WPS5963 Policy Research Working Paper 5963 Uganda’s Infrastructure A Continental Perspective Rupa Ranganathan Vivien Foster The World Bank Africa Region Sustainable Development Department February 2012 Policy Research Working Paper 5963 Abstract Uganda has made substantial progress on its remains a challenge, and further investment is needed to infrastructure agenda in recent years. The early and increase rural connectivity and improve road safety. successful ICT reform detonated a huge expansion Addressing Uganda’s infrastructure challenges will in mobile coverage and penetration resulting in a require sustained expenditure of around $1.4 billion per highly competitive market. Power sector restructuring year over the next decade, strongly skewed towards capital has paved the way for a rapid doubling of power expenditure. Uganda already spends approximately $1 generation capacity. Uganda is doing well on the water billion per year on infrastructure, equivalent to about and sanitation MDGs, and has made effective use of 11 percent of GDP. A further $0.3 billion a year is lost performance contracting to improve utility performance. to inefficiencies, the bulk of which are associated with However, a number of important challenges remain. underpricing and distribution losses in the power sector. Despite reforms, the power sector continues to Uganda’s annual infrastructure funding gap is about hemorrhage resources due to under-pricing and high $0.4 billion per year, most of which is associated with distribution losses, while electrification rates are still very irrigation as well as water and sanitation infrastructure. low. Providing adequate resources for road maintenance This paper is a product of the Sustainable Development Department, Africa Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at vfoster@worldbank.org. The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Produced by the Research Support Team     Uganda’s Infrastructure: A Continental Perspective Rupa Ranganathan and Vivien Foster JEL: H. Public Economics and L. Industrial Organization SB: Energy and Mining (EM), Transport (TRAN), Water (WAT) Key words: infrastructure, Africa   Acknowledgments This paper draws on contributions from sector specialists from the Africa Infrastructure Country Diagnostic Team; notably, Heinrich Bofinger on air transport, Alberto Nogales on roads, Carolina Dominguez on water, Michael Minges on information and communication technologies, Nataliya Pushak on public expenditure, and Alvaro Federico Barra on spatial analysis. The paper is based on information provided from colleagues in the Uganda country team; notably, Mukami Kariuki (Sector Leader), Jos Verbeek (Lead Economist), Anton Dobronogov (Senior Economist), Charles Kunaka (Senior Trade Specialist), Negede Lewi (Senior Highway Engineer), Somin Mukherji (Senior Financial Analyst), Victorio Ocaya (Senior Highway Engineer), Robert Scholetterer (Senior Financial Analyst) and Rachel Sebudde (Senior Economist).   2    Introduction The continental perspective The Africa Infrastructure Country Diagnostic (AICD) has gathered and analyzed extensive data on infrastructure in more than 40 Sub-Saharan countries, including Uganda. The results have been presented in reports covering different areas of infrastructure—information and communication technology (ICT), irrigation, power, transport, and water and sanitation—and different policy areas, including investment needs, fiscal costs, and sector performance. This report presents the key AICD findings for Uganda over the period 2001 to 2006, allowing the country’s infrastructure situation to be benchmarked against that of its African peers using data collected over the same period, and providing a baseline against which to assess Uganda’s subsequent progress in the infrastructure sectors. Uganda is a low-income state that has recently discovered oil; therefore, both low-income and resource-rich benchmarks will be used to evaluate its performance. Detailed comparisons will also be made with immediate regional neighbors in the East African Community (EAC) in some cases. Several methodological issues should be borne in mind. First, because of the cross-country nature of data collection, a time lag is inevitable. The period covered by the AICD runs from 2003 to 2009. Most technical data presented are for 2009 (or the most recent year available), while financial data are typically averaged over the available period to smooth out the effect of short-term fluctuations. Data on benchmark countries, however, typically relate to the somewhat earlier period 2001 to 2006. Second, to make comparisons across countries, it was necessary to standardize the indicators and analysis so that everything was done on a consistent basis. This means that some of the indicators