Research Seminar: Money, Time, and Grant Design

The Growth Lab Research Seminar series is a weekly seminar that brings together researchers from across the academic spectrum who share an interest in growth and development.

Speaker: Wei Yang Tham is a Research Scientist at the Laboratory for Innovation Science at Harvard (LISH) and Harvard Business School

Abstract: The design of research grants might be a useful tool for incentivizing more socially valuable science. To better understand the value of grant design as a policy instrument, we conduct two sets of thought experiments in a nationally representative survey of academic researchers. First, we test whether grants with randomized attributes induce different research strategies. Longer grants increase researchers’ willingness to take risks, but only amongst tenured professors, suggesting that job security and grant duration are complementary incentives. Larger grants increase researchers’ willingness to expand ongoing projects, while smaller grants increase researchers’ focus on starting new projects. In our second experiment, we estimate researchers’ willingness to trade off grant size and duration. We find that researchers are relatively unwilling to trade off the amount of funding a grant provides in order to extend the duration of the grant — more money is much more valuable than more time.

Whether attending in-person or online, please register in advance. Room attendance is limited to the Harvard community. Seating is available on a first-come, first-served basis. Zoom attendance is open to the public.

About the speaker:

Wei Yang Tham is a Research Scientist at the Laboratory for Innovation Science at Harvard (LISH) and Harvard Business School. He completed his PhD in Economics at Ohio State University in 2019. Dr. Tham studies innovation and knowledge production in the context of science. His recent work includes eliciting researchers’ preferences and responses to grant design, studying how funding delays affect the movement of human capital across sectors and borders, and estimating the knowledge production function to better understand the optimal distribution of resources in research.