Tom Daula points us to this article, “Mortgage-Backed Securities and the Financial Crisis of 2008: A Post Mortem,” by Juan Ospina and Harald Uhlig. Not our usual topic at this blog, but then there’s this bit on page 11: We break down the analysis by market segment defined by loan type (Prime, Alt-A, and Subprime). […]
The post The AAA tranche of subprime science, revisited appeared first on Statistical Modeling, Causal Inference, and Social Science.
Michael Masinter writes: As a longtime blog reader sufficiently wise not to post beyond my academic discipline, I hope you might take a look at what seems to me to be a highly controversial attempt to use regression analysis to blame the ACLU for the recent rise in homicides in Chicago. A summary appears here […]
The post Understanding Chicago’s homicide spike; comparisons to other cities appeared first on Statistical Modeling, Causal Inference, and Social Science.
Nudge unto others as you would have them nudge unto you. Do not recommend to apply incentives to others that you would not want for yourself. Background I was reading this article by William Davies about Britain’s Kafkaesque immigration policies. The background, roughly, is this: Various English politicians promised that the net flow of immigrants […]
The post The Golden Rule of Nudge appeared first on Statistical Modeling, Causal Inference, and Social Science.
Joseph Delaney points to a post by Kevin Drum pointing to a post by Bob Somerby pointing to a magazine article by Natalie Wexler that reported on the latest NAEP (National Assessment of Educational Progress) test results. In an article entitled, “Why American Students Haven’t Gotten Better at Reading in 20 Years,” Wexler asks, “what’s […]
The post Rising test scores . . . reported as stagnant test scores appeared first on Statistical Modeling, Causal Inference, and Social Science.
In econometrics, or applied economics, a “placebo test” is not a comparison of a drug to a sugar pill. Rather, it’s a sort of conceptual placebo, in which you repeat your analysis using a different dataset, or a different part of your dataset, where no intervention occurred. For example, if you’re performing some analysis studying […]
The post A potential big problem with placebo tests in econometrics: they’re subject to the “difference between significant and non-significant is not itself statistically significant” issue appeared first on Statistical Modeling, Causal Inference, and Social Science.
Back in 2013, I wrote a post regarding a controversial claim that high genetic diversity, or low genetic diversity, is bad for the economy: Two economics professors, Quamrul Ashraf and Oded Galor, wrote a paper, “The Out of Africa Hypothesis, Human Genetic Diversity, and Comparative Economic Development,” that is scheduled to appear in the American […]
The post A couple more papers on genetic diversity as an explanation for why Africa and remote Andean countries are so poor while Europe and North America are so wealthy appeared first on Statistical Modeling, Causal Inference, and Social Science.
Colleen Flaherty asks: Do you get asked to peer review a lot? I’m guessing you do… This new very short paper says it’s not a crisis, though, since only the people who publish the most are getting asked to review a lot… The authors pose two solutions: either we need to “democratize” the system of […]
The post Mouse Among the Cats appeared first on Statistical Modeling, Causal Inference, and Social Science.
Max Kasy and Isaiah Andrews sent along this paper, which begins: Some empirical results are more likely to be published than others. Such selective publication leads to biased estimates and distorted inference. This paper proposes two approaches for identifying the conditional probability of publication as a function of a study’s results, the first based on […]
The post “Identification of and correction for publication bias,” and another discussion of how forking paths is not the same thing as file drawer appeared first on Statistical Modeling, Causal Inference, and Social Science.
Nathan Yau (link from Dan Hirschman) constructed the above excellent visualization of data from the Consumer Expenditure Survey. Lots of interesting things here. The one thing that surprises me is that people (or maybe it’s households) making more than $200,000 only spent an average of $160,000. I guess the difference is taxes, savings (but not […]
The post Who spends how much, and on what? appeared first on Statistical Modeling, Causal Inference, and Social Science.
Nathan Yau (link from Dan Hirschman) constructed the above excellent visualization of data from the Consumer Expenditure Survey. Lots of interesting things here. The one thing that surprises me is that people (or maybe it’s households) making more than $200,000 only spent an average of $160,000. I guess the difference is taxes, savings (but not […]
The post Who spends how much, and on what? appeared first on Statistical Modeling, Causal Inference, and Social Science.
