Enhancing productive capabilities through intra-regional trade and cross-border investments in Southern Africa

ABSTRACT

Regional integration is an important factor for enabling knowledge flows between economies and enhancing the capacity of firms within the integrated block to benefit from local knowledge spillovers. This study analyses data on economic interactions between Botswana and its technologically more advanced southern neighbour, South Africa, to examine the extent to which knowledge flows facilitated by geographical proximity translate into fostering technological learning and productivity of manufacturing firms. Industry- and firm-level data on bilateral capital goods trade and investments over the period 1991–2013 are used to assess the technological learning of the manufacturing sector in Botswana. This study also applies the Hunt, J, & Tybout, J (1999. Does Promoting High-Tech Products Spur Development? FEEM Working Paper REG 42. Milan: Fondazione Eni EnricoMattei) technological sophistication framework to analyse the role played by regional trade and investment flows between the economies of South Africa and Botswana in the skills intensification of manufacturing firms. Skills intensity decomposition reveals that Botswana’s manufacturing technical intensity has been positively influenced by the extent of capital goods trade and investment linkages with South African economy.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1 Barba Navaretti & Tarr (2000) provide a detailed review of the various theoretical models that conceptualise how trade and their interactions affect knowledge diffusion, together with the corresponding empirical evidence.

2 Nonetheless, some scholars, like Alden & Soko (2005), have alleged that South African companies operate like sub-imperial agents as they care less for backward integration or growing local capabilities of indigenous companies.

3 Some authors have argued that South Africa benefits more from this Custom Union than other members and that some of the initiatives that could have deepen further regional integration in the sub-region have been frustrated by the country.

4 Its major strengths include its physical and economic infrastructure, natural mineral and metal resources, a growing manufacturing sector, and strong growth potential in the tourism, higher value-added manufacturing, and service industries.

5 Indeed, as shown by Blundell & Bond (1998), standard GMM estimation (as in Arellano & Bond, 1991) has poor finite sample properties and is also downwards biased, especially when the time dimension T is small. The bias is only sufficiently small for T = 30 or more. If difference GMM was applied instead, such biases would otherwise make its inferences unreliable, as explained by Roodman (2006).