A week of links

Links this week:

  1. American hippopotamus. HT: Scott Alexander.
  2. A walk in the park increases poor research practices and decreases reviewer critical thinking.
  3. Encourage more students to study science and put their future employment at greater risk.
  4. Behavioural economics and savings.
  5. The economic future for men.
  6. Why twitter is terrible. I don’t spend much time there any more.
  7. The mainstream may be getting dumber by the day, but we are living in what looks like a golden age of publishing for, of all people, the university presses.

And if you missed them, my posts from the last week:

  1. Sam Bowles on the death of Homo Economicus.
  2. A grumpy rant on behavioural economics.

A grumpy take on behavioural economics

I missed this when it was first posted, but John Cochrane has posted a great rant (not that I agree with it all) in response to a couple of articles on Richard Thaler’s new book Misbehaving: The Making of Behavioral Economics (HT: Diane Coyle).

A couple of excerpts:

When it gets to economics, though — market outcomes, not individual decisions —  a common complaint is that “behavioral” approaches study small-potatoes effects. OK, some asset might have a price 10 basis points off. OK, Dick knows how to rebase exams to get a bit better teaching ratings. OK, so your non-economist spouse wants roses on Valentine’s day. But really, in the big picture of growth, unemployment, inequality, climate — you name it — has this risen past cuteonomics? How do I use psychology to study the practical problems of everyday economics, say How much does progressive taxation hinder innovation and growth; How do I separate the risk premium from expected inflation in reading long-term bonds; How much carbon would a tax reduce, and so on?

That’s an interesting debate. We could have it. We should have it. There are good points on both sides. Too bad Dick chose not to address it at all.

On libertarian paternalism:

The case for the free market is not that each individual’s choices are perfect. The case for the free market is long and sorry experience that government bureuacracies are pretty awful at making choices for people. “Empirically demonstrating” that some people do silly things does not empirically demonstrate that other people, organized into the US regulatory agencies, can make better choices for them. This is another simple failure of basic logic.

And psychological, social-psychological, sociological, anthropological, and sociological study of bureaucracies and regulatory agencies, trying to understand their manifest “irrationality,” rather than just bemoan it as libertarians tend to do, ought to be a tremendously interesting inquiry. Where is behavioral public choice? (More in a previous post.)

And on being an outcast:

Most of the Wall Street Journal review passes along Thaler’s of complaining about how people resisted his early ideas. Really, now, complaining about being ignored and mistreated is a bit unseemly for a Distinguished Service professor with a multiple-group low-teaching appointment at the very University of Chicago he derides, partner in an asset management company running $3 billion dollars, recipient of numerous awards including AEA vice president, and so on.

Thaler is now AEA president.

Read the full post. A response by Noah Smith is here.

A week of links

Links this week:

  1. Highly rated doctors may not be that good. HT: Scott Alexander
  2. A Nobel prize for the inventor of vaping?
  3. Vaccinated people can still spread whooping cough.
  4. More complex products require elaborate networks of teamwork, and only a few places manage the trick.
  5. Intelligence and criminal behaviour by Joseph Schwartz and friends. No surprises here.
  6. Self control and political ideology. HT: Tyler Cowen
  7. Why the US can’t copy Sweden.
  8. Not enough studies involve blinding.

And if you missed them, my posts from the last week:

  1. The Evolutionary Foundations of Economics.
  2. Please experiment on us.
  3. The more we can send the message we have no idea, the better.

We have no idea

I have been listening to a podcast of an excellent talk by David Spiegelhalter on “Thinking and Feeling About Risk”. The video of the lecture is below.

The lecture covers a lot of interesting material – from the misrepresentation of cancer screening statistics to bicycle helmets – and I recommend listening to or watching the whole thing.

gdpmktmay15One interesting point was about the presentation of estimates of GDP growth. The Bank of England produces quarterly forecasts of GDP growth, but when they present them graphically, they don’t include their central estimate. The May 2015 graphic is to the left.

The story Spiegelhalter tells is that providing a central estimate leads to everyone focusing on that, rather than the considerable range of uncertainty. He shows a similar example where removing the central line for prediction of hurricane movements results in people who sit within the “cone of uncertainty” taking the risk to them more seriously.

I see another benefit of this GDP growth forecast chart. It effectively communicates that The Bank of England has little idea what the level of growth will be. In fact, there is a large range for what they believe the growth rate was. If people are going to insist on publishing forecasts such as this (whatever their merits), the more people who come to understand that we have no idea, the better.

Please experiment on us

Michelle Meyer and Christopher Chabris write:

Companies — and other powerful actors, including lawmakers, educators and doctors — “experiment” on us without our consent every time they implement a new policy, practice or product without knowing its consequences. When Facebook started, it created a radical new way for people to share emotionally laden information, with unknown effects on their moods. And when OkCupid started, it advised users to go on dates based on an algorithm without knowing whether it worked.

Why does one “experiment” (i.e., introducing a new product) fail to raise ethical concerns, whereas a true scientific experiment (i.e., introducing a variation of the product to determine the comparative safety or efficacy of the original) sets off ethical alarms?

In a forthcoming article in the Colorado Technology Law Journal, one of us (Professor Meyer) calls this the “A/B illusion” — the human tendency to focus on the risk, uncertainty and power asymmetries of running a test that compares A to B, while ignoring those factors when A is simply imposed by itself.


[A]s long as we permit those in power to make unilateral choices that affect us, we shouldn’t thwart low-risk efforts, like those of Facebook and OkCupid, to rigorously determine the effects of those choices. Instead, we should cast off the A/B illusion and applaud them.


