A week of links

Links this week:

  1. An excellent Econtalk podcast with Jonathan Haidt. Just don’t buy his lines about group selection – my reasons here.
  2. Steven Pinker’s amusing article on the Ivy League. Pinker also pointed out this oldie but goodie – Bell Curve Liberals.
  3. Greg Clark applies his work on social mobility to immigration. Reihan Salam comments.
  4. A great swipe at “talent deniers”.
  5. Tracking supercentenarians.
  6. The agricultural origins of time preference – I’ll blog about this once I digest. HT: Tyler Cowen
  7. The cognitive gains from Head Start fade out by elementary school.
  8. I’m back into my habit of linking to Andrew Gelman articles every week – this time a great rant about expected utility titled “It’s as if you went into a bathroom in a bar and saw a guy pissing on his shoes, and instead of thinking he has some problem with his aim, you suppose he has a positive utility for getting his shoes wet

Nudging citizens to be risk savvy

I should start this review of Gerd Gigerenzer’s least satisfactory but still interesting book, Risk Savvy: How to Make Good Decisions, by saying that I am a huge Gigerenzer fan and that this book is still worth reading. But there was something about this book that grated at times, especially against the backdrop of his other fantastic work.

In part, I continue to be perplexed by Gigerenzer’s ongoing war against nudges (as I have posted about before), despite his recommendations falling into the nudge category themselves. Nudges are all about presenting information and choices in different ways – which is the staple of Gigerenzer’s proposal to make citizens “risk savvy”. Gigerenzer’s use of evidence and examples throughout the book also fall well short of his other work, and this is ultimately the element of the book that left me somewhat disappointed.

The need to make citizens risk savvy comes from Gigerenzer’s observation (which matches that of most of Gigerenzer’s faux adversaries – the behavioural scientists) that people misinterpret risks when they are presented in certain ways. If I say that screening reduces the risk of dying from breast cancer by 20 per cent, most people will interpret it to mean that 200 of every 1,000 people will be saved, rather than understanding that it means screening reduces the risk of death from 6 in 1,000 to 5 in 1,000 – effectively saving one out of 1,000.

Gigerenzer’s contribution to this area is to show that if presented in natural frequencies (i.e. tell people about the statistics as proportions of, say, 1,000 people), people are better able to understand the actual risks. This includes doctors, who are equally confused by statistics as everyone else, and who Gigerenzer suggests need training to communicate risks in ways that their patients can understand.

This ability to make citizens and experts risk savvy leads Gigerenzer to argue that people do not always need to be at the mercy of their biases. People can be educated to understand risks and experts can present them in ways that others understand. He advocates risk literacy programs in school, showing that simple decision tools can dramatically increase understanding of probability and statistics, although he spends little time discussing how well this education sticks. In making his point, Gigerenzer takes aim at the behavioural science crowd by claiming that natural frequencies won’t help if people are subject to cognitive illusions – a strawman argument. As he does at semi-regular intervals through the book, Gigerenzer clouds an interesting argument with an attempt to engage in a battle that doesn’t really exist.

That said, I did enjoy this part of the book and have found myself quoting a lot of the examples. His arguments about how to present risk are compelling. Further, it is enjoyable to read Gigerenzer’s evisceration of the presentation of risk by various high-profile cancer organisations.

There are parts of the book where Gigerenzer is more pessimistic about the ability to educate the masses, such as when he channels Nassim Taleb and berates the finance industry for not understanding the difference between risk and uncertainty. In a world of uncertainty – where we do not know the probability of events – simple rules often outperform more complex models that are overfitted to past data. This provides a natural entry point to Gigerenzer’s well-established work (and subject of some of his better books) on the accuracy of heuristics. Risk Savvy has plenty of additional advocacy for their use with Gigerenzer arguing that we can be trained to use useful heuristics in making better decisions. Gigerenzer covers areas from marriage (set your aspiration level and choose the first person who meets it) to business to the stability of financial institutions, building on decades of evidence he has accumulated on the accuracy of simple rules.

