Journal Issue

Chapter 1. Energy Subsidies in Sub-Saharan Africa (SSA): Stylized Facts

Trevor Alleyne, and Mumtaz Hussain
Published Date:
August 2013
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Recent Developments in Fuel Pricing and Fiscal Implications1

International oil and oil products prices rose sharply in 2003–2012 in two sequences (Figure 1). They increased steadily since 2003 and more than doubled from early 2007 to mid 2008 when they peaked. They fell precipitously until the end of 2008 before rebounding strongly. This evolution has been challenging for many importing countries that saw their energy bills surge, but it has also made it increasingly difficult for many countries to resist social demands for less than full pass-through into retail fuel prices.

Figure 1.International Petroleum Product Prices, US$ a Liter

Source: U.S. Energy Information Administration.

Since end-2008, the fuel price pass-through in SSA has been lower than that of advanced economies and emerging Europe, but has been in line with pass-through in the rest of the world (Box 1).2 Only about two-thirds of the increase in international prices was passed through to domestic prices (Figure 2). From end-2008 to end-2011, when prices resumed their upward trend, the median pass-through in SSA was 66 percent. That was about the same level as in Latin America and Asia and Pacific, but well above that in the Middle East and Central Asia. Fuel price pass-through was higher than 100 percent in advanced economies and emerging Europe.

Figure 2.Fuel Price Pass-Through, Fuel Taxes, and Fiscal Cost

Sources: IMF World Economic Outlook and staff calculations.

Between end-2008 and end-2011, fiscal costs increased in SSA as a result of relatively low pass-through of international fuel price increases during that period. Increases in international fuel prices not fully passed through imply a loss of tax revenue and/or increased subsidies. The median increase in fiscal cost was 1.6 percent of GDP in SSA and was second only to that of the Middle East and Central Asia (Figure 2.2). These two regions experienced losses of more than twice those recorded by Asia and Pacific and Latin America and the Caribbean.

Box 1.Methodologies and Key Concepts


Fuel Subsidies

The estimation of fuel subsidies has usually relied on two methods (and its variants): (1) a price pass-through analysis; and, (2) a price benchmark analysis.

The price pass-through analysis is dynamic in the sense of making inferences about the evolution of fuel subsidies or tax revenues over a certain period. An important advantage of this method is its simplicity in terms of data requirements. In fact, it only requires collecting domestic retail prices and the international fuel price for two points in time (for example, end-2008 and end-2011). By comparing the changes in domestic retail prices against the changes in international prices over that period, changes in fiscal tax/subsidy levels (be it in terms of lower fiscal revenue or budgetary outlays) can be obtained. In Figure 2, this methodology is used to highlight the fact that, in 2011, the median SSA country lost 1.6 percent of GDP in fuel tax revenue because of increased subsidization of fuel relative to end-2008. At the same time, this method has limitations. First, it assumes no changes in the cost structure of domestic fuels over time (e.g., transportation and distribution costs), although this may not be a serious problem when comparing two relatively close time periods. Second, it is quite sensitive to the choice of the starting point for the analysis.

The price benchmark analysis relies on detailed cost structures to determine cost-recovery fuel price benchmarks. The subsidy (tax) per liter of fuel product is obtained by subtracting the relevant benchmark from the domestic retail price. Benchmark prices are computed by adding CIF fuel import prices, national margins, and costs (e.g., transportation, distribution) and indirect taxes. There are various variants to this approach. On the one hand, pre- and posttax fuel subsidies can be obtained depending whether indirect taxes are excluded or included, respectively, from the measurement of the benchmark price. The presence of pretax subsidies (i.e., negative taxes) would clearly indicate operating losses within the supply chain and/or sale of fuel products. However, this measure may not fully reflect the true fiscal cost of the subsidies: even if the pretax subsidy is negative, thereby indicating positive revenue, those revenues may be less than if the rates stipulated in the official fuel pricing formula were applied.

There are various options to compute “posttax” fuel subsidies, which seek to measure the fiscal cost (and sometimes other costs). In this study, the benchmark fuel taxation level was taken to be the sub-Saharan Africa average of gross tax (i.e., VAT and excises) per liter. Such a benchmark focuses on the revenue potential of fuel taxation as stipulated by the tax rates in the countries’ fuel pricing formulas, where applicable. However, the recent IMF Board paper on energy subsidy reform (IMF, 2013) uses the national VAT rate to compute the benchmark fuel taxation level and also adds a corrective (or Pigouvian) tax to charge for externalities associated with CO2 emissions, local pollution, and other externalities such as traffic congestion and accidents. Clearly, the estimate of posttax subsidies will be very sensitive to the choice of the benchmark fuel taxation level.

