Will collaborators make scientists move? A Generalized Propensity Score analysis

作者:Meijun Liu, Xiao Hu

期刊:Journal of Informetrics

语言:English

DOI:10.1016/j.joi.2020.101113

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摘要

Through collaboration, scientists' human and social capital is accumulated,which is considered important in the academic job market. However, little is known about whether academic past collaboration influence scientists’ mobility. To deal with treatment endogeneity, we conduct a Generalized Propensity Score analysis (GPS) and apply a novel application of the Dose-Response Function model. Using the data on 15,968 Chinese scientists from 2000 to 2012 as an illustrative case, we find that 1) the number of domestic and overseas collaborators are positively associated with scientists’ mobility and upward move, while the magnitude of the effect of overseas collaborators is far smaller than that of domestic collaborators; 2) domestic collaborators’ productivity is positively related to scientists’ move and upward move; 3) there is a stronger effect of collaborators from higher-tier universities on scientists’ upward move; 4) we do not observe a significant relationship between the recent stock of collaborators and scientists’ mobility. In addition to implications for talent policies and scientists’ career development, this study makes significant methodological contributions through introducing a new method, GPS, to address selection bias of the independent variable, i.e., scientists’ collaboration. Our results show that, with great potential to capture causality, GPS facilitates research in informetrics, scientometrics and science policy from a quantitative perspective, and enriches policy relevance of the findings.

引用

Liu, M., & Hu, X. (2021). Will collaborators make scientists move? A Generalized Propensity Score analysis. Journal of Informetrics, 15(1), 101113. doi:https://doi.org/10.1016/j.joi.2020.101113