I have just left the Social Decision Making: Bridging Economics and Biology conference, with one of the last speakers being Paul Seabright, author of The Company of Strangers. I will post some thoughts on Seabright’s presentation (and some of the other presentations at the conference) after Easter and once I have read the related papers.

In the meantime, the night before Seabright’s talk I flipped through the revised edition of his book (it is a few years since I read the first edition). In the introduction is the following:

If it were somehow possible to assemble together all your direct same-sex ancestors – your father and your father’s father and so on if you’re male, your mother and your mother’s mother and so on if you’re female; one for each generation right back to the dawn of agriculture – you and all of these individuals could fit comfortably in a medium-sized lecture hall. Only half of you would have known the wheel, and only 1 per cent of you the motor car. But you would be far more similar to each other – genetically, physically, and instinctually – than any group of modern men or women who might have assembled there by chance. … [E]xcept in some dimensions such as height and perhaps in skin color, the biological differences between you and your furthest ancestor would be hard to distinguish from random variation within the group. If you are reading this book in a train or an airplane, this means your most distant ancestor from Neolithic times was probably more like you, biologically, than the stranger sitting in the seat next to you now.

As occurred to me the time I first read it, I am not sure that the last sentence is true. I expect that this could be empirically tested on a genetic basis (so this post should be put in the “I might be wrong” category), but there are a couple of issues in my mind.

First, it is likely that a Western European stranger would share many common ancestors with me within the last 10,000 years. If we go back 10,000 years, or around 400 generations, I have approximately 2^400 direct ancestors (which is approximately 10^120, or more than the number of atoms than there are estimated to be in the observable universe). Obviously, this is more ancestors than there were people at that time, which points us to the fact that many of my ancestors from this time are ancestors through multiple ancestral lines. Many ancestors are likely to be shared with anyone of a similar ethnic origin. On this basis, there is no ground to expect that the direct ancestor of 10,000 years ago would be more similar than the stranger.

Applying Seabright’s particular scenario, I wrote this post while sitting on a train in Northern Italy, with an Italian the stranger sitting next to me. As far as I have traced, I have English, Welsh and Irish heritage. That reduces the chance that we share common ancestors within the last 10,000 years compared to a scenario where I sit next to someone from the United Kingdom or Ireland. Even so, there is still a significant probability of common ancestors, as would be suggested by my Y-chromosome haplogroup (R1b1a2a1a1a under the 2011 nomenclature), with earlier versions of this haplogroup present in both United Kingdom and Italian populations (and that, of course, is just the male-male lineage).

A second issue is who this ancestor is. Depending on the genes of each ancestor and the traits expressed by those genes, selection will have resulted in certain ancestors contributing more to my genome than others. If we picked one of my ancestors who contributed through a single line 10,000 years ago, they are likely to be less similar to me than an ancestor who has contributed through ten orders of magnitude more lines (remembering that I have 10^120 ancestral lines from 400 generations ago). Whether the ancestor we use for the comparison is more similar to me than the modern stranger might depend on whether we picked an ancestor randomly, the ancestor who made the median or mean contribution to my genome or the ancestor who made the greatest.

After posting Friday’s piece on Hansson and Stuart’s paper on natural selection and savings, I realised I had not commented on one of the most important assumptions made by the authors. To get their result that people would save such that they maximise consumption across generations, Hansson and Stuart assumed that consumption corresponded with fitness (a relative measure of reproductive success). To maximise fitness, one would need to maximise consumption.

This makes some sense over the very long-term, regardless of whether you consider that consumption contributes to fitness directly, by (say) improving health, or indirectly as a signal of quality. In the signalling case, it has been shown that conspicuous consumption as a handicap can be consistent with the standard utility approach to consumption used in economics.

While I can hand-wave my way through that explanation, some of the attempts in economics to more explicitly consider fertility and fitness have run into a larger problem. In a presentation by Alan Grafen on Sunday (at this conference), he went through four papers on the boundary of evolutionary biology and economics, and one of those he picked was by Robert Barro and Gary Becker. In Barro and Becker’s model, they created a utility function which included both consumption and fertility. An agent in the model would be interested in increasing consumption and their number of offspring. But as Grafen asked, what is the purpose of consumption in the model from an evolutionary perspective?

