Seth's Blog

• An Epidemic of Absence (book about allergies and autism)
• Professor of medicine who studies medical error loses a leg due to medical error. “Despite calls to action by patient advocates and the adoption of safety programs, there is no sign that the numbers of errors, injuries and deaths [due to errors] have improved.” Nothing about consequences for the person who made the error that caused him to lose a leg.
• Doubts about spending a huge amount of research money on a single project (brain mapping). Which has yet to produce even one useful result.
• Cancer diagnosis innovation by somebody without a job (a 15-year-old)
• Someone named Rob Rhinehart has greatly reduced the time and money he spends on food by drinking something he thinks contains all essential nutrients. Someone pointed out to him that he needs bacteria, which he doesn’t have. (No doubt several types of bacteria are best.) He doesn’t realize that Vitamin K has several forms. I suspect he’s getting too little omega-3. This reminds me of a man who greatly reduced how much he slept by sleeping 15 minutes every 3 hours. It didn’t work out well for him (his creativity vanished and he became bored and unhappy). In Rhinehart’s case, I can’t predict what will happen so it’s fascinating. When something goes wrong, however, I’ll be surprised if he can figure out what caused the problem.

Thanks to Amish Mukharji.

Two thought-provoking paragraphs from Matt Ridley:

From ancient Egypt to modern North Korea, always and everywhere, economic planning and control have caused stagnation; from ancient Phoenicia to modern Vietnam, economic liberation has caused prosperity. In the 1960s, Sir John Cowperthwaite, the financial secretary of Hong Kong, refused all instruction from his LSE-schooled masters in London to plan, regulate and manage the economy of his poor and refugee-overwhelmed island. Set merchants free to do what merchants can, was his philosophy. Today Hong Kong has higher per capita income than Britain.

In July 1948 Ludwig Erhard, director of West Germany’s economic council, abolished food rationing and ended all price controls on his own initiative. General Lucius Clay, military governor of the US zone, called him and said: “My advisers tell me what you have done is a terrible mistake. What do you say to that?” Erhard replied: “Herr General, pay no attention to them! My advisers tell me the same thing.” The German economic miracle was born that day; Britain kept rationing for six more years.

This is standard libertarianism. I like the stories but I don’t agree with the interpretation. I don’t think it is “economic planning and control” that causes stagnation in these examples.  I believe  it is expertise — more precisely, rent-seeking experts who know too little and extract too much rent. There are libertarian experts, too. They too are capable of doing immense damage (e.g., Alan Greenspan), contradicting Ridley’s view that “economic liberation” always causes  prosperity. In both of Ridley’s examples, the experts give advice that empowers the experts. In the first example, Cowperthwaite is told by “LSE-schooled” economists to “plan, regulate and manage the economy.” All that planning, regulation and management require expertise, in particular expertise similar to that of the experts who advised it. Which you cannot buy — you have to rent it. You must pay the experts year after year after year to plan, regulate, and manage. Because the advice must empower the experts, there is  a strong bias away from truth. That is the fundamental problem. (more…)

Is online teaching (e.g., MOOC) a big deal? In an essay (“Why Online Education Works”), Alex Tabarrok argues for the value of online education (meaning online lectures) compared to traditional lectures. A friend told me yesterday that MOOC was “a frontier of pedagogy”. No doubt online lectures will make lecture classes cheaper and more available. Lots of things have gone from scarce/expensive to common/cheap. With things whose effects we understand (e.g., combs), the result is straightforward: more people benefit. With things whose effects we don’t understand, the results are less predictable. Did the spread of sugar help us? Hard to say. Did the spread of antibiotics help us? Hard to say.  It may have helped sustain simplistic ideas about what causes disease (e.g., “acne is caused by bacteria”, “ulcers are caused by bacteria”) reducing effective innovation. Do we have a good idea of the effects of lectures (or their lack of effect), or a good theory of college education? I don’t think so. Could their spread help sustain simplistic ideas about education? Maybe. (more…)

If you open the American edition of Forbes, you will find articles about the richest people in America. If you open the Russian edition, you will find articles about the richest people in Russia. If you open the Chinese edition, you will find articles about the richest people in America.

A Russian friend of mine noticed this. He happened to know an sophomore economics major at Tsinghua. It is incredibly difficult to get into Tsinghua and the economics major is the most desirable major of all. To be an economics major at Tsinghua you need a test score that is in something like the top 1 out of 100,000. Staggeringly high. My Russian friend asked the Tsinghua economics major, “Who is the richest person in China?”

The economics major didn’t know. He seemed a little angry. “Why should I know? We’ve never been taught that,” he said.

Tyler Cowen links to a paper by Frank Lichtenberg, an economist at Columbia University, that tries to estimate the benefits of drug company innovation by estimating how much new drugs prolong life compared to older drugs. The paper compares people equated in a variety of ways except the “vintage” (date of approval) of the drugs they take. Does taking newer drugs increase life-span? is the question Lichtenberg wants to answer. He concludes they do. He says his findings “suggest that two-thirds of the 0.6-year increase in the life expectancy of elderly Americans during 1996-2003 was due to the increase in drug vintage” — that is, to newer drugs.

An obvious problem is that Lichtenberg has not controlled for health-consciousness. This is a standard epidemiological point. People who adopt Conventional Healthy Behavior X (e.g., eat less fat) are more likely to adopt Conventional Healthy Behavior Y (e.g., find a better doctor) than those who don’t. For example, a study found that people who drink a proper amount of wine eat more vegetables. Another reason for a correlation between conventionally-healthy practices is mild depression. People who are mildly depressed are less likely to do twenty different helpful things (including “eat healthy” and “find a better doctor”) than people who are not mildly depressed. (And mild depression seems to be common.) Perhaps doctors differ. (Lichtenberg concludes there are big differences.) Perhaps better doctors (a) prescribe more recent drugs and (b) do other things that benefit their patients. Lichtenberg does not discuss these possibilities.

A subtle problem with Lichtenberg’s conclusion that we benefit from drug company innovation is that drug-company-like thinking — the notion that health problems should be “solved” with drugs — interferes with a better way of thinking: the notion that to solve a health problem, we should find out what aspects of the environment cause it. I suppose this is why we have Schools of Public Health — because this way of thinking, advocated at schools of public health, is so incompatible with what is said and done at medical schools. Public health thinking has a clear and impressive track record — for example, the disappearance of infectious disease as a major source of death. There are plenty of other examples: the drop in lung cancer after it was discovered that smoking causes lung cancer, the drop in birth defects after it was discovered that folate deficiency causes birth defects. Thinking centered on drugs has done nothing so helpful. Spending enormous amounts of money to develop new drugs shifts resources away from more cost-effective research: about environmental causes and prevention. Someone should ask the directors of the Susan K. Komen Foundation: Why “race for the cure”? Wouldn’t spending the money on prevention research save more lives?

• On using patents to measure innovation. Fails to ask if using patents to measure innovation is better than nothing.
• Kimchi basics. “So much depth of flavor.”
• Reubin Andres, important weight control researcher, dies. “For some reason the idea has grabbed us that the best weight throughout the life span is that of a 20-year-old,” Dr. Andres said in a 1985 interview with The New York Times. “But there’s just overwhelming evidence now that as you go through life, it’s in your best interests to lay down some fat.”
• Margaret Wente, Globe & Mail columnist and serial something or other. Wente defends herself, plus 1922 comments, few or none of which support her. For example, “Apparently Margaret thinks that a compilation of her journalistic lapses is irrelevant if the person documenting them over time and bringing them to light is a person she doesn’t like.” More comment on Wente. Another Globe & Mail columnist uses her column to sell her house. The Globe & Mail is the New York Times of Canada.

Thanks to Rashad Mahmood.

Ecologists understand the exploit/explore distinction. When an animal looks for food, it can either exploit (use previous knowledge of where food is) or explore (try to learn more about where food is). With ants, the difference is visible. Trail of ants to a food source: exploit. Solitary wandering ant: explore. With other animals, the difference is more subtle. You might think that when a rat presses a bar for food, that is pure exploitation. However, my colleagues and I found that when expectation of food was lower, there was more variation — more exploration — in how the rat pressed the bar. In a wide range of domains (genetics, business), less expectation of reward leads to more exploration.  In business, this is a common observation. For example, yesterday I read an article about the Washington Post that said its leaders failed to explore enough because they had a false sense of security provide by their Kaplan branch. “Thanks to Kaplan, the Post Company felt less pressure to make hard strategic choices—and less pressure to venture in new directions,” wrote Sarah Ellison.

Striking the right balance between exploitation and exploration is crucial. If an animal exploits too much, it will starve when its supply of food runs out. If it explores too much, it will starve right away. Every instance of collapse in Jared Diamond’s Collapse: How Socieities Choose to Fail or Succeed was plausibly due to too much exploitation, too little exploration (which Diamond, even though he is a biologist, fails to say). I’ve posted several times about my discovery that treadmill walking made studying Chinese more pleasant. I believe walking creates a thirst for dry knowledge. My evolutionary explanation is that this pushed prehistoric humans to explore more.

I have never heard an economist make this point: the need for proper balance between exploit and explore. (more…)

Shortly before Obama took office, many American banks, including the largest ones, were given a huge amount of money by the Federal government (“bailed out”). Why? Because Secretary of the Treasury Henry Paulson, Chairman of the Federal Reserve Ben Bernanke and other economists (not necessarily independent of Paulson and Bernanke) predicted a second Great Depression if they weren’t. I didn’t believe Paulson et al. — their track records of prediction were terrible. They hadn’t foreseen the crisis. Why should I think they knew how to fix it? I believed their predictions of disaster were too confident.

At the time I didn’t know this bit of history:

The blood-curdling threats [now] being issued by Eurocrats should sound familiar to British readers. We went through precisely the same experience 20 years ago, when we were stuck with an over-valued exchange rate in the Exchange Rate Mechanism.

As in Greece, our leaders – all the main parties, the CBI, the TUC, the Bank of England – assured us that leaving the ERM would be disastrous. On September 11, 1992, John Major solemnly told us that withdrawal was ‘the soft option, the inflationary option, the devaluer’s option, a betrayal of our country’s future’.

Four days later, we left the system, and our recovery began immediately. Inflation, interest rates and unemployment started falling, and we enjoyed 15 years of unbroken growth

Those who don’t know the past are doomed to over-trust experts.

In a Planet Money show about whether Super Bowls help host cities, a sports economist named Victor Matheson, a professor at College of the Holy Cross, described himself and other sports economists:

We’re economists. And we’re concerned about equity and we’re concerned about efficiency. And what most economists see . . . “

He didn’t say “We’re concerned about innovation”. The way he ignores innovation reflects the whole field of economics. Here’s the same thing from Christine Romer. In an editorial about whether manufacturing deserves special treatment, she considers only productivity and equity:

It might be better to enact policies that will make all American businesses and workers more productive and successful. . . Today, we face a profound shortfall of demand. . . .We need actions that raise overall demand. [She doesn't say we are in a period of profound stagnation in most industries, which is also true.] . . . More aggressive monetary policy that lowered the price of the dollar would stimulate all our exports . . . Moving is very costly for dislocated workers with ties to their communities. . . Manufacturing jobs are seen as one of the few sources of well-paying jobs for less-educated workers. . . . Public policy . . . should be based on hard evidence of market failures, and reliable data on the proposals’ impact on jobs and income inequality.

As if innovation (and lack of it) don’t exist. Here’s an example from Robert Reich, in a post “rebut[ing] the seven biggest economic lies”:

Shrinking government generates more jobs. Wrong again. It means fewer government workers – everyone from teachers, fire fighters, police officers, and social workers at the state and local levels to safety inspectors and military personnel at the federal. And fewer government contractors, who would employ fewer private-sector workers. According to Moody’s economist Mark Zandi (a campaign advisor to John McCain), the $61 billion in spending cuts proposed by the House GOP will cost the economy 700,000 jobs this year and next.

Nothing about the effect of shrinking government on innovation. Many types of innovation increase jobs.

This is like doctors ignoring the immune system. Ignoring the effect of this or that policy on innovation is likely to lead to decisions that reduce innovation in favor of something easier to measure or defend, such as productivity or equity. The cumulative effect of ignoring innovation is stagnation and decline, caused by problems that got worse and worse as, due to lack of innovation, they failed to be solved.

Tyler Cowen (The Great Stagnation) and Alex Tabarrok (Launching the Innovation Renaissance) are absolutely right to focus on innovation and the lack of it. The obesity epidemic is 30 years old — a good example of a problem that has gotten worse and worse. Judging by Tara Parker-Pope’s reporting, mainstream weight researchers don’t have a clue — in the form of empirical results — how to solve it. Outside mainstream academia, the dominant weight-loss idea is a low-carb diet. That idea is a hundred years old (Banting). How little innovation there has been. That Parker-Pope failed to criticize researchers for their lack of progress shows how deep the problem is. She appears not to grasp the possibility.

In the latest issue of American Scientist, Andrew Gelman (an old friend) and Kaiser Fung criticize Freakonomics and Superfreakonomics by Steve Levitt and Stephen Dubner (who wrote about my work). Although the article is titled “Freakonomics: What Went Wrong?” none of the supposed errors are in Freakonomics. You can get an idea of the conclusions from the title and this sentence: “How could an experienced journalist and a widely respected researcher slip up in so many ways?”

Gelman and Fung examine a series (“so many ways”) of what they consider mistakes. I will comment on each of them.

1. The case of the missing girls. I agree with Gelman and Fung: Levitt and Dubner accepted Emily Oster’s research too uncritically.

2. The risk of driving a car. I think Gelman and Fung miss the point. Yes, the claim (driving drunk is safer than walking drunk) was not well-supported by the evidence provided because the comparison was so confounded. However, I read the whole example differently. I didn’t think that Levitt and Dubner thought drunk people should drive. I thought their point was more subtle — that comparisons are difficult (“look how we can reach a crazy conclusion”).

3. Stars are made not born. I think Gelman and Fung fail to see the big picture. The birth-month effect in professional sports, which Gelman and Fung dismiss as “very small,” is of great interest to many people, if not to Gelman and Fung.  It suggests what Levitt and Dubner and Gladwell and others say: Early success matters. That’s not obvious at all. There are lots of similar associations in epidemiology. They have been the first evidence for many important conclusions, such as smoking causes lung cancer. Are professional sports important? Maybe. But epidemiology and epidemiological methods are surely important. By learning about this effect, we learn about them. Lots of smart people fail to take epidemiology seriously enough (e.g., “correlation does not equal causation”).

4. Making the majors and hitting a curve ball. Gelman and Fung point out that one sentence is misleading. One sentence. This is called praising with faint damn.

5. Predicting terrorists. Gelman and Fung say that the terrorist prediction algorithm of a man named Ian Horsley, which Levitt and Dubner seem to take seriously, is not practical. But their review fails to convince me it was presented as practical. Since there are no data about how well the algorithm works, and Levitt and Dubner are all about data….

6. The climate change dust-up. I agree with Gelman and Fung that Nathan Myrvold’s geoengineering ideas are unimportant. (My view of Myrvold’s patent trolling.)  But in this case, I’d say both sides — Gelman and Fung and Levitt and Dubner — miss what’s really important, namely that the usual claims that humans are dangerously warming the planet are held far too strongly. The advocates of this view are far too sure of themselves. I have blogged about this many times. In a nutshell, the climate models that we are supposed to trust have never been shown to persuasively predict the climate ten or twenty years from now (or even one year from now). There is no good reason to believe them. That Levitt and Dubner seem to take that stuff seriously is the only big criticism I have of their work . At least in that geoengineering stuff Levitt and Dubner were dissenting from conventional wisdom. Gelman and Fung do not. They fail to realize that something we’ve been told thousands of times is nonsense (in the sense of being wildly overstated). It was Levitt and Dubner’s comments about this that led me to look closely at all that climate-change scare stuff. I was surprised how poor the evidence was.

The biggest problem with Gelman and Fung’s critique is that they say nothing about the great contribution of Steve Levitt to economics. They fail to grasp that he has made economics considerably more of a science, if by science you mean a data-driven enterprise as opposed to an ideologically-driven or prestige-driven one (mathematics is prestigious, the more difficult, the more prestigious). He did so by pioneering a new way to use data to learn interesting things. His method is essentially epidemiological, except his methods are considerably better (better matching, less formulaic) and his topics much more diverse (e.g., sumo wrestling) than mainstream epidemiology. A large fraction of prestige economics is math, divorced from empirical tests. This stuff wins Nobel Prizes, but, in my and many other people’s opinion, contributes very little to understanding. (Psychology has had the same too much math, too little data problem — minus the Nobel Prizes, of course.) To persuade a big chunk of an entire discipline to pay more attention to data is a huge accomplishment.

Levitt’s methodological innovation makes Freakonomics far from what Gelman and Fung call “pop statistics”. It is actually an amusing and well-written record of something close to a revolution. In the 1980s, a friend of mine at UC Berkeley took an introductory economics class. She told me a little of what the teacher said in class. All theory. What about data? I said. It’s a strange science that doesn’t care about data. My friend went to office hours. She asked the instructor (a Berkeley economics professor): What about data? Don’t worry about data, he replied. Gelman and Fung fail to appreciate what economics used to be like. The ratio of strongly-asserted ideas to persuasive data used to be very large. Now it is less.

Thanks to Ashish Mukharji.