Global Value Chains (GVCs) participation patterns and impacts on productivity growth in the Asian economies

Abstract

The paper examines the dynamic impact of GVCs on productivity growth in 14 Asian economies, from 1995 to 2016. OECD and Asia Productivity Organisation data show that in the last few decades there has been a rapid expansion of GVCs in the majority of the Asian economies. We employ the panel Auto-regressive Distributed Lag method to empirically evaluate the impact of GVCs participation on ‘total factor productivity growth’ and ‘labor productivity growth’. The empirical results point to the significant effect of GVCs on domestic productivity growth in the long run in the selected Asian economies, while the effect on labor productivity growth is larger than that on total factor productivity growth. However, GVCs does not affect it in the short-run. If excluded the six high-income economies and only focused on the middle-income countries, we find forward GVCs promotes domestic productivity in long run, while the backward GVCs does not.

Keywords:

• Global economic integration
• GVCs
• productivity
• panel ARDL
• Asian Economy

JEL CLASSIFICATIONS:

• F02
• F60
• F43
• R11
• R12

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 The different tasks relating to the production process involve design, branding, marketing, etc.

2 Philippines Department of Trade and Industry: Policy Briefs - The Philippines and Global Manufacturing Value Chains https://industry.gov.ph/wp-content/uploads/2017/11/DTI-Policy-Brief-2017-01-The-Philippines-and-Global-Manufacturing-Global-Value-Chains.pdf, retrieved 12 Jan 2022.

3 Thailand has also established efficient automotive clusters of multinational assemblers, parts and components suppliers, mainly those from US and Japan.

4 East Asia Forum: The key to integrating Cambodia into global value chains: https://www.eastasiaforum.org/2019/08/03/the-key-to-integrating-cambodia-into-global-value-chains/ retrieved 12 Jan 2022.

5 The reason is that the value of F-statistics which is computed by Pesaran et al. (2001) to decide the presence of the long-run equilibrium, does not work if one of the variables is I (2).

6 Unit root test results are to be provided if requested.

Additional information

Notes on contributors

Jagannath Mallick

Jagnaath Mallick has a about two decades of research experience in macroeconomics, globalisation, trade, productivity, regional economics, Growth, large data, big data analysis, nowcasting and forecasting, applied econometrics and time series analysis, in the context of Asian economies focusing on India, Japan and China. He has worked with various intuitions such as SBIL of State Bank of India, ICRIER Delhi, ISID Delhi, University of Pardubice and University of Hyogo. As the professional recognition of his research work, he has received 10 prestigious awards/grants including Japan Society for Promotion of Science (JSPS) International Research fellowship by the Government of Japan; ‘Dr. Raghuram Rajan's Young Scholars Award 2013’, granted by Ministry of Finance (GoI) and World Bank Award, etc. He has acted as reviewer for various grants and awards including MARTÍ FRANQUÈS (MFP) COFUND Fellowship Programme 2018 and 2020, and Japanese Award for Outstanding Research on Development 2020 and 2021, Global Development Network (GDN). He has organised and moderated international events on ‘State of Global Economy’.

Anqi Zhang

Anqi Zhang is an applied microeconomist and interests in Development Economics and Labour Economics. She received the Ph.D. in Economics from the University of Manchester and now is the post-doctoral fellow in Fudan University Shanghai. She specialises in applied econometrics and is interested in public policies and households welfare, as well as the ageing population.

She has received the Faculty's Outstanding Studentship in Economics, Economics Excellence in Teaching Awards and Fellow of The Higher Education Academy in UK from 2017–2020. In 2021, she won the Super-Postdoc Award in Shanghai.