Proceedings of the 39th International Academic Conference, Amsterdam




Economic disparities across provinces and local municipalities are remarkable in developing countries such as South Africa. Economic development practitioners, policy makers, development planners, investors and business people alike have much to gain from a careful consideration of the economy. It is very important for local and foreign investors to know which industry is more concentrated in a particular area and which is non-existent. The identification of these industries allow investors to carefully take calculated opportunities and for development policy makers to prudently provide the right economic development direction. The main objective of this paper is to offer an empirical investigation of the geographic concentration of the main South African industries. This paper focuses on two economic base analysis techniques namely the location quotient and shift share technique that both seek to examine industrial dis/advantages, structure and competitiveness. The goal of economic base analysis is to uncover and reveal characteristics, strengths, weaknesses and trends that describe a regional economy. In this case, the industry Location Quotient (LQ) is a way of quantifying how concentrated industries are for each province compared to South Africa as a whole. Using data from Quarterly Labour Force Survey (QLFS) by Statistics South Africa (Stats SA) the paper report the findings over the period of 2012 to 2016. Preliminary key findings indicate that the comparative advantage of agriculture and mining declined between 2012 and 2016 in Mpumalanga, Limpopo and North West, whereas that of utilities, manufacturing improved in Northern Cape, KwaZulu Natal, Free State and Limpopo Provinces has increased. Furthermore, under the dynamic location quotient analysis, the agriculture and mining both have a location quotient in excess of 1.0, but require “intensive care” in terms of planning and investment as their advantage have declined over time in three out of nine provinces. In addition, in terms of the dynamic location quotient, community services, finance, manufacturing and transport (ranked according to employment size) can be regarded as “pre-emergent” industries in the Mpumalanga, Gauteng and Western Cape Provinces. In terms of shift share analysis, employment changes due to regional competitiveness were similar to changes due to industrial mix factors experienced in the mining, construction, transport and finance in the Eastern Cape, Mpumalanga and North West Provinces. Overall, the results suggest that policy makers should speed up the construction of large and medium sized industrial enterprises, promoting the development of secondary industry and actively enhance development of the tertiary industry.

Keywords: Employment, economic growth, competitiveness, Location quotient, shift-share analysis

DOI: 10.20472/IAC.2018.039.033

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