Electricity Subsidies

In general, power utilities in sub-Saharan Africa are quasi-fiscal entities. These utilities channel a variety of transfers to consumers through underpricing, uncollected electricity bills, and a number of other inefficiencies (e.g., large power distribution losses). However, the total cost of such transfers is not reflected in the budget because a large portion is implicit or involuntary (e.g., power theft).

This study computes a unified measure of both explicit and implicit electricity subsidies called the quasi-fiscal deficit (QFD), which is defined as: “the difference between the actual revenue charged and collected at regulated electricity prices and the revenue required to fully cover the operating costs of production and capital depreciation” (Saavalainen and Joy ten Berge, 2006). The QFD is calculated as follows:

QFD = Cost of underpricing of electricity + Cost of nonpayment of bills + Cost of excessive line losses


Cost of underpricing of electricity = Q*(AC-P e); where Q is the quantity of electricity billed to all types of consumers; AC is average cost of producing one kWh of electricity, including capital depreciation; and P e is the weighted average effective tariff per kWh that is applied by the power utility. The effective tariff rate is the price per kWh of electricity consumed at a specific consumption level when all charges—variable and fixed—are taken into account.

Costs of nonpayment of power bills = Q* P e *(1-c); where c is the collection rate that varies between 0 percent and 100 percent.

Costs of excessive line losses = Q* P e *(L-Ls); where L is actual line losses in the distribution of electricity as a percent of total consumption and Ls is the level of standard line losses—assumed at 10 percent in case of sub-Saharan Africa, in line with the generally held view of experts.

Thus, the quasi-fiscal deficit of a power utility is measured as:

Some Key Concepts

Price pass-through: Pass-through is defined as the absolute change in domestic retail prices divided by the absolute change in international prices, both in domestic currency. Pass-through above (below) 100 percent implies that net fuel taxes (i.e., taxes less subsidies) are increasing (decreasing). Pass-through is calculated based on end-of-period data on domestic retail prices, international prices, and domestic currency exchange rates. For instance, pass-through from end-2008 to end-2011 is calculated as the change in the domestic retail price in this period (expressed in domestic currency) divided by the change in the international price in this period (also in domestic currency).

Pretax fuel subsidy: The pretax fuel subsidy for gasoline, kerosene, and diesel is defined as the difference between an estimate of cost-recovery price (defined as CIF import price plus margins and costs) and domestic retail prices. This estimate is multiplied by fuel consumption to obtain the pretax fuel subsidy. All this information was obtained from official national sources. In computing total fuel subsidies both positive and negative values are added, hence products with positive taxes partially offset those with negative taxes (i.e., subsidies).

Posttax fuel subsidy: The posttax fuel subsidy for gasoline, kerosene, and diesel is defined as the difference between an estimate of cost-recovery price (defined as CIF import price plus margins and costs) plus the SSA average of gross tax per liter and domestic retail prices. This estimate is multiplied by fuel consumption to obtain the posttax fuel subsidy. All this information was obtained from official national sources. In computing total fuel subsidies both positive and negative values are added, hence products with positive taxes partially offset those with negative taxes (i.e., subsidies).

There is a clear difference in the pass-through behavior of oil exporters and oil importers in SSA (Figure 2.3). Looking at the period after the price shock (i.e., end-2008 to end-2011), the median pass-through for oil exporters was much lower than the median for oil importers. Oil exporters found it harder to pass through changes in international oil prices to consumers, who may consider low fuel prices the most convenient way to share in the oil wealth of their countries. As a result, the increase in fiscal cost in SSA oil-exporting countries was almost twice as high as in SSA oil-importing countries (Figure 2.4). This reflects both a lower pass-through and higher fuel consumption in oil-exporting countries.