The Evolutionary Foundations of Economics

I posted this paper on SSRN a few months ago, but neglected to blog about it – I’ve written (with my supervisors) a review of the literature incorporating evolutionary theory into economics. The abstract:

The Evolutionary Foundations of Economics

As human traits and preferences were shaped by natural selection, there is substantial potential for the use of evolutionary biology in economic analysis. In this paper, we review the extent to which evolutionary theory has been incorporated into economic research. We examine work in four areas: the evolution of preferences, the molecular genetic basis of economic traits, the interaction of evolutionary and economic dynamics, and the genetic foundations of economic development. These fields comprise a thriving body of research, but have significant scope of further investigation. In particular, the growing accessibility of low cost molecular data will create more opportunities for research on the relationship between molecular genetic information and economic traits.

The paper is fairly flat in tone as I wrote it as the introductory review chapter for my thesis. If you’re familiar with the blog, you will have read some more critical pieces on the papers covered in my article before. Links to some of those critiques can be found down the bottom of my evolutionary biology and economics reading list page.

And the disclaimer – this paper isn’t about “evolutionary economics” in the way that term is typically used. I’m interested in the biological angle:

The subject matter of this paper needs to be distinguished from what is commonly called “evolutionary economics”. Evolutionary economics uses biological concepts, such as natural selection, and applies them to the dynamics of firms, business processes and institutions. The economy is seen as a complex adaptive system in which innovation and change are central considerations. The origin of evolutionary economics is often traced to Veblen (1898), and was revived by Alchian (1950) and later Nelson and Winter (1982), whose seminal work inspired a vast literature. The subject matter of this paper differs from evolutionary economics in that we focus on human biology rather than seeking to apply a biological analogy to higher levels such as firms. This paper is about the application of evolutionary biology to economic processes at the level of humans and their genes and their interactions at the population level.

A week of links

Links this week:

  1. Storytelling about famous experiments tends to go a bit askew.
  2. Noah Smith takes on Deirdre McCloskey.
  3. Chimps on the drink.
  4. A review of Richard Thaler’s ‘Misbehaving: The Making of Behavioural Economics’.
  5. The gender gap in tech.

And if you missed them, my posts from the last week:

  1. MSiX 2015 is on July 30 in Sydney, and features yours truly.
  2. Humans cause accidents.

The human factor in accidents

The below passage is from a neat article on how mistakes can save lives.

CRM [crew resource management] as born of a realisation that in the late 20th century the most frequent cause of crashes wasn’t technical failure, but human error. Its roots go back to the Second World War, when the US army assigned a psychologist called Alphonse Chapanis to investigate a curious phenomenon. B-17 bombers kept crashing on to the runway on landing, even though there were no apparent mechanical problem with the planes. Rather than blaming the pilots, Chapanis pointed to the instrument panel. The lever to control the landing gear and the lever that operated the flaps were next to each other. Pilots, weary after long flights, were confusing the two, retracting the wheels and causing the crash. Chapanis suggested attaching a wheel to the handle of the landing lever and a triangle to the flaps lever, making each easily distinguishable by touch alone. Problem solved.

Chapanis had recognised that human beings’ propensity to make mistakes when they are tired is much harder to fix than the design of levers. His deeper insight was that people have limits, and many of their mistakes are predictable effects of those limits. That is why the architects of CRM defined its aim as the reduction of human error, rather than pilot error. Rather than trying to hire or train perfect pilots, it is better to design systems that minimise or mitigate inevitable human mistakes.

In the 1990s, a cognitive psychologist called James Reason turned this principle into a theory of how accidents happen in large organisations. When a space shuttle crashes or an oil tanker leaks, our instinct is to look for a single, “root” cause. This often leads us to the operator: the person who triggered the disaster by pulling the wrong lever or entering the wrong line of code. But the operator is at the end of a long chain of decisions, some of them taken that day, some taken long in the past, all contributing to the accident; like achievements, accidents are a team effort. Reason proposed a “Swiss cheese” model: accidents happen when a concatenation of factors occurs in unpredictable ways, like the holes in a block of cheese lining up.

James Reason’s underlying message was that because human beings are fallible and will always make operational mistakes, it is the responsibility of managers to ensure that those mistakes are anticipated, planned for and learned from. Without seeking to do away altogether with the notion of culpability, he shifted the emphasis from the flaws of individuals to flaws in organisation, from the person to the environment, and from blame to learning.

The science of “human factors” now permeates the aviation industry. It includes a sophisticated understanding of the kinds of mistakes that even experts make under stress.

I recommend reading the full article. Among other things, it has a lot of interesting material about mistakes in medical settings.

Marketing Science Ideas Xchange (MSiX) 2015

The 2015 Marketing Science Ideas Xchange – MSiX – has been announced for 30 July in Sydney. As it says in the blurb, MSiX “is dedicated to exploring how brands can benefit from the interface between behavioural science and marketing.”

The headline speaker is Michael Norton, Harvard professor, author of Happy Money: The Science of Happier Spending and developer of the first set of experiments on the IKEA effect (that last point is the reason I knew his name when I heard he would be speaking).

The rest of the speakers and further detail on the conference are here – with the speaking line-up including me. I’ll be talking about how behavioural economics (science) could benefit from a good dose of evolutionary biology, and how that evolutionary lens can be valuable in understanding consumer behaviour.

Last year’s event – headlined by Rory Sutherland (who linked me into this MSiX world) – was a pretty good day, and this year looks promising too.

And here’s Norton doing the TED thing.