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R&D and productivity in OECD firms and industries: a hierarchical meta-regression analysis

R&D and productivity in OECD firms and industries: a hierarchical meta-regression analysis

Ugur, Mehmet ORCID: 0000-0003-3891-3641, Trushin, Esref, Solomon, Edna M. and Guidi, Francesco ORCID: 0000-0002-2682-189X (2015) R&D and productivity in OECD firms and industries: a hierarchical meta-regression analysis. [Working Paper]

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Abstract

Effects of R&D investment on frim/industry productivity have been investigated widely thanks to pioneering contributions by Zvi Griliches and others in late 1970s and early 1980s. We aim to establish where the balance of the evidence lies and what factors may explain the variation in the research findings. Using 1,258 estimates from 65 primary studies and hierarchical meta-regression models, we report that the average elasticity and rate-of-return estimates are both positive, but smaller than those reported in prior narrative reviews and meta-analysis studies. We discuss the likely sources of upward bias in prior reviews, investigate the sources of heterogeneity in the evidence base, and discuss the implications for future research. Overall, this study contributes to existing knowledge by placing the elasticity and rate-of-return estimates under a critical spot light and providing empirically-verifiable explanations for the variation in the evidence base.

Item Type: Working Paper
Uncontrolled Keywords: R&D; knowledge capital; productivity; meta-analysis;
Subjects: H Social Sciences > H Social Sciences (General)
Faculty / School / Research Centre / Research Group: Faculty of Business
Faculty of Business > Department of International Business & Economics
Faculty of Business > Institute of Political Economy, Governance, Finance and Accountability (IPEGFA)
Faculty of Business > Institute of Political Economy, Governance, Finance and Accountability (IPEGFA) > Greenwich Political Economy Research Centre (GPERC)
Related URLs:
Last Modified: 04 Aug 2021 16:33
URI: http://gala.gre.ac.uk/id/eprint/14080

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