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What do we know about R&D spillovers and productivity? Meta-analysis on heterogeneity and statistical power

What do we know about R&D spillovers and productivity? Meta-analysis on heterogeneity and statistical power

Ugur, Mehmet ORCID: 0000-0003-3891-3641, Awaworyi Churchill, Sefa and Luong, Hoang Minh (2018) What do we know about R&D spillovers and productivity? Meta-analysis on heterogeneity and statistical power. [Working Paper]

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Abstract

Endogenous growth theory and the knowledge capital model predict that research and development (R&D) investment is associated with increasing returns and positive externalities. These insights have informed public support for R&D investment directly and indirectly. We aim to establish where the balance of the evidence lies, the extent to which the evidence has adequate statistical power, and which factors may explain the variation in the empirical findings. Drawing on 983 spillovers and 501 own-R&D effect-size estimates from 60 empirical studies, we find that the average productivity effect of spillovers: (i) is smaller than what is reported in most narrative reviews; (ii) is even smaller when only adequately-powered evidence is considered; (iii) differs by spillover types; and (iv) is not larger than that of own-R&D. We also report that the percentage of adequately-powered evidence is low (30%-55%). We highlight the implications of these findings for future research and public policy design.

Item Type: Working Paper
Uncontrolled Keywords: Knowledge externalities, R&D spillovers, productivity, public policy, meta-analysis,
Subjects: H Social Sciences > HD Industries. Land use. Labor
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Greenwich Political Economy Research Centre (GPERC)
Faculty of Business > Institute of Political Economy, Governance, Finance and Accountability (IPEGFA) > Greenwich Political Economy Research Centre (GPERC)
Last Modified: 29 Apr 2019 15:32
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/21942

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