Abstract
Rapid urbanization will define Africa’s demographic future. How, then, can policymakers create urban environments that support economic growth and raise living standards for local households? We examine this question from the perspective of the Gauteng City-Region—the South African mega-metropolis anchored by Johannesburg. The Gauteng City-Region has made significant progress over the past two decades. GDP per capita is nearly one-quarter higher today than in 2000. Educational attainment is up. However, productivity and GDP per capita growth have both slowed since 2010. High levels of unemployment, income inequality, and social exclusion reflect the region’s apartheid legacy. The region can bolster its position as the “Gateway to Africa” by embracing trade and investment, enhancing technology commercialization, and boosting employability through improved connections between school and work.
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Notes
- 1.
Employment figures for the years 2009 to 2015 come from the Quarterly Labor Force Survey (QLFS) of Statistics South Africa. This survey was adopted in March 2009 to better measure employment. As a result the employment figures for the years 2000–2008, which were based on the Labor Force Survey (LFS), and the new series were not comparable. To bridge this gap in the times series Oxford Economics estimated employment between 2007 and 2008 using GVA series and sectoral productivity trends. The data prior to 2007 was estimated using a combination of sectoral GVA, productivity trends and total employment from the original LFS. By using total employment data from the original LFS, the estimated profile follows the pattern of the original series. At each stage of the process, all provinces were constrained to be consistent with the national total.
- 2.
Defining a “tradable” industry has become more complicated as technology and transportation have redefined the types of economic activity that can be traded. In order to compare metropolitan areas in different countries, this analysis defines the tradable industries as: Agriculture, forestry & fishing; Mining; Manufacturing; Transport and communications; and Financial & business services. This definition is based on previous analysis by Spence and Hlatshwayo (2011) and Jensen and Kletzer (2005), but we were unable to recreate exactly the industrial definitions from these analyses. For instance, financial and business services include real estate activities, which are not tradable.
- 3.
The Gauteng City-Region Observatory (GCRO), who partnered on the research for this report, is acknowledged for extracting, and furnishing to the authors specific Quantec data used at various points in this City Profile. Under the auspices of a license for Quantec data held by the University of the Witwatersrand (Wits) where GCRO is based, which license was jointly paid for by GCRO, GCRO accessed selected Quantec datasets and provided data to the authors as excel tables for the purposes of analysis. Quantec is referenced as the original source of the data wherever applicable.
- 4.
Authors analyzed trade data from Quantec, a data provider that receives provincial trade statistics from SARS, which provides the following disclaimer. “The import and export statistics from SARS are tied to postal codes. These are the postal codes of the head office or agent that report importing and exporting activity. Quantec publishes the import and export statistics for each province and municipality by aggregating the figures for all the postal codes in each province or municipality. The data Quantec receives from SARS incorporates two issues over which Quantec has no control. First, the postal code may not reflect the actual importer/exporter address but that of an agent that handles the actual international trade (smaller agricultural exporters are sometimes a good example of this). The agent may therefore not be in the same province/municipality as the exporter or importer. Second, the importer or exporter may have several branches but all international trade transactions are handled by head office (the petroleum and mining industries are sometimes a good example of this). The head office may therefore not be in the same province/municipality as the branches.”
- 5.
Authors’ analysis of data from the Globalization and World Cities Network (GaWC).
- 6.
Authors’ analysis of OECD REGPAT data.
- 7.
Author’s analysis of Statistics SA data.
- 8.
Author’s analysis of Statistics SA data.
- 9.
Authors’ analysis of data from the Education Management Information Systems database.
- 10.
Authors’ analysis of data from the South African Quarterly Labor Force Survey.
- 11.
Authors’ analysis of World Bank’s Doing Business indicators.
- 12.
Authors’ analysis of Sabre data.
- 13.
Authors’ analysis of Sabre data.
- 14.
Authors’ analysis of data collected through speed tests at Ookla.net. There are few sources that provide comparable measures of Internet speed across cities. At the time of this analysis, the best available data was from Ookla, a leader in broadband testing and web-based network diagnostic applications. Over three million people a day use Ookla software. These data are self-reported by user-generated speed tests, and therefore should be interpreted with caution. Further, they likely offer a better approximation of residential Internet speed than commercial Internet speed.
- 15.
Authors’ analysis of 2015 World Bank Doing Business data.
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Parilla, J., Trujillo, J.L. (2018). The International Competitiveness and Connections of African Cities: Profiling South Africa’s Gauteng City-Region. In: Adeleye, I., Esposito, M. (eds) Africa’s Competitiveness in the Global Economy. AIB Sub-Saharan Africa (SSA) Series. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-67014-0_4
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