• Media type: E-Book
  • Title: Cassatts in the Attic
  • Contributor: Koffi, Marlène [Author]; Marx, Matt [Author]
  • Corporation: National Bureau of Economic Research
  • Published: Cambridge, Mass: National Bureau of Economic Research, June 2023
  • Published in: NBER working paper series ; no. w31316
  • Extent: 1 Online-Ressource; illustrations (black and white)
  • Language: English
  • Keywords: Cassatt, Mary 1844-1926 ; Geschlechterunterschiede ; Erfindung ; Forschung ; Kommerzialisierung ; Innovationsdiffusion ; Wissenschaftliche Publikation ; Bibliometrie ; USA ; Economics of Gender; Non-labor Discrimination ; Innovation and Invention: Processes and Incentives ; Arbeitspapier ; Graue Literatur
  • Reproduction note: Hardcopy version available to institutional subscribers
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  • Description: We analyze more than 70 million scientific articles to characterize the gender dynamics of commercializing science. The double-digit gender gap we report is explained neither by the quality of the science nor its ex-ante commercial potential, and is widest among papers with female last authors (i.e., lab heads) when publishing high-quality science. Using Pitchbook database, we show that when authors self-commercialize scientific discoveries via new ventures, no gap appears, raising the question of whether incumbent firms are unaware of--or ignore--scientific contributions by women. A natural experiment based on the Obama administration's staggered introduction of open-access requirements for federally-funded research reveals that although easier access to scientific articles might facilitate commercialization, this benefit accrues primarily to male authors. Articles written with more "boastful" language are commercialized more often, and female scientists generally boast less, but even when they do their discoveries are commercialized no more often. We also observe gender homophily between scientific authors and commercializing inventors, the majority of whom are male. We conclude with the potential welfare effects of the gender gap: the disparity is more pronounced for higher-quality discoveries, as indicated by academic and patent citations or by predicted probabilities of commercialization derived from deep-learning algorithms