Idea and Economic Spillovers from Publicly-funded Biomedical Research

该项目的目标是促进对生物医学研究回报的理解。该项目研究了新的科学知识如何在不同地点和机构环境中流动，以及这些知识流动如何影响科学创新、健康和经济增长。该项目考察了思想溢出效应（科学家迁移到新的地理位置会影响同事的生产力）和经济溢出效应（公共资助的基础研究最终被商业公司转化为新药，设备或治疗方法）。该研究使用了调查小组在过去几年中收集的独特数据集，该数据集与1975年至2006年期间医学院教师和NIH资助者的完整名册的出版物输出，NIH资金和专利相匹配。它还利用了美国专利和商标局（USPTO）自1976年以来发布的所有生物医学专利的数据。智力优势：该研究的一个主要贡献是评估了创意溢出在空间中的本地化程度。 因此，它促进了对向心力的理解，这种向心力随着时间的推移而维持着以研发为基础的地理集群（如南旧金山弗朗西斯科、肯德尔广场或拉霍亚）。特别是，它提供了直接估计的程度，企业的研发生产率建立在学术研究。 对知识溢出作用机制的探索为如何在组织间分配人才提供了见解。 该项目促进了对影响主体之间信息流动的技术和政策如何影响技术创新的速度和方向的理解。更广泛的影响：除了促进对科学经济学的理解，并为当代政策辩论提供信息外，该项目还有几个额外的产出。首先，将专利引用与生物医学文章相匹配的模糊匹配算法对于对科学和技术政策感兴趣的广泛学者是有用的。第二，在该领域的研究是促进了几个开放源码软件程序的修改下，以前的NSF支持下开发的。最后，通过各种媒体向广大受众传播调查结果，以促进与学术界、决策者、行业代表和其他利益攸关方的公开对话

The goal of this project is to advance understanding of the returns to biomedical research. The project examines how new scientific knowledge flows across locations and institutional settings, and how these knowledge flows affect scientific innovation, health, and economic growth. This project examines both idea spillovers (where the movement of scientists to new geographic locations affects productivity of their colleagues) and economic spillovers (where publicly-funded basic research is eventually translated into new drugs, devices, or treatments by commercial firms). The research uses a unique dataset assembled by the investigative team over the past several years, which matches publication output, NIH funding, and patents for the complete roster of medical school faculty and NIH grantees between 1975 and 2006. It also utilizes data from the US Patent and Trademark Office (USPTO) on all biomedical patents issued since 1976.Intellectual Merit: A major contribution of the research is that it assesses the degree to which idea spillovers are localized in space. As such, it promotes understanding of the centripetal forces that sustain R&D-based geographic clusters (such as South San Francisco, Kendall Square, or La Jolla) over time. In particular, it provides direct estimates of the extent to which firms' R&D productivity builds on academic research. The exploration of the mechanisms through which knowledge spillovers operate provides insights on how to allocate talent across organizations. The project advances understanding of how the technologies and policies that influence the flow of information between agents affect the rate and direction of technological innovation.Broader Impact: Beyond advancing understanding in the economics of science, and informing contemporary policy debates, this project has several additional outputs. First, the fuzzy-matching algorithm that matches patent citations to biomedical articles is useful to a wide range of scholars interested in science and technology policy. Second, research in the area is facilitated by the modification of several open-source software programs developed under prior NSF support. Finally, the findings are disseminated through various media to a wide range of audiences, to facilitate an open dialogue with academics, policymakers, industry representatives, and other stakeholders