In addition to looking at the dynamic behavior of fuel prices between end-2008 and end-2011 to calculate the change in fuel taxation/subsidization, estimates of the absolute size of fuel subsidies at end-2012 were also calculated. Based on a detailed survey conducted for SSA countries, the fuel subsidies for gasoline, kerosene, and diesel were estimated based on the difference between an estimate of cost-recovery price and domestic retail prices. This estimate was multiplied by fuel consumption to obtain the fuel subsidy. Two alternative measures were computed. The “pretax” subsidy compares a cost-recovery price that includes the CIF import price plus national margins and costs with the retail price. The “posttax” subsidy compares an adjusted cost-recovery price (i.e., the CIF import price plus national margins and costs plus a measure of gross taxes per liter) with the retail price. For this paper, the SSA average gross tax per liter was used, but clearly other formulations could be justified (e.g., in IMF [2013], posttax subsidies were calculated using an adjusted cost-recovery price that includes the cost of externalities, such as CO2 emissions and traffic congestion). Although the “pretax” subsidy reflects the more common understanding of a subsidy, the “posttax” subsidy aims to measure the fiscal cost or unutilized fiscal space.

Most SSA countries do not have “pretax” subsidies on fuel (Figure 3a). In other words, the retail price of fuel products is typically greater than the cost recovery price. However, while only 10 percent of oil importers have pretax subsidies, almost all of the oil exporters do and the median cost of the subsidies for this group is 0.8 percent of GDP.

Figure 3a.Pretax Fuel Subsidies in Sub-Saharan Africa (2012)

(percent of GDP)

Sources: Authorities’ data and IMF staff estimates.

Note. Negative values represent a tax. The pre tax data for gasoline, kerosene, and diesel in each country are calculated as the difference between an estimate of cost-recovery price (defined as: CIF import price plus national “margins and costs”) and domestic retail prices

“Posttax” fuel subsidies are significantly higher and more widespread across the region (Figure 3b). At 1.9 percent of GDP, these subsidies were almost five times higher in oil-exporting countries than in SSA oil importing countries (0.4 percent of GDP).

Figure 3b.Fuel Subsidies in Sub-Saharan Africa (2012) on Posttax Basis

(percent of GDP)

Sources: Authorities’ data and IMF staff estimates.

Note: Negative values represent a tax. The post tax data for gasoline, kerosene and diesel in each country are calculated as the difference between an estimate of cost-recovery price (defined as: CIF import price plus national “margins and costs” plus the SSA average gross tax per liter) and domestic retail prices.

Electricity Subsidies and Cost Recovery Tariffs3

This subsection gives estimates of fiscal and quasi-fiscal costs in the power sector in SSA countries and analyzes the factors that underlie these costs. A power utility company generates hidden costs when its realized revenue is less than the revenue it would collect were it operated with cost recovery tariffs based on efficient operations (i.e., operations with normal line losses and full collection of bills). In the last few decades, power companies in SSA tended to experience substantial hidden costs, which in turn constrained their ability to invest in new power capacity, to expand access, and to improve service quality. As a result, per capita installed generation capacity in SSA (excluding South Africa) is about one-third of that in South Asia and one-tenth of that in Latin America (Eberhard and Shkaratan, 2012). Similarly, per capita consumption of electricity in SSA (excluding South Africa) is merely 10 kWh a month, in contrast to about 100 kWh in developing countries and 1000 kWh in high-income countries.

Most countries in SSA have highly regulated electricity markets. A survey on SSA countries (Appendix 1) suggests that most countries implement some form of administered pricing for electricity, most frequently ad hoc nonautomatic price setting schemes (Figure 4). Even in countries with de jure pricing policies based on an automatic formula, these automatic mechanisms are frequently suspended or intervened. Most electricity utilities are state owned, and it appears that policymakers are reluctant to adopt market-based pricing policies, partly because of concerns related to access, affordability, and institutional capacity.

Figure 4.Sub-Saharan Africa: Electricity Pricing Mechanisms

Source: Survey of IMF country teams for SSA countries (April 2012).

Subsidies for electricity services are common in SSA. A majority of countries have explicit subsidies for electricity (Figure 5). Despite shortcomings in terms of data availability, it is clear that explicit subsidies are substantial. We estimate that direct power subsidies average 0.4 percent of GDP for SSA, but can reach up to 0.8 percent (Mali). In addition, there has been a build-up of arrears by state-owned power utilities (on average 0.6 percent of GDP) and debt accumulation (on average 1.5 percent of GDP).

