MOD: Estimating the Effect of Exposure to Superstar Scientists: Evidence from Academia and the Biopharmaceutical Sector

通过衡量研究赠款的“培训”效果和研究工作之间的协同作用，该项目提供了关于公共研究和适当资助水平的益处的常年辩论背后的重要和缺失的要素。地理影响力的措施也告知当前的政策问题，美国的竞争力相对于高质量的研究施加在公司在国际范围内的位置选择的磁性拉力。此外，由于本研究的一部分探讨了知识溢出的运作机制，因此该项目应该对组织之间的人才分配以及影响代理人之间信息流动的技术和政策如何对经济中的技术创新水平和速度产生重要影响产生有价值的见解。是实证估计的重要性，溢出效应从“超级明星科学家”的科学进步，在生物医学领域。该研究依赖于研究人员在过去几年中收集的独特数据集。该数据集匹配了1977年至2003年期间医学院教师和NIH受资助者的完整名册的出版物输出，NIH资金和专利。本研究的中心模型估计了接触“超级明星”科学家对学术生命科学领域其他研究人员的科学生产力的影响。接触被认为是一个多层面的结构，有三个不同的影响渠道：（a）共同作者（“社会距离”）;（B）共同地点（“地理距离”）;（c）研究重点的重叠/互补（“科学距离”）。因为科学家们不会随机定位或合作，所以特别关注准实验，这些实验可以帮助区分因果关系和纯粹的相关性。作为本研究的一部分，开发了开源软件工具，以构建个体科学家之间的社会和科学距离的措施。除了对政策辩论的知识贡献外，该项目还将产生其他一些影响。首先，为测量研究人员之间的社会和科学距离而开发的软件将对对科学和技术政策感兴趣的广泛学者有用。开放源码格式旨在鼓励未来的用户修改和改进软件，以便该领域的研究工具继续发展。该软件沿着源代码和用户手册将免费向公众提供，供科学政策学者和其他有关方面使用。 其次，这项研究所产生的软件有望通过公开大量的交叉文件，大大降低生物科学中个人层面专利、出版物和研究资金数据的匹配成本。最后，研究结果将通过各种媒体向广大受众传播，从而促进与学术界同事以及生物医学行业的决策者和公司进行公开对话。

By measuring the "training" effects of research grants and synergies across research efforts, this project provides significant and missing elements in the calculus behind the perennial debates about the benefits from public research and appropriate levels of funding. Measures of geographic influence also inform current policy questions about U.S. competitiveness vis-a-vis the magnetic pull that high quality research exerts on the locational choice of firms in an international context. Moreover, since part of this research explores the mechanisms through which knowledge spillovers operate, the project should generate valuable insights about the allocation of talent across organizations and how the technologies and policies that influence the flow of information between agents has important implications for the level and rate of technological innovation within the economy.The purpose of this project, therefore, is to empirically estimate the importance of spillovers from "superstar scientists" for scientific progress in the biomedical area. The study relies on a unique dataset that the investigators have assembled over the past several years. The dataset has matched publication output, NIH funding and patents for the complete roster of medical school faculty and NIH grantees between the years 1977 and 2003. The central model of this study estimates the effect that exposure to "superstar" scientists exerts has on the scientific productivity of other researchers within the academic life sciences. Exposure is assumed to be a multidimensional construct, with three distinct channels of influence: (a) co-authorship ("social distance"); (b) co-location ("geographic distance"); and (c) overlap/complementarity of research foci ("scientific distance"). Because scientists do not locate or collaborate at random, particular attention is given to the quasi-experiments that can help tease apart causal relationships from mere correlations. As part of this study, open-source software tools are developed to construct measures of social and scientific distance between individual scientists. Beyond intellectual contributions to policy debates, this project will have several additional impacts. First, the software developed to measure social and scientific distance between researchers will be useful to a wide range of scholars interested in science and technology policy. The open-source format is designed to encourage future users to modify and improve the software so that research tools in this area continue to advance. This software along with source code and user manuals will be made publicly available at no charge for use by science policy scholars and other interested parties. Second, the software resulting from this study is expected dramatically to reduce the cost of matching individual-level patent, publication and research funding data in the biosciences by making a number of cross-walk files publicly available. Finally, the findings will be disseminated through various media to a wide range of audiences, thereby facilitating an open dialogue with colleagues in the academy, as well as policy makers and firms in the biomedical industry.