(Weight-) loss aversion and other stories

Christmas is coming…then New Year…a time for excesses and for making (usually ineffective) pledges to quit smoking, lose weight, take more exercise, and whatever else feels “appropriate” at that time of year.  With me, it’s generally about stopping smoking, but if I’m honest I probably gave up on that one long long ago.  Most smokers have been there… midnight comes on New Year’s Eve, the cigarettes go in the dustbin, good intentions perhaps – but we’re invariably in the garbage by 1am, fishing out the now-soggy cigarette packet and thinking “maybe next year instead”…   Procrastination rules ok!

In behavioural economics, the concept of loss aversion is quite well known, of course.  Kahneman and Tversky were probably the first to demonstrate experimentally that we will pretty much always favour a £5 discount to a £5 surcharge, even if the overall outcome is economically the same.  Can this tell us anything useful in terms of our New Year resolutions, though?

As this recent post from Talya Miron-Shatz at Princeton shows, loss aversion can be a really useful concept to know about at this time of year.  Most of us try to reward ourselves for sticking with a new behaviour, such as staying off the cigarettes or taking more exercise to lose weight.  If we don’t want our resolutions to go out of the window, however, it seems we should really be focusing on setting up ways we could incur losses if we don’t get off that sofa and jog!

I could be biased, but…

Whenever I introduce students to the world of behavioural economics, I typically start with heuristics and biases as a fun way into the subject.  It’s wonderful to see the reaction of a group of MBAs when they find their Student IDs really do correlate with their bids in an auction of random junk from my office, for instance, or to see a seminar discussion descend into chaos when one lone voice just refuses to accept that the odds of this week’s lottery numbers being the same as last week’s are no greater than for any other random combination of balls dropping from the machine.

Invariably, I’m asked about other biases to the “old staples” I cover each time and to recommend a good accessible source students can use to explore the subject further.  Ok, there are quite a few good texts out there and I’d probably stick to one of Dan Ariely’s books as a starting point for the behavioural economics virgin.  Recently, though, I came across this little gem from the guys over at Psy-Fi.  Aptly named the Big List of Behavioral Biases, this neat no-frills resource covers all the usual stuff (anchoring, halo effects, the Monty Hall problem) and more in a series of very reader-friendly bite-size chunks.