Move over, Behavioral Economics: Hello, Emotional Finance
by Ignacio Mas, CEME Senior Fellow & Academic Director for the Certificate in Digital Money
Our brains are imperfect calculating machines: who could argue otherwise? There are cognitive biases galore: I get that. So psychology matters: sure.
But I have always had a hard time with run-of-the-mill behavioral economics, which portrays these cognitive biases as deviations from the straight path, as disturbances from some kind of ideal rationality that people need to be somehow brought back (or nudged) towards. Through trickery, if necessary: framing, setting defaults, etc. Your psychology is your problem; we can save you from yourself. If only one could find the mental switch that finally makes you want to care appropriately about the future and save…
The behavioral economics industry is having a field day with financial inclusion, and development more broadly. It comes down to this: how can we help poor people be and act more like us, or at least more like the person we wish we were? This smacks of the kind of paternalism that development economists have always had a hard time escaping. But before rejecting this approach, we need to understand two things: whether it is the case that poor informally employed people are often less rational, and if so, whether this makes them more vulnerable to their own psychology.
Gigerenzer, unlike me a bona fide academic psychologist, provides clues as to when people will be better served by deciding instinctively on the basis of unexamined, information-poor, bias-ridden heuristics (Kahneman’s system 1) rather than using the more deliberate, analytical mental processes, which can draw more fully on available information (system 2).
There are two key differences in the living conditions of poor people that make it so. First is that their perception of the future is much more filled with uncertainty (unknown outcomes on which they have little probabilistic handle – unknown unknowns) than with risk (unknown outcomes with reasonably assessable probabilities – known unknowns). Their livelihoods may be in farming, subject to (to them) unfathomable weather patterns and international price oscillations. Severe illnesses are more likely to be caught late or to be misdiagnosed, triggering unexpected chain reactions, and can more easily overwhelm their means. If you deal with uncertainty, if you don’t have a basis for modeling future outcomes, trying to process all available information is often counterproductive: intuitive decision-making based on a few key parameters is often better.
Second, for poor informally employed people, practically every monetary transaction comes with new information. Today I had a good day: I made two extra dollars. Whereas for the salaried, new relevant financial information is much more infrequent – the annual performance review and promotion cycle. Richer folk’s income is more predictable, so they tend to develop preset spending patterns through budgets and many more routines that they can more easily stick to. So the financial lives of the informal poor are much more intense, involving constant, emotionally draining decision-making.
Much higher frequency of decision-making (think muscle control for walking), and a more precarious handle over the probability distribution of future outcomes (think white blood cells reacting to an invading foreign cell) – that’s precisely where automated decision-making works best (which is why our motion and immune systems don’t depend on our explicit cerebral decisions). So moving poor people into a more deliberate thinking mode for their day-to-day money management that requires a more exhaustive review of all possibilities may be counterproductive.
For all their acceptance of imperfect agents and hence markets, models of behavioral economics feel as static and deterministic as all economic theories that have come before. In contrast, the new field of Emotional Finance places a much stronger emphasis on how varying mental states, rather than just genetically propagated fixed mental biases, can affect thinking processes. How we tell ourselves shifting stories to emotionally glue together our subjective assessment of reality, the dissonant objective facts that squeeze through our selective perception barriers, and our beliefs about imagined futures. How individual narratives get confronted and reinforced by those of others, and how they can drive group-think. From this follows: finance as markets for varying moods and emotional stories. (Read Tuckett for a full jargon-ridden elaboration)
This literature developed around an exploration of how traders and portfolio managers make investment decisions, in an attempt to explain the set of extreme behaviors that led to the global financial crisis. The answer, in a nutshell: traders and investors get emotionally vested on narratives that helped them support their investment positions.
What should big shot, sophisticated traders in plush offices in global financial centers have in common with poor people everywhere? Well, trading is fundamentally about betting on future sentiment, which is inherently filled with unknowable outcomes and probabilities. And when you have a large trading position, you are (at least implicitly) in a position of constantly having to decide on it – if only to leave the position intact. Uncertainty and constant decision-making: the two circumstances that render the use of analytical, data-intensive decision-making ineffective, if not counterproductive. Just like poor people going through their daily lives.
Does this make traders’ seemingly irrational actions OK then? Absolutely not. The point is that no amount of looking at historical data charts and rocket science modeling helped them either. We are not going to solve the perennial problem of investor exuberance by developing fancier financial models, or by manipulating traders’ mental switches (for rationality, risk-taking, greed) so that they can get more true meaning out of the existing data. Instead, there may be a policy role in influencing broad narratives, beyond setting incentives through regulation and policing behaviors through supervision.
If exploring narratives is a useful way of understanding the dynamics of global financial markets, it is at least worth giving it a try to understand the financial habits of poor people. This emotional, narrative-based understanding of how people make decisions may be a much more fruitful source of inspiration for the development of financial products than the kind of paternalistic nudges that behavioral economics has spawned. Think of financial discipline as a process of reinforcing your money stories, of building people’s emotional resilience across mental states.
I wasn’t aware that this was the journey I was on when I worked on collecting people´s money stories (in collaboration with Kim Wilson of The Fletcher School) or creating a narrative-based sketchbook of common coping strategies (with the support of CGAP´s Customers at the Center team). I am sure that Emotional Finance experts would shudder at my clumsy use of psychological terms and concepts, but now I find it emotionally satisfying knowing that I am back in the fold of a New Label.
Ignacio Mas is a former economist and currently the Academic Director for the Certificate in Digital Money, a course offered by the Fletcher School in partnership with the Digital Frontiers Institute. Dr. Mas is also CEME Fellow, Institute for Business in a Global Context, the Fletcher School.