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on Sociology of Economics |
| By: | Marlène Koffi; Roland Pongou; Leonard Wantchekon |
| Abstract: | This paper investigates the existence of racial disparities in the dissemination of ideas using the paper citation network in economics. Exploiting a comprehensive dataset of over 330, 000 publications from 1950 to 2021, combined with manually collected data from the CVs of thousands of economists, we document that papers authored by non-White scholars (Black, Hispanic, or Asian) receive 5.1% to 9.6% fewer citations than those authored by White scholars. The citation gap remains or even amplifies with increasing author seniority and conventional quality indicators and is especially pronounced for Black authors. Moreover, papers authored by non-White scholars are less likely to serve as citation bridges and are less often cited by highly cited papers as measured by the centrality indexes, limiting both their direct and indirect influence. Our analysis indicates that this disparity is not attributable to differences in research quality, author ability, or visibility. Rather, it is largely driven by homophily in citation patterns and racial clusters in networks, where scholars tend to cite authors from their racial group. These findings can be rationalized by a simple theoretical model where citation costs and peer-review preferences influence citation behavior. Then, we provide suggestive evidence that reducing information friction—thereby lowering the cost of citing—could reduce the racial citation gap by up to 50%. Finally, using natural language processing, we highlight the complementarity across racial groups in research and discuss potential losses from racial barriers to idea diffusion. |
| JEL: | A14 I23 J15 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33150 |
| By: | Samuel Arts; Nicola Melluso; Reinhilde Veugelers |
| Abstract: | New scientific ideas drive progress, yet measuring scientific novelty remains challenging. We use natural language processing to detect the origin and impact of new ideas in scientific publications. To validate our methods, we analyze Nobel Prize-winning papers, which likely pioneered impactful new ideas, and literature review papers, which typically consolidate existing knowledge. We also show that novel papers have more intellectual neighbors published after them, indicating they are ahead of their intellectual peers. Finally, papers introducing new ideas, particularly those with greater follow-on reuse, attract more citations. |
| Keywords: | natural language processing, science, novelty, impact, breakthrough, Nobel, OpenAlex |
| Date: | 2025–01–13 |
| URL: | https://d.repec.org/n?u=RePEc:ete:msiper:757417 |
| By: | Matthew Mitchell; Florian Schuett |
| Abstract: | This paper studies how to reward obvious and non-obvious ideas differently when researchers have private information about obviousness, and non-obvious ideas are important but particularly costly to develop. Because obvious ideas might still value rewards like publications or patents, screening with fees or delay is not possible. Instead the planner must use costly scrutiny. We show that when scrutiny is imperfect, there is a tension between screening for obviousness and the efficient development of ideas: non-obvious ideas are less developed, and obvious ideas sometimes more developed, than they would be in the full-information optimal allocation. The constrained efficient allocation has features that look like the publication process, including tiers of journals and a top tier that is very exclusive. Changes in scrutiny costs predict changes to journal articles that are in line with empirical evidence on top journals. |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ete:ceswps:757471 |