A week of links

Links this week:

  1. The Genetic Genealogist responds to Vox’s tabloid piece on genetic testing.
  2. Attempts to correct false claims often entrench them – the backfire effect. But telling politicians they will be fact checked still reduced their number of lies.
  3. Razib on heritability. Low heritability doesn’t make it easier to shape our children – once we’re above some minimum thresholds, we don’t really know what works.
  4. Tyler Cowen suggests the gender gap will close. I’m not so sure.
  5. Violence in chimps an evolutionary adaptation.
  6. Another study showing low social mobility. HT: Jayman
  7. A great collection of papers on altruism, reciprocity and the glucose model of self control.

Scarcity of time, money, friends and bandwidth

Sendhil Mullainathan and Eldar Shafir’s Scarcity: Why Having Too Little Means So Much is full of interesting insight and experimental results. It presents a novel way of looking at scarcity that extends beyond the typical analysis in economics, the original “science of scarcity”, and will certainly change the way I think about it.

But by the time I reached the end of the book, I was not entirely satisfied. I have plenty of new buzzwords and some interesting experiments to talk and think about, but I’m not convinced they have been presented with a coherent new perspective on how the world works. Scarcity reminded me of a Malcolm Gladwell book – I got presented with a lot of cool results, they were spun into an interesting narrative that has made me think, but I don’t buy the authors’ main message.

So first, to the buzzwords, which added to the Gladwell-esque feeling. Scarcity is having less time, money, friends or packing space than you feel you need (Note the subjective element – scarcity could be caused by relative rather than absolute scarcity. And it can apply across a range of domains). Scarcity can have good effects, such as the focus dividend when scarcity captures the mind. It can make us experts in the area in which we are scarce, with poor people better able to judge the value of a dollar saved despite the context in which it appears. However, scarcity also causes us to tunnel, which is to focus single-mindedly on the scarcity at hand, potentially at the neglect of more important or less timely demands. Scarcity also reduces bandwidth, a combination of  cognitive function and executive control. Scarcity imposes a bandwidth tax. When people suffer from scarcity and tunnel, they are also forced to juggle, as they move from one pressing task to the next. The way to avoid scarcity is to have some slack, an untapped budget we  can turn to in times of need.

The most salient example of the negative effects of scarcity comes from a study in a New Jersey mall. Mullainathan, Shafir and Jiaying Zhao presented people with a scenario where they need to fund some car repairs. They then gave the participants tests for fluid intelligence and cognitive control. When the cost of the repairs was $150, high and low-income people scored similarly in the tests. But when the shortfall was $1,500, the performance of the poor plunged – the equivalent of losing 13 or so IQ points. The authors point out that this result has been replicated many times, suggesting it is a robust result. By causing the poor to focus on their lack of resources through a high and potentially unmanageable repair bill, the poor’s bandwidth for completing the tests was taxed. In another experiment, people were effectively made rich or poor by the flip of a coin, with the poor demonstrating greater present bias. In that case, the bandwidth tax was clearly not due to the inherent traits of the poor.

Mullainathan and Shafir take these results to mean that we don’t need talent or inherent trait-based explanations for differences between the rich and poor. Instead, scarcity makes the poor perform poorly, leaving them in a scarcity trap. They suggest that the effect of scarcity on bandwidth is a good explanation for differences as it can make sense of diverse empirical facts across behaviour, time and place. But it leaves open the question why they imply that scarcity induced and inherent trait-based explanations are mutually exclusive, or why inherently low bandwidth can’t explain an equally diverse set of facts.

Part of the difference between their and my interpretation is that they are observing a short-term dynamic and extrapolating that to the longer term. My view is that over the longer-term, inherent explanations play a larger role.

For example, when we look at twin studies, we find that IQ and other traits inherently differ between people. Adoption studies show long-term outcomes are representative of biological and not adoptive parents. Differences in scarcity of financial or other resources due to differences in adoptive parents have almost no effect on IQ, income, obesity or a range of other long-term outcomes.

