2019
DOI: 10.1111/ecin.12762
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Young “Stars” in Economics: What They Do and Where They Go

Abstract: We construct a data set of job flyouts for junior economists between 2013 and 2018 to investigate three aspects of the market for “stars.” First, what is the background of students who become stars? Second, what type of research does the top of the market demand? Third, where do these students take jobs? Among other results, we show that stars are more likely to be international and male than PhDs overall, that theoretical and semi‐theoretical approaches remain dominant, that American programs both produce the… Show more

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Cited by 11 publications
(11 citation statements)
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References 27 publications
(40 reference statements)
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“…Similarly, we assume that a citation in a top journal is as important as a citation in a lower‐tier journal. Our framework should also be tested with alternative performance measures, such as salaries (Gibson et al, 2017), the placement of young stars (Bryan, 2019), and technology transfer (Showalter & Jensen, 2019). We show that different segments of the market—cohort, field, and rank—view different aspects of academic performance differently, but did not test for other characteristics, such as gender and nationality.…”
Section: Discussionmentioning
confidence: 99%
“…Similarly, we assume that a citation in a top journal is as important as a citation in a lower‐tier journal. Our framework should also be tested with alternative performance measures, such as salaries (Gibson et al, 2017), the placement of young stars (Bryan, 2019), and technology transfer (Showalter & Jensen, 2019). We show that different segments of the market—cohort, field, and rank—view different aspects of academic performance differently, but did not test for other characteristics, such as gender and nationality.…”
Section: Discussionmentioning
confidence: 99%
“…Therefore, the academic department's demand for H is derived from its demand for N. Given that the academic department hires several faculties with N, the remaining positions are filled by H and, as a consequence, H = H(N), H (N) > 0. In sum, the working hypotheses of our model are that (1) departments choose to hire faculty based on pedigree (whether they hold a doctorate from the top-or lower-ranked departments) (Kocher and Sutter 2001;Han 2003;Klein 2005;Wu 2005;Bryan 2019;Wapman et al 2022;Wright 2023), and (2) job market candidates from top departments have an advantage because their professors dominate the main journals of the area (Colussi 2018;Heckman and Moktan 2020;Wright 2023). This network effect translates into more publications, thus increasing their value in the job market (Oyer 2006;Heckman and Moktan 2020;Wright 2023).…”
Section: Network Effects In Academic Labor Marketsmentioning
confidence: 99%
“…Seo et al (2021) and Li and Horta (2021) analyse factors influencing PhD students' choice of careers inside or outside academia. Bryan (2019) investigates young ‘star’ economists in the United States (US), including their backgrounds, research fields and the places where these top PhD graduates take jobs. He shows that a majority of stars work in top US economic programs, but governments (other than central banks and the World Bank) hire no stars and almost no stars go to the private sector.…”
Section: Introductionmentioning
confidence: 99%