A week of links

Links this week:

  1. A good Jared Diamond interview.
  2. The 10,000 hours rule – the best you can do is find the peak of your own ability.
  3. Tinder works because a picture is “worth that fabled thousand words, but your actual words are worth… almost nothing”. (HT: Razib)
  4. Dumb incentives, although economists would be the first to point out a lot of the unintended consequences.
  5. No evidence for the benefits of expertise for fund managers.
  6. Drunks are more utilitarian. And maybe you should do that drinking on an empty stomach.
  7. Are social psychologists biased against Republicans?

Improving behavioural economics

A neat new paper has appeared on SSRN from Owen Jones – Why Behavioral Economics Isn’t Better, and How it Could Be (HT: Emanuel Derman via Dennis Dittrich). My favourite part is below. As I have said many times before, giving a bias a name is not theory.

[S]aying that the endowment effect is caused by Loss Aversion, as a function of Prospect Theory, is like saying that human sexual behavior is caused by Abstinence Aversion, as a function of Lust Theory. The latter provides no intellectual or analytic purchase, none, on why sexual behavior exists. Similarly, Prospect Theory and Loss Aversion – as valuable as they may be in describing the endowment effect phenomena and their interrelationship to one another – provide no intellectual or analytic purchase, none at all, on why the endowment effect exists. …

[Y]ou can’t provide a satisfying causal explanation for a behavior by merely positing that it is caused by some psychological force that operates to cause it. That’s like saying that the orbits of planets around the sun are caused by the “orbit-causing force.” …

[L]oss aversion rests on no theoretical foundation. Nothing in it explains why, when people behave irrationally with respect to exchanges, they would deviate in a pattern, rather than randomly. Nor does it explain why, if any pattern emerges, it should have been loss aversion rather than gain aversion. Were those two outcomes equally likely? If not, why not?

Part of the solution provided by Jones, as reflected in much of his past work, rests in evolutionary theory.

An updated economics and evolutionary biology reading list and a collection of book reviews

I have updated my economics and evolutionary biology reading list, with a few new additions including John Coates’s The Hour Between Dog and Wolf, Gregory Clark’s new book on social mobility and Jonathan Haidt’s The Righteous Mind. As before, I have been selective, adding only the best books (or articles) in the area. That said, I am always open for suggestions or comment.

When updating the list, I realised I have written a lot of book reviews over the last few years. I have collected most of them together on one page, which you can find here. It includes a lot of good books that aren’t on the reading list as they are not on topic. It also contains a few books that are on topic but haven’t made the cut.

A week of links

Links this week:

  1. Cooperation in humans versus apes.
  2. In praise of pilots.
  3. Are women better decision makers? You can ask about some sex differences.
  4. Amazon is doing us a favour. Goodbye book publishers.
  5. The logic of failure.
  6. The Behavioural Insights Team has lunch with Walter Mischel. Mischel’s work is fantastic and his new book is on my reading list, but the mention of brain plasticity and epigenetics (in the same sentence!) has reduced my expectations.
  7. Charles Murray on Ayn Rand. HT: Alex Tabarrok

Finding taxis on rainy days

A classic story on the play-list of many behavioural economics presentations is why you can’t find taxis on rainy days. The story is based on the idea that taxi drivers work to an income target. If driver wages are high due to high demand for taxis, such as when it rains, they will reach their income target earlier and go home for the day. The result is you can’t find a taxi when you need one most.

The story is such a favourite as it conflicts with conventional economic wisdom that people are maximisers who respond positively to incentives such as higher wages. Instead, drivers are satisficers who quit work for the day once have hit their target, even though the high wages would allow them to earn more than normal.

This story originates from a 1997 article by Colin Camerer and friends (I suggest following Camerer on twitter). They analysed taxi trips in New York and found that as wages went up, labour supply (taxis on the street) goes down. Their preferred explanation, based on what some drivers said, was that taxi drivers work to a daily income target. Their article did not include the reference to the rain, but it has become the way the story is traditionally told.

But, a new study suggests this negative relationship between wages and supply might not generally be the case for New York taxi drivers. Using a much bigger dataset of New York taxi driver activities, Henry Farber has found that, as standard economic theory would suggest, taxi drivers drive more when they can earn more. There was no evidence of income targeting in the data.

