The conceptual and empirical framework

Introduction The goal of this book is to build a better understanding of how returns to research are generated. That understanding is facilitated here by creating explicit linkages between what is funded, who is funded, and the results. This chapter spells out the conceptual and empirical basis of the approach on which the book is grounded and provides a roadmap to the rest of the book. The core insight that drives our approach is importance of the people – students, principal investigators, postdoctoral researchers, and research staff – who conduct research, create new knowledge, and transmit that knowledge into the broader economy (1). Much has been made of the role of documents – like papers and patents – but this chapter instead builds on Oppenheimer's insight that the best way to send knowledge is to wrap it up in a person (2). Indeed, the regional economic activity surrounding universities strongly suggests that regionally bound human beings, not globally accessible documents, are the key to understanding economic impact. The conceptual framework is straightforward. Undergraduate students, graduate students, and postdoctoral fellows employed as part of scientific projects obtain valuable training while at the same time creating new knowledge that can be transmitted to their employers once their training is complete. The gains that result from the application of knowledge acquired through research and training accrue to both the employing firm and the workers. Researchers create new ideas that either directly generate new businesses or are transmitted through social and scientific networks to the private sector. Propinquity is a major driver of these effects (3). The empirical framework mirrors the conceptual framework. It uses university data on grant expenditures to characterize who is working on which grants, then traces their subsequent activity through matches with administrative data from the universities, US Census Bureau and other sources. This approach permits new insights into the impact of science. The size of the dataset is large enough to examine outcomes of quite narrowly defined fields, such as food safety research, or different demographic groups. The link to Census Bureau data opens a whole host of possibilities. With these data, one can describe the arc of a scientific career or trace economic impact over time and on an ongoing basis. It is now possible to describe real economic impact, because identifying comparison groups has become feasible.