Gigerenzer’s heuristics don’t always match up with his optimism that we can make people risk savvy. One heuristic he suggests is: “If reason conflicts with a strong emotion, don’t try to argue. Enlist a conflicting and stronger emotion.” He also recognises the limits to education, with heuristics such as “don’t buy financial products you don’t understand.” But given that a lot of people don’t understand compound interest, we might need to rely on the Dunning-Kruger effect to allow people to follow this rule and still make any investments.

One interesting point made by Gigerenzer is that there is still a role for experts (and even consultants) in a world where we use simple heuristics. Suppose we replace our complex asset allocation models with a 1/N rule – allocate our assets equally across N choices. This still leaves questions such as the size of N, what we will include in N, or when you should rebalance. For many heuristics, there may be more complex underlying choices – although I imagine heuristics could be developed for many of these too.

Gigerenzer is also a stout defender of gut instinct – again, as covered in his other books. Gigerenzer suggests (and I agree) that data is often gathered due to a culture of defensive decision-making and not because data is the major reason in the decision. This is, however, the weakest area of the book, as Gigerenzer’s stories reek of survivorship bias. Gigerenzer notes that leading figures in business reveal in surveys that they rely on gut instinct and not data in making major decisions. But how many corpses who relied on gut instinct are strewn along the road of entrepreneurship?

As another example, Gigerenzer talks of a corporate headhunter who had put a thousand senior managers and CEOs into their positions. The headhunter said that nearly all the time he based his selection on a gut decision. He was now being replaced by tests by psychologists. Gigerenzer puts this down to a negative error culture, with the procedures designed to protect the decision makers. But what is the evidence that the headhunter has been good at their job and could outperform the psychologists armed with tests?  Similarly, Gigerenzer suggests listening to those with good track records in business. Again, survivorship bias could make this a useless exercise. When talking of predictions of exchange rates in other parts of the book, Gigerenzer effectively makes this very same point – the successful people you see in front of you could simply be the lucky survivors.

However, the evidence that Gigerenzer has developed in the past would make it folly for anyone in business to throw gut instinct out the window – or to completely discard Gigerenzer’s arguments. But the way he makes the case through Risk Savvy feels built on anecdote and weak examples.

There is one rule I am going to take away from the book – an extension of my usual habit of flipping a coin for decisions about which I’m indifferent. Gigerenzer suggests flipping a coin and as it spins, considering what side you don’t want to come up. He used this example in the context of choosing a partner, but it’s not a bad way to elicit that gut instinct that you can’t otherwise hear.

A week of links

Links this week:

  1. Two pieces on diet. First, an excellent article on how the poisons in vegetables might be making you stronger. Second, a new study in the fat-carb wars.
  2. Andrew Gelman on the strength of statistical evidence.
  3. Two excellent podcasts. Gregory Clark on social mobility (and the genetics behind it) and Paul Sabin on the Simon-Ehrlich bet. Some of my thoughts on Julian Simon are here and here.
  4. Economists are happier. The reasons? More cash and religion.

The biology of boom and bust

CoatesJohn Coates’s excellent The Hour Between Dog and Wolf: Risk Taking, Gut Feelings and the Biology of Boom and Bust tells the story of the effect of hormones on decision making in finance. By the end of the book, the idea that traders are rational calculating machines driven by their brains is torn apart.

As Coates shows, the divide between body and mind is not as Descartes or economists would have us believe. Signals travel both ways. The body can influence the brain. Physiological reactions triggered by pre-conscious regions of the brain affect emotion and mood. New to me was the existence of the enteric nervous system, which comprises around 100 million neurons in our gastrointestinal lining. It can operate autonomously of the central nervous system. Messages flow back and forth between the brain and enteric nervous system via the vagus nerve, the decisions of one affecting the decisions of the other.

The basic dynamic of decision making described by Coates involves the hormones testosterone, adrenalin, cortisol and dopamine. In anticipation of an opportunity on the trading floor, a trader’s hormones kick into action. Testosterone levels increase, bringing with it increased oxygen carrying capacity, confidence and appetite for risk. Adrenalin surges, quickening reactions and tapping into glucose deposits in the liver, which provides energy for the upcoming challenge.