The interesting thing about Barro and Becker’s paper is that by adding an evolutionary biology flavour to the model, they have created a trade-off between fitness and consumption. Higher consumption reduces fitness, and no hand waving like I used for Hansson and Stuart’s model can justify consumption biologically. Any defence of Barro and Becker’s model will have to look to its predictive power, with the evolutionary explanation to come later. Given that most people in developed countries consume much more than can be justified biologically and do not seem to be maximising their fitness (sperm donation anyone?), there is room to defend it on this ground (in at least the short term).

The other issue that I should mention about Hansson and Stuart’s paper is that they implicitly assume that if one saves, the saver has effective protection of their private property and is able to pass it down to their children without fear of appropriation. As I have posted about before, violence may be a significant obstacle to the development of behaviour such as saving. While Hansson and Stuart saw differences in saving and labour preferences arising from environmental conditions, another plausible driver of differences would be the probability of any savings being stolen.

I am at the Social Decision Making: Bridging Economics and Biology conference (the abstracts of which can be downloaded here). As the name suggests, the basic idea behind the conference is to pull together economists and evolutionary biologists to develop new collaborations and examine how their respective approaches to social decision-making might be useful to each other.

So far, the most surprising observation (to me) is how many of the evolutionary biologists are working in the behavioural economics area and conducting experiments with human subjects. That is certainly a good thing, as behavioural economics could do with an evolutionary framework.

During the opening presentations there was a slight flavour of “bash the economists”, but the targets have generally been fair enough – I just wish that individual economists’ positions would not be taken to be the entire profession’s position. When you consider the evolutionary approaches of the economists whose work has been mentioned, such as Gary Becker or Herbet Gintis, they are poles apart and not necessarily indicative of modern approaches.

The other thing that stands out is that there is little discussion of what economists can offer evolutionary biologists. As is a central theme of this blog, I believe that economics could be much improved by considering humans as evolved (evolving) animals. But what insights by economists should evolutionary biologists be considering in their work that they aren’t now? Once you move past methodologies (such as the raft of experimental experience in behavioural economics), I am not sure that I can name a central insight that might have a significant effect on evolutionary biology.

I’m not sure how much I’ll be posting during the rest of the conference or over the following Easter break, but I’ll be posting on the conference content over the next few weeks.

David Henderson has posted on a recent presentation by Garett Jones of George Mason University in which Jones discussed IQ and cooperation.

As Jones notes, higher IQ people cooperate more in repeated prisoner’s dilemma games, are more trusting, have lower levels of divorce and engage more in activities such as voting and organ and cash donation. Jones suggests that if this link between trust and IQ improves a country’s institutions, countries should seek to raise national IQ, and one way of achieving this is by boosting immigration of high IQ populations.

Henderson states that:

In Q&A, I asked him if he was suggesting something like Canada’s immigration rules that seem to put a higher weight on IQ indirectly or whether he would be happy with a Bryan Caplan solution that would allow pretty much anyone in who wanted to come. …. Garett seemed to lean to the former and said that one thing the government could so is, when an immigrant got a Ph.D., “staple a green card to it.”

It is interesting that Jones might suggest such an indirect method of achieving his objective. Would a simple IQ test be more effective? Or does Jones hope to capture people with other traits that a PhD might be indicative of, such as a propensity to work? Another question is whether a country should adopt such a passive method of giving residency to those who have already come to a country (which as Henderson notes, probably has some selection effects in itself)? Could a country be more aggressive and set up IQ testing stations in countries around the world and encourage immigration by all those who pass?

A natural implication of this policy is that it will lower the average IQ of the donor country, and following Jones’s logic, lead to poorer institutions in that country. The net effect for the high IQ person is likely to be overwhelmingly positive, but the long-run dynamic effects on the donor country could be negative.

This is my last post on David Sloan Wilson’s series Economics and Evolution as Different Paradigms (my earlier three posts are here, here and here). While much of Wilson’s attack on economics is against a caricature of the discipline, he ties up his series with a few recommendations that are worth noting.

One is the need for behavioural economics to adopt evolutionary thinking to allow it to move from being a list of anomalies and biases to a coherent framework. There is no argument from me there. Wilson has an underlying aim to this, however, which is that it may give a platform for the overthrow the classical economics assumptions of rationality.

I am not sure that would be the result. People generally want more (for themselves), they want less as the price rises, they discount costs and benefits in the future, and so on. There are all sorts of specific situations where behavioural economics has shown that this does not apply, but if I want to know the effect of putting a price cap on petrol prices, thinking about the rational actor is a sound starting point. Behavioural economics will only see the overthrow of the rational agent when it has a coherent framework and when incorporating the framework into models produces models with higher predictive power.

