Original Research

Assessing the asymmetric linkages between foreign direct investments and indigenous innovation in developing countries: A non-linear panel auto-regressive distributed lag approach

Benjamin Azembila Asunka, Zhiqiang Ma, Mingxing Li, Oswin Aganda Anaba, Nelson Amowine, Weijun Hu
South African Journal of Economic and Management Sciences | Vol 23, No 1 | a3496 | DOI: https://doi.org/10.4102/sajems.v23i1.3496 | © 2020 Benjamin Azembila Asunka, Zhiqiang Ma, Mingxing Li, Oswin Aganda Anaba, Nelson Amowine, Weijun Hu | This work is licensed under CC Attribution 4.0
Submitted: 17 December 2019 | Published: 21 December 2020

About the author(s)

Benjamin Azembila Asunka, School of Management, Jiangsu University, Zhenjiang, China; and School of Business and Management Studies, Bolgatanga Technical University, Bolgatanga, Ghana
Zhiqiang Ma, School of Management, Jiangsu University, Zhenjiang, China
Mingxing Li, School of Management, Jiangsu University, Zhenjiang, China
Oswin Aganda Anaba, School of Management, Jiangsu University, Zhenjiang, China; and School of Applied Science and Arts, Bolgatanga Technical University, Bolgatanga, Ghana
Nelson Amowine, School of Management, Jiangsu University, Zhenjiang, China
Weijun Hu, Art College, Jilin University, Changchun, China


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Abstract

Background: The contributions of indigenous innovation and foreign direct investments (FDI) inflows are critical elements of economic growth and hence very important for developing economies. FDI inflows have been recognised as having a direct influence on innovation in host countries. The relationship between these two variables is explored and well documented in literature. However, these studies have focused on linear relationships between FDI and indigenous innovation, ignoring a possible asymmetric relationship between them.

Aim: The current study aims to analyse the existence of hidden cointegration and asymmetries between the two variables using a non-linear approach.

Setting: The focus of this study is on developing countries. Five countries are selected from the regions of Africa, Asia, Europe and South America. These countries are chosen on the basis of economic status (all countries are developing countries) and data availability.

Methods: The study employs panel data of 20 developing countries from 1993 to 2017. The study employs the non-linear auto-regressive distributed lag model to test for an asymmetric relationship between the variables. The variables are deconstructed into their negative and positive components to identify possible hidden cointegration and asymmetries that exist between them. This method allows for the detection of long-run asymmetric relationships in a non-linear fashion.

Results: The empirical findings show that a long-run cointegration and asymmetric relationship exists between the negative and positive components of FDI and indigenous innovation. For the four regions, positive changes in FDI directly influence positive changes in indigenous innovation. Negative changes in FDI have no effect on the positive changes in indigenous innovation in the countries under study. However, negative changes in FDI influence negative changes in indigenous innovation across the four regions.

Conclusion: FDI inflows have a positive and significant effect on indigenous innovation in developing countries, and reduction in FDI can lead to reduction in innovation output in the long term. Policy directions in developing countries will be effective if they are centred on non-linear relationships between the investigated variables.


Keywords

indigenous innovation; FDI; asymmetric cointegration; non-linear panel auto-regressive distributed lag model; developing countries.

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