Cortisol is also produced. Unlike the short-term action of adrenalin, cortisol acts over the longer term and stops metabolically expensive functions such as growth, reproduction, digestion or immune function. The initial release of cortisol also stimulates the release of dopamine, delivering a rush. Dopamine rewards us when we take actions that result in an unexpected reward. It makes us want to repeat and crave these actions (as a result, animals would rather work for food than simply be given it). Traders crave the rush of the floor.

When the trader has a win, his testosterone shoots up further. This testosterone infused trader will then take more risks. On average, more risk means more reward, so he earns higher profits. In fact, his testosterone levels in the morning are predictive of his afternoon profit. Hormones also make an appearance when this trader has a loss. His cortisol levels increase, decreasing his risk appetite and causing him to see danger everywhere.

The effects of biology are not only important for the people or firms involved, but can have systemic effects. Hormones exacerbate the market cycle. In a bull market, testosterone surges through the population of traders. Each takes larger and larger risks, pushing markets to new highs and triggering further cascades of testosterone. Irrational exuberance has a chemical base.

Similarly, in bear markets, cortisol levels peak. At the very time it might be best to buy, the market dries up as tentative traders retreat into their shells. Over the longer term, excessive cortisol impairs memory and causes anxiety.

As I mentioned in a previous post on an article by Coates, central banks could take this knowledge and use it to curb market cycles. In a bubble or crash, the population of traders could even enter a clinical state under the influence of pathologically elevated hormone levels. If that occurs, they could become insensitive to interest rates or other attempts by regulators to curb or control their activities.

Coates extends his idea to some interesting speculation on market cycles. Testosterone levels fluctuate over the year. In humans, they rise until autumn and fall through to spring. The drop in testosterone in autumn can cause males to suffer from ‘irritable male syndrome’. Given most major market crashes have occurred in October, is it autumn moodiness that takes stock markets down? Similarly, does ‘seasonal affective disorder, possibly also affected by testosterone, underlie underperformance between the autumn equinox and winter solstice?

For those in the industry, Coates offers advice on how to apply these findings, some relatively futuristic. We  can already record a range of physiological features, including hormone levels. Why not test them in the morning and set traders’ tasks or risk limits based on those measurements? We already have consumer products that perform real-time health monitoring. It is simply adding hormone levels to the suite of measures – although other measures such as heart rate, sweat levels and the like could also be useful indicators.

These physiological measures are probably better indicators than simply asking the traders how they are feeling. Whereas Coates found that hormone levels closely tracked the volatility of trading results and uncertainty in the market, surveys of these same traders about how stressed they were had almost no relationship to trading conditions, volatility or whether they were losing money.

Toward the end of the book, Coates includes some interesting material on how we might train our stress responses. One simple suggestion is exposure to acute stress, with those who have experienced moderate but short-lived stressors being toughened. In one study of rats, those rats exposed to stress when young had larger adrenal glands but a more muted response to stress. This was reflected in trader stress responses, with experienced traders having higher initial stress responses to events, but being able to quickly return to normal. However, once those stressors shift from being acute to chronic, problems begin. Exercise might also offer some protection, with sports science a potential source of new ideas.

One interesting piece of speculation is whether cold weather might provide useful training. Rats exposed to cold water have a quick arousal but quick recovery, with the stress response based more on adrenalin than cortisol. To the extent this occurs in humans, cold weather or water could be part of our training regime. Even more speculatively, Coates asks if the shift to more climate controlled environments has prevented a toughening of our psychological mechanisms, unlike that experienced by our ancestors.

An alternative to training could be to simply hire more women and older men who are less susceptible to testosterone feedback loops. However, I am not sure whether firms would want to implement this solution, with higher testosterone and risk taking leading to higher profits. The costs are across society when the crash comes and government steps in to lend a hand. Coates indicates this misalignment of incentives through the book, which suggests more than hiring policies are required.