In Wilson’s final post, he notes a few avenues by which the mission to reconcile economics and evolutionary biology will progress. One of these was a letter submitted to the National Science Foundation. Written by Wilson and John Gowdy, the letter was also signed by 64 other signatories including Elinor Ostrom, Paul Ehrlich and Edward O Wilson. It had four main points on how to integrate economics and evolutionary science.

First, as discussed above, it states that evolutionary theory could help make sense of the findings of behavioural economics.

The second was that:

Evolution can help decision makers understand the large-scale and long-run consequences of economic policies, particularly environmental and social policies

As a headline, I couldn’t agree more. But when this point is discussed in the letter, it focuses on the use of evolutionary theory to understand where people behave in their own interest at the expense of the larger group. This reflects Wilson’s earlier attacks on the invisible hand.

This sells the potential contribution of evolutionary theory to economics short. Evolutionary theory can help the understanding of how people act, what objectives they pursue, which people have (or had) higher fitness, what the consequences of policies will be in the long-run (regardless of whether they are benign to a group), and so on. If evolutionary theory is used solely as (another) attack on libertarian arguments, there will not be widespread (or useful) adoption.

The third point in the letter was that the proximate-ultimate distinction is important in economics, as it is in evolutionary theory. This point is a hangover from Wilson’s attack on Milton Friedman and I am not sure that it is important. As I wrote in my previous post, Friedman’s position is milder and the economics profession is less narrow than Wilson suggests.

The final point of the letter is that the non-adaptive products of evolution are best understood from an evolutionary perspective. Again, this seems to sell the opportunity short. What of the adaptive products of evolution, such as intelligence or patience?

Having now worked through Wilson’s posts, I am not overly optimistic that there will be much useful coming out of the Evolution Institute. There are no shortages of coherent attacks on the neo-classical, hyper-rational model of economics and if the Evolution Institute is going to simply join the queue, we will not hear much more interesting out of them. We will see if my pessimism is borne out when the Institute moves from its methodological critique and starts to deliver substantive policy proscriptions.

*My four posts on David Sloan Wilson’s Economics and Evolution as Different Paradigms can be found here, here, here and here.

Jonah Lehrer has expanded his recent focus on measurement and grit (on which I recently posted) in an article on the usefulness of the Wonderlic test, a quasi-IQ test, in predicting quarterback performance. Lehrer cites a paper by David Berri and Rob Simmons which suggests that some metrics, including the Wonderlic test, are influencing draft position even though they are not predictive of performance. Lehrer writes:

While they found that Wonderlic scores play a large role in determining when QBs are selected in the draft — the only equally important variables are height and the 40-yard dash — the metric proved all but useless in predicting performance. The only correlation the researchers could find suggested that higher Wonderlic scores actually led to slightly worse QB performance, at least during rookie years.

Unlike Lehrer’s piece on which I previously posted, I’m sympathetic to the argument that this suggests that some people are acting on some not particularly useful measurements. However, I’m not as convinced when Lehrer (again) moves into the idea that the missing element is grit. Lehrer closes the article with the following:

So where is all this heading? How will grit become a bigger part of the scouting equation? The first step is to finally acknowledge that maximal tests aren’t effective. “I really see the Wonderlic as a reading test,” says former NFL executive Michael Lombardi, now with the NFL Network. “Until we get a better test, teams are just going to have to evaluate players the old-fashioned way, by watching them play in actual games. It takes good instincts to be a QB. Maybe it takes good instincts to find one, too.”

Hasselbeck suggests that teams pay more attention to the fundamentals of college quarterbacks, since their passing mechanics are often a window into how much grit they possess. “You know these guys have been coached for years,” he says. “So if you see a QB with flawed fundamentals, you gotta wonder what’s wrong. Is he coachable? Will he work to improve? Because that’s important. You can teach a kid to throw the ball, but only if he wants to learn.”

After all, deliberate practice makes perfect.

This first paragraph is almost the opposite of Michael Lewis’s Moneyball, where he suggested that there was too much faith in instinct and not enough in measured performance. Having years of college performance at hand, I’d be sceptical if some measures of “grit”, assuming it was the important missing variable, do not already exist.

On that note, the second paragraph suggests an opportunity. Maybe we should see some predictions in the lead-up to the next few drafts, where some of these grit loving experts could assess “passing mechanics” as a measure of grit, state who the teams should draft where and see if their performance measure is a better indicator of future success than actual draft position. That is what was impressive about Moneyball. Rather than being a story about someone complaining that teams should do a difficult task better,  it was a story about someone taking their belief and acting on it (and with the presence of Michael Lewis, putting one season’s draft selections on the record for an assessment of those beliefs).

