andrew_gelman_stats andrew_gelman_stats-2011 andrew_gelman_stats-2011-1060 knowledge-graph by maker-knowledge-mining
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Introduction: Kaiser and I tell the story . Regular readers will be familiar with much of this material. We kept our article short because of space restrictions at American Scientist magazine. Now I want to do a follow-up with all the good stories that we had to cut. P.S. Let me remind everyone once again that Freakonomics (the book and the blog) has some great stuff. Kaiser and I are only picking on Levitt & co. because we know they could do so much better. P.P.S. Just to emphasize: our point that Freakonomics has mistakes is nothing new—see, for example, the articles and blogs by Felix Salmon, Ariel Rubenstein, John DiNardo, and Daniel Davies. The contribution of our new article is explore how it was that all these mistakes happened, to juxtapose the many strengths of the Freakonomics franchise (much of the work described in the first book but also a lot of what appears on their blog) with its failings. In some ways these contrasts are characteristic of social science research in
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1 Regular readers will be familiar with much of this material. [sent-2, score-0.115]
2 We kept our article short because of space restrictions at American Scientist magazine. [sent-3, score-0.079]
3 Let me remind everyone once again that Freakonomics (the book and the blog) has some great stuff. [sent-7, score-0.082]
4 Just to emphasize: our point that Freakonomics has mistakes is nothing new—see, for example, the articles and blogs by Felix Salmon, Ariel Rubenstein, John DiNardo, and Daniel Davies. [sent-13, score-0.112]
5 The contribution of our new article is explore how it was that all these mistakes happened, to juxtapose the many strengths of the Freakonomics franchise (much of the work described in the first book but also a lot of what appears on their blog) with its failings. [sent-14, score-0.402]
6 In some ways these contrasts are characteristic of social science research in general: a mix of careful assessment of assumptions (for example, in the use of instrumental variables analysis rather than simple comparisons to estimate causal effects) and casual storytelling. [sent-15, score-0.481]
7 ” story has an additional factor: Levitt’s somewhat unstable mix of skepticism and trust, as indicated by, on one hand, his self-labeling as a “rogue economist” and, on the other, his experiences as a corporate consultant and student and teacher at elite universities. [sent-17, score-0.493]
8 As we write: We attribute many of these errors to the structure of the authors’ collaboration, which, from what we can tell, relies on an informal social network that has many potential failure points. [sent-18, score-0.339]
9 In the original Freakonomics, much of whose content appeared originally in columns for the New York Times Magazine, the network seems to have been more straightforward: Levitt did the research, Dubner trusted Levitt, the Times trusted Dubner, and we the readers trusted the Times’s endorsement. [sent-19, score-1.024]
10 In SuperFreakonomics and the authors’ blog, it becomes less clear: Levitt trusts brilliant stars such as [software executive Nathan] Myhrvold or [economics professor Emily] Oster, Dubner trusts Levitt, and we the readers trust the Freakonomics brand. [sent-20, score-0.877]
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Introduction: Kaiser and I tell the story . Regular readers will be familiar with much of this material. We kept our article short because of space restrictions at American Scientist magazine. Now I want to do a follow-up with all the good stories that we had to cut. P.S. Let me remind everyone once again that Freakonomics (the book and the blog) has some great stuff. Kaiser and I are only picking on Levitt & co. because we know they could do so much better. P.P.S. Just to emphasize: our point that Freakonomics has mistakes is nothing new—see, for example, the articles and blogs by Felix Salmon, Ariel Rubenstein, John DiNardo, and Daniel Davies. The contribution of our new article is explore how it was that all these mistakes happened, to juxtapose the many strengths of the Freakonomics franchise (much of the work described in the first book but also a lot of what appears on their blog) with its failings. In some ways these contrasts are characteristic of social science research in
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Introduction: A friend/colleague sent me some comments on my recent article with Kaiser Fung on Freakonomics. My friend gave several reasons why he thought we were unfair to Levitt. I’ll give my reply (my friend preferred that I not quote his email, but you can get a general sense of the questions from my answers). But first let me point you to my original post, Freakonomics 2: What went wrong? , from a couple years ago, in which I raised many of the points that ultimately went into our article. And here’s my recent note. (I numbered my points, but the email I was replying to was not numbered. This is not a point-by-point rebuttal to anything but rather just a series of remarks.) 1. Both Kaiser and I are big fans of Freakonomics. It’s only because Levitt can (and has) done better, that we’re sad when he doesn’t live up to his own high standards. If we didn’t convey this sense of respect in our American Scientist article, that is our failing. 2. I think it was at best tacky and
Introduction: Jonathan Cantor pointed me to a new blog post by Stephen Dubner in which he expresses disagreement with what Kaiser and I wrote in our American Scientist article , “Freakonomics: What Went Wrong?”. In response, I thought it would be interesting to go “meta” here by considering all the different ways ways that I could reply to Dubner’s criticism of our criticism of his writings. (In the same post, Dubner also slams Chris Blattman (or, as he calls him, “a man named Chris Blattman”), but I won’t get into that here.) In reacting to Dubner, I will give several perspectives, all of which I believe . Usually in writing a response, one would have to choose, but here I find it interesting to present all these different perspectives in one place. 1. Understand. I understand where Dubner is coming from. We say some positive things and some negative things about his work, but it’s natural for him to focus on the negative. I’m the same way myself, probably almost all autho