One other interesting idea – only loosely linked to the major thesis – concerns fatigue. Fatigue might be seen as simply the result of running out of energy. But Coates points out a new model in neuroscience that suggests fatigue is a signal that the benefit from our current activity has dropped below its metabolic cost. It is a signal to stop the current search and start elsewhere. As a result, the cure for fatigue is a new task, not rest. Coates points to research suggesting overtime leads to hypertension and heart disease if we have no control over our attention, but otherwise it is not a problem. Flexibility in work could be as good as a vacation.

If I were to highlight one weakness of the book (more due to the state of the field than any fault of the author), it is that the foundation of studies on which it is built is fairly small, and largely based on data from a couple of trading floors. It would be great to see longitudinal data across a range of market participants during a number of cycles. Another potentially interesting extension would be to look at the hormone cycle in politics. Politicians can experience rational exuberance or appear to be exhibiting a constant state of panic. Are these the same biologically driven problems that Coates found in traders? Looking in new arenas such as this could provide a substantial contribution to our understanding of how humans make decisions.

A week of links

Links this week:

  1. Daniel McFadden on how people make choices.
  2. Not that new but only spotted this week – Gerd Gigerenzer has a great rants on statistics. (HT: Noah Smith)
  3. Forty per cent of modern Chinese are patrilineal descendants of only three super-grandfathers from 6,000 years ago. (HT: Carl Zimmer)
  4. Anti-marijuana advocates funded by drug companies.
  5. There were no associations between childhood family income and subsequent violent criminality and substance misuse once we had adjusted for unobserved familial risk factors.

Twin studies stand up to the critique, again

The history of twin studies is littered with attempts to discredit them – such as this bit of rubbish. Yet every challenge has been met, with a couple of newish studies knocking off another.

The basic idea of twin studies is that by comparing the similarity of fraternal twins to the similarity of identical twins, you can tease out the influence of their genes. Twin studies tend to find that most behaviours have heritability of at least 0.2 (that is, 20 per cent of the variation is due to variation in genotype), IQ a heritability of over 0.5 and height around 0.8. However, twin studies require an assumption that identical and fraternal twins have equally similar environments, and this is where the critiques begin. If identical twins have a more similar environment, the estimates of heritability may be too high.

The responses, however, are plenty. There are studies of twins reared apart. Adoption studies find similar results. For those who believe that identical twins are treated differently to fraternal twins, there are studies of misidentified twins – where everyone thought they were identical or fraternal, but they were the other. Peter Visscher and friends took advantage of the differences in relatedness between siblings to generate estimates of heritability consistent with twin studies (You are 50% related to your siblings on average, which means you can test how similarity varies with variation in relatedness . For me, that study should have been the final nail in the coffin of any arguments that twin studies hadn’t told us anything).

One critique still floating around is that people who look more similar are treated similarly (although the misidentified twin studies deal with this to a degree). And the New York Times has reported two studies that take on that argument. In the first, Nancy Segal assessed the similarity in personality of 23 pairs of unrelated lookalikes. The similarity – effectively zero. Then in a replication, Segal got a skeptic, Ulrich Ettinger, involved in the project. They found the same result – no resemblance – unlike Ettinger’s expectation that people who looked alike would have similar personalities as people would treat them the same.

As Razib points out, these studies involves a small sample. However, they are yet another piece of evidence pointing in the same direction as all the rest.

A week of links

Links this week:

  1. Side effect warnings increase sales by building trust. Similar effects for disclosing conflicts of interest (ungated pdf).
  2. Absorbing information on paper versus kindle. Even without digital search, I often find it easier to find favourite passages in the physical form.
  3. Humans aren’t the only ones fighting wars.
  4. I pointed out a couple of weeks ago that Geoffrey Miller had joined forces with Tucker Max to give sex and dating advice. Their reading list is very good, even if you’re not after any advice. Their suggestions as to which movies might provide insight is quite amusing.
  5. Twin research.