In David Sloan Wilson’s blog series Economics and Evolution as Different Paradigms (which I have recently posted about here and here), Wilson discusses the invisible hand metaphor that is used in economics.

The invisible hand metaphor comes from Adam Smith’s Wealth of Nations, and although the particular use of the invisible hand metaphor by Smith relates to preferring domestic to foreign industry, the metaphor has come to encapsulate this broader idea of Smith:

It is not from the benevolence of the butcher, the brewer or the baker, that we expect our dinner, but from their regard to their own self interest. We address ourselves, not to their humanity but to their self-love, and never talk to them of our own necessities but of their advantages.

Wilson contrasts this view of self-interest enhancing the common good with an evolutionary perspective in which a slacker or exploiter within a group will have an evolutionary advantage, suggesting that natural selection favours traits that undermine the common good. To reconcile evolution and the invisible hand, Wilson states that group-level selection must operate as a counterbalance to within-group selection. He suggests that the invisible hand can operate because:

[M]any of our psychological traits evolved by virtue of causing groups to survive and reproduce better than other groups, not by causing individuals to best members of their own groups.

I am not sure that a group selection argument is required to show why the invisible hand metaphor might have some value.  (In fact, I am not sure the group selection arguments put forward by Wilson add much to evolutionary theory – when I was looking around to understand what precisely is Wilson’s position, I found this great presentation by Stuart West which seems to nail all the main arguments in less than 20 minutes.) To explain why the invisible hand metaphor has such power, I’d prefer a simpler explanation around the need to produce something of value in a market economy.

Where I do (obliquely) agree with Wilson is that evolutionary theory can show that when everyone acts in their own self-interest, there can be negative aggregate outcomes. Economics has no shortage of those – the tragedy of the commons and failure to internalise externalities such as pollution being the classics. Over-investment in signalling would be another. However, while recognising that there can be (and are) problems, I’m generally fairly optimistic. But this is not through any principle of evolution, or group-selection based argument. Wilson’s following illustration provides an indication why.

Over his next two posts (here and here), Wilson looked at the work of Elinor Ostrom, winner of the Nobel Memorial Prize in Economic Sciences. He considered that Ostrom’s work illustrated the invisible hand operating through group selection. Ostrom’s career focused on the use of common pool resources and how institutional arrangements could emerge to manage those resources and often avoid the “tragedy of the commons” despite there being no private ownership or government regulation.

Wilson sees Ostrom’s work as showing that life is full of situations where the invisible hand does not operate. Behaviours for the good of the group require constraint and coordination.

I take a different perspective on Ostrom’s work. Ostrom’s work expands the range of situations where it can be argued that positive outcomes can emerge without top down interference. The rules and norms that develop to manage the resource could be argued to be as driven by the invisible hand as the distribution and the use of the resource itself. This reflected my familiarity with Ostrom’s work via libertarian and Austrian (school) economists who used her work to show that even the tragedy of the commons does not always require a solution to be imposed from above.

Ostrom identified a number of conditions for these emergent solutions, which Wilson sees as being a mix of conservative and liberal principles. While there is local autonomy, Wilson argues that the groups, not individuals, must have autonomy. He also suggests that there is a need for a framework to govern relationships between groups. This leads to a middle-ground on which political discourse can be held.

I am not sure how Wilson saw Ostrom’s work as promoting a middle-ground of discourse, nor of it being a mix of liberal and conservative principles. Where the conditions identified by Ostrom for these emergent local solutions are not met, we are back to the usual dichotomy between state-ownership and top down control versus private ownership. If they are met, the libertarians have their way.

*My four posts on David Sloan Wilson’s Economics and Evolution as Different Paradigms can be found here, here, here and here.

As indicated in my last post, between December 2009 and October 2010, evolutionary biologist David Sloan Wilson wrote a series of posts titled Economics and Evolution as Different Paradigms. Wilson’s basic line of reasoning is that evolutionary biology should play a larger role in economics, and I naturally agree with that position.

