Decision Science News

AUTOMATIC INDIVIDUAL RETIREMENT ACCOUNTS

The New York Times has an interesting article called Savings Accounts for All: Simple but not Easy, which talks of the Obama administration’s plans to set up an automatic IRAs (Individual Retirement Accounts) for workers in the USA.

This is clearly policy in the behavioral economics / Nudge tradition, which is no surprise as Nudge author Cass Sunstein will be named head of the Office of Information and Regulatory Affairs in the present administration. The article even mentions research on the effects of autoenrollment, though it would have been nice had the NYT named the academics who carried out the research. Since the article does not, Decision Science News will give some citation love here:

• Brigitte C Madrian & Dennis F Shea. (2001). The Power of Suggestion: Inertia in 401 (k) Participation and Savings Behavior. The Quarterly Journal of Economics, 116(4), 1149-1187.
• Richard H. Thaler & Shlomo Benartzi (2004) Save More Tomorrow Using Behavioral Economics to Increase Employee Saving. Journal of Political Economy, 112 (1, pt. 2), S164-S187.

SIDENOTE
On a sidenote, the article mentions that in the proposed plan “There would be a standardized default investment, probably some kind of mutual fund with a mix of stocks and bonds that gets more conservative over time.” Since many outside of Finance do not know this, Decision Science News would like to direct its readers’ attention to the fact that there is not universal agreement among academics that portfolios should get more conservative with age. Some think one ought to pick the right asset allocation and stick with it throughout life. See this clearly-written article for a review.

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Photo credit: Amazon.com

THE VALUE OF NOT FOLLOWING INSTRUCTIONS

As Shane Frederick has noted, if you say “A bat and a ball cost $1.10. The bat costs $1 more than the ball. How much is the ball?”, you will notice that the vast majority of your friends will say “10 cents” instead of the correct “5 cents”, because they don’t pay attention to the “more than the ball” bit. They assume you mean that the bat costs a buck.

But Decision Science News would like to pause and say a few words in defense of not listening to exactly what is said. What if we took instructions literally? If we did, when we got emails from British Airways saying “Your British Airways flight is moving to Heathrow Terminal 3” as their subject, we would actually believe that our recently booked British Airways flight (to Geneva) was moving to Heathrow Terminal 3. And we’d be wrong.

If we then went on to read that the change only affects flights to Barcelona, Nice, and three other cities where we are NOT going, we would be completely perplexed, thinking “How can my flight be moving and not moving at once? It’s impossible!” We’d panic. We’d call BA. But we don’t do any of that. We just shake our heads and think “Worst … subject line … ever”.

As Decision Science News reflects and tries to find cases in which it pays to be perfectly literal, it can’t. Even when dealing with computers, even when reading the output of statistical routines, one needs regularly to think “Ok, SAS (or R or STATA or SPSS) you say that, but we both know you don’t mean that.”

ALL ABOUT REVOLUTION COMPUTING’S R DISTRIBUTION

Decision Science News was intrigued by a company called REvolution Computing that got some attention of late for spinning their own mix of the R language for statistical computing and giving it away for free. So DSN asked to interview them to see what it’s all about

Decision Science News: So who are you guys and what is your scientific background?

REvolution: Well, at this point our team has grown and we have about 30 employees with diverse backgrounds, from bioinformatics to finance to core statistics and software engineering. However when we got started with REvolution, we were a group that had tremendous experience with high performance computing and building production software. Our first application with R was something called ParallelR , which enables users of R to seamlessly benefit from optimized performance by automatically running on multiple cores, servers, and clusters (we even have a cloud-based deployment). Our team today is a combination of employees and an extended community, from R community participants, to package developers, to researchers and related consultants.

Decision Science News: how did you get started working with R professionally?

REvolution: Traditionally our customers came to us for parallel computing solutions based in languages like C, Fortran, or Java. More and more we started to see pull from our customers toward scripting languages, and R in particular. Some of our pharma partners particularly were compelled by the proposition of optimizing the performance of R, and many of our first references are related to those applications (gene expression, classification, etc. [case study])

Decision Science News: What’s so great about your R compared to the regular download?