Figure 5.Sub-Saharan Africa: Explicit Electricity Subsidies

Source: Survey of IMF country teams for SSA countries (April 2012).

Factors Contributing to the Under-Recovery of Power Costs

Excluding South Africa, the average cost of supplying one kWh in sub-Saharan African countries is the highest among developing countries (Eberhard and Shkaratan, 2012). Using the latest annual data for 2008–10, the average cost of electricity in SSA was about US$0.15 a kWh. The average cost of power was even higher in countries that rely primarily on thermal generation—US$0.21 a kwh (Figure 6). Besides inefficiencies in power companies, high use of costly emergency power generation (e.g., in Uganda until early 2012), low economies of scale in generation, and limited regional integration also contributed to these high unit costs.

Figure 6.Sub-Saharan Africa Countries: Average Cost of Power Generation

(US cents a kWh)

Source: The World Bank’s AICD database and various country reports. Data is for 2008-10 (latest year available). South Africa is excluded.

Effective power tariffs are generally set well below the historical average cost of supplying electricity (Figure 7).4 Despite residential tariffs in SSA countries being much higher than in other regions of the world (Briceño-Garmendia and Shkaratan, 2011), they cover, on average, only about 70 percent of the cost of power (based on data for the latest year in 2005–09).

Figure 7.Cost Recovery: Average Tariffs as a Percent of Average Historical Costs

Source: Briceño-Garmendia and Shkaratan (2011) and various country reports from the World Bank.

In addition, power utilities tend to be subject to high line losses—in some cases half of power injected into the distribution system is lost—and undercollection problems. On average, distribution losses (the amount of electricity injected into the distribution network that could not be billed) are around 25 percent—well above the international norm of 10 percent (Figure 8). Similarly, the average collection rate was around 85 percent. The costly power supply relative to per capita income in SSA has contributed to power theft and nonpayment of bills. Evidence from household surveys indicates that as much as 60 percent of poorer households do not pay their electricity bills (Briceño-Garmendia and Shkaratan, 2011).

Figure 8.Sub-Saharan African Countries: Distribution Line Losses of Power Utilities

(Losses in percent of power supplied)

Source: Eberhard and others (2008) and various country reports from the World Bank.

Power Sector’s Quasi-Fiscal Deficits in SSA Countries

Quasi-fiscal deficits of power utilities in SSA countries are large in terms of GDP (Figure 9). Using the latest available data for 2008–10, the median quasi-fiscal deficit (QFD) was about 1.7 percent of 2009 GDP. However, there are large variations in QFDs across countries: from about 11 percent of GDP in Zimbabwe to less than 0.5 percent of GDP in Botswana and Chad. Also, a number of countries have managed to reduce deficits (e.g., Kenya) while others have experienced increased QFDs (partly due to increased reliance on emergency power generation). Kenya implemented a number of reforms in its power sector during the last decade that reduced the QFD by about 0.7 percent of GDP. In any case, these estimates of total subsidy are about three times as large as the levels reported as direct fiscal transfers in the AFR survey (Appendix 1).

Figure 9.Sub-Saharan African Countries: Quasi-Fiscal Deficits of Power Utilities

(QFD in percent of 2009 GDP)1

Source: IMF staff calculations based on data from the IMF, the World Bank, and International Energy Agency.

1 Zimbabwe, which had QFD of 11 percent of GDP in 2009, is excluded from the calculation of average.

SSA countries have made little progress in reducing QFDs (Table 1). The median power sector’s QFD has remained unchanged between 2005 and 2010. A slight reduction in underpricing was mostly offset by increased distribution losses.

Table 1.Sub-Saharan Africa: Trends in Quasi-Fiscal Deficits of Power Utilities(Percent of GDP, averages unless otherwise noted)
Quasi-fiscal deficit generated by:
Distribution line losses0.70.8
Undercollection of bills0.20.2
Total quasi-fiscal deificit (excluding Zimbabwe)1.91.8
Total quasi-fiscal deificit (median)1.71.7
Source: IMF staff calculations based on data from country authorities, the IMF, the World Bank, and International Energy Agency.
Source: IMF staff calculations based on data from country authorities, the IMF, the World Bank, and International Energy Agency.

Affordability vs. Cost Recovery: Is There Room for Raising Power Tariffs to Cost Recovery Levels?

