Decision Science News

DECISION SCIENCES TENURE TRACK JOB AT IESE

Spain has some of the finest decision scientists anywhere. Consider living the good life and applying for the following post.

The Decision Sciences department at IESE Business School (Barcelona) invites applications for a tenure track position (assistant professor level). Applicants should have a research interest in managerial decision making, broadly defined, and show ability do mathematical modelling as well as experimental research work. IESE is an international business school with top-ranked MBA and executive programs. The school has campuses in Barcelona and Madrid, and offers regular programs in Munich and Sao Paulo.

Interested candidates should send a cv, research statement, and representative paper/s by E-mail to mbaucells at iese.edu. Candidates should also arrange for two or three letters of recommendation to be sent separately. Review of materials will begin on May, 5th, 2006, and will continue until the position is filled.

ASSESSING RISK TOLERANCE WITH A SIMPLE GAMBLE

Want to estimate risk tolerance with just one question? Thanks to Bob Clemen who has written a nice piece about it in the Decision Analysis Newsletter, and to the SJDM mailing list, here’s the one question:

“Suppose you face a gamble where you can win $x with probability 0.5 or lose $x/2 with probability 0.5. What is the largest x for which you would be just willing to take this gamble? I’m looking for the largest x that makes you just indifferent between taking the gamble or not.”

In Clemen’s book Making Hard Decisions, in the solutions manual, he gives a derivation of how to get from the respose to that question into an estimate of the risk tolerance parameter R in the exponential utility function U(x) = 1-exp(-x/R).

Another way to estimate risk tolerance is using the Distribution Builder

WHO TALKS TO WHOM: INTRA- AND INTERDISCIPLINARY COMMUNICATION OF ECONOMICS JOURNALS

A talk by Jeffrey Pfeffer currently touring the world cites some stats from Who Talks to Whom? Intra- and Interdisciplinary Communication of Economics Journals, a 2002 paper by Rik Pieters and Hans Baumgartner:

” * 90% of citations in economics is intradisciplinary
* The 5 economics journals studied made no citations to management, marketing, anthropology, or psychology journals
* Economics is cited 4333 times by its sister disciplines between 1995 & 1997, while economics cites other disciplines (mostly finance at 79%) 601 times”

ABSTRACT of Pieters and Baumgartner:
Citation patterns between 42 journals in economics from 1995 to 1997 are examined, plus between economics and anthropology, political science, psychology, sociology and five business disciplines. Building on social network theory, we identify a hierarchical organization of journals in economics and seven journal clusters. Major citation flows are found from all areas of economics to the general interest and theory and method clusters, but not the other way around. Economics emerges as a significant source of interdisciplinary knowledge for the other social sciences and business. However, no area of economics appears to build substantially on insights from its sister disciplines.

Also note this recent piece in Foreign Policy by Moisés Naím suggest economics is overly inward gazing given its limited ability to preform its bread and butter task of forecasting the future(a point also made in a forthcoming book by Nassim Taleb).

AUTHORS:
Jeffrey Pfeffer
Rik Pieters
Hans Baumgartner

R STATISTICAL LANGUAGE MULTI-SITE SEARCH

Image (C) R Foundation, from http://www.r-project.org

Decision researchers and fellow bloggers Jon Baron and Andrew Gelman are big fans and supporters of the R project for statistical computing.

Searching for information on R can be difficult (though Baron’s R search tool is a great help), so DSN has put together a search widget that only queries R sites:

R Statistical Language Multi-Site Search

Simply click the image above to search and see the results from many sites. Sites searched include:

finzi.psych.upenn.edu
cran.r-project.org
wiki.r-project.org
lib.stat.cmu.edu/S
lib.stat.cmu.edu/R
tolstoy.newcastle.edu.au/R

and DSN welcomes suggestions for additions and deletions.

INFORMATION SCIENCE

When DSN was visiting Stanford’s Department of Management Science and Engineering in the late 90s, it was called “Engineering-Economic Systems and Operations Research”. A change for the better, no? One thing that hasn’t changed is the excellence of the people there.

We just got our copy David Luenberger’s new Information Science. Not only is it a handsome book (big but not heavy, with cottony paper), it’s like an entire college education on a field you never knew existed, looking at everything from file compression to marketing to microeconomics through one beautiful framework set forth by Claude Shannon in 1949. It includes a nice Shannon quote, from 1953:

The first [method] I might speak about is simplification. Suppose that you are given a problem to solve, I don’t care what kind of problem—a machine to design, or a physical theory to develop, or a mathematical theorem to prove or something of that kind—probably a very powerful approach to this is to attempt to eliminate everything from the problem except the essentials; that is, cut it down to size. Almost every problem that you come across is befuddled with all kinds of extraneous data of one sort or another; and if you can bring this problem down into the main issues, you can see more clearly what you are trying to do an perhaps find a solution. Now in so doing you may have stripped away the problem you’re after. You may have simplified it to the point that it doesn’t even resemble the problem that you started with; but very often if you can solve this simple problem, you can add refinements to the solution of this until you get back to the solution of the one you started with.

Luenberger comments “Shannon’s approach of abstraction to an essence should become clear as we study his contributions throughout this text. His work is a testament to the power of the method.”

REFERENCE:
Shannon, Claude E. Creative Thinking. Mathematical Sciences Research Center, AT&T, 1993.