presented here may be slightly different from those that are routinely reported and discussed at the country level. Country context Despite conflict, political unrest, and various geographical disadvantages, Uganda has sustained relatively high and robust growth rates over two decades. Annual gross domestic product (GDP) growth rates averaged 7 percent in the 1990s and accelerated to more than 8 percent over the first seven years of the 2000s. Growth was around 6.1 percent in 2010, and is predicted to grow to over 7 percent in the foreseeable future. But due to rapid population growth, real GDP growth per capita averaged only 3.4 percent in the 1990s and around 4 percent in the 2000s. Strong growth performance has contributed to a substantial decline in poverty levels. The proportion of people living in poverty fell from 57 percent in 1992–93 to 31 percent in 2005–06. However, 3    significant inequities persist between urban and rural areas. The national Gini coefficient1 rose from 0.35 percent in 1997 to 0.41 percent in 2006, in part because Uganda’s growth path has created greater opportunities in urban areas in the central and western parts of the country, while more remote rural areas, particularly wide swathes of the north and east, , have not grown as fast. Nrthern Uganda, which has now emerged from conflict, recorded high and persistent levels of income poverty at 60 percent of the population. While new opportunities are opening up in the post-conflict environment, agricultural production has yet to reach levels that would have a sustained impact on poverty. Uganda is on track to meet at least two of eight Millennium Development Goals (MDGs). The country is close to halving poverty and has made substantial progress toward achieving universal primary education and addressing gender inequality. Uganda may even achieve the targets for combating HIV/AIDS, malaria, and other communicable diseases, ensuring environmental sustainability, and developing global partnerships. MDGs on reducing child mortality and improving maternal health, however, are unlikely to be met. Despite progress, Uganda ranked 156 of 179 in the fiscal 2009 Human Development Index (HDI) of the United Nations Development Programme (UNDP). The low overall ranking reflects the low starting point for Uganda along many development related indicators. Uganda has one of the youngest and most rapidly growing populations in the world. The country’s population growth rate, at 3.3 percent in 2010, is well above the African average. Population growth has been consistently high aside from during the AIDS epidemic in the early 2000s. The total fertility rate is estimated at 6.7 children per woman according to the government’s data and 6.4 according to UN data. About half (48.7 percent) of Uganda’s population is below 15 years of age, well beyond Sub-Saharan Africa’s average of 43.2 percent and the world average of 26.8 percent. Both the high level of fertility and the youthfulness of the population have created a very high youth dependency ratio (World Bank 2011b). Improvements in services—health, education, and infrastructure—have been unable to keep pace with rapid population growth. Sustaining the positive trends in growth will require massive investments in all of these areas, but in infrastructure in particular. Improved transport services will be needed to connect economically depressed areas and producers to markets and improve mobility of labor. Industry also needs reliable electricity to boost productivity and competitiveness. Levels of urbanization in Uganda in 2002 were relatively low compared to other African countries at 12 percent, but are expected to more than double over the next 15 years to reach almost 35 percent. Rapid urbanization needs to be accompanied by better urban services such as adequate access to water and sanitation. The recent discovery of oil reserves promises significant fiscal and development gains to the country. Even under conservative price assumptions, oil production could increase annual government revenues by about 10 percent of GDP within 6–10 years (World Bank 2011a) Higher oil income presents greater economic opportunities as well as challenges. Increased oil income can be expected to have positive repercussions in the economy as a whole, but evidence across the world points to a mixed story. In particular most cases of increased oil wealth and dependence on natural resources have produced outcomes of increased income disparity, often resulting in political instability (Angola, Bolivia, and                                                              1 The Gini coefficient is a measure of the inequality of income distribution. It ranges between zero (describing a situation where everybody has the same income level) to one (describing a situation where all income is concentrated in the hands of one person). In practice, Gini coefficients typically fall in the range of 0.2 to 0.6. 