South Africa’s spatial inequality translates in significantly different lived experiences among members of different communities across the country. Statistics South Africa gathers data on a range of socio-economic outcomes of individuals and households through an array of national surveys; these data can be analysed at the national, provincial, district and sometimes municipal level, and provide us with a sense of well-being, deprivation and inequities in these, between these different geographies. However, there is not yet one standardised set of data that would allow for a coherent, systematic and longer-term understanding, visualisation and tracking of a broad set of indicators on well-being, that allows for a better understanding of socio-economic outcomes at the community level. Yet, understanding this local context is important, as it is within that local reality that policies and interventions aim to make a difference. South Africa’s government has recognised this too and, with the introduction of its District Development (DD) Model, aims to see different spheres and departments of government work together for larger impact, “higher performance and accountability for coherent service delivery and development outcomes”. A consolidated, central point of information that is accurate and regularly updated, would provide a strong basis for the implementation South Africa’s DD Model.
This project therefore proposes the development of an interactive, online Community Explorer that would allow researchers, policy-makers and civil society members to build a stronger understanding of well-being at the community (or main area) level in South Africa. Such an understanding is crucial to inform development efforts implemented at that community level. We suggest drawing on the local level information for the Steve Tshwete municipality to pilot the Community Explorer approach.
The local municipality of Steve Tshwete is part of the Mpumalanga province, an area that is home to one of the country's largest coal mining areas and accounts for 83% of the coal produced in South Africa. Steve Tshwete can be considered as one of the commercial centers of this province, with one of the largest local economies in the district dominated by the mining, manufacturing and financial sectors. As such, coal mining and the three coal-fired power plants currently in operation are by far the largest contributor to local employment, accounting for 40% of it.
This project is part of the Extension of the EU-AFD Research Facility on Inequalities. Coordinated by AFD and financed by the European Commission, the Extension of the Research Facility will contribute to the development of public policies aimed at reducing inequalities in four countries: South Africa, Mexico, Colombia and Indonesia over the period 2021-2025.
This project proposes to leverage the data and tools already available on the South African Youth Explorer (and the related WaziMap tool). The SA Youth Explorer is a SALDRU-led project that constructs and maps a range of indicators that measure key dimensions of well-being among young people, at various geographical levels. Using Census 2011 data, these indicators are currently constructed for the following domains: demographics, education, living environment, economic opportunities and youth poverty (including income poverty and multidimensional deprivation). In addition, the project has begun the construction, verification and maintenance of a central database of service provision, that allows for government-provided services to be mapped down to the main area level. Finally, it is the project’s aim to explore the possibilities of adding a third layer of knowledge with local labour market demand side information. As such, the overall aim of the proposed project is to provide “an understanding of the functionings of geographical areas as economic and social systems” and thereby “to promote the construction of an integrated and effective” approach to policy and planning that would ultimately contribute to the social betterment of all.
In addition, the project will use the administrative South African Revenue Service (SARS) and National Treasury (NT) Firm-Level (SARS-NT) Panel data developed as a joint SARS–National Treasury–UNU-WIDER initiative which gives matched employee-employer level information and thus allows computing labor market demand indicators. The greatest advantage of the administrative SARS–NT Panel data over other firm-level surveys is that it allows us to have employee-related information such as income, age and gender, as well as firm-level information such as labour costs, gross sales, industry sector, firm age, productivity, firm size, learnership and training cost . Another advantage of the administrative SARS–NT Panel data which is important for the project is that the worker and firm information can be aggregated to four different geographical levels, namely: province, district municipality, local municipality, and main place . With these geographical levels, it is possible to create local averages of various worker and firm variables that can then be mapped alongside Higher Education Institutes present at the local level.
on the same region
on the same topic