Michele Pezzoni

Gender and the Publication Output of Graduate Students: A Case Study.

We examine gender differences among the six PhD student cohorts 2004–2009 at the California Institute of Technology using a new dataset that includes information on trainees and their advisors and enables us to construct detailed measures of teams at the advisor level. We focus on the relationship between graduate student publications and: (1) their gender; (2) the gender of the advisor, (3) the gender pairing between the advisor and the student and (4) the gender composition of the team. We find that female graduate students co-author on average 8.5% fewer papers than men; that students writing with female advisors publish 7.7% more. Of particular note is that gender pairing matters: male students working with female advisors publish 10.0% more than male students working with male advisors; women students working with male advisors publish 8.5% less. There is no difference between the publishing patterns of male students working with male advisors and female students working with female advisors. The results persist and are magnified when we focus on the quality of the published articles, as measured by average Impact Factor, instead of number of articles. We find no evidence that the number of publications relates to the gender composition of the team. Although the gender effects are reasonably modest, past research on processes of positive feedback and cumulative advantage suggest that the difference will grow, not shrink, over the careers of these recent cohorts.

Is This Novel Technology Going to Hit

While there is a rising interest in identifying individual breakthrough inventions, little work has investigated how novel technologies embodied in these inventions diffuse. This paper shows that t...

Innovation and Market Structure in Pharmaceuticals: an Econometric Analysis on Simulated Data

Summary The contribution of this paper is twofold. First, it presents the results of a “history-friendly” simulation model of evolution of the pharmaceutical industry. Second, it aims at contributing to a more general methodological discussion about agent-based models by proposing an econometric analysis of the results of the simulations. The case of the pharmaceutical industry has been studied extensively by scholars because, despite the high level of R&D intensity, the industry has been characterized by a relatively low levels of concentration. The model is able to reproduce the main stylized facts of the industry in an evolutionary perspective. In this paper we extend the analysis conducted in two previous works (Garavaglia et al. 2012, 2013) by further qualifying the findings with an extensive econometric investigation of the model outputs. The paper focuses the attention on the determinants of market structure, the innovative performance of the industry, the diversification in multiple submarkets and the level of prices. We find that the properties of the technological and demand regimes are key determinants of the patterns of industry evolution and that the main mechanisms driving the model are the random processes of search, the discovery of new submarkets as well as the interactions between patent protection, imitation and price competition. In addition, this paper emphasizes how the emerging leaders in the industry are those innovative early entrants which entered in large submarkets, showing the importance of the first mover advantage and of the size of the “prize” accruing to innovators when they discover a new rich submarket.