Sectoral sources of sub-Saharan Africa’s convergence

ABSTRACT

From 1970 to 2010, sub-Saharan African’s (SSA) labour productivity hovered at around 6% of the US level. This lacklustre performance, which remained stubbornly low despite the SSA’s growth spurt that started in the mid-1990s, masks a great deal of variations across sectors and countries. Using a structural decomposition, we examine, for a representative sample of SSA countries, the sectoral sources that hold back their convergence to the US frontier. Our results suggest the presence of strong – and possibly long-lasting – headwinds that have wiped out the favourable effects of substantial, yet circumstantial, tailwinds. Headwinds, quantified by the unfavourable within- and reallocation-effects, are indicative of significant capital-deepening and technology gaps, both of which are extremely hard to bridge. The tailwinds, represented by favourable between-effects, result from the convergence of the SSA labour force to sectors where some US sectors have seen a slowdown of their productivity relative to that of the whole economy – a development unrelated to the fundamentals underlying the SSA economy. Although few exceptions emerged out of this general pattern, these results are indicative of a bleak outlook for the SSA economic performance at least in the medium run.

KEYWORDS:

• Convergence decomposition
• productivity growth
• structural change
• sub-Saharan Africa

JEL CLASSIFICATION:

• N10
• O47
• O55
• O57

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ This sample includes some landlocked, resource-scarce economies (Ethiopia and Malawi), some coastal, resource-scarce economies (Ghana, Kenya, Mauritius, Senegal and Tanzania) and some resource-rich countries (Botswana, Nigeria, South Africa and Zambia).

² http://www.rug.nl/research/ggdc/data/africa-sector-database

³ Kenya, Malawi, Botswana and Mauritius became independent in 1963, 1964, 1966 and 1968, respectively.

⁴ http://www.rug.nl/research/ggdc/data/10-sector-database

⁵ Historical data for the United States are from Dennis and İşcan (2009).

⁶ The figures are 7% in 2010, down from 49% in 1970 (Timmer, De Vries, and De Vries 2014).

⁷ This hump-shaped pattern in manufacturing employment shares is well-known for the developed world. The experience of Mauritius looks like the Korean one. In South Korea, manufacturing employment share increased from 13.6% in 1970 to 28.1% in 1988, and by 2010 it fell to 18.2% (Timmer, De Vries, and De Vries 2014).

⁸ In countries like Ghana, Senegal and Tanzania, the levels of productivity in business services are extraordinarily large. This is due to the fact that employment is so low (relative to the value added figures) in these sectors so that they do not have major aggregate effects.

⁹ In fact, the question, How did Botswana and Mauritius managed to avoid the long and steady fall well below the frontier that features the development experience of the majority of other countries?, has led to studies exploring the success stories of these two countries (see, e.g., Carroll and Carroll, 1997; Acemoglu, Johnson, and Robinson 2003; Frankel 2010).

¹⁰ The Dutch disease is a process by which the boom in a natural resource sector results in shrinking nonresource tradables, making the economy prone to resource-specific shocks. Several studies have corroborated this result for Botswana (see Van Der Ploeg 2011 and the references therein).

¹¹ The detailed derivations are available in Caselli and Tenreyro (2006).