How ICTs Moderate the Effect of Global Value Chains’ Participation on Economic Growth in Sub-Saharan Africa?

Abstract

Using data from Sub-Saharan African (SSA) countries over the period 1990–2015, this study examines the effects of Global Value Chains’ (GVCs) participation on economic growth by distinguishing participation in upstream, participation in downstream and sectors-based participation. The study also focuses on how the economic growth effect of GVCs’ participation can be affected by the ICTs. The Driscoll and Kraay’ estimation approach applied to the cross-lagged panel model enabled to overcome the cross-sectional dependence, heteroscedasticity, errors’ autocorrelation and reverse causality problems. The generalized method of moments (GMM) is further employed for the robustness check. The findings are robust and indicate that the GVCs’ participation (general, upstream, downstream and sectorial) boosts economic growth in SSA countries. These positive effects hold and are even more intensive when the GVCs’ participation is modulated by the ICTs. Furthermore, the study demonstrates that SSA countries should focus on the downstream GVCs’ participation that is the production and export of the (high technologies) intermediate goods that are essential for the production activities of other GVCs’ stakeholders. For the sectors-based participation, the study seems to show that participation in the services sector promotes more economic growth, followed to some extent by the mining, agriculture and manufacturing sectors.

Keywords:

• GVCs’ participation
• ICTs
• economic growth
• cross-sectional dependence
• panel
• Sub-Saharan Africa

JEL Classifications:

• F43
• O10
• O40
• O55

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data Availability Statement

The data that support the findings of this study are available were derived from the following resources available in the public domain:

World Development Indicators

https://databank.worldbank.org/source/world-development-indicators.

World Integrated Trade Solution-Eora (WITS-Eora)

https://wits.worldbank.org/gvc/gvc-data-download.html.

United Nations Development Programme- Human Development Reports

https://hdr.undp.org/data-center/documentation-and-downloads.

Bjørnskov-Rode regime data

http://www.christianbjoernskov.com/bjoernskovrodedata/

Notes

1 See the UNCTAD Digital Economy Report 2021: https://unctad.org/system/files/official-document/der2021_en.pdf.

2 See also Moundigbaye et al. (2018) and Reed and Ye (2011) for some drawbacks generally associated with other estimation techniques

Additional information

Notes on contributors

Hodabalo Bataka

Hodabalo Bataka He is Assistant Professor at the University of Kara, Togo. His research fields cover the Effects of Non-tariff Measures to Trade, Macroeconomics Policies, Global Value Chains and Effects of Globalization.

Wonyra Kwami Ossadzifo

Wonyra Kwami Ossadzifo He is former the Economic and Financial Advisor of the Prime Minister of Togo and Associate Professor and Deputy Directeur of Research and Parternships at the University of Kara, Togo. He teaches courses in International Trade, Trade Policy Practice, Trade Negotiations and Applied Econometrics. His researches cover the liberalization of trade in services, the effects of regional trade agreements, non-tariff barriers, macroeconomics policies, global value chains. He did also research on impact evaluation of trade policies implemented in developing countries.