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Introduction: Responding to journalist Elizabeth Kolbert’s negative review of Freakonomics 2 in the New Yorker, Stephen Dubner writes , that, although they do not have any training in climate science, it’s also the case that: Neither of us [Levitt and Dubner] were Ku Klux Klan members either, or sumo wrestlers or Realtors or abortion providers or schoolteachers or even pimps. And yet somehow we managed to write about all that without any horse dung (well, not much at least) flying our way. But Levitt is a schoolteacher (at the University of Chicago)! And, of course, you don’t have to be a sumo wrestler to be (some kind of an) expert on sumo wrestling, nor do you have to teach in the K-12 system to be an expert in education, nor do you have to provide abortions to be an expert on abortion, etc. And Levitt has had quite a bit of horse dung thrown at him for the abortion research. The connection is that abortion and climate change matter to a lot of people, while sumo wrestling and pimps and
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Introduction: Stephen Dubner writes : Freakonomics Experiments is a set of simple experiments about complex issues—whether to break up with your significant other, quit your job, or start a diet, just to name a few. . . . a collaboration between researchers at the University of Chicago, Freakonomics, and—we hope!—you. Steve Levitt and John List, of the University of Chicago, run the experimental and statistical side of things. Stephen Dubner, Steve Levitt, and the Freakonomics staff have given these experiments the Freakonomics twist you’re used to. Once you flip the coin, you become a member of the most important part of the collaboration, the Freakonomics Experiments team. Without your participation, we couldn’t complete any of this research. . . . You’ll choose a question that you are facing today, such as whether to quit your job or buy a house. Then you’ll provide us some background information about yourself. After that, you’ll flip the coin to find out what you should do in your situati
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Introduction: Jonathan Cantor pointed me to a new blog post by Stephen Dubner in which he expresses disagreement with what Kaiser and I wrote in our American Scientist article , “Freakonomics: What Went Wrong?”. In response, I thought it would be interesting to go “meta” here by considering all the different ways ways that I could reply to Dubner’s criticism of our criticism of his writings. (In the same post, Dubner also slams Chris Blattman (or, as he calls him, “a man named Chris Blattman”), but I won’t get into that here.) In reacting to Dubner, I will give several perspectives, all of which I believe . Usually in writing a response, one would have to choose, but here I find it interesting to present all these different perspectives in one place. 1. Understand. I understand where Dubner is coming from. We say some positive things and some negative things about his work, but it’s natural for him to focus on the negative. I’m the same way myself, probably almost all autho
Introduction: Steven Levitt writes :. Diamond often would fall asleep in seminars, often for large chunks of time. What was amazing, however, is that he would open his eyes and then make by far the most insightful comment of the entire seminar! Now that we have n=2 [see the first part of the title of this blog entry], I’m wondering . . . maybe this sort of thing is more common than Levitt and I had realized. P.S. Levitt also writes: The one thing that puzzles me [Levitt] is why in the world would he want to be on the Board of the Federal Reserve? One thing economists just don’t understand are people’s preferences. To get meta here for a moment . . . just as Levitt can’t understand Diamond’s preferences, I find it extremely difficult to understand that Levitt is puzzled by Diamond’s desire to serve on the Federal Reserve, It’s obvious, no? Diamond has expertise on macroeconomics and, I assume, some strong and well-informed opinions on monetary policy; the Federal Reserve determ
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Introduction: In his review in 1938 of Historical Development of the Graphical Representation of Statistical Data , by H. Gray Funkhauser, for The Economic Journal , the great economist writes: Perhaps the most striking outcome of Mr. Funkhouser’s researches is the fact of the very slow progress which graphical methods made until quite recently. . . . In the first fifty volumes of the Statistical Journal, 1837-87, only fourteen graphs are printed altogether. It is surprising to be told that Laplace never drew a graph of the normal law of error . . . Edgeworth made no use of statistical charts as distinct from mathematical diagrams. Apart from Quetelet and Jevons, the most important influences were probably those of Galton and of Mulhall’s Dictionary, first published in 1884. Galton was indeed following his father and grandfather in this field, but his pioneer work was mainly restricted to meteorological maps, and he did not contribute to the development of the graphical representation of ec
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Introduction: A couple things in this interview by Andrew Goldman of Larry Summers currently irritated me. I’ll give the quotes and then explain my annoyance. 1. Goldman: What would the economy look like now if $1.2 trillion had been spent? Summers: I think it’s an artificial question because there would have been all kinds of problems in actually moving $1.2 trillion dollars through the system — finding enough bridge projects that were ready to go and the like. But the recovery probably would have proceeded more rapidly if the fiscal program had been larger. . . . 2. Goldman: You’re aware of — and were making light of — the fact that you occasionally rub people the wrong way. Summers: In meetings, I’m more focused on trying to figure out what the right answer is than making everybody feel validated. In Washington and at Harvard, that sometimes rubs people the wrong way. OK, now my reactions: 1. Not enough bridge projects, huh? I don’t believe it. We’ve been hearing fo
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