Tag Archives: Project

The Data We Need

Almost all research into human behavior focuses on particular behaviors. (Yes, not extremely particular, but also not extremely general.) For example, an academic journal article might focus on professional licensing of dentists, incentive contracts for teachers, how Walmart changes small towns, whether diabetes patients take their medicine, how much we spend on xmas presents, or if there are fewer modern wars between democracies. Academics become experts in such particular areas.

After people have read many articles on many particular kinds of human behavior, they often express opinions about larger aggregates of human behavior. They say that government policy tends to favor the rich, that people would be happier with less government, that the young don’t listen enough to the old, that supply and demand is a good first approximation, that people are more selfish than they claim, or that most people do most things with an eye to signaling. Yes, people often express opinions on these broader subjects before they read many articles, and their opinions change suspiciously little as a result of reading many articles. But even so, if asked to justify their more general views academics usually point to a sampling of particular articles.

Much of my intellectual life in the last decade has been spent in the mode of collecting many specific results, and trying to fit them into larger simpler pictures of human behavior. So both I and the academics I’m describing above in essence present themselves as using these many results presented in academic papers about particular human behaviors as data to support their broader inferences about human behavior. But we do almost all of this informally, via our vague impressionistic memories of what has been the gist of the many articles we’ve read, and our intuitions about what more general claims seem how consistent with those particulars.

Of course there is nothing especially wrong with intuitively matching data and theory; it is what we humans evolved to do, and we wouldn’t be such a successful species if we couldn’t at least do it tolerably well sometimes. It takes time and effort to turn complex experiences into precise sharable data sets, and to turn our theoretical intuitions into precise testable formal theories. Such efforts aren’t always worth the bother.

But most of these academic papers on particular human behaviors do in fact pay the bother to substantially formalize their data, their theories, or both. And if it is worth the bother to do this for all of these particular behaviors, it is hard to see why it isn’t be worth the bother for the broader generalizations we make from them. Thus I propose: let’s create formal data sets where the data points are particular categories of human behavior.

To make my proposal clearer let’s for now restrict attention to explaining government regulatory policies. We could create a data set where the datums are particular kinds of products and services that governments now provide, subsidize, tax, advise, restrict, etc. For such datums we could start to collect features about them into a formal data set. Such features could say how long that sort of thing has been going on, how widely it is practiced around the world, how variable has been that practice over space and time, how familiar are ordinary people today with its details, what sort of justifications do people offer for it, what sort of emotional associations do people have with it, how much do we spend on it, and so on. We might also include anything we know about how such things correlate with age, gender, wealth, latitude, etc.

Generalizing to human behavior more broadly, we could collect a data set of particular behaviors, many of which seem puzzling at least to someone. I often post on this blog about puzzling behaviors. Each such category of behaviors could be one or more data points in this data set. And relevant features to code about those behaviors could be drawn from the features we tend to invoke when we try to explain those behaviors. Such as how common is that behavior, how much repeated experience do people have with it, how much do they get to see about the behavior of others, how strong are the emotional associations, how much would it make people look bad to admit to particular motives, and so on.

Now all this is of course much easier said than done. Is it a lot of work to look up various papers and summarize their key results as entries in this data set, or just to look at real world behaviors and put them into simple categories. It is also work to think carefully about how to usefully divide up the space of actions and features. First efforts will no doubt get it wrong in part, and have to be partially redone. But this is the sort of work that usually goes into all the academic papers on particular behaviors. Yes it is work, but if those particular efforts are worth the bother, then this should be as well.

As a first cut, I’d suggest just picking some more limited category, such as perhaps government regulations, collecting some plausible data points, making some guesses about what useful features might be, and then just doing a quick survey of some social scientists where they each fill in the data table with their best guesses for data point features. If you ask enough people, you can average out a lot of individual noise, and at least have a data set about what social scientists think are features of items in this area. With this you could start to do some exploratory data analysis, and start to think about what theories might well account for the patterns you see.

Now one obvious problem with my proposal is that while it looks time consuming and tedious, it isn’t obviously impressive. Researchers who specialize in particular areas will complain about your data entries related to their areas, and you won’t be able to satisfy them all. So you will end up with a chorus of critics saying your data is all wrong, and your efforts will look too low brow to cower them with your impressive tech. So I can see why this hasn’t been done much. Even so, I think this is the data set we need.

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Imagine Libertopia

In this post I’ll talk primarily to people who, like me, lean libertarian. The rest of you can take a break.

Libertarians want to move more products and services from being provided directly by government, to being provided privately. And for those that are provided privately, libertarians want to weaken regulations. These changes would increase liberty.

Libertarians tend to offer arguments that are relatively abstract and theory-based. That is, they focus more on why more liberty is more moral, or why it should in theory give better outcomes. They focus less on showing that liberty has in practice worked out better. When libertarians do focus on data, they tend to be very broad, or randomly specific. That is, they talk about how West Germany is better than East Germany, or South Korea better than North Korea. Or they pick on very specific examples, like regulations limiting eyeglass ads, and leave audiences wondering how cherry-picked are such examples.

