Brexit and Trump provided plenty of fodder for the behavioural science community. I enjoyed reading the multiple, diverse explanations that people offered to explain these events [1], [2], [3], [4], and many more.
Despite none of these behavioural science explanations being the complete and correct story, I found Heintz’s explanation quite compelling [5]. He refers to Kahneman and Tversky’s Prospect Theory [6].
Heintz reminds us that Prospect Theory explains both risk avoiding and risk seeking behaviour. People’s risk attitude depends on whether they consider themselves to be in a state of gain or a state of loss. In a state of gain, people are risk averse, e.g. most people would rather take $900 as a sure thing, than bet where there is a 90% chance of winning $1,000 or 10% chance of winning nothing. In a state of loss, people are risk seeking, e.g. if they stand to lose $900, most people would rather take the bet that gives them a 10% chance of fully recovering their losses or a 90% chance of losing $1,000, than settling for a sure loss of $900.
How does this relate to Brexit and Trump? Heintz explains: “The political discourses of the Trump and Brexit advocates have framed the stakes in terms of losses rather than gains. The slogans ‘Make America great again’ and ‘Take back control’ clearly refer to the lost grandeur of the past. This sets the reference point as a lost state that was much better than the current one. […] this motivates citizens to favour risky options [5]”.
Prospect Theory also explains situations where the outcome is a mere possibility (say 10%) rather than a near certainty (say 90%, like the above examples). In these cases, our behaviour switches to risk seeking for gains and risk averse for losses.
So, how do people behave when the chances are 50/50? Numerous studies have shown a clear demonstration of loss aversion, not just in the lab, but in field settings too. A superb example is the robust review of 2.5 million golf putts where the researchers show that even the world’s top professional golfers putt more accurately for par (i.e. to avoid a bogey) than for a birdie [7].
I see evidence of loss aversion first-hand when I run workshops on Strategic Decision Making. I ask participants (typically there are about 30 at a time) to pick the smallest number for which they would be willing to enter a fair coin toss bet. The bet is that if they lose, they pay me $1,000 and if they win I pay them the number that they have selected. The smallest numbers for which people are willing to enter into the bet generally range from even money, i.e. $1,000 on a win, to $10,000 or even more sometimes. Yes, everyone ultimately has a price! Note that the participants could all afford to lose $1,000, but at the same time it will hurt a lot, i.e. they are quite well off, but are not super-wealthy. Irrespective of the range, the median value is always between $2,000 and $3,000. In other words, consistent with the predictions of loss aversion, losses loom larger than gains, two to three times larger.
Just more theory, or does this really matter?
Well, if the Brexit and Trump explanation does not convince you that it matters, then perhaps this investment story will hit closer to home. Thaler, in his recent book “Misbehaving” [8], describes a situation where he conducts a workshop with the CEO and 23 divisional heads of a diversified publishing company. Each of the 23 divisional heads could invest in a deal that has a 50% chance of making $2 million and a 50% chance of losing $1 million. These 23 deals would be independent of each other. Only 3 of the 23 executives said that they would invest. Thaler then asked the CEO, who had been sitting quietly in the background, how many of the investments he would like them to take and his answer, not surprisingly (since the expected value of each investment is a positive $0.5 million), was all 23. The executives explained that their reluctance was based on weighing up the prospect of a bonus (should they make the $2m) or possibly being fired (should they lose $1m). In loss aversion speak, their assessment of the consequence of a good outcome was not large enough to offset their assessment of the consequence of a bad outcome.
While this illustrates loss aversion, it is also a stark reminder of the importance of rewarding good effort, not outcome – see [Reward good effort, not outcome].
References:
[1] https://www.linkedin.com/groups/112700/112700-6208365621508481027
[2] https://hbr.org/2016/11/blindsided-by-trumps-victory-behavioral-science-explains
[3] http://www.rawstory.com/2016/08/a-neuroscientist-explains-what-may-be-wrong-with-trump-supporters-brains/
[4] https://www.research-live.com/article/opinion/cognitive-biases-that-made-us-brexit/id/5009472
[5] http://cognitionandculture.net/blog/christophe-heintzs-blog/does-prospect-theory-explain-trump-and-brexit-votes
[6] https://en.wikipedia.org/wiki/Prospect_theory
[7] http://faculty.chicagobooth.edu/devin.pope/research/pdf/Website_Golf.pdf
[8] “Misbehaving: The Making of Behavioral Economics”, Richard Thaler