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on Sociology of Economics |
| By: | Akcigit, Ufuk; Chikis, Craig A.; Dinlersoz, Emin; Goldschlag, Nathan |
| Abstract: | We construct a novel dataset linking academic publication records to U.S. Census employer–employee data to track 42, 000 AI researchers over two decades. We document systematic changes in the allocation of AI talent. Industry increasingly attracts younger and foreign-born researchers, while gender representation improves more in academia. The top 1% of publishing industry scientists now earn $1.5 million more annually than comparable academics, a fivefold increase since 2001. Rising wage premia coincide with greater sorting into large incumbent firms. Researchers who move to industry publish less but patent more, consistent with a shift from open science toward proprietary innovation. |
| Keywords: | Artificial intelligence; open science; Innovation; Research and development |
| JEL: | I23 J45 L33 O31 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21293 |
| By: | Rohner, Dominic; Vanden Eynde, Oliver; Widmer, Philine |
| Abstract: | Academic freedom has come under growing strain across the world. To study whether and how academics react to political pressure, we exploit a natural experiment: the U.S. government's "blacklist" of undesirable words released in early 2025. We find that the release of this list leads to a sharp reduction in the use of banned words in sensitive contexts among economists working at universities that rely heavily on NSF funding. The drop is particularly marked for content related to gender, race, and environment. Our findings are consistent with scholars responding strongly to political pressure through career incentives. |
| Keywords: | Censorship; Science |
| JEL: | D73 I23 O38 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21228 |
| By: | Furnas, Alexander; Jia, Ruixue; Roberts, Margaret; Wang, Dashun |
| Abstract: | This study provides evidence that geopolitical considerations systematically shape funding evaluations of international collaboration proposals. We examine this dynamic in the consequential context of U.S.–China collaboration. Across two large-scale randomized experiments with U.S. policymakers and U.S.-based scientists, we find substantial and consistent penalties for proposals involving China-based collaborators. Policymakers express much greater unconditional support for proposals with Germany-based collaborators than for otherwise identical proposals with China-based collaborators (68% vs. 28%). Crucially, this penalty is not confined to policymakers: scientists themselves exhibit a sizeable 18 percentage-point gap (48% vs. 30%), despite professional expectations of merit-based evaluation. Much of the difference reflects a shift from unconditional to conditional approval rather than outright rejection. These penalties are remarkably consistent across scientific fields and respondent characteristics, with little evidence of heterogeneity, indicating that they reflect geopolitical rather than domain-specific concerns. Overall, the findings suggest that geopolitics influences gatekeeping judgments in government funding, with broad implications for peer review, scientific norms, and the future of international collaboration in an era of intensifying geopolitical competition. |
| Keywords: | Science evaluation; Peer review; International collaboration |
| JEL: | F52 H57 O31 H41 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21173 |
| By: | Johan Fourie (Department of Economics, Stellenbosch University) |
| Abstract: | I study how cheaper AI-assisted research changes the institutions that certify science. AI lowers the cost of producing a polished manuscript faster than it lowers the cost of judging whether the underlying contribution is valuable. Polish therefore loses information, entry expands and the average quality of the uncertified pool can fall. At a fixed standard, the willingness to pay for credible certification then rises because the outside option deteriorates. A certifier with market power can capture this premium; competition and alternative disclosure rules need not produce the same fee. With fixed review capacity and weak commitment, certification instead dilutes. In that extension, the partial Pigouvian toll on submissions and the shadow value of review capacity both rise with AI-assisted entry. The contribution is to connect the economics of AI and scientific production to signaling, certification and peer review: cheaper production shifts scarcity downstream, from making research look credible to verifying which research is credible. |
| Keywords: | economics of science, certification and peer review, artificial intelligence, signaling, attention, scientific publishing |
| JEL: | D82 D83 I23 L15 O33 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:sza:wpaper:wpapers397 |
| By: | Sahoo, Biresh K. |
| Abstract: | This paper computes research productivity of 108 faculty from XLRI and XIMB across five quality threshold (CABS-all, ABDC-all, CABS Top 4, ABDC Top3, and CABS Top 3) using data envelopment analysis. Four revelations emerge. First, XLRI’s apparent productivity edge over XIMB stems from heavier teaching loads at XIMB, not faculty talent. Second, while CABS and ABDC rankings converge at low threshold (broad) level, they diverge significantly at higher (stricter) thresholds. Third, threshold stringency, not the ranking source, primarily drives rank volatility. Adopting the strictest CABS Top 3 reconfigures productivity rankings drastically, displacing 73% of faculty by over ten positions. Fourth, redefining disadvantage as rank incoherence rather than absolute productivity loss reveals a disciplinary cleavage: Marketing and Operations Management retain internal cohesion, whereas Information Systems, Accounting & Finance, and Organizational Behavior & Human Resources Management experience a decoupling of broad-list success from top-tier eminence due to severe faculty attrition. As regards policy implications, XIMB must urgently expand its research faculty cohort and reduce excessive teaching loads to improve research productivity. To rectify linear research-incentive inequities, we propose a multi-layered reward mechanism that values mid-tier publications while directing its heaviest investment toward impactful research. |
| Keywords: | Research productivity; Productivity ranking; Journal quality list; Journal quality thresholds; Data envelopment analysis |
| JEL: | D24 I23 I28 |
| Date: | 2026–06–23 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:129705 |
| By: | Rodríguez-Pose, Andrés; Xiang, Leiboyu; Lee, Neil |
| Abstract: | This paper presents the first systematic city-level mapping of global scientific talent, analysing the top 200, 000 star scientists across 3, 635 cities worldwide annually between 2019 and 2023. We use a novel Knowledge Generation Index (KGI) that combines researcher quantity with research impact to reveal extreme spatial concentration in knowledge production. Just four cities — New York, Boston, London and the San Francisco Bay Area — host 12% of the world's star scientists, while much of the Global South remains virtually excluded from frontier research. Beijing's ascent into the global top ten represents a rare challenge to established hierarchies. Our analysis uncovers striking disciplinary variations. Resource-intensive fields like clinical medicine cluster heavily and traditionally dispersed disciplines are increasingly gravitating toward major hubs. Despite these differences, concentration is intensifying across most scientific fields. Even the pandemic's remote collaboration experiment failed to level the playing field. Established innovation centres continued strengthening their advantages while peripheral regions fell further behind. Overall, we find that geography remains destiny, with profound implications for innovation policy confronting widening spatial inequalities in global scientific capacity. |
| JEL: | O25 O31 R12 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:20970 |