4    Nigeria provide clear examples). Through a phenomenon known as Dutch Disease, oil booms can also have adverse consequences for the nonoil sectors of the economy, as an appreciating exchange rate caused by surging oil exports renders other products uncompetitive (Adam and Bevan 2003; Garber 2004; Same 2008). It will therefore be critical for Uganda to capitalize on oil revenues—particularly during boom periods—and use them to make investments in assets such as infrastructure that will help to promote economic diversification into more sustainable sectors. Why infrastructure matters Adequate infrastructure is key for economic growth and competitiveness in Uganda. The country’s current inadequate infrastructure is impeding faster growth. Empirical evidence between the 1900s and early 2000s shows that infrastructure improvements in Uganda contributed over 1.5 percentage points to Uganda’s per capita growth rate (figure 1a). The ICT sector made the strongest impact on growth followed by power as a distant second. Looking ahead, if Uganda could improve its infrastructure to the level of Africa’s best performing country—Mauritius—growth performance could be enhanced by as much as 3.8 percentage points per capita, with the most significant contributions coming from upgrades to the power and ICT infrastructure (figure 1b). Figure 1. Infrastructure’s contribution to economic growth: Benchmarking Uganda against other Sub- Saharan nations 1995-2005 a. Infrastructure’s contribution to annual per capita economic b. Potential contributions of infrastructure to annual per capita growth in East African countries, in percentage points, 2001– economic growth in East African countries, in percentage 05 points 2 6 Changes in per capita growth  Potential contributions of per capita growth 1.5 5 1 4 0.5 3 0 -0.5 2 -1 1 Kenya Cameroon Tanzania Sudan East Africa Cote d'Ivoire Uganda Congo, Rep 0 Cameroon Sudan East Africa Cote d'Ivoire Kenya Tanzania Uganda Congo, Rep of ICT Power Roads ICT Power Roads Source: Calderón 2009. Note: ICT = information and communication technology.  Evidence from enterprise surveys suggests that in 2006 infrastructure constraints were responsible for as much as 58 percent of the productivity handicap faced by Ugandan firms (figure 2a), with the 5    remainder traceable to poor governance, red tape, and financing constraints. Infrastructure constraints in Uganda at that time were among the highest in the region. Inadequate power was the constraint that weighed most heavily on the country’s firms (figure 2b). Customs clearance processes before export was the second largest constraint hindering firms’ productivity. The average output loss owing to electricity supply problems is about 10 percent; a number higher than in most countries in Sub-Saharan Africa (World Bank 2005). However, since then, some improvements have been made including the formation of a common Customs Union under the umbrella of the East African Common Market. Figure 2. Infrastructure deficits erode firms’ productivity 2002-2006 Mauritius Mauritius Kenya Tanzania Uganda Tanzania Malawi Ethiopia Kenya Uganda Ethiopia Malawi 0% 20% 40% 60% 80% 100% percent of productivity deficit attributable to sectors 0% 50% 100% Electricity Customs clearance Transportation ICT Water percent of productivity deficit attributable to sectors Infrastructure Others Source: Escribano, Guasch, and Pena 2010 The state of Uganda’s infrastructure This report begins by reviewing achievements and challenges in each of Uganda’s major infrastructure sectors, with the key findings summarized in table 1. Hereafter, attention turns to the problem of how to finance Uganda’s infrastructure needs. 6    Table 1. The achievements and challenges of Niger’s Uganda infrastructure sectors Achievements Challenges Transport Relatively low cost of moving goods across Improving infrastructure and transport services to borders. hinterland countries particularly South Sudan. Trucking sector is liberalized and more mature Addressing bottlenecks at regional ports. than other parts of Africa. Roads Adequate road density and high traffic volumes. Providing adequate funding for road maintenance. National network is in relatively good condition. Improving rural road quality and connectivity. Improving road safety conditions. Railways Kenya-Uganda railway is one of the more Boosting traffic and productivity. heavily used railways in East Africa. Air transport Liberalized air transport markets with growing Boosting air safety standards. traffic and good connectivity to East African hubs. Water resources Well endowed with water resources relative to Managing conflicts