It seems to me that libertarians focus too much on trying to argue abstractly that liberty would be better, and not enough on just concretely describing how liberty would be different. Yes for you the abstract arguments seem best; they persuade you plenty, and they bring the most prestige in your circle. But typical libertarians today are a distinct personality type; most people are not like you. Most people just cannot be comfortable with a proposal for change if they cannot imagine it in some detail, and imagine that they’d like that detail. Such people don’t need more abstract arguments and examples; they instead credible concrete descriptions.

True, people have sometimes written fiction set in libertarian settings. But such fiction doesn’t usually come with a careful analysis of why one should believe in its many details. Yes, part of the attraction of liberty is that it frees up people to innovate in ways that one can’t anticipate in advance. But that doesn’t mean that we can’t go a long way to better describe a world of more liberty.

On reflection, I realize that when I try to imagine more liberty, I mostly draw on a limited set of iconic comparisons, such as comparing airlines, trucks, and phones before and after US deregulation, or comparing public to private schools and mail in the US. Alas, we and our audiences should worry that we cherry-pick such examples to support conclusions we like.

We should be able to do much better than this. By now there are vast literatures discussing many industries in many places before and after regulation or deregulation, and describing specific times and places where certain products and services provided directly by governments, or provided privately. From this vast literature we should be able to identify many concrete patterns and “stylized facts” about how government-provision and heavy-regulation tends to change products and services.

I recall these suggestions for typical features of industries with more liberty:

  1. Less “gold-plating” in materials and methods
  2. More product variety, including more low quality versions
  3. Faster innovation and product cycles
  4. Fewer guarantees to workers or customers
  5. Price, features vary more with customer features
  6. Workers have less school and seniority
  7. Less overhead spend on paperwork
  8. more?

Some people should work to extract patterns like these from our vast related literatures – I’ve looked, and there just aren’t many such summaries today. With such patterns in hand, we would be in a much better position to credibly describe how familiar products and services would concretely change if we were to provide them privately, or to regulate them less. And such credible concrete descriptions might allow many more people to become comfortable with endorsing such expansions of liberty.

This sort of project seems well within the abilities of the median grad student. It doesn’t require great creativity or technical skills. Instead, it just requires methodically surveying and summarizing related literatures. Perhaps some libertarian students should shy away from it in hopes of impressing via more difficult methods. But surely there must be other students for which this sort of project is a good match.

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The Why-Policy-Wiki











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Why National Med?








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Academic Blog Credit?

Martin Weller considers academic credit for blogs:

The answer to … whether new approaches such as blogging constitute scholarly activity, is an emphatic yes. Which leads us to a more problematic question: How should we recognize it? …

Tenure committees have increasingly come to rely upon journal-impact factors to act as a proxy for research quality. In short, we know what a good publication record looks like. But these criteria begin to creak and groan when we apply them to blogs and other online media. Simple metrics are subject to gaming, and because of the removal of the peer-review filter, may be meaningless anyway. I may have a YouTube clip of a skateboarding octopus with two million hits, but that doesn’t make it scholarly work.


… I’ve found that since becoming a blogger, I publish fewer journal articles, so it has had a “negative” impact on that aspect of my academic life. However, it has led to so many other unpredictable benefits—such as the establishment of a global peer network that helps me stay up to date with my topic, increased research collaboration, and more invitations to give talks—that it’s been worth the trade-off. (more)

Yes universities care about getting good and much “press”, but they are not willing to tenure professors merely for getting good press. The self-concept of professors only lets them give at most a minor weight to press, and sometimes the weight is negative.

The key difference is between getting attention vs. making impressive original intellectual contributions. Being cited by major news media, or having so many blog readers, can credential you as getting attention. But so far only journal articles, Ph.D. theses, and certain books and conference papers are accepted as credentials for impressive original intellectual contributions. For these, high quality experts are seen to judge the intellectual contribution.

Yes blog posts can contain impressive original intellectual contributions. Newspaper columns can contain them as well. So can speeches. Even spontaneous party conversations can contain them. The problem is, we don’t have systems set up for experts to evaluate these things in such terms. And if an intellectual contribution isn’t credentialed as such by academic experts, then it basically doesn’t exist as far as academia is concerned.

So either blogs will be continue to be seen mainly as a way to get “press” attention, or some folks will develop a system of expert evaluation of the intellectual contribution of blog posts. And as with academic journals, the main obstacle to doing that is: getting sufficiently prestigious academies to spend enough time doing their evaluations.

Now it turns out that many prestigious academic already read a lot of blog posts. So one approach would be to create a special “review” section where only prestigious academics can enter quick reviews of blog posts they read. Perhaps these reviews would be anonymous to the blog author and readers, and a more centralized part of the system would weigh their prestige, and degree of topical expertise, to compute a post evaluation.

But even with lots of new whizzy software support, it isn’t obvious you’d get enough reviews to make it work. People write reviews of journal articles in part because they hope doing so will favorably dispose editors toward their later submissions. People who write reviews of blog posts couldn’t have that motivation.

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Big Changes Test Econ

For students motivated by grades, ways to teach are limited by ways to test. No matter how insightful your lectures, grade-focused students will only attend to what it takes to pass your tests. So better ways to test give better ways to teach.

