Category: Economics

“Identification of and correction for publication bias,” and another discussion of how forking paths is not the same thing as file drawer

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 […]

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Who spends how much, and on what?

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 […]

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Who spends how much, and on what?

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 […]

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Let’s get hysterical

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 […]

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Let’s get hysterical

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 […]

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It should be ok to just publish the data.

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 […]

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It should be ok to just publish the data.

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 […]

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Some thoughts after reading “Bad Blood: Secrets and Lies in a Silicon Valley Startup”

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 […]

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Some thoughts after reading “Bad Blood: Secrets and Lies in a Silicon Valley Startup”

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.

“Seeding trials”: medical marketing disguised as 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. […]

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“Seeding trials”: medical marketing disguised as 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. […]

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How dumb do you have to be…

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…

Journals and refereeing: toward a new equilibrium

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 […]

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Journals and refereeing: toward a new equilibrium

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 […]

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The Ponzi threshold and the Armstrong principle

Mark Palko writes of the Ponzi threshold: “sometimes overhyped companies that start out with viable business plans see their valuation become so inflated that, in order to meet and sustain investor expectations, they have to come up with new and increasingly fantastic longshot schemes, anything that sounds like it might possibly pay off with lottery […]

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Chasing the noise in industrial A/B testing: what to do when all the low-hanging fruit have been picked?

Commenting on this post on the “80% power” lie, Roger Bohn writes: The low power problem bugged me so much in the semiconductor industry that I wrote 2 papers about around 1995. Variability estimates come naturally from routine manufacturing statistics, which in semicon were tracked carefully because they are economically important. The sample size is […]

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