between alternative water uses. benchmarks. Protecting water resources, such as wetlands, from encroachment, degradation and pollution Irrigation Development of irrigation has been strategically Exploiting major potential for development of high-return, planned around areas of high cultivation. small-scale schemes on the eastern side of the country. Water supply and Achievement of MDG for sanitation and close to Expanding supply of utility water to keep pace with rapid sanitation achieving MDG for water based on expansion of urbanization. intermediate service levels. Increasing access to improved water and sanitation Efficiency of water utility improved significantly services for poor households due to use of performance contracts. Addressing stubbornly high system losses and further improving cost recovery. Power Major power sector reform. Accelerating electrification, particularly in rural areas. Recent doubling of power generation capacity. Addressing very high system losses and improving cost recovery of the utility. Information and Early and successful ICT sector reform. Optimizing industry tax burden. communication Huge expansion of mobile telephony penetration Reducing costs of broadband services. technology (ICT) and footprint with highly competitive market. Terrestrial connection to new submarine cables via Kenya. Source: Authors’ elaboration based on findings of this report. Note: MDG = Millennium Development Goals.  7    Figure 3. Uganda’s poverty is heavily concentrated in the north of the country and population toward the eastern, central, and southern part of the country. 2005 a. Population b. Poverty c. Natural resources d. Topography Source: AICD Interactive Infrastructure Atlas for Uganda, downloadable from http://www.infrastructureafrica.org/library/doc/661/uganda-interactive-infrastructure-atlas Poverty rates are more pronounced in the northeast. This disparity comes despite some degree of homogeneity in the country’s elevation and topography, and is reflected in uneven distribution of 8    infrastructure networks that hinder more uniform development of the country as a whole. The conflict that has been experienced in the northeast of the country to a significant extent explains these patterns. Economic activity is largely concentrated along the coast of Lake Victoria and in pockets that border Rwanda and the Democratic Republic of Congo. The area around Kampala has the highest concentration of economic activity in Uganda overall. The area that borders Lake Victoria and spreading into the south central part of Uganda has a density of around 100–500 inhabitants per square kilometer (km2), while the rest of country is relatively sparsely populated, with less than 50 inhabitants per 100 km2 (figures 3a and 3b). Oil discoveries have been made in western Uganda in the vicinity of Lake Albert bordering the Democratic Republic of Congo. The Lake Albert region is an environmentally sensitive area, rich in biodiversity. Pipeline infrastructure to transport the oil to regional markets has been under consideration. Uganda has sizable expanses of fertile land and is exploiting its agricultural potential (figure 3d). In a large share of the land in the eastern-central part of the country, agricultural cultivation is relatively intense with more than half of available arable land under cultivation. Uganda is increasingly perceived as a potential breadbasket for East Africa with agricultural exports comprising 50 percent of all export revenues (World Bank 2010a). But climate variability is resulting in low crop yields, while increased human activity has led to degraded soils . Rainfall has also become more variable in nature wit]h more frequent floods and droughts. The infrastructure networks in Uganda more or less reflect economic development and population distributions. With regards to transport infrastructure, Uganda is integrated with the rest of East Africa through the Northern and Central Corridors. Northern road links to South Sudan have been of poor quality, but are improving rapidly due to new investments. Road infrastructure provides 90 percent of passenger and freight traffic and comprises of over 10,000 km of national roads, 27,500 km of district roads, and 4,800 km of urban roads. There is a marked absence of paved roads in the far northeast and southwest. Uganda has an emerging national power grid, with regional interconnections planned. The power generation plants are mainly located around Lake Victoria, though a number of planned projects are underway both in the Lake Victoria area and beyond. The transmission grid covers a substantial portion of the country, but excludes the extreme northeast (figure 4b). As part of the East Africa Power Pool, Uganda is planning a number of cross-border interconnectors with neