The impact of R&D on factor-augmenting technical change – an empirical assessment at the sector level

Smeets Kristkova, Z., Gardebroek, C., van Dijk, M., & van Meijl, H. (2017). The impact of R&D on factor-augmenting technical change – an empirical assessment at the sector level. Economic Systems Research 1-33. 10.1080/09535314.2017.1316707.

[thumbnail of The impact of R D on factor augmenting technical change an empirical assessment at the sector level.pdf]
Preview
Text
The impact of R D on factor augmenting technical change an empirical assessment at the sector level.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (2MB) | Preview

Abstract

The aim of the paper is to quantify endogenous factor-augmenting technical change driven by R&D investments in a panel of 11 OECD countries over 1987–2007. This paper contributes to the scant empirical evidence on the speed, sources and direction of technical change for various sectors and production factors. Assuming cost-minimization behavior, a CES framework is used to derive a system of equations that is estimated by a GMM system estimator. The estimated factor-augmenting technology parameters show that in most sectors, technical change was labor-augmenting and labor-saving. Statistically significant effects of manufacturing and services R&D were found on factor-augmenting technical change (with the highest R&D elasticities found in the high-tech manufacturing and transport, storage and communication sectors). Whereas ‘in-house’ R&D stimulates total factor productivity, R&D spilled over to other sectors has a capital-augmenting effect accompanied by a higher use of labor. The results of this study provide a starting point for incorporating endogenous factor-augmenting technical change in impact assessment models aimed at broad policy analysis including economic growth, food security or climate change.

Item Type: Article
Uncontrolled Keywords: Factor-augmenting technical change, R&D, CES function, GMM regression
Research Programs: Ecosystems Services and Management (ESM)
Depositing User: Luke Kirwan
Date Deposited: 08 May 2017 07:26
Last Modified: 27 Aug 2021 17:41
URI: https://pure.iiasa.ac.at/14568

Actions (login required)

View Item View Item