WEB EXPERIMENTS MUST BE GOOD WEB SITES

To do a good web-based experiment, a researcher needs to keep the drop-out rate as low as possible. Good Web design is key to getting people to take experiments seriously and to finish what they start. By encouraging good coding practices, it also improves cross-platform and cross-browser performance.

DSN likes the simple heuristics-based approach of the book Defensive Design for the Web by 37signals, Matthew Linderman, and Jason Fried, which contains 40 practical guidelines for how to improve a site.

VISUAL LEAST SQUARES

(Click on the image to interact with the tool)

Back when the DSN editor was a student at Chicago, he learned Statistics and History of Statistics from Steve Stigler, who proposed a visual demonstration of least squares regression. Together they came out with a now-obsolete Mac version. Today, DSN is proud to announce a version that will run on any browser that does Flash.

The demonstration should be self-explanatory to anyone who understands simple regression, and if not, might suffice as a tutor. And if not, there is always the linear regression article in Wikipedia.

FAQ

Can I use this to teach my class?

Yes, and please let us know how it goes! A benefit of the web-based version is that it can be reached from any place with a Web connection. This program is made available through a Creative Commons License (Attribution-NonCommercial-NoDerivs) which means that you are welcome to use it for non-commercial purposes.

Can you make a convenient URL for this tool?

Yes, how about http://www.dangoldstein.com/regression.html

RUNAWAY POPULARITY EFFECTS IN MUSIC DOWNLOADING

Back when DSN was headquatered at Columbia, it helped out a bit with Matt Salganik and Duncan Watts’ project on runaway popularity effects in music downloading. The paper is now out in Science (vol 311, page 854): Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market.

It’s a fascinating look at how popularity breeds popularity in a controlled but realistic setting with an enormous sample size of over 14,000 people. Have a read.

Quote
“One explanation for the observed inequality of outcomes [in cultural markets] is that the mapping from quality to success is convex (i.e., differences in quality correspond to larger differences in success), leading to what has been called the superstar effect, or winner-take-all markets. Because models of this type, however, assume that the mapping from quality to success is deterministic and that quality is known, they cannot account for the observed unpredictability of outcomes. An alternate explanation that accounts for both inequality and unpredictability asserts that individuals do not make decisions independently, but rather are influenced by the behavior of others”

Books by Duncan Watts
* Small Worlds
* Six Degrees

ANNOUNCING THE JUDGMENT AND DECISION MAKING JOURNAL

Jon Baron has announced A new online journal for judgment and decision making.

A new journal is always a risk. If people will read it and cite it, submitting there now is wise. If nobody will read it or cite it, submitting there now is foolish.

In an exclusive interview, DSN asked Jon Baron the following questions :

Before a journal has a reputation, what should one do? Submit early? Or wait and see? If you submit early, you may have good chances of getting in, and your article may get great exposure if the journal succeeds, but if the journal fails, your article may slip into oblivion. If you wait and see before submitting, and others do too, the journal will surely fail.

What makes this journal a safe bet? I believe that unlike most journals, this one will be reachable by search engines, so articles there may get more exposure than one in a traditional journal.

Jon Baron replies:

“I think there are a few answers about “why submit,” and I didn’t want to harp on some of them in a general post sent everywhere.

1. As you point out, this gets lots of exposure.

2. By going after short articles, we are looking for good ones that get rejected from Psychological Science, of which there are
many. There is no other outlet for these. Most main-line journals do not take short ones, e.g., with one experiment. Moreover, the Psychological Science review process has become slow, so it is a bigger risk to send things there, and you might want to try us first. (I don’t know if you should say the last thing. Say it if you agree with it, but perhaps don’t attribute it to me. It is, however, true.)

3. There are successful on-line journals of societies, e.g., the Journal of Vision (published by ARVO).

4. This seems to have a lot of support, as indicated by those who agreed to be on the board.

5. The usual journals (OBHDP and JBDM) have very low penetration and citation rates. This is, I think, largely because most institutional libraries do not get them. As a result, they don’t really count as “prestigious” when people come up for tenure. So there is little to lose. See the proposal for documentation.

In sum, yes, this is a risk, but I’m really not sure it is a very big risk. A publication in a refereed journal is, after all, a publication in a refereed journal. And our rejection rate will, I think, be high.”

STANFORD SUMMER SCHOOL IN NEUROECONOMICS 2006

This year’s Summer School in Neuroeconomics will take place July 17 – July 28, 2006 at Stanford. The application deadline is March 15th, 2006, so you’d better hurry.

The organizers inlcude Colin Camerer (Caltech), Paul Glimcher (NYU), and Antonio Rangel (Stanford). The aim of the Stanford Summer School in Neuroeconomics is to provide an introduction to the new field of neuroeconomics to graduate students and post-docs in neuroscience, psychology, and economics.

Part of the meeting will focus on “computational neuroeconomics”, which provides the unifying framework for the field, and a common language for the three related fields. This part of the program describes state-of-the art models of how the brain makes economic decisions (Which variables are computed? How are they computed? How do they interact with each other to generate choices?) The other part of the program covers several experimental techniques and their applications to neuroeconomics. The program also includes daily research talks by leading scholars in the field and a student project.

Graduate students and post-doctoral scholars in neuroscience, psychology, and economics are invited to apply. Those interested in attending the course should send the materials listed below by e-mail no later MARCH 15, 2006. 40 applicants will be selected and notified by email in mid-April, 2006.

For more information visit http://neuroeconomics-summerschool.stanford.edu/