MONITORING FRAMEWORKS
2.5 THE STRUCTURE OF LOW ENERGY ACCESS IN EASTERN AFRICA
2.5.1 Demand Side Constraints
Income, effective demand and access levels: The demand for modern forms of energy, including electricity, as in any other commodity in a market, is dependent on the level of income of consumers. It is intuitive to expect that as income levels increase over-time, the level of demand for modern forms of energy also increases. The willingness to pay for modern energy is income sensitive. A study by KIPPRA (2010) based on interview of 6,346 households in Kenya demonstrate that the willingness to pay per kWh/month for households in urban areas was KSh132.41 (~US$1.6), compared with KSh88.84 (~US$1.1) for rural areas and KSh35.45 (~US$0.44) for low income households. Leach’s (1992) energy ladder hypothesis ascertain that switching to modern energy services for cooking, lighting and eclectic appliances is dependent on the level of income, and its change overtime. The implication of this hypotheses is that at the lower income level, consumption of biomass and charcoal are predominant, switching to electricity, LPG, fossil fuels and appliances with income shifting to higher brackets (Masera, et al., 2000, Heltberg, 2005). The speed of transition to modern energy services will be dependent on their relative affordability, which is relative to income (IEA, 2004).
This relationship between income levels and electricity consumption is evidenced in the Eastern Africa sub-region, as shown in Fig. 32, where countries at relatively higher levels of
40 0 2
4 6 10 8 12
Burundi Rwanda Ethiopia Madagascar Uganda Tanzania D.R. Congo Kenya Djibouti India Zimbabwe Brazil China Seychelles South Africa United … France United States
GDP per capita (log) Electricity Consumption per capita (log)
income per capita exhibit higher per capita electricity consumption levels. This pattern is further demonstrated in countries outside the sub-region demonstrated in the figure. Therefore, the low level of income, on the demand side, is a key deterrent in accessing electricity.
Figure 31: The relationship between per capita income and electricity consumption (kWh).
Source: World Bank national accounts data, and OECD National Accounts data files, IEA, World Energy Outlook 2010 and data from country missions.
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Figure 32: Assessment of the electricity access gap in Eastern African countries relative to sub-regional, sub-Saharan, middle income and “universal access” levels.
-25% -24%
-17% -15% -12% -11% -10% -9% -7%
6%
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29%
70%
-31% -30%
-23% -21% -19% -17% -16% -15% -13%
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64%
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-73% -70% -68% -67% -65% -65% -63%
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-27%
14%
-99% -98%
-91% -89% -86% -85% -84% -83% -81%
-68%
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-4%
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South Sudan Burundi Uganda D.R. Congo Tanzania Rwanda Kenya Ethiopia Madagascar Eritrea Comoros Djibiouti Seychelles
Access gap to Eastern Africa Average Access gap to sub-Saharan Africa Average Access gap to Middle Income Averate Access gap to Universal Access
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The electricity consumption constraining nature of the level of income in countries in the sub-region has implication to access levels. Low income levels lead to lower effective demand for energy services, and hence lower levels of energy consumption and access. The access constraining nature of lower income levels are demonstrated in Fig. 33, which depicts that countries in the sub-region with better development levels, and better per capita income, have higher electricity access rates. These observations demonstrate that energy sector development is linked with economic development and transformation in the region that will determine the pace of income growth. The relatively lower level of economic development in the sub-region is one reason why observed energy access levels are quite low. Addressing energy access in the sub-region is interlinked with advancing economic development and enhancing consumer income.
Figure 33: The relationship between per capita income and electricity access levels.
Source: World Bank national accounts data.
Despite these strong linkages for policy makers to leverage, Mekonnen and Kohlin (2008) warn that higher income levels not necessarily lead to rapid increase in the use of modern energy services. By using the case of urban Ethiopia, they argue that urban residents, even with rising income levels, may still consider biomass a normal, as opposed to inferior, good the consumption of which need not decline with growing income. This phenomenon, known as fuel stacking, mean that growing income encourages higher consumption of modern energy sources, but in conjunction with a diverse traditional energy source portfolio, slowing the speed of switching to modern energy.