For the foundation of his argument, the second post of Wilson’s series contains a reasonably typical attack on modern economics (I’ll accept this monolithic caricature for the moment). I wouldn’t call it the most convincing of attacks, particularly when it starts by providing an example that modern economics deals with quite well:

Consider the following proposition: I’ll give you 1 million dollars for sure or a 50:50 chance at 2.1 million dollars. What’s your choice? If you’re like me, you’ll choose the certain 1 million. Yet, that is a violation of core economic theory that became known as the “Allais Paradox“.

Unfortunately, that is not an example of the Allais Paradox, but an example of risk aversion (and a number of the comments on Wilson’s post pointed this out). The Allais Paradox is, however, nicely set out in the Wikipedia article to which Wilson links. This mistake tends to make much of Wilson’s critique that economics cannot deal with variance of utility fall flat, as for the example given, a simple utility model with risk aversion does this well.

Moving past that hiccup, Wilson suggests that we can find the reason that the Allais Paradox has not been incorporated into modern economic theory in Milton Friedman’s essay The Methodology of Positive Economics (the first essay in his book Essays in Positive Economics). Friedman suggested, among other things, that it is not problematic if the assumptions underpinning the model are unrealistic if the predictive power of the model is good. We should test models by their predictive power. Wilson states that this approach is a recipe for confirmation bias (although, what isn’t?) and that the lax criteria for assessing models allows economists to ignore the Allais Paradox.

Whenever someone uses this essay by Friedman to attack economics, I feel that the reader generally misunderstands what Friedman means when he suggested that the assumptions do not have to be descriptively realistic. Friedman notes that assumptions, by their very nature, never are descriptively realistic, but that they need to be sufficiently good for the purpose at hand. This is a rather mild claim, as any model (and its assumptions) must be more simple than reality or there will be no value to the model.

Regardless, Wilson suggested that the Allais Paradox presented a risk to economic theory. He states:

It violated the principle of maximization of returns, it could not easily be incorporated into the body of formal analytical theory, and it was a move toward realism that would definitely have consequences for economic predictions.

I only partially agree with that assessment. If a paradox like the Allais Paradox is particularly important for a set of decisions that an economic model is seeking to predict, then Friedman’s test of predictability is useful in determining whether it should be incorporated in the model. If it is not important, then it won’t improve the model’s predictive power.

That reflects the general issue I have with the Allais Paradox, and the many other of the biases that behavioural economics has unearthed. Are there tangible examples of how they could be incorporated into an economic model and out-predict a neoclassical model that ignores these biases (they may exist – I am asking this question more of ignorance than confidence that they don’t)? Part of the reason for this is that much of behavioural economics is a catalogue of biases and it lacks an evolutionary framework (and as I noted in my last post, the Evolution Institute seeks to address this).

This is not to say that we should ignore the raft of biases. But instead of pointing out each individual bias and demanding to know why it isn’t incorporated in the model, we should ask whether there is a more systematic problem that the bias is symptomatic of. Instead of trying to add bias by bias, we could be asking more fundamental questions, such as what the agent(s) actual objective is.

I have more sympathy with Wilson’s argument that testing the predictive power of a model can be difficult where the evidence is in a complex system and difficult to collect and document. In this case, Friedman’s test of predictive power may not be a particularly strong filter. Despite this, it is an underused filter for many economic theories. As I have discussed before, economics has no shortage of theories that are still kicking around despite a lack of any empirical support. Use of that filter might get rid some of highly complex, mathematically beautiful but predictively useless models that should have been discarded long ago.

*My four posts on David Sloan Wilson’s Economics and Evolution as Different Paradigms can be found here, here, here and here.

In the first of a series of blog posts by David Sloan Wilson on economics and evolution (which I will blog about in the coming weeks as the posts contain some interesting ideas), Wilson introduced The Evolution Institute, a think tank that seeks to apply evolutionary theory to modern policy problems.

I had not heard of the Institute before, but naturally I consider that integration of evolutionary thinking into any policy framework can bring value. It will be interesting to see whether the Institute is be used as a vehicle to push pre-established economic views, or for a genuine exploration about how evolutionary biology might add something to current economic thought. From my brief look through the Institute’s website, it does not seem that the Institute has produced any tangible outcomes yet, but there are plenty of statements of intent. It will be interesting to see what actually emerges.