REvolution: Well, we’re not competing with the “regular” download – we actively collaborate with the core team, and utilize the codebase. What we have done is on several fronts. First, we have added capability and functionality related to optimization and high performance. Second, we are adding specific support for the 64-bit Windows platforms (and other more obscure OS distributions). Third, we are actively working on an IDE, large data handling, and other interesting capabilities (stay tuned!).

In addition to these aspects, we have packaged REvolution R into a commercially supported distribution around which we also provide training and consulting services. It’s a fully supported product in the same spirit as, say, RedHat Linux.

Decision Science News: Is there any risk that getting ‘locked in’ to your distribution of R? What if your distribution goes away, will our code still run on vanilla R?

REvolution: We prefer to say “mandatory customer loyalty” than lock-in. (KIDDING!) Of course, “open source” is a big part of “commercial open source,” and users of REvolution R can run their codebase on vanilla R.

HOW TO MAKE MORE REALISTIC ESTIMATES OF FUTURE BEHAVIOR

The Journal of Consumer Research is getting awfully good at getting articles picked up in the New York Times. The JCR Web site has directed our attention to an article by Robin Tanner and Kurth Carlson that looks people’s forecasts of their own future exercise behavior.

The gist is that when people answer a question like “how often will you exercise next week?”, they reply as if the question were “under ideal circumstances, how often will you exercise next week?”

Of course, most weeks aren’t ideal weeks, so if you are interested in getting a more accurate forecast of your own behavior in the future, it helps to be reminded of this.

So, how to use behavioral science to help yourself? When asked to make a forecast 1) generate an answer under ideal conditions, then 2) generate your forecast. Though you’d think the ‘ideal conditions’ would skew your forecast upwards due to anchoring, it does not. In fact, it causes you to generate more realistic forecasts of your own behavior.

(This reminds me of when I was running a seminar series and the visiting speaker asked me how long it would take to get from Columbia to Penn Station after the talk. I gave him my estimate, which he naturally believed was biased — some decision researchers think that everybody else is biased — and that it wouldn’t give him enough time. He demanded proof. So, I pulled up the train timetables from the MTA website and, sure enough, my estimate not only factored in waiting time and travel time, but also a generous buffer for the late trains. Being a nerd, I’d timed the trip perhaps 30 times and recorded it in my Palm Pilot; I live to make accurate forecasts. I was very close to replying “Dude. Like you, I decision-making biases for a living. I think I can give you a calibrated estimate of a trip I take every day.” But I held my tongue. –Ed).

Photo credit: http://flickr.com/photos/66535891@N00/2701310395/

PASSWORD CHART

Most of us use the same password for many sites. And most of us have thought that it would be a good idea to use different passwords for different sites. But then many of us fear that if we do this, we are tempting fate to forget or lose some of those passwords.

So, many of us have thought about making a different password for each site by combining some part of the site’s name with our standard password. So, for example, if your standard password is mypass123:

Your Gmail password might be mypass123_gmail and
your eBay password might be mypass123_ebay and
your Facebook password might be mypass123_facebook
(or perhaps something a bit less obvious)

This beats using the same password everywhere, but it is kind of clunky.

Along comes password chart. You can give it your standard password and enter the site for which you wish to have a password created. Out pops a much longer and more secure password than you would generate on your own.

The best part is that if you ever forget your strong password, you can go back to password chart, pop in the base password and the site name, and you’ve recovered your secure password. Easy!

Though these are browser-based tools, they do not send your password over the internet. You can even save the code to your local machine and run it offline if you’re doubtful. The code is free and open to inspect.

Here’s another tool that does basically the same thing: http://blog.tetrack.com/2009/02/too-many-passwords/

SUMMER WORKSHOP ON DECISION NEUROSCIENCE

The University of Michigan’s Ross School of Business and INSEAD will jointly host a Summer Workshop entitled “Decision Neuroscience: How Neuroscience Can Inform Behavioral Decision Making Research – Overview, Methods & Applications”.

The workshop is co-organized by Jim Bettman, Joe Kable, Hilke Plassmann and Carolyn Yoon, and will be held in Ann Arbor, Michigan from August 21-23, 2009.

The aim of the workshop is to provide an introduction to the field of decision neuroscience/neuroeconomics for graduate students interested in neuroscience and behavioral decision making, with a particular focus on those interested in marketing and consumer behavior. The workshop will feature lectures and presentations by top researchers in fields related to decision neuroscience, and will also provide opportunities for networking and discussions among faculty and students.

