Matthias Kehrig from Duke University will present “Allocative Efficiency of Public R&D: Evidence from NIH Funding” (joint with Cem Özdemir and Daniel Xu).

Abstract: This paper studies the allocative efficiency of public R&D funding using detailed data on NIH grants. We develop a framework in which heterogeneous research recipients transform public funds into knowledge and innovation outputs, measured by scientific publications and patents based on those publications. The model highlights how distortions in funding allocation – captured as wedges between marginal products and marginal costs – affect aggregate research productivity. We estimate knowledge and innovation production functions exploiting panel variation in funding and introduce a novel identification strategy based on shifts in the composition of congressional committees and using dynamic panel data methods. Combining these estimates with administrative data linking grants to publications and patents, we recover recipient-level productivity and quantify misallocation across research areas. Our results show substantial heterogeneity in returns to funding across fields and recipients. Misallocation in knowledge production is economically large, with aggregate productivity losses ranging from roughly 10% to 85% relative to an efficient benchmark, while misallocation in innovation (patents) is more limited due to lower returns to scale. These findings imply that reallocating existing funds could generate sizable gains in scientific output without increasing total spending.