2.2.1 2.3 Electricity consumption
The sectoral distribution of electricity consumption in South Africa provides some insight into the
relative importance of each sector in terms of consumption. Figure 2 illustrates the relative con-
sumption for the following sectors: Residential, Commerce, Agriculture, Transport and Industry,
using the Department of Minerals and Energy price report data set.
INSERT FIGURE 2 HERE
From Figure 2, it is evident that the bulk supply of electricity to municipalities (which include
Residential, Industrial and Commercial demand for electricity) comprises the largest component of
electricity consumption, followed by the Agriculture and Transport sectors. It is important to note
that these sales reflect the direct sales of Eskom to these sectors.
INSERT FIGURE 3 HERE
Figure 3 shows that there is a relationship between electricity prices and the two most studied
price indices, namely the CPI and the Producer Price Index (PPI). However, the CGE model is not
well-suited to comment on the causality of these relationships, since it is a relative price model. The
important point to note from Figure 3 and Table 5 is that electricity prices have generally increased
by less than the inflation rate in most time periods, while Eskom would have preferred that they
could increase prices to stay in sink with inflation.
INSERT TABLE 5 HERE
To enable a more detailed analysis of the impact of a change in electricity prices on the real
exchange rate of South Africa, different scenarios are analysed using a CGE model. Since a CGE
model takes into account all inter-industry adjustments, including a decline in demand, before it
arrives at an equilibrium price level, the results are different from those of partial equilibrium models
that simply multiply a change in price with the CPI weight associated with electricity. Partial
analysis models usually assume that demand remains constant irrespective of changes in the level
of the price and is clearly inconsistent with economic theory. In such models, the effects of price
increases will be over-estimated.
3 Data and Model
The data used in the paper are the official 1998 Social Accounting Matrix (SAM) of South Africa,
developed by Statistics SA (StatsSA, 2001). The SAM divides households into 12 income groups
and 4 ethnic groups, and distinguishes between 27 sectors. The elasticities used for the Constant
Elasticity of Substitution (CES) functions in the model have been taken from De Wet (2003), who
estimated the elasticities using time-series data.
The model is the static CGE model of the Department of Economics at the University of Pretoria,
called UPGEM. It is similar to the ORANI-G-model of the Australian economy, and is written and
solved using GEMPACK, a flexible software system for solving CGE models (Harrison and Pearson,
1996). In general, the model allows for limited substitution on the production side while it focuses
on substitution in consumption. It is a static model with an overall Leontief production structure
and CES sub-structures for (i) the choice between labour, capital and land; (ii) the choice between
the different labour types in the model; and (iii) the choice between imported and domestic inputs
into the production process. Household demand is modelled as a linear expenditure system that
differentiates between necessities and luxury goods, while households’ choices between imported and
domestic goods are modelled using the CES structure.
3.1 Assumptions
We model both the short-run and long-run effects of an increase in the price of electricity. The
standard closures1 are described here, but in the scenarios that we model, we make slight adjustments
1We use the word “closure” to indicate which variables in the model are exogenous.