Greg Clark’s work on social mobility shows the long-term persistence of status across many generations, despite short-term shocks that would affect scarcity. If Mullainathan and Shafir’s thesis were true, a shock one generation would carry through future generations, rather than seeing the next generation reverting to the underlying status (genotype). Under Mullainathan and Shafir’s explanation, we would also see immigrants’ IQ increase when they move country and ease their scarcity (although if scarcity is relative, perhaps their relative position may not have improved). We would see large increases in the IQ of previously poor lottery winners, who would experience a sudden surge in mental resources. In The Son Also Rises, Clark pulls together a few examples of windfalls of this nature and demonstrates the lack of long-term effect. In one case, a lottery of land parcels had no effect on the outcomes of the winners’ children.

As a result, I am not convinced that their arguments truly capture the differences between the poor and the rich, or the rushed and the relaxed. Perhaps someone might eat more from time to time due to the bandwidth tax. They might take an ill-advised payday loan when they are stretched for money. But despite this short-term effect, we see little trace of it in long-term outcomes. Something is allowing some people but not others to break the cycle of scarcity.

I also doubt that Mullainathan and Shafir’s description of the poor as suffering from scarcity is generally true. When it comes to time, the poor watch more television, invest less time in caring for their children, have plenty of free time to think about what they will eat, and yet are more likely to be obese. Their characterisation of the poor having a lot on their mind whereas the rich are relaxed despite their more complex employment does not seem particularly strong.

The book is least satisfying when Mullainathan and Shafir start pulling up examples of scarcity from other domains – the padding to turn an interesting idea into a book length argument. Many of them are banal and simply involve scarcity in the way economists might think of it, with no evidence that people were suffering anything more than a lack of time. For example, they talk of the Benihana restaurant, where the chef cooking in front of people sets a quick pace for the meal, allowing more customers to come through. It is a story of scarce time, but provides no interesting insight into their thesis. The fact the Benihana restaurant management took to the time to solve their problem suggests they were not overly taxed. Mullainathan and Shafir discuss the crash of NASA’s Mars Orbiter, which had to be launched by a certain date, leading to shortcuts. But what is the evidence that there was tunnelling or taxed bandwidth as opposed to a simple lack of time to do all the checks they would have liked to have done? They don’t present the evidence to distinguish.

When we turn to solutions, it is interesting that many of them do not depend on Mullainathan and Shafir’s argument being true. They are solutions that would be equally useful in dealing with inherently untalented or impatient people. Savings reminders could be useful regardless of the cause of the lack of foresight. Presenting pay day loans in terms of dollars rather than interest rates is standard behavioural economics fare and may work for people lacking bandwidth regardless the cause.

The short-term fluctuation of bandwidth does present some interesting possibilities. They suggest that if education fails due to low bandwidth, we should time education when people can best learn. They also give an example of Kenyan farmers failing to use fertiliser and missing out on large gains to their yields. By getting farmers to pre-purchase the fertiliser when they were flush with cash after harvest, more benefited from the yield gains. (Although again, are their decisions because they are inherently shortsighted or taxed?)

Ultimately, the long-term solution to the costs of scarcity is creating bandwidth and a buffer stock of slack. This makes sense, but this point drew me back to an example early in their book. They describe an experiment involving Indian vendors who were provided with money to allow them to escape loans with exorbitant interest rates that consumed much of their income. But despite having their debts cleared, bit by bit they fell back into the scarcity trap. Mullainathan and Shafir accredit their return to the trap to shocks. But why did they not save what they would otherwise have been paying in interest to create a buffer from shocks. Why did the new bandwidth not allow at least some of them to escape? Their income had effectively doubled.

One interesting idea Mullainathan and Shafir leave lying around is whether the bandwidth of whole economies can fluctuate through good times and bad. As a random idea of my own, is the Flynn effect due to the easing of scarcity in the modern world? [No]

Having said the above, the ideas in the book are well worth considering, especially for contemplating how short-term mental capacity might be affected by the environment. But extrapolating the results to the long-term despite evidence from twin studies, adoption studies and social mobility analysis needs far more. You cannot simply throw the effect of inherent talent and traits out of the window.

*As a postscript, after writing most of this review I searched for other reviews of the book and came across this piece by Tim Harford. Many of the same points – Harford notes the buzzwords and provides a Gladwell reference too. I should note that, as it seems for Harford, the Gladwell comparison is at least part praise.

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

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.