Power sector reforms to enhance efficiency and reduce losses should help reduce substantially the QFD of power utilities. Average residential tariffs in SSA are already higher (in some cases twice as much) than in other regions of the world, while average per capita incomes in Africa are substantially lower. Therefore, it could be argued that tariff policy is not an effective tool to reduce QFDs because further tariff hikes only lead to lower collection rates and increased distribution losses (e.g., theft). This argument has some truth to it and points to the need to address these operational inefficiencies as part of any credible subsidy reform strategy (this is discussed in detail in Chapter 2). In fact, long-run marginal costs estimated by the World Bank are about 12 percent less than historical costs and as much as 50 percent less in some cases (e.g., Malawi, Cameroon, Botswana, Tanzania) (Briceño-Garmendia and Shkaratan, 2011).

Nevertheless, cost-recovery tariffs can be achieved when combined with better services from power utilities. It is important to note that households and firms spend considerable amounts to deal with intermittent power supply and shortages (e.g., purchase and operation of petroleum-powered generators). The costs of own generation (by firms) is estimated in the range of US$0.3–US$0.7 a kWh—about three to four times as high as the price of electricity from the public grid (Foster and Steinbuks, 2008). These costs are even higher for households.

Who Benefits from Energy Subsidies?5

Fuel and electricity consumption in SSA countries is highly skewed toward higher income households. Available data show that patterns of fuel and energy consumption across households in various income quintiles vary significantly (Table 2). Household survey evidence from nine African countries (Arze del Granado, Coady, and Gillingham, 2012) suggests that poorer households consume directly a much smaller share of the total fuel and electricity supplied. In fact, households in the richest quintile spent on per capita terms close to 20 times more on fuel and electricity than households in the poorest quintile (kerosene is the only exception, with broadly evenly distributed consumption across households). Beside relatively higher incomes, better access to energy resources (particularly electricity in urban areas) contributes to the higher fuel consumption of richer households.

Table 2.Sub-Saharan African Countries: Per Capita Spending by Household Income Groups(PPP values in 2005 U.S. dollars, sample averages)


Spending on diesel fuel$ amount0.
ratio of Q5 to Q120.0
Spending on gasoline$ amount0.
ratio of Q5 to Q127.4
Spending on kerosene$ amount1.
ratio of Q5 to Q11.8
Spending on electricity$ amount0.
ratio of Q5 to Q117.0
Countries in the sample are (survey year in brackets): Cameroon (2007), Cöte d’Ivoire (2008), Ethiopia (2004),, Ghana (2005), Mozambique (2009), Rwanda (2005), Senegal (2005), Uganda (2010), and Zambia (2010).Source: World Bank (2012) Africa Pulse Database.
Countries in the sample are (survey year in brackets): Cameroon (2007), Cöte d’Ivoire (2008), Ethiopia (2004),, Ghana (2005), Mozambique (2009), Rwanda (2005), Senegal (2005), Uganda (2010), and Zambia (2010).Source: World Bank (2012) Africa Pulse Database.

Furthermore, differences in effective tariffs across various electricity consumption levels are small. About two-thirds of sub-Saharan African countries use increasing block tariffs (IBTs) (Briceño-Garmendia and Shkaratan, 2011). However, the progressivity of tariffs is limited in most countries partly because of relatively large fixed monthly charges. This results in rather modest differences in effective tariffs at vastly different levels of electricity consumption by households (Figure 10).

Figure 10.Sub-Saharan Africa: Effective Residential Tariffs by Consumption Levels

(US cents per kWh)

In this context, it is not surprising to find that fuel and electricity subsidies tend to benefit the better off. Because the richer households have higher consumption levels of fuel and electricity than the lower-income households, they capture the majority of the funds allocated to universal subsidies—such subsidies are per unit of fuel or electricity consumption regardless of consumers’ income levels. In sub-Saharan Africa, on average, the households in the top consumption quintile capture about 45 percent of fuel subsidies, while the poorer segments of the population (the bottom 40 percent of households) receive about 20 percent of the subsidy benefit (Figure 11).

Figure 11.Sub-Saharan Africa: Distribution of Benefits from Fuel Subsidies

Source: Arze del Granado, Coady, and Gillingham (2010).

If protecting poor and vulnerable groups is a key policy objective, universal subsidy schemes do not do a good job. The evidence suggests that providing 1 dollar of relief to the poorest 40 percent of the population under the universal subsidy policy requires the government to spend 5 dollars, of which about half would accrue to the richest quintile.

