychologists, on the other hand, say that markets are not immune from human irrationality, whether that irrationality is due to optimism, fear, greed, or other forces.

Now, a new analysis published the week of July 1 in the online issue of the Proceedings of the National Academy of Sciences (PNAS) supports the latter case, showing that markets are indeed susceptible to psychological phenomena. "There's this tug-of-war between economics and psychology, and in this round, psychology wins," says Colin Camerer, the Robert Kirby Professor of Behavioral Economics at the California Institute of Technology (Caltech) and the corresponding author of the paper.

Indeed, it is difficult to claim that markets are immune to apparent irrationality in human behavior. "The recent financial crisis really has shaken a lot of people's faith," Camerer says. Despite the faith of many that markets would organize allocations of capital in ways that are efficient, he notes, the government still had to bail out banks, and millions of people lost their homes.

In their analysis, the researchers studied an effect called partition dependence, in which breaking down—or partitioning—the possible outcomes of an event in great detail makes people think that those outcomes are more likely to happen. The reason, psychologists say, is that providing specific scenarios makes them more explicit in people's minds. "Whatever we're thinking about, seems more likely," Camerer explains.

For example, if you are asked to predict the next presidential election, you may say that a Democrat has a 50/50 chance of winning and a Republican has a 50/50 chance of winning. But if you are asked about the odds that a particular candidate from each party might win—for example, Hillary Clinton versus Chris Christie—you are likely to envision one of them in the White House, causing you to overestimate his or her odds.

The researchers looked for this bias in a variety of prediction markets, in which people bet on future events. In these markets, participants buy and sell claims on specific outcomes, and the prices of those claims—as set by the market—reflect people's beliefs about how likely it is that each of those outcomes will happen. Say, for example, that the price for a claim that the Miami Heat will win 16 games during the NBA playoffs is $6.50 for a $10 return. That means that, in the collective judgment of the traders, Miami has a 65 percent chance of winning 16 games.

The researchers created two prediction markets via laboratory experiments and studied two others in the real world. In one lab experiment, which took place in 2006, volunteers traded claims on how many games an NBA team would win during the 2006 playoffs and how many goals a team would score in the 2006 World Cup. The volunteers traded claims on 16 teams each for the NBA playoffs and the World Cup.

In the basketball case, one group of volunteers was asked to bet on whether the Miami Heat would win 4–7 playoff games, 8–11 games, or some other range. Another group was given a range of 4–11 games, which combined the two intervals offered to the first group. Then, the volunteers traded claims on each of the intervals within their respective groups. As with all prediction markets, the price of a traded claim reflected the traders' estimations of whether the total number of games won by the Heat would fall within a particular range.

Economic theory says that the first group's perceived probability of the Heat winning 4–7 games and its perceived probability of winning 8–11 games should add up to a total close to the second group's perceived probability of the team winning 4–11 games. But when they added the numbers up, the researchers found instead that the first group thought the likelihood of the team winning 4–7 or 8–11 games higher than did the second group, which was asked about the probability of them winning 4–11 games. All of this suggests that framing the possible outcomes in terms of more specific intervals caused people to think that those outcomes were more likely.

The researchers observed similar results in a second, similar lab experiment, and in two studies of natural markets—one involving a series of 153 prediction markets run by Deutsche Bank and Goldman Sachs, and another involving long-shot horses in horse races.

People tend to bet more money on a long-shot horse, because of its higher potential payoff, and they also tend to overestimate the chance that such a horse will win. Statistically, however, a horse's chance of winning a particular race is the same regardless of how many other horses it's racing against—a horse who habitually wins just five percent of the time will continue to do so whether it is racing against fields of 5 or of 11. But when the researchers looked at horse-race data from 1992 through 2001—a total of 6.3 million starts—they found that bettors were subject to the partition bias, believing that long-shot horses had higher odds of winning when they were racing against fewer horses.

While partition dependence has been looked at in the past in specific lab experiments, it hadn't been studied in prediction markets, Camerer says. What makes this particular analysis powerful is that the researchers observed evidence for this phenomenon in a wide range of studies—short, well-controlled laboratory experiments; markets involving intelligent, well-informed traders at major financial institutions; and nine years of horse-racing data.

The title of the PNAS paper is "How psychological framing affects economic market prices in the lab and field." In addition to Camerer, the other authors are Ulrich Sonnemann and Thomas Langer at the University of Münster, Germany, and Craig Fox at UCLA. Their research was supported by the German Research Foundation, the National Science Foundation, the Gordon and Betty Moore Foundation, and the Human Frontier Science Program.

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Marcus Woo
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Wednesday, May 8, 2013
Dabney Hall, Lounge – Dabney Hall

Free jazz demonstration and concert

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