Ian Ayers refers to the research by Brett Pelham, Matthew Mirenberg, and John Jones that people are likely to have names that are related to their occupations, places of birth, etc. Pelham et al. write:
Taken together, the names Jerry and Walter have an average frequency of 0.416%, compared with a frequency of 0.415% for the name Dennis. Thus, if people named Dennis are more likely than people named Jerry or Walter to work as dentists, this would suggest that people named Dennis do, in fact, gravitate toward dentistry. A nationwide search focusing on each of these specific first names revealed 482 dentists named Dennis, 257 dentists named Walter, and 270 dentists named Jerry.
In his blog, Ayres referred to this finding but wrote:
To be honest, I [Ayres] am not fully persuaded that either of these results is true.
I think that Ayres is saying this because the effect sounds so large: Even if there really were something going on, could it really explain the difference between 482 and 257, nearly a factor of 2?
Let me repost a simple conditional probability calculation that might put Ayres’s mind at ease:
There were 482 dentists in the United States named Dennis, as compared to only about 260 that would be expected simply from the frequencies of Dennises and dentists in the population. On the other hand, the 222 “extra” Dennis dentists are only a very small fraction of the 620,000 Dennises in the country; this name pattern thus is striking but represents a small total effect. If we assume that 222 of these Dennises are “extra” dentists–choosing the profession just based on their name–that gives 221/620000= .035% of Dennises choosing their career using this rule. I can certainly believe that the naming effect could be as high as .035%.
What percentage of people pick their job based on their name?
And here is my quick calculation that approximately 1% of Americans choose their career based on their first name:
I start with this approximate formula for the proportion of people who choose a career based on their first name:
p1 * first_letter_effect + p2 * first_2_letters_effect + p3 * first_3_letters_effect
Here, p1 is the proportion of careers that begin with the first letter of your name, and the “first letter effect” is the extra proportion of people in a specific career beginning with the same first letter of their name. Similarly, p2 is the proportion of careers that share the first 2 letters of your name, and the “first 2 letters effect” is the extra proportion with that career, and similarly for p3. One could go on to p4 etc., but the idea is that, after p3, the probability of actually sharing the first 4 letters is so low as to contribute essentially nothing to the total.
Now, for some quick estimates: The simplest estimates for p1, p2, p3 are 1/26, 1/26^2, 1/26^3, but that’s not quite right because all letters are not equally likely. Just to make a guess, I’ll say 1/10 for p1, 1/50 for p2, and 1/150 for p3.
What about the “letter effects”? For “Dennis” the effect was estimated to be about 221/(482-221) = .85–that is, about 85% more dentists named Dennis than would be expected by chance alone. But “Dennis” and “dentist” sound so much alike, so let’s take a conservative value of 50% for the “first-3-letters-effect.” The first-2-letters-effect and first-letter effects must be much smaller–I’ll guess them at 5% and 15%, respectively.
In that case, the total effect is
(1/10)*.05 + (1/50)*.15 + (1/150)*.50 = 0.011, or basically a 1% effect.
More on the Pelham et al. article
Several comments on Ayres’s blog entry focused on potential problems with the Dennis/Dentist study. But there’s really much more to the Pelham et al. paper than that single example. I recommend you read the entire article. Here’s the abstract:
Because most people possess positive associations about themselves, most people prefer things that are connected to the self (e.g., the letters in one’s name). The authors refer to such preferences as implicit egotism. Ten studies assessed the role of implicit egotism in 2 major life decisions: where people choose to live and what people choose to do for a living. Studies 1-5 showed that people are disproportionately likely to live in places whose names resemble their own first or last names (e.g., people named Louis are disproportionately likely to live in St. Louis). Study 6 extended this finding to birthday number preferences. People were disproportionately likely to live in cities whose names began with their birthday numbers (e.g., Two Harbors, MN). Studies 7-10 suggested that people disproportionately choose careers whose labels resemble their names (e.g., people named Dennis or Denise are overrepresented among dentists). Implicit egotism appears to influence major life decisions. This idea stands in sharp contrast to many models of rational choice and attests to the importance of understanding implicit beliefs.
And there’s lots more good stuff there, including:
Hardware store owners were about 80% more likely to have names beginning with the letter H as compared with R. In contrast, roofers showed the reverse pattern. They were about 70% more likely to have names beginning with R as compared with H.
Expected values dictated that 308.8 of the 45,908 women sampled should have resided in cities named after Saints who happened to share their first names. The actual number of women who showed this name-city matching effect was 445, which is 44% greater than the chance value. On the basis of expected values, 3,476.0 out of 594,305 men should have lived in Saint cities bearing their first names. The actual number of men who did so was 3,956, which is 14% greater than the chance value.
P.S. If you go to the Name Voyager, you find that, not only did the name Dennis peak during the 1940s and 1950s, but the set of names beginning with D peaked around then also. (You’ll be happy to know that E has had the opposite pattern, while F has steadily gone down the tubes.