Citation
Abstract
Firms that invest in knowledge introduce more technological advances, while firms that innovate have greater labour productivity. This study aims to investigate the impact of the cost of training, level of educational attainment and research and development (R&D) investment on labour productivity in Malaysia’s manufacturing industry. Using 3 digit levels of panel data set from 53 manufacturing industries, this study applies the System-Generalized Method of Moments (SYS-GMM) estimator technique to capture the effects of human capital variables on productivity. The study finds that the cost of training sponsored by a firm, level of educational attainment and R&D investment are significant and influence labour productivity. This study also finds that the level of education attained by employees significantly influences labour productivity. However, employees whose educational credentials do not proceed further than diploma and SPM level education remain insignificant in influencing labour productivity. The results are consistent with the objectives of the Economic Transformation Programme of the Malaysian government, which aims to enhance the quality of skilled labour to successfully develop a high income economy. In order to attain the status of a high income economy, 60 percent of jobs in Malaysia must consist of skilled workers and quality skilled workers, which are crucial to accelerating economic development. Consequently, manufacturing industries could improve their competitive position by raising their respective employment shares of high-skilled labour.
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Economics and Management |
Publisher: | Penerbit Universiti Kebangsaan Malaysia |
Keywords: | Education; GMM-SYS; Human capital; Labour productivity; R&D expenditures; Training |
Depositing User: | Ms. Nuraida Ibrahim |
Date Deposited: | 04 Sep 2023 15:45 |
Last Modified: | 04 Sep 2023 15:45 |
URI: | http://psasir.upm.edu.my/id/eprint/37138 |
Statistic Details: | View Download Statistic |
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