Measuring governments’ R&D funding response to COVID-19: An application of the OECD Fundstat infrastructure to the analysis of R&D directionality

Leonidas Aristodemou, Fernando Galindo-Rueda, Kuniko Matsumoto and Akiyoshi Murakami
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Fernando Galindo-Rueda: OECD

No 2023/06, OECD Science, Technology and Industry Working Papers from OECD Publishing

Abstract: This paper presents new evidence on the size and direction of governments’ R&D funding response to the COVID-19 pandemic through the exploration of a novel data infrastructure, the OECD Fundstat initiative for the analysis of government-funded R&D projects. The document reports on the exploratory development and application of automatic classification tools to detect relevant COVID-19 R&D funding, map salient topics and classify and allocate project funding according to priorities in the WHO COVID-19 R&D Blueprint, as well as comparing results with similar analysis of scientific publication output data. The results provide new insights on which areas of enquiry were prioritised by governmental R&D funding bodies.

Keywords: classification; COVID-19; directionality; Government funding; large language models; R&D; Research and Development; topic modelling (search for similar items in EconPapers)
JEL-codes: C38 C45 O32 O38 (search for similar items in EconPapers)
Date: 2023-10-16
New Economics Papers: this item is included in nep-ino and nep-inv
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Persistent link: https://EconPapers.repec.org/RePEc:oec:stiaaa:2023/06-en

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