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 thirty candidate characteristics with four primary factors: general ability, execution vs. interpersonal, charisma vs. analytic, and strategic vs. managerial. CEO candidates tend to score higher on these factors; CFO candidates score lower. Conditional on being a candidate, executives with greater interpersonal skills are more likely to be hired, suggesting that such skills are important in the selection process. Scores on the four factors also predict future career progression. Non-CEO candidates who score higher on the four factors are subsequently more likely to become CEOs. The patterns are qualitatively similar for public, private equity and venture capital owned companies. We do not find economically large differences in the four factors for men and women. Women, however, are subsequently less likely to become CEOs, holding the four factors constant.
I really don’t know what to do with this sort of thing. On one hand, the selection processes for business managers are worth studying, and these could be valuable data. On the other hand, the whole study looks like a mess: there’s no real sense of seeing all the data and once; rather, it looks like just a bunch of comparisons grabbed from the noise. So I have no real reason to take any of these empirical patterns seriously in the sense of thinking they would generalize beyond this particular dataset. But you have to start somewhere.
It was hard for me to bring myself to read a lot of the article; the whole thing just seemed kinda boring to me. If it were about sports, I’d be interested. But my decision to set the paper aside because it’s boring . . . that brings up a real bias in the dissemination of these sorts of reports. If a paper makes a strong claim, however ridiculous (Managers who wear red are more likely to perform better in years ending in 9!), or some claim with political content (Group X does, or does not, discriminate against group Y) then it’s more likely to get attention, also more likely to attract criticism. It’s just more likely to be talked about.
But, again, my take-home point is I don’t have a good way of thinking about this sort of paper, in which a somewhat interesting dataset is taken and then some regressions and comparisons are made. What I really think, I suppose, is that the academic communication system should be changed so it becomes OK to just publish interesting data, without having to clothe it in regressions and statistical significance. Not that regression is a bad method, it’s just that in this case I suspect the main contribution is putting together the dataset, and there’s no need for these data to be tied to some particular set of analyses.