Sticky preferences and attitudes: switching to energy technologies, and accessing modern forms of energy away from traditional ones, faces the challenge of culture, attitudes and preferences. Consumers often prefer energy sources they have come to rely and use for a long time, and demonstrate resistance to switch. Murphy (2001) demonstrated that in the context of rural areas of Eastern Africa, cultural factors limit the ability of the population to rapidly switch to alternative energy technologies. Existing strong preferences can also pose a challenge (Horst and Hovorka, 2009). Mekonnen and Kohlin (2008) also demonstrated, using data from Ethiopia, that preferences for traditional fuels tend to stick even with rising urban income, partly due to sticky preferences for traditional fuels. In providing the cultural and attitudinal factors,
0 20 40 60 80 100 120 140
GDP per capita in '00
Electricity Access Rate
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Erumban and Jong (2006) demonstrate their importance in the context of differences in the adoption of ICT across countries. They find that the ICT adoption rate of a country is closely related with national culture, particularly the dimension of uncertainty avoidance. Greater access to modern energy sources will therefore need to consider demand side constraints, including the role of strong preferences, culture and attitudinal factors that shape the demand for modern energy
Settlement patterns and physical accessibility: settlement of population away from major grid network poses access challenges, given the limited diffusion of off-grid energy systems in many parts of the Eastern Africa sub-region. Illegal settlement and land use patterns pose legal and physical barriers to the urban poor. Illegal tenancy arrangements (largely unrecognized by utilities and city administration) and settlements away from the national grid pose difficulties in the face of demand (Fall, et al. 2008; Dhingra, et al., 2008). In progressive energy programs that attempt to deliver energy access to the urban poor and slum residents pose cost difficulties, attempting to deliver energy from grids that could be as far as 30 kms away, and the need for higher up-front costs that can limit access expansion to the urban poor. The high infrastructure and connection cost to most of the urban poor and rural population currently unconnected reduces their capacity to effectively demand it without some form of price-support. While rural electrification programs attempt to deal with the lack of physical accessibility of grid-based power to rural residents, UN Habitat (2009) notes that slum electrification programmes are often not prioritized and mainstreamed into national policies and programmes.
Figure 34: Electricity access in slum areas.
Source: In2EastAfrica, Photo - Residents fighting fire which destroyed over 5,000 houses in Mukuru-Mariguini, Mukuru-Kanaro, Mukuru-Chakati, Mukuru Fuata-Nyayo and Mukuru slums in South B, Nairobi, on February 28, 2011.
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Targeted subsidy, price support programs and affordability: affordability of energy is a relevant consideration in energy access promotion strategies. Subsidizing energy prices is a common feature in the Eastern Africa sub-region. While costly, these policy efforts reduce the effective price of energy to households, increasing access and consumer welfare. However, these programs often come at a hefty cost to governments and utilities. The announcement from the Government of Uganda in January, 2012 about removal of electricity generation subsidies has drawn much attention. The government spent nearly Shs 1.5 trillion in electricity subsidies since 2005, and with the commissioning of new hydroelectric systems has decided to no longer commit such sizeable subsidies. As a result, the Electricity Regulatory Authority (ERA) announced the rise in consumers pay from Shs 385.6 to Shs 524.5 per unit, a rise in commercial users pay from 358.6 to Shs 487.6 per unit, a rise in medium industries pay from Shs 333.2 to Shs 458.9 per unit and large industries’ tariff increased from Shs 184.8 to Shs 312.8 per unit.
The savings from these subsidy changes is planned to finance the other hydroeclectic projects, including Karuma Hydro Power project. The challenge of keeping electricity rates affordable and that of keeping the system financially sustainable is an on-going challenge in the sector.
Moreover, electricity subsidies that reduce the tariff to consumers largely benefit those who are already connected, and may benefit the population that have not yet accessed it, demonstrated from Eastern and Southern Africa experiences (Hosier and Kipondya, 1993;
Dube, 2003; Kebede, 200613) and from Asian experience (Shelar, et al., 2007). Since consumers already connected to access modern energy are at a relatively higher income, most of the subsidy schemes, if untargeted, goes to them, with limited impact on population access rates.
One model program is from South Africa, where subsidies are targeted to poor households who are provided access to 20-50 kWh of energy per month for free, beyond which they are exposed to rates (UNDP, 2010).
The utilization of improved cookstoves and energy efficient appliances by households is also constrained by affordability factors in the Eastern Africa sub-region. Karekezi, et al. (2008) identify that accessibility to cleaner energy sources are impeded due to taxes on imported kerosense stoves, reaching as high as 51% of the value which prices majority of households out.
Karekezi and Kithyoma (2002) also note that the cost of clean energy technologies, reaching 131% to 363% of per capita GNP in Eastern Africa, and in the face of fluctuating household income, poses serious impediment to switching to modern energy supplies.
System reliability: the demand for electricity is dependent on how reliable the energy system is over-time. The reliability of the energy system can be observed by consumers based on degree of service interruptions, the cost imposed by such interruptions, and the duration of interruptions when they occur. The frequency and intensity of power outage in select countries in the Eastern Africa sub-region is depicted in Fig. 35. While most recent data on outages is not available for most of the sub-regional countries, the indicative measures in Fig. 29 demonstrate that outages, in terms of number of days per year, are anywhere between 65-185. The number of outages per month range from less than 5 in Rwanda to close to 20 in D.R. Congo. Such systemic and frequent power outages discourage reliance of consumers on the grid, and encourage household and business investment in alternative energy supplies. Power outages in Eastern Africa exceed even sub-Saharan average by significant margins. The quality of power is
13 Kebede, B. 2006. “Energy Subsidies and Costs in Urban Ethiopia: the Cases of Kerosene and Electricity.”
Renewable Energy 31(13): 2140-2151.
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also a related problem. Households are required to install load regulators to protect household appliances from irregular currents, particularly during interruption and resumption of electrical services. Power quality is particularly a challenge to industry, where costly appliances and technology can be damaged by irregular and poor quality power supply.
Figure 35: Power outage days per year (panel 1) and number of electrical outages in a typical month (panel 2) in select countries in the Eastern Africa sub-Region.
Source: Based on data from World Bank Enterprise Survey.
Note: Data is for the following years: D.R. Congo (2010); Madagascar (2009); Uganda (2006); Burundi (2006);
Tanzania (2006); Kenya (2007); Ethiopia (2011) and Rwanda (2011).
The industrial demand for consistent and reliable energy is affected by the power interruption challenge. Based on World Bank Enterprise Survey data, Fig. 36 depicts out of the total constraints to business identified in sample of countries, the share related to electricity.
The data allows looking at the energy constraint to industry by three industrial classes: small (with 5-19 employees); medium (with 20-99 employees); and large (with 100+ employees) enterprises. In Uganda and Tanzania small, medium and large enterprises have identified electricity accounting 60 to 90% of their business challenge, even when one considers issues of crime and theft, customs and trade regulation, available human capital, labor regulations, political instability, corruption, business licensing and permits, access to land and finance, and transportation. The scale of the energy problem to industry is quite sizeable in these countries.
In Burundi, small and medium enterprises consider energy to account to over 40% of their business operation challenge, though large enterprises see energy accounting to about 16% of their business constraints. In Ethiopia, Kenya and Madagascar, large enterprises consider energy to account to over 20% of their business challenge, though small and medium enterprises put the level at relatively lower level. In D.R. Congo and Rwanda, while the share of concern enterprises allocate to electricity is relatively lower, it is nonetheless viewed as a barrier.
Figure 36: Enterprises identifying electricity as a share of overall business constraints (%).
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Source: Based on data from World Bank Enterprise Survey.
Note: Small=small enterprises with employment of 5-19; Medium = medium size enterprises with employment of 20-99; and Large=large enterprises with employment of 100+.
Furthermore, Fig. 37 demonstrates the share of enterprises who own or share generators as a back-up and self-generation system. Compared to the sub-Saharan average of 44%, the share of large enterprises who own or share generators reaches 81% in Burundi, 75%
in Ethiopia, 92% in Kenya, 44% in Madagascar, 73% in Rwanda, 91% in Tanzania, 97% in Uganda and 94% in D.R. Congo. The level of energy self-generation and losses due to outages are
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also sizeable, even by sub-Saharan average. Electricity demand in the Eastern African sub-region is therefore impacted by the reliability and consistency of supply to households and industry.
Figure 37: Enterprises owning generators and self-generating given power outages and revenue losses.
Source: Based on data from World Bank Enterprise Survey.
Note: Data is for the following years: D.R. Congo (2010); Madagascar (2009); Uganda (2006); Burundi (2006);
Tanzania (2006); Kenya (2007); Ethiopia (2011) and Rwanda (2011).
: Small=small enterprises with employment of 5-19; Medium = medium size enterprises with employment of 20- 99; and Large=large enterprises with employment of 100+.
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Average losses due to outages (% of annual sales)
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Generation capacity: the structurally low level of electricity access in the Eastern Africa sub-region is related to existing low power generation capacity. In looking at the structure of energy production and consumption in the sub-region (see Table 6), the share of thermal and electricity production and consumption are low compared with energy generated from biomass. In much of the sub-region, the share of electricity in final consumption is below 5%, and thermal ranging from 3.18% in Burundi to a high of 21.43% in Kenya. The structure of energy production and consumption demonstrates the low contribution of electricity to final consumption, partly due to poor levels of generation.
Table 6: Energy balances in East Africa, 2009.
Country
Total energy Production (%) Final consumption (%) Thermal Electricity Biomass Thermal Electricity Biomass
Burundi 3.28 0.88 95.99 3.18 0.74 96.07
Note: East Africa average doesn’t include Comoros, Djibouti, Seychelles, Somalia and South Sudan due to lack of data.
Existing generation capacity in half of the sub-regional countries is much below 500 MW (see Fig. 39), ranging from Comoros (24), Burundi (49) and Seychelles (95), to Rwanda (103), Djibouti (123) and Eritrea (139). Larger countries similarly demonstrate lower level of generation, ranging from Uganda (822) to D.R. Congo (2,300). Even though the generation level is quite low in small States, the per capita
consumption (see Fig. 38) is relatively better
Figure 38: Sub-Regional distribution of energy
consumption per person.
in Sychelles, Djibouti and Comoros than in large States, such as Uganda and Ethiopia.
But the small states of Burundi and Rwanda have low generation and consumption levels. The growing population, economy and demand for electricity in the region put pressure on existing generation capacity.
Meeting the country and regional electricity access targets will require enhancing the weak electricity generation capacity in the sub-region.