As another blow to the rainy day story, Farber also found that taxi drivers didn’t earn more when it was raining. As traffic was worse and they travelled less distance, their earnings didn’t increase despite the higher demand. There were less taxis on the street when it was raining, but this must be due to causes such as drivers preferring not to work when traffic is bad.

So how do we reconcile these conflicting findings? A starting point is in the original study. In a show of humility, Camerer and colleagues were open to the idea that their result might not be robust. They close with the following paragraph:

Because evidence of negative labor supply responses to transitory wage changes is so much at odds with conventional economic wisdom, these results should be treated with caution. Further analyses need to be conducted with other data sets (as in Mulligan [1995]) before reaching the conclusion that negative wage elasticities are more than an artifact of measurement or the special circumstances of cabdrivers. If replicated in further analyses, however, evidence of negative wage elasticities calls into question the validity of the life-cycle approach to labor supply.

To use the cliché, more research is required. And there has been a lot more research since Camerer and friends’ had their study published. While I’ve pitched the story as a new paper tearing up an almost 20-year old favourite, there has been a sequence of papers over the years with both supporting and conflicting results, including by Farber.

Farber’s explanation for the result in his latest paper is that he had access to a larger dataset – five million shifts compared to a few thousand in Camerer and friends’ or Farber’s earlier studies. Technological progress in recording taxi data also allowed Farber’s work to be at a much finer level of detail than was possible at the time of the original study. Other studies also had small datasets or used less reliable data such as from surveys (such as this one from Singapore), but there have also been at least one involving similarly large sets of taxi data that did find a negative relationship (such as a second from Singapore, although in that case the negative relationship seemed of too low a magnitude to support income targeting).

Another explanation might lie in the methodological battle about how you should measure the relationship between wages and supply for taxi drivers. Farber’s 2005 paper picked apart the original methodology, particularly around their assumptions on wages, and he chose a different approach based on drivers deciding whether to continue or not at the end of each ride. When I previously invested some time to understand it, I found Farber’s critique reasonably persuasive. However, I haven’t taken the time to understand the finer points of Farber’s new analysis and to what extent methodology determines the result, so it will be interesting to see some responses to this latest salvo.

Another potential distinction is that Camerer and friends’ original study was able to distinguish between owner-operators and employee drivers, each of which face different incentives. Farber wasn’t able to tease the two apart. However, Camerer and friends found a negative relationship for both groups, so at a minimum, Farber’s work suggests that the finding would not hold across both. Farber did consider whether there might be many different types of driver, which there may be. But if the satisficers do exist, there are not many of them.

On a brighter note, there is some hope that we will be better able to catch a taxi on rainy days in the future. With current taxi regulation and fixed pricing, the inconvenience of driving in bad traffic results in less taxis on the road. But with new entrants such as Uber able to charge more and adjust pricing at times of high demand, we might actually get more taxis or other vehicles on the road when we need them most. And we can have some comfort that when those taxis are needed most, there will be plenty of maximisers around to fill our need.

A week of links

Links this week:

  1. Was the paper proposing that mice can pass their fears onto their offspring and grandchildren via epigenetic mechanisms too good to be true? Neuroskeptic comments (and read the comments to Neuroskeptic’s post).  And my favourite epigenetics statement of the week: “Women too can succeed in business. Because epigenetics.”
  2. What are agent based models?
  3. The Bell Curve 20 years on.
  4. Genetic engineering will create the smartest humans who have ever lived.
  5. Is low fertility really a problem?

The invisible hand of Jupiter

I’m note sure how I hadn’t come across this before (one need only read the Wikipedia entry “invisible hand”), but Adam Smith used the phrase “invisible hand” three times. It is used once in The Theory of Moral Sentiments (1759) and The Wealth of Nations (1776) – both of those I knew. The third time comes from a posthumously published (1795) essay The History of Astronomy, written before The Theory of Moral Sentiments. Smith wrote:

