THE EFFECTS OF R&D AND ITS DIFFERENT TYPES ON FIRM PRODUCTIVITY: EVIDENCE FROM CHINA

Yuanyuan Guo (), Ping Gao and Daojin Cheng ()
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Yuanyuan Guo: School of Economics and Management, China University of Petroleum, Qingdao 266580, China
Ping Gao: ��Global Development Institute, The University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom
Daojin Cheng: ��School of Economics, Qufu Normal University, Rizhao 276825, China

International Journal of Innovation Management (ijim), 2022, vol. 26, issue 08, 1-30

Abstract: This paper employs the Olley and Pakes [(1996). The dynamics of productivity in the telecommunications equipment industry. Econometrica, 64(6), 1263–1297.] method and the generalised propensity score (GPS) methodology to estimate the effects of R&D and its different types, including research activity and development activity, on productivity. Our research sample is an unbalanced panel data consisting of 1808 Chinese listed manufacturing firms from the period 2006–2015. Our analysis reveals how R&D and its different types impact firm productivity: (1) there exists an S-shaped relationship between firm R&D intensity and productivity, which implies the existence of the threshold and diminishing marginal return of R&D for productivity growth. Due to the unbalanced composition of R&D in China, after R&D intensity reaches a critical level (around 50%) a negative marginal effect of R&D presents; (2) an increase of research intensity can improve firm productivity. However, research intensity reaches a saturation point (around 65%) beyond which firm productivity plateaus; (3) there exists an inverted U-shaped relationship between firm development intensity and productivity. The marginal effect of development on firm productivity is negative when development intensity is over 28%. Our empirical evidence implies that firms need to optimise the composition of R&D expenditure in order to realise sustained productivity growth.

Keywords: Firm productivity; R&D; research activity; development activity; R&D composition; generalised propensity score (GPS) (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S1363919622500657

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