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Modelling composition of growth, FDI and welfare in Africa: a SEM approach

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Abstract

While there have been separate studies on FDI–growth and FDI–welfare links, few or no studies exist that simultaneously examine FDI–growth–welfare link at aggregate or sectoral level. This study adopted a recent causality method and a simultaneous equation model to analyse the effect of FDI on sectoral growth and welfare using a cross-sectional panel of 23 countries, spanning 1990‒2019. The study accounted for sectoral spillover effects, heterogeneity, simultaneity and cross-sectional dependence in our model. Findings suggest that FDI promotes output in the manufacturing and services sectors more than in the agriculture sector, while it fosters human development (HD). Also, the results show that while HD promotes output in the agricultural sector, it deters output in the manufacturing and service sectors. Further findings show that only agricultural output improves HD among the countries. This study therefore recommends that for African countries to improve sectoral output growth and welfare using FDI as a catalyst, a policy framework toward attracting more FDI into the three key sectors (especially in the manufacturing and services) is desirable for increased output and human development in Africa.

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Availability of data and materials

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

Notes

  1. The United Nations defined Human Development Index (HDI) as composite measure of a country’s total wellbeing which comprised health, education and standard of living.

  2. Sector specific prices are used, except in the case of the service sector for which we did not use any commodity price due to data unavailability. Specifically, world agricultural commodity prices were used in the agricultural sector, while beverages commodity prices (by definition this captured manufactured cocoa and tea) was used as proxy for manufacturing sector price.

  3. All variables are expressed in logs except Rule of Law, Population Growth Rate and Human Development Index.

  4. See Appendix for the list of countries.

  5. We also employed the Households and NPISHs Final consumption expenditure per capita (constant 2010 US$) as a measure of general wellbeing to check for robustness of results. This data was obtained from the World Bank data base online (WDI 2021).

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Acknowledgements

We appreciate the support of the Editor and the valuable comments and suggestions of the anonymous reviewer.

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Authors and Affiliations

  1. Department of Economics and Development Studies, Alex Ekwueme Federal University, Ndufu-Alike, Abakaliki, Nigeria

    Anayochukwu Basil Chukwu & Tobechi F. Agbanike

  2. Department of Economics, University of Ibadan, Ibadan, Nigeria

    Adeolu O. Adewuyi, Adebowale M. Adeleke & Banji B. Awodumi

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  1. Anayochukwu Basil Chukwu
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  2. Adeolu O. Adewuyi
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  3. Adebowale M. Adeleke
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  4. Banji B. Awodumi
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Appendix

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See Table 11.

Table 11 Foreign direct investment, net inflows (%) of GDP.
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Chukwu, A.B., Adewuyi, A.O., Adeleke, A.M. et al. Modelling composition of growth, FDI and welfare in Africa: a SEM approach. Econ Change Restruct 55, 2445–2478 (2022). https://doi.org/10.1007/s10644-022-09390-8

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