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Guest: And particularly in the world that you are describing, which is full of interested parties and advocates. In some cases it's ideological, but often it's commercial or it's based on some sort of faith in particular strategies. So, in the education world there's no end of approaches to schools that people are strongly committed to, not based on the evidence but based on a belief about how students learn or perhaps they even have a product to sell--we see that in the case of computer-aided instruction. In the developing country world, you have many actors, philanthropists, governments, non-governmental agencies, who have an idea to sell. Maybe it's smaller family size; maybe it's a particular kind of social organization. Maybe it's a particular technology. And it's very useful for an outside party to come in and say, 'let's take a look at this.' A great example recently is the surge in enthusiasm for computers in early education in developing countries. Many, many people became convinced--and I'm talking about politicians and policy makers and scientists--that it would be extraordinarily beneficial to put laptops or iPads in the hands of young kids in, say, Peru or Thailand or someplace like that. And others came and looked at that. In some cases, the idea that we should look at it was resisted. But we have good experimental evidence that that's probably not going to improve outcomes in those settings.
Russ:But in so many cases--this is tragedy, this is to be warned[?], not celebrated--a particular experiment which has statistical significance--when I say--my worry about sample size, it's not a moral issue. It's the question of whether you've sufficiently randomized across the unobservable variable that you can't control for; and therefore it's always possible that what you have measured is not really there. A lot of times, those studies don't replicate when they go try to find the results. Now, agreed, it's nice to open a question and it's nice to look at it. But I find it fascinating how often those results don't replicate. And that's a problem of development in randomized trials in poor countries. It's an enormous problem in epidemiology, where they often have enormous samples but they still have results that cannot be replicated on different samples or across different types of people or different cultures. And yet, the results that were established initially become waved around. An example was recently written about in the New Republic, the enthusiasm for deworming in Africa that seems perhaps, based on a followup study--and maybe it's not a good study--they suggest that many of those studies do not get repeated. There's not benefits from deworming, for student performance in education. So, that's--I'm not suggesting we shouldn't do empirical work. I'm suggesting that we should be much more humble about its reliability.
Guest: I'm all for humble. I think it's important not to throw the baby out with the bathwater. The idea that findings can be misleading--you know, I'm the first to say that. And I'm known for being a harsh critic on other people's empirical work, and I try to apply the same standards to my own work. I don't agree with the sort of nihilistic proposition that nothing is ever learned, that it's all for naught.
Russ: It's depressing, isn't it?
Guest: No. I'm not depressed.
Russ: Nod, it would be, if it were true. If it were true.
Guest: I think there are a lot of people who are sort of retreating into that. I'm not sure why. Again, don't let the perfect be the enemy of the good. And try to keep some perspective. I was at a conference that the Center for Open Science sponsored. And most of the studies that seemed to generate the majority of the handwringing that we saw at that conference came from psychology, where there would be a small sample and there would be kind of a quirky finding. And I would have said, why did you pay any attention to that, anyway? And you know, you are probably right that the Atlantic likes that sort of thing--
Russ: Yup; New York Times. They make the front page--
Guest: Somebody does a little study about men and women do this or that--women are actually more competitive than men--
Russ: Better investors, whatever it is--
Guest: Under the right circumstances, men will eat their children. Or some wacky psychological thing. It doesn't concern me too much. I'm not sure that there's any policy that's reacting to that. I think in some sense that's just kind of a consumption good. It's lots of fun. I like to read it by myself.
Russ: Find what's wrong with it. Yeah. Point out what's wrong with it. I understand.
Guest: I would worry if everything we do turns out to be wrong, perhaps because the researchers are dishonest or manipulating results. That's not my impression, though.
Russ: No; I think the bigger worry is that they are honest, and either they are fooling themselves or they are unintentionally fooling others about the reliability of the work. It's a lot more important, I think, to understand what happens when you spend $780-$805 or whatever it turned out to be, billion dollars on stimulus or whether you have helped or hurt the lowest skilled people with an increase in the minimum wage. There's a lot more at stake.