However, a subsidy reform implying an increase in energy prices would still have a sizable impact on the poorest segments of the population. For example, an increase of $0.25 a liter in fuel prices in SSA countries would reduce, on average, the 40 percent poorest households’ real income by 5.7 percent (Table 3). Over half of this purchasing power loss would occur through the indirect effect—pass-through of higher fuel prices into food and transportation costs—reflecting the importance of fuel as an intermediate input in the production process.6 Such an impact might be even larger if distribution of electricity spending is adjusted for the disparity in the access to electricity. Electricity in SSA countries is skewed to richer households—among the poorest 40 percent of households, this access rate is below 10 percent, whereas it rises to close to 80 percent for the richest household quintile (Eberhard and Shkaratan, 2012). When corrected for this disparity in access, the cost of electricity to low-income households (having access to the grid) rises substantially. For example, an analysis for Burkina Faso undertaken by Arze del Granado, Coady, and Gillingham (2012) suggests that the poorest 40 percent of the population with electricity provision devote, on average, 4.4 percent of their budgets to electricity consumption (rather than the 0.4 percent implied by an analysis including all households regardless of access).7

Table 3.Africa: Total Welfare Impact of Fuel Price Increases per Consumption Quintile(Impact in percent of total household consumption)
Household Groups (per Capita Consumption Quintiles)
Direct impact2.
Indirect impact3.

Although the overall impact of a fuel price increase looks similar across income groups, there would be significant variation in the distribution of the direct impact across fuel products. In fact, the distributional impact of a price hike for kerosene is substantially different from a gasoline price increase. The direct impact of an increase in gasoline prices has a more pronounced effect on the richest households, while a similar increase in the price of kerosene has a much larger impact on real consumption of households in the bottom quintiles (Figure 12). In other words, the welfare loss from gasoline price hikes is progressive (the richer households get a larger percent decline in purchasing power), and the welfare loss from kerosene price increases is regressive (the price increase reduces the welfare of poorer households to a greater extent). This pattern is broadly similar across the world.

Figure 12.Distribution of Direct Impact of Increases in Gasoline and Kerosene Prices

Energy Subsidies and Economic Efficiency8

An important aspect of energy subsidies is their impact on economic efficiency, competitiveness and growth, the environment, and macroeconomic management. Although some countries have rationalized their use of energy subsidies as a way to enhance competitiveness and the development of certain economic activities, this section argues that energy subsidies in their various forms can have a detrimental impact on growth and efficiency by misallocating resources, reducing investment, creating significant negative externalities and unintended distortions, and complicating overall macroeconomic management.

Energy subsidies generate welfare deadweight losses. Figure 13 illustrates the deadweight loss from a fuel subsidy of size s, under the assumption that the supply of fuel is infinitely elastic, as is likely to be the case for a small economy. The subsidy lowers the market price of fuel and increases the quantity consumed. Note that the increase in consumer surplus (represented by areas A+B) falls short of the subsidy’s fiscal cost (A+B+C). The difference (area C) is the deadweight loss of the subsidy.

Figure 13.The Deadweight Loss from a Fuel Subsidy

As shown in Figure 13, the most significant example of misallocated resources owing to energy subsidies is overconsumption of energy owing to distorted price signals. The extent of overconsumption depends on the elasticity of demand, for which cross-country empirical estimates vary widely in the literature.9Figure 14 offers some evidence of overconsumption in SSA countries in which consumer fuel prices fall short of appropriate benchmark levels. The figure suggests that lower fuel taxes (and correspondingly higher fuel subsidies) are associated with higher per capita energy consumption by the road sector in SSA countries. An additional effect comes from changes in the nature of energy demand: Burke and Nishitateno (2011) and Beresteanu and Li (2011) find that lower gasoline prices induce consumers to switch to less fuel-efficient vehicles. The dynamic effects of overconsumption should also be considered: it leads to faster depletion of nonrenewable resources, necessitating higher prices in the future than would otherwise be the case.

Figure 14.Fuel Taxes vs. Per Capita Road Sector Energy Consumption, 2003–08

Sources: IMF Fiscal Affairs Department (FAD) and World Economic Indicators (WDI) databases.