The Institute frames its economics focal topic around the need to have an economics that reflects how humans actually act, with behavioural economics as the immediate focus of integrating evolution into economics. Interestingly, the objective of the topic is not to introduce more behavioural economics findings into mainstream economic theory, but to give a framework to behavioural economics itself. The website states:

There is widespread agreement that economic theory must become based on a more accurate conception of human nature to successfully guide public policy. That is the objective of behavioral economics, which has become prominent within the larger field of economics. However, behavioral economics needs to become more broadly based in the human behavioral sciences, which in turn must be grounded in evolutionary theory. The purpose of our project is to properly ground behavioral economics in evolutionary science, including the study of proximate mechanisms in a more fully rounded sense.  We intend to provide the most accurate conception of human nature possible based on current scientific knowledge, oriented toward the formulation of economic theory and public policy.

If a project of this type succeeds, behavioural economics would be much more useful. It might actually extend beyond being a catalogue of paradoxes and biases and offer a framework under which economic decisions might be understood.

*My four posts on David Sloan Wilson’s Economics and Evolution as Different Paradigms can be found here, here, here and here.

Following from my recent post on Scott Barry Kaufman’s heritability measurement nihilism, Jonah Lehrer has gone a step further and taken a swipe at measurement in general, and in particular, at short-term tests. Lehrer argues that:

The larger lesson is that we’ve built our society around tests of performance that fail to predict what really matters: what happens once the test is over.

I’m not averse to arguments that some people use measurements in inappropriate ways. However, Lehrer overstates his case in this article as he misses a crucial element of his argument – that people are actually mis-using the performance measures in the way he suggests.

Lehrer pulls out three examples in support of his position. First, Lehrer notes that tests of short-term cashier speed had a surprisingly weak correlation with longer term speed as measured by the electronic cashier system. There was a gap between maximum performance when they were being tested and typical performance when they weren’t. All I can say on this example is that I am sure that grocery store workers don’t get tested once for 30 items and then get left alone for the rest of their scanning careers.

Second, Lehrer points out that while SAT scores can predict around 12 per cent of the variation in freshman grade point average, they are less effective in predicting post-graduation achievement. Similarly, the LSAT had almost no relationship with career success. (I do not know which studies Lehrer is referring to here, so I can’t comment on the specific results.) On this example, I might be concerned if SAT scores were the sole entry measurement and they had such low predictive power, but SAT scores are not used on their own. College admission departments combine them with grade point averages, interviews and examination of the applicant’s CV. The SAT score may give context to the grade point average by indicating the mix of talent and hard work that led to their high school performance.

Third, Lehrer calls the NFL Scouting Combine (a week-long event showcasing around 300 NFL aspirants during which they undergo a series of tests) “a big waste of time” as according to a recent study there is no consistent statistical relationship between the results of the Combine and NFL performance. Lehrer draws this conclusion from a study by Kuzmits and Adams. Looking at the original paper, one of the performance indicators used in the study was draft position. The authors found that there was no consistent statistical relationship between Combine performance and draft position, except for the speed of running backs. The lack of a correlation between Combine performance and draft position suggests that for the teams making the draft decision, they already know the lack of predictive ability of many of the Combine’s tests.

The study authors also noted that a range of other activities take place at the Combine, such as team interviews, injury evaluations and urine tests. If we consider the advertising and other fan interest generated by the event, there are a number of plausible benefits. Instead, Lehrer has taken an indicator that the teams do not use and argues that as that measurement does not matter, the Combine is a waste.

While my perspective is that these measurements aren’t being abused in the way Lehrer implies, Lehrer identifies the problem with these short-term tests as the failure to identify “grit”. Lehrer states:

The problem, of course, is that students don’t reveal their levels of grit while taking a brief test. Grit can only be assessed by tracking typical performance for an extended period. Do people persevere, even in the face of difficulty? How do they act when no one else is watching? Such traits often matter more than raw talent. We hear about them in letters of recommendation, but hard numbers take priority.

It is interesting that Lehrer does not consider that there are any short-term tests which might indicate how people act in the face of difficulty or when people are not watching. Lehrer is certainly aware of Walter Mischel’s marshmallow test and the large predictive power this test (given to four-year old children) had for future life success. Lehrer also seems to ignore that when colleges make decisions using SAT scores or Combine results, the decision makers use long-term performance data in the form of high school grades and college football performance.

I wonder what Lehrer would recommend be done about these tests. Would he simply abolish the Combine and SAT? My perspective is that, if anything, we are not measuring enough. Like Michael Lewis argued in Moneyball was the case for baseball drafting, I am sympathetic to the view that we pay too little attention to measurement and too much to gut instinct. For Lehrer to convincingly argue that short-term measurement is playing too much of a role, I’d like to see some evidence that there are alternative measurements that outperform those indicators that are actually being used.