Following up on our discussion of hysteresis in the scientific community, Nick Brown points us to this article this article from 2014, “Excellence by Nonsense: The Competition for Publications in Modern Science,” by Mathias Binswanger, who writes: To ensure the efficient use of scarce funds, the government forces universities and professors, together with their academic […]
The post Let’s get hysterical appeared first on Statistical Modeling, Causal Inference, and Social Science.
Following up on our discussion of hysteresis in the scientific community, Nick Brown points us to this article from 2014, “Excellence by Nonsense: The Competition for Publications in Modern Science,” by Mathias Binswanger, who writes: To ensure the efficient use of scarce funds, the government forces universities and professors, together with their academic staff, to […]
The post Let’s get hysterical appeared first on Statistical Modeling, Causal Inference, and Social Science.
Gur Huberman asked for my reaction to a recent manuscript, Are CEOs Different? Characteristics of Top Managers, by Steven Kaplan and Morten Sorensen. The paper begins: We use a dataset of over 2,600 executive assessments to study thirty individual characteristics of candidates for top executive positions – CEO, CFO, COO and others. We classify the […]
The post It should be ok to just publish the data. appeared first on Statistical Modeling, Causal Inference, and Social Science.
Gur Huberman asked for my reaction to a recent manuscript, Are CEOs Different? Characteristics of Top Managers, by Steven Kaplan and Morten Sorensen. The paper begins: We use a dataset of over 2,600 executive assessments to study thirty individual characteristics of candidates for top executive positions – CEO, CFO, COO and others. We classify the […]
The post It should be ok to just publish the data. appeared first on Statistical Modeling, Causal Inference, and Social Science.
I just read the above-titled John Carreyrou book, and it’s as excellent as everyone says it is. I suppose it’s the mark of any compelling story that it will bring to mind other things you’ve been thinking about, and in this case I saw many connections between the story of Theranos—a company that raised billions […]
The post Some thoughts after reading “Bad Blood: Secrets and Lies in a Silicon Valley Startup” appeared first on Statistical Modeling, Causal Inference, and Social Science.
I just read the above-titled John Carreyrou book, and it’s as excellent as everyone says it is. I suppose it’s the mark of any compelling story that it will bring to mind other things you’ve been thinking about, and in this case I saw many connections between the story of Theranos—a company that raised billions […]
The post Some thoughts after reading “Bad Blood: Secrets and Lies in a Silicon Valley Startup” appeared first on Statistical Modeling, Causal Inference, and Social Science.
Paul Alper points to this horrifying news article by Mary Chris Jaklevic, “how a medical device ‘seeding trial’ disguised marketing as science.” I’d never heard of “seeding trials” before. Here’s Jaklevic: As a new line of hip implants was about to be launched in 2000, a stunning email went out from the manufacturer’s marketing department. […]
The post “Seeding trials”: medical marketing disguised as science appeared first on Statistical Modeling, Causal Inference, and Social Science.
Paul Alper points to this horrifying news article by Mary Chris Jaklevic, “how a medical device ‘seeding trial’ disguised marketing as science.” I’d never heard of “seeding trials” before. Here’s Jaklevic: As a new line of hip implants was about to be launched in 2000, a stunning email went out from the manufacturer’s marketing department. […]
The post “Seeding trials”: medical marketing disguised as science appeared first on Statistical Modeling, Causal Inference, and Social Science.
I (Phil) just read an article about Apple. Here’s the last sentence: “Apple has beaten earnings expectations in every quarter but one since March 2013.”
[Note added a week later: on July 31 Apple reported earnings for the fiscal third…
As we’ve discussed before (see also here), one of the difficulties of moving from our current system of review of scientific journal articles, to a new model of post-publication review, is that any major change seems likely to break the current “gift economy” system in which thousands of scientists put in millions of hours providing […]
The post Journals and refereeing: toward a new equilibrium appeared first on Statistical Modeling, Causal Inference, and Social Science.