Note: Fuel taxes (or subsidies) are obtained as the difference between domestic (tax-inclusive) fuel prices and benchmark prices (based on the international price at the nearest international hub plus standardized transportation and distribution costs).

Underpricing and subsidies have negative effects on energy supply through various channels. If the cost of the subsidy is borne by the energy companies, which are forced to consistently sell below cost (including normal returns on investment), this will affect the entire supply chain, both in the short and the long term. Low profitability leads to underinvestment and poor maintenance, and this in turn results in persistent shortages, reduced quality, and deteriorating infrastructure along the entire energy supply chain. Nigeria’s and Ghana’s dilapidated petroleum refining infrastructure are examples, as is the huge electricity supply shortage across SSA. While proponents of energy subsidies argue for the need to lower costs to boost competitiveness, inadequate or unreliable supply of electricity has forced customers across SSA to invest heavily in self-generation, raising the effective cost above the subsidized price. In many cases, it is the inadequate supply of electricity rather than its price that weighs most heavily on competitiveness. Indeed, in countries that have undertaken reforms, evidence from surveys shows that customers are willing to pay higher tariffs if better service can be guaranteed. In the AFR survey, 28 countries had frequent or significant electricity shortages (such as load shedding or blackouts), while only 4 had infrequent or insignificant electricity shortages.10Figure 15 shows that it takes longer to get an electricity connection (a form of rationing) in SSA countries in which electricity firms cannot recover their costs.

Figure 15.Cost Recovery by Electricity Firms vs. Ease of Getting Electricity

Sources: World Bank databases.

Even if the cost of subsidies is borne directly by the government, the problem of undersupply and inefficiency may not be resolved. First, direct government transfers to refineries and power companies (e.g., to compensate for underpricing) can lead to soft budget constraints and reduce the incentive for restructuring and efficiency improvements, including efforts to improve collection rates. Refineries, in particular, tend to be subsidized for a variety of reasons, including job protection and supply security. However, oil refining is a capital-intensive industry (i.e., the number of jobs at stake is small). Relying on poorly maintained refineries might actually reduce the security of energy supplies. Second, subsidizing refineries is also sometimes times justified as a way to reduce fuel prices, particularly in oil-exporting countries. However, the small market size in most SSA countries makes it difficult to achieve scale efficiencies.11 Third, in oil-exporting countries there might be a misconception about the true cost of producing refined products: crude oil (their main input) is mistakenly valued at its actual production cost, rather than at its opportunity cost (i.e., its export value). Using the former creates an incentive to run inefficient refineries cushioned by the wedge between opportunity and productions costs. Finally, subsidizing fuel to lower the cost of thermal power–generating plants may reduce the incentive to explore more economical options for producing power, including regional power pools.

Deficient power infrastructure and shortages dampen economic growth and weaken competitiveness. Escribano, Guasch, and Peña (2008) find that in most SSA countries infrastructure accounts for 30–60 percent of the adverse impact on firm productivity, well ahead of factors like red tape and corruption. Moreover, in half the countries analyzed in that study, power accounted for 40–80 percent of the infrastructure effect. Kojima, Matthews, and Sexsmith (2010) estimate that potential efficiency gains in electricity generation and distribution could create savings of more than 1 percentage point of GDP for at least 18 SSA countries. Calderón (2008) uses simulations based on panel data to show that if the quantity and quality of power infrastructure in all sub-Saharan African countries were improved to that of a better performer (such as Mauritius), long-term per capita growth rates would be 2 percentage points higher. The scarcity of power in sub-Saharan Africa also affects the delivery of social services and the quality of life: without electricity, clinics cannot safely deliver babies at night or refrigerate essential vaccines. Similarly, lack of illumination restricts the ability of children to study at night and fosters crime.

The argument in favor of energy subsidies as a way to foster competitiveness and encourage private investment in certain sectors (e.g., manufacturing) often fails to fully account for the full implications of these policies. Subsidies have to be financed somehow, by either higher taxes or lower spending (including on infrastructure or human capital). High taxes, poor infrastructure, and low stocks of human capital reduce a country’s attractiveness to private investors.

Energy subsidies might crowd out more productive government spending. Figure 16 shows a negative relationship between fuel subsidies and public spending on health and education. In Nigeria, fuel subsidies exceeded federal capital expenditure by 20 percent in 2011. Ad hoc government interventions in energy pricing can result in heightened uncertainty, which makes business planning more difficult and turns away investors.

