Innovation Networks and R&D Allocation by Song Ma (Yale SoM)

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 benet other sectors’ future innovations. Theoretically, we solve for the optimal path of R&D resource allocation. We show a planner valuing long-term growth should allocate more R&D toward upstream sectors in the innovation network, but the incentive is muted in open economies that rely on foreign knowledge spillovers. We derive sucient statistics for evaluating the welfare cost of R&D misallocation. Empirically, we build the global innovation network based on patent citations and establish its empirical importance for knowledge spillovers. We evaluate R&D allocative eciency across countries using model-based sucient statistics. Japan has the highest allocative eciency among the advanced economies. For the U.S., reducing R&D misallocation down to Japan’s level could generate more than 28% welfare gains.

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