Evaluating and comparing the performance of research funding programmes is challenging because programmes differ in how they (a) select grants and (b) select research areas for funding. Do... Show moreEvaluating and comparing the performance of research funding programmes is challenging because programmes differ in how they (a) select grants and (b) select research areas for funding. Do programmes perform well because they are good at selecting research projects, or because they concentrate funding in high-output research areas? These mechanisms can be distinguished if we can identify and control for a set of research projects in common scientific areas. Previous approaches have used costly and arbitrary manual classification of research projects, or relied on coarse research groupings defined by bibliometric services. We propose a new solution: Apply machine learning to map research projects funded by one agency into the funding structure of a different agency. We identify and control for common areas of research, and separately identify the effects of grant selection from research area composition. We apply our method to compare three high-impact high-risk research programmes funding early-career life scientists: The U.S. National Institutes of Health’s New Innovators Award (NIH-NIA), the European Research Council Starting Grant (ERC-StG), and the Singapore National Research Foundation Fellowship (NRFF). We show that the NIH-NIA and NRFF concentrate research funding in selective portions of the life sciences, compared to the ERC-StG which by design evenly distributes research funding. Within common research areas, NIH-NIA and NRFF researchers exhibit faster growth in citations, and to a lesser extent publications, than equivalent ERC-StG researchers. This suggests the NIH-NIA and NRFF are able to select researchers who deliver superior research outcomes. Show less
The impact of large scale research grant on early-career scientific research is examined by studying Singapore’s NRF Fellowship, launched in 2007. This scheme offers generous grants worth up to S$... Show moreThe impact of large scale research grant on early-career scientific research is examined by studying Singapore’s NRF Fellowship, launched in 2007. This scheme offers generous grants worth up to S$ 3 million (~ €1.8M) over 5 years and is open annually to international applications without restriction on nationality. We estimate the causal impact of large-scale grants awarded to early career scientists by using the NRF Fellowship’s highly selective award process as a source of quasi-experimental variation. Our empirical strategy relies on using the shortlisted non-awardees to form a counterfactual, allowing us to estimate the impact of the NRF Fellowship grant on the scientific output of early career scientists. Overall, our evidence suggests the NRF Fellowship’s large grant quanta are effective at increasing aggregate publication output. This is an important finding given that the ostensible purpose of such large, internationally competitive grant programs is generally to promote leading edge, high impact research not possible without generous unrestricted funding. The results suggest that the NRF selection process and the generous grant quanta certainly help the awardees with scientific successes by most definitions, having accumulated a substantial number of publications and citations.The results shed light on the public policy initiatives taken by many emerging-countries to jump-start scientific research and development through large-scale scientific funding programs. Results suggest that large-scale funding could effectively stimulate aggregate scientific output of early-career scientists. Show less