Applications are due February 23, 2009.

If you’re interested in more information, please see
http://www.bus.umich.edu/Conferences/DecisionNeuroscience

Photo credit: http://flickr.com/photos/jacobkearns/318221213/sizes/m/

ELKE WEBER TO SPEAK IN LONDON JAN 27, 2009

Those who will attend tomorrow’s Economics of Behaviour and Decision Making Seminar Series are in for a treat as Elke Weber, of Columbia University’s Psychology Department and Graduate School of Business, will present “When do we want it? Now! A Query Theory process account of Intertemporal Choice.”

Tuesday January 27th, 2009
Location: Westminster Business School seminar room MR2
Time: 17h30-19h00

Abstract
Psychologists and behavioral economists agree that many of our preferences are constructed, rather than innate or pre-computed and stored. Little research, however, has explored the implications that established facts about human attention and memory have when people marshal evidence for their decisions. This talk provides an introduction to query theory, a psychological process model of preference construction, and uses it to explain a range of phenomena in intertemporal choice, including our impatience when we are asked to delay consumption. Behavioral data in combination with neuroscience evidence (fMRI and TMS) will be provide support for query theory’s assumptions about the processes underlying intertemporal preference construction.

A paper on the theory can be found here.

Londoners who are not hip to the Economics of Behaviour and Decision Making Seminar Series can join the email list by visiting http://tinyurl.com/yvw2sr to opt in. You can easily unsubscribe anytime. Please pass this message on to those who may be interested in joining the email list.

DESIGNING FOR BETTER HEALTH

Richard Thaler writes

The Robert Wood Johnson Foundation is sponsoring a contest to come up with ideas for improvements in choice architecture, or “nudges”, that can improve health, broadly defined. You can find a description of it on our nudging blog or at http://www.changemakers.net/en-us/designingforbetterhealth

This initiative might be interesting to JDMers at two levels. First, it is a contest to come up with ideas of the sort that JDMers are good at so feel free to enter. Second, the idea of using a contest to generate solutions to societal problems is of interest in and of itself. The prizes for the winners are nominal, $5000, (unlike the X prize, for example), but the Foundation has funds to pour significant resources behind winning ideas. So the idea is that you can get lots of clever people to think about an important problem by dangling a modest bit of fame and fortune and you might come up with something that could change the world. Cool huh?

Read about it on the Nudge blog
Read about it on the Robert Wood Johnson Foundation site
Read about it at the Changemakers site

They have some nice tips on designing nudges in the articles How To Nudge and Nudge Your Customers Toward Better Choices.

NEW YORK TIMES STORY ON THE APPEAL OF R

(click to view movie)

It is no secret that Decision Science News is crazy about the R language for statistical computing. Find out why R is so great in this New York Times article. Then start to teach yourself R with our short series of video tutorials.

• Decision Science News R Video Tutorial Number 1
• Decision Science News R Video Tutorial Number 2

Addendum: Check out the hordes of R supporters in this comments of this Freakonomics blog post, correcting an assumption by Ayers that happens to be 180 degrees in the wrong direction.

Animation credit: Friend of Decision Science News Yihui Xie.

JDM TALKS AT THE SOCIETY FOR MEDICAL DECISION MAKING CONFERENCE

The 2008 annual meetings of the Society for Judgment and Decision Making (SJDM) and the Society for Medical Decision Making (SMDM) included a “symposium exchange.” A symposium by SJDM members was presented at SMDM 2008 (Pennsylvania, PA) and a symposium by SMDM members was presented at SJDM 2008 (Chicago, IL). Support for these symposia was provided by the National Science Foundation (grants SES-0817831 and SES-0820329 to Alan Schwartz and J. Sanford Schwartz).

Click here to watch the talks, featuring JDMers Hal Arkes, Benjamin Djulbegovic, Elke Weber, Anirban Basu, Joe Johnson, Leslie John & Valerie Reyna.

Also, if you like things that are animated (and who doesn’t) you may get a kick of participating in this interactive experiment on retirement income by Issac Gonzalez and William Sharpe. Internet Explorer only (I know, I know…).