Figure 16.Energy Subsidies vs. Public Spending on Education and Health

Sources: IMF Fiscal Affairs Department (FAD) database and staff calculation for energy subsidies.

Competitive advantages gained through fuel subsidies are likely to be temporary and unsustainable. Because these subsidies tend to be strongly correlated with world prices, some sectors or industries would benefit from the subsidy in the presence of high world prices. However, this advantage would disappear as soon as international prices fall. This is what happened to some (large-scale) resource-based industries (e.g., aluminum, steel) in oil-exporting countries during and after the 1970s oil booms (Gelb, 1988). In addition, even if oil prices were to remain high, those sectors or industries would be vulnerable to the reduction of the subsidies (e.g., because of fiscal constraints).

Subsidies may invite rent seeking and their removal might become politically difficult. Examples include the copper-mining industry in Zambia and the aluminum-smelting industries in Cameroon, Ghana, and South Africa, where the offer of low, subsidized energy prices was meant as a temporary policy to lock in large-scale energy projects. Given the growth in energy demand in these countries, these arrangements are no longer needed and are extremely costly but are politically difficult to terminate. Given the potential large benefits from rent seeking, there is also a risk that it encourages corruption that substantially inflates the fiscal costs of the subsidy, as demonstrated by recent revelations of widespread abuses in Nigeria’s fuel subsidy regime.

Energy subsidies often misallocate resources to unintended beneficiaries or with unintended consequences. In Burkina Faso, fuel subsidies appear to exist mainly to sustain the truck transport sector, which is cartelized and less efficient than rail. Large foreign-owned hotels in the Seychelles and international airlines in Equatorial Guinea seem to be the main beneficiaries of subsidized fuel. Given that kerosene (typically subsidized for equity reasons) is a perfect substitute for jet fuel, significant amounts of it get diverted for alternative uses. Kerosene might also be mixed with diesel, for which it is only an imperfect substitute, resulting in damage to diesel engines. Fuel subsidies may have significant unintended cross-border spillover effects. The existence of large gasoline subsidies in Nigeria has encouraged widespread smuggling to other countries in West Africa. For example, it is estimated that official gasoline sales accounted for only 10–15 percent of total sales in Benin in 2011. While the informal fuel trade between Nigeria and Benin generates a transfer to the consumers of Benin, the Beninese government lost revenue of about 2 percent of GDP. Energy subsidies might generate perverse labor shifts, given that urban populations tend to be their main beneficiaries. Reduced labor supply in agriculture could lead to higher food prices—this happened in several oil-exporting countries during the 1970s boom (Gelb, 1988). Spending on agricultural infrastructure would be much more productive than energy subsidies in these countries.

Energy subsidies produce negative externalities and have a significant environmental impact. Some of these externalities could be local: traffic congestion and accidents, road damage, air pollution, and urban sprawl. Their adverse effect on human health and productivity constrains long-term economic growth. These externalities could also be global—emissions of CO2 and other greenhouse gases contribute to global climate change. Figure 17 suggests that lower fuel taxes (and correspondingly higher fuel subsidies) are associated with higher CO2 emissions in SSA countries.12

Figure 17.Fuel Taxes vs. CO2 Emissions

Sources: IMF Fiscal Affairs Department (FAD) and World Bank World Development Indicators databases.

Note: Fuel taxes (or subsidies) are obtained as the difference between domestic (tax-inclusive) fuel prices and benchmark prices (based on the international price at the nearest international hub plus standardized transportation and distribution costs).

Energy subsidies complicate macroeconomic management (beyond their impact on fiscal revenue). Fuel subsidies are procyclical in oil-exporting countries (i.e., they tend to be positively correlated with oil prices). This procylicality is sometimes hidden, because the fuel subsidies tend to be implicit: they are not included in the budget but instead are offset against oil-export revenue (e.g., in Nigeria). Monetary policy gets more complicated as well. The introduction of energy subsidies drives the inflation rate down and hides the true stance of monetary policy. If the subsidies are unsustainable, their sudden removal could lead to sudden spikes in prices and negatively affect inflation expectations. Energy subsidies also affect the balance of payments and the exchange rate. The overconsumption of petroleum products induced by subsidies may put pressure on the balance of payments of oil-importing countries and limit the amount of oil available for export in oil-exporting countries.

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