For it may be observed, that in all Polytheistic religions, among savages, as well as in the early ages of heathen antiquity, it is the irregular events of nature only that are ascribed to the agency and power of the gods. Fire burns, and water refreshes; heavy bodies descend, and lighter substances fly upwards, by the necessity of their own nature; nor was the invisible hand of Jupiter every apprehended to be employed in those matters. But thunder and lightning, storms and sunshine, those more irregular events, were ascribed to his favour, or his anger. Man, the only designing power with which they were acquainted, never acts but either to stop, or to alter the course, which natural events would take, if left to themselves. Those other intelligent beings, whom they imagined, but knew not, were naturally supposed to act in the same manner; not to employ themselves in supporting the ordinary course of things, which went on of its own accord, but to stop, to thwart, and to disturb it. And thus, in the first ages of the world, the lowest and most pusillanimous superstition supplied the place of philosophy.

In this case, the invisible hand of Jupiter is the explanation that “savages” and those in “the early ages of heathen antiquity” apply to otherwise unexplainable irregular events. It isn’t much help in interpreting the other two uses.

HT: Jag Bhalla

Lazy analysis – inequality edition

Over at WSJ Real Time Economics, Josh Zumbrun turns the following chart into a claim that “the SAT is just another area in American life where economic inequality results in much more than just disparate incomes.”

SAT- Student Affluence Test

But what does the chart actually tell us? In a perfect meritocracy, the smartest students will score the highest. But as intelligence is heritable, the smarter kids will tend to have smarter and higher income patterns, giving us the pattern we see in the chart. In an alternative world where parents pay for results, we end up with the same pattern. So that charts tell us nothing. It’s consistent with both worlds.

I’m not exactly Robinson Crusoe in criticising this article. See also Arnold Kling and James Pethokoukis – although the assortative mating Pethokoukis refers to isn’t necessary to get a graph that looks like this, even though it is almost certainly playing a role.

Having picked on this article, the use of a bivariate analysis (a natural result of using a graph) while ignoring other confounding variables is a disappointingly common feature in the increasingly popular “data journalism”.

A week of links

Links this week:

  1. Plenty of press and interesting articles sparked by Peter Thiel’s new book. First, he has a swipe at business schools. And some great one-liners. But is he wrong about the future?
  2. Another tech-billionaire – Elon Musk wants to put people of Mars. But he doesn’t need one million people to get enough genetic diversity.
  3. Eric Crampton has some great posts this week on public health. First, where should the money be going?  Some thoughts on soda taxes and fat taxes. And drinking when pregnant.
  4. Cameron Murray risks walking onto Steven Landsburg’s lawn.
  5. Rajiv Sethi defends agent based models from Chris House. House tends to overreach when he strolls into the unfamiliar and attacks the heterodox rather than his standard (and also not overly convincing) defense of the orthodox.
  6. Put your laptops away kids.
  7. The missing heritability puzzle is slowing being chipped away. But the genetic post-modernists continue their losing battle.
  8. The heritability of educational attainment reflects many genetically influenced traits, not just intelligence. A Science Daily summary. Plus, emotional intelligence is overrated (HT: Stuart Ritchie). Intelligence is important, and to the extent other traits matter, they are heritable too.
  9. Does evolutionary theory need a rethink? No.
  10. Doctor decision fatigue – more unnecessary antibiotics in the afternoon.

A week of links

Links this week:

  1. The workplace is needed to overcome our lack of self control.
  2. Resisting instant gratification – the FT explores Walter Mischel’s the Marshmallow Test.
  3. Most critiques of twin studies recycle the same discredited 40-year-old arguments. Here’s another paper pulling them apart.
  4. The college educated are still getting married, just later. The same can’t be said for everyone else.
  5. A critique of the 10,000 hour rule. But people should not feel obliged to follow every mention of the role of genetics with an apology for war, slavery and genocide (surprised eugenics didn’t get a mention).
  6. People respond to prices on medical procedures. Demand curves still slope down.
  7. Your baby looks like your ex. Slightly disturbing.
  8. A collection of W. Brian Arthur papers on complexity in economics is due out at the end of the month.
  9. Matt Ridley reviews Steven Johnson’s book How We Got To Now.
  10. Neuroskeptic skewers claims that “this will change your brain”.
  11. Young, middle-aged and old men all want women in their 20s. But they’re realistic about what they can get.
  12. Academics writing stinks.
  13. French regulators are mad. Or at least a touch madder than the rest.