Guest: Right. But there are plenty of examples where there's a body of work emerging. So, you know, in labor, it's certainly been hard in repeated good efforts to find dis-employment effects of the minimum wage. I'm not saying that's the end of the story. It's been hard in repeated efforts, mostly based on random assignment, to find training programs that are very likely to support the lower tail of the income distribution in any substantial way. It's been relatively easy in repeated efforts to find strong evidence that schooling boosts earnings. There's quite a few findings out there that are worth paying attention to and worth taking account of when it comes time to make policy.
Russ: Well, I think learning boosts earnings. I don't think we've been very good at proving that schooling does. I think that's a big challenge, especially in poor countries, and Lant Pritchett's work I think is very alarming and probably true.
Guest: Well, you need to read Chapter 6 of Mastering 'Metrics. Which is all about the relationship between schooling and earnings. And we trace the history of that question. And we go through the evidence and we explain why the picture that emerges there is reasonably convincing.
Russ: Well, sometimes knowledge is correlated with schooling. I don't deny it.
Russ: Let's close--
Guest: No, but I'm talking about the effect of schooling on earnings specifically. Measured schooling and earnings. That's what Chapter 6 in Mastering 'Metrics is about.
Russ: Right but a huge part of that--
Guest: And we use that as a question to walk the reader through our application of our serious 5 econometric techniques. And, not every study is equally well done. But there's a body of evidence there that's worth taking a serious look at.
Russ: Oh, I totally agree with you. But again, I'm not blaming you for this; the fact that it has led to billions--to say billions of dollars being spent on schooling in poor countries with no impact is tragic. And that's not your fault; it's not the fault of that literature; it's not the fault that that literature doesn't apply to certain countries and settings. And the fact that, say, schooling and education are not always correlated. But I agree with you: when they are, there's no doubt it has an impact. I think people, even without economics degrees, believe it, and believed it before we quantified it.
Russ:Let me close with a philosophical question, because we're out of time. Your paper is a [?] paper. It's a paper of an evangelist. And I have a lot of respect for what you do. The fact that I don't agree with every jot and tiddle of it is not relevant; and I'm not your target audience, anyway. But, I'm Diane Ravitch in econometrics to your econometrics writings. But, Leamer and Sims, who are critical in response to your paper, are remarkably unconvinced of the credibility revolution. And by the way, we're going to put up links to all these papers. As well as to your book and anything else you want to share with us. But, why do you think you've made so little headway with that audience? Is it their biases? Or is it your flavor that's not appealing to them? They don't find--again, I'm irrelevant. But they are not convinced. Why do you think they are not convinced, and do you think that will change over the next 20, 30 years as the next generation of graduate students comes out?
Guest: You know, I don't know why they are not convinced. But I guess, with all due respect to Leamer and Sims, I'm not too concerned with whether they are convinced. Mostly Harmless Econometrics, I think it's fair to say, has had a huge influence on graduate education. It sold about 50,000 copies--this is a graduate textbook in a specialized field. It's a source of discussion; it's widely cited. It's a reference point in scholarly work in Ph.D. programs all over the country. That's the measure of our success, what Ph.D. students are learning and what young faculty are doing. And I think by that standard, we're winning.
Russ: Right; but I'm asking a different question, which is: Should you be? You are of course going to be happy that your book is popular; and of course graduate students are going to flock to books that tell them that they are going to change the world and save it and make it better and that they have the tools to do so. But maybe you are not right. Maybe you are overly confident. And Leamer and Sims are saying, 'Whoa.' And you are saying they don't matter? Is it just that they are stubborn? They don't get it?
Guest: Yeah; I don't really want to personalize it. Obviously we convince some people and others are not convinced. I think there's a lot of good empirical work today, and if we had a lot more time, we could go through it. We've mentioned some of it that's convincing, that's worth taking note of when it comes time to make policy. In my area on schools I see two sorts of consensus emerging. One is that a certain type of charter school seems to be extraordinarily effective in urban districts. Another is that teachers matter both for achievement and earnings in the longer run. That's convincing work. It matters to scholars and it matters for policy. I think there are more examples like that today than there were when I was in graduate school in the 1980s.
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