Economics is usually taught as a series of abstract concepts, and such concepts are usually tested in the abstract as well. Alas, this encourages neglect of how to apply abstract concepts to concrete situations.

Yes, one can instead ask concrete questions, about what would happen in the world if a specific social change were made. For example: what would happen if we discovered a huge new oil field? Problem is, there are many ways to guess at specific consequences without using abstract economic theory. People come to economics with lots of complex intuitions about how the social world works, or how it should work, so if you ask them specific questions they tend to use such intuitions instead of abstract concepts.

For example, lots of questions about changes within the usual range of experience can be answered merely by projecting observed trends, or by making analogies to similar situations. Yes, these are reasonable ways to guess at social consequences, but they can get in the way of assimilating economic concepts. Yes, tests can reward using abstract concepts, but even so it can be hard to get students into that habit.

A related problem is that small changes seem to have limited consequences. One might notice a few immediate consequences, but indirect consequences seem to quickly fade into “pretty much no effect” on more distant parts of society.

So to teach (and test) students to really apply economic concepts, it helps to consider concrete changes well outside of their usual range of experience. For changes that are big and dramatic enough, students can see the inadequacy of analogy and trend projection, and so are willing to look to abstract theory. And big changes more obviously have distant indirect effects.

My post yesterday on Tube Earth Econ was an example. If I ask you to estimate the social consequences of your planet having a very different shape, it is hard to make analogies to similar past events. That will push you more to go back to basic concepts and work from there.

I apply this concept in my masters level microeconomics course. One quarter of the grade is for this assignment:

Big Change Paper – Imagine a single big change to our economy, and then use microeconomics to describe the consequences of that change, including whether those changes are good or bad. You might, for example, imagine how things would be changed if people became immortal, if Star Trek style “transporters” were available, if very reliable lie detectors were available, or if no one needed sleep.

We talk about the consequences of similar big changes in class, to give students examples to follow in their papers. Such discussions and assignments are especially fun for people like me who enjoy science fiction and the drama of thinking about big dramatic social changes.

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Consulate Care




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Continuous Cooperation

In a prisoner’s dilemma, two sides have an incentive to defect, even though mutual defection is worse for both sides than mutual cooperation. It is well known that in theory and in reality people cooperate more when then expect to interact over more repetitions, and when they care more about the future.

It is hard to make people live longer, or care more about the future. It can be just as helpful, however, and often much easier, to make people interact more frequently. In the limit of continuous interaction, people should cooperate the most. My once co-author Ryan Oprea has a paper with Daniel Friedman in the latest AER, showing this:

We study [lab experiment] prisoners’ dilemmas played in continuous time with flow payoffs accumulated over 60 seconds. In most cases, the median rate of mutual cooperation is about 90%. Control sessions with repeated matchings over 8 subperiods achieve less than half as much cooperation, and cooperation rates approach zero in one-shot control sessions.

They introduce some new theory to explain details of this behavior:

Inspired by a strand of existing theoretical literature, we postulated a particular class of epsilon equilibria and derived formulas predicting how cooperation rates respond to adjustment lags and to payoff parameters. These predictions accounted well for the Continuous, Grid-8 and (trivially) One-Shot data. They also nicely explained a set of second-round data from Grid-n sessions, which varied the number of subperiods from 2 to 60. Thus the formulas correctly predict defection in one shot games, cooperation in continuous time and intermediate results on the path between the two. The underlying intuition is simple. When your opponent can react very quickly, defecting from mutual cooperation is likely to earn you the temptation paypoff only briefly and may cost you the cooperation payoff for the rest of the period.

So do online firms cooperate more when they can vary their prices more frequently? What rapidly-changeable actions would help nations to cooperate more?

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Farm vs Pet Medicine

We now spend a huge fraction of income on medicine. Today the US spends ~18% of GDP on medicine, while in 1940 we spent ~4%. Why the huge increase?

A supply explanation is that doctors have invented lots of new useful treatments. A demand explanation, in contrast, is that we want more medicine as we get richer, either because we care more about health, or about showing that we care.

One way to distinguish supply vs. demand explanations is to look at farm vs. pet animal medicine. Both kinds of animal medicine are treated similarly by most supply changes – new medical treatments help both kinds of animals. But most demand changes treat them differently – farm animals today aren’t that much more valuable than they were long ago, but we treat our pets as if they were far more valuable.

While I can’t find good historical data, what I do find suggests we’ve seen a huge switch in animal medicine, from a focus on food animals to a focus on pets. On recent pet med spending increases:


On vets long ago:

Very early veterinarians were mainly concerned with the care of livestock and horses and mules. … Prior to World War II, very few people would consider paying more than a token amount for the medical care of their pets any more than the average person today would consider taking an injured chipmunk to the vet. (more)

On the focus of US vets in 2011:


Thus much, perhaps most, of the rise in animal med spending is a demand effect. More careful data analysis might give a more precise estimate.

Now pets probably live to be older than farm animals, so a supply shock mainly relevant for older animals might explain an increase of pet med relative to farm animal med. But that seems pretty unlikely to be the main thing going on here.

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Virtual Office Design









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