Provincial Equitable Share Allocations in South Africa
Centre of Policy Studies/IMPACT Centre Working Papers from Victoria University, Centre of Policy Studies/IMPACT Centre
The main source of income to the nine provinces in South Africa are grant transfers from the national government. Over 97 per cent of provincial income is from these transfers. The provincial equitable share (PES) formula is used to distribute nationally raised government revenue over the nine provinces. The formula composes of six components from which a weighted average is calculated. This weighted average is used to distribute national raised government revenue to the nine provinces. The purpose of this paper is to present the underlying theory and data describing the determination of the equitable share for each province (hereafter PES module). The PES module is an independent module that can be linked to the existing TERM-GPT model. TERM-GPT is a dynamic regional CGE model of South Africa with fiscal detail on a regional and national level. The current version of the TERM-GPT model treats national transfers to the provinces as determined outside the model. The PES module proposes a framework where these transfers from national government to the provinces are determined within TERM-GPT. Thus, changes in the underlying drivers of the PES module are linked to changes in variables determined in TERM-GPT. As an illustrative example, we reduce the percentage of people in each province with private medical aid insurance. Our results shows that reducing the number of people with private medical aid impact only the health component, which contributes 27 per cent to the weighted equitable share for each province. The health component includes two sub-components, (i) risk-adjusted population which accounts for the part of the population with and without medical aid, and (ii) the output subcomponent, which accounts for hospital related factors such as the number of visit to primary health care centres. The risk-adjusted component is impacted by reducing the number of people with medical aid insurance. Our simulation shows that the main driver for changes in the risk-adjusted component is population growth-which is based on Statistics South Africa's mid-year population growth forecast. In their forecast Gauteng and Western Cape shows the highest population growth. Our results shows that Gauteng and Western Cape's share in national transfers increases between 2020 and 2024, while the remaining provinces' share falls. By 2024, this amount to an increase of 5,048 and 1,618 million Rand for Gauteng and Western Cape. KZN and Limpopo are the two worst affected provinces.
Keywords: Provincial; Equitable; Share; South; Africa; Regions (search for similar items in EconPapers)
JEL-codes: H27 C68 (search for similar items in EconPapers)
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