Innovation Networks and R&D Allocation

113 Pages Posted: 27 Dec 2021 Last revised: 26 May 2023

See all articles by Ernest Liu

Ernest Liu

Princeton University - Princeton University

Song Ma

Yale School of Management; National Bureau of Economic Research (NBER)

Date Written: December 2021

Abstract

We study the cross-sector allocation of R&D resources in a multisector growth model with an innovation network, where one sector's past innovations may benefit other sectors' future innovations. Theoretically, we solve for the optimal allocation of R&D resources. We show a planner valuing long-term growth should allocate more R&D toward central sectors in the innovation network, but the incentive is muted in open economies that benefit more from foreign knowledge spillovers. We derive sufficient statistics for evaluating the welfare gains from improving R&D allocation. Empirically, we build the global innovation network based on patent citations and establish its empirical importance for knowledge spillovers. We evaluate R&D allocative efficiency across countries using model-based sufficient statistics. Japan has the highest allocative efficiency among the advanced economies. For the U.S., improving R&D allocative efficiency to Japan's level could generate more than 19.6% welfare gains.

Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Suggested Citation

Liu, Ernest and Ma, Song, Innovation Networks and R&D Allocation (December 2021). NBER Working Paper No. w29607, Available at SSRN: https://ssrn.com/abstract=3994285 or http://dx.doi.org/10.2139/ssrn.3994285

Ernest Liu (Contact Author)

Princeton University - Princeton University ( email )

Joseph Henry House
Princeton, NJ 08542
United States

Song Ma

Yale School of Management ( email )

165 Whitney Ave
P.O. Box 208200
New Haven, CT 06511
United States

HOME PAGE: http://faculty.som.yale.edu/songma/

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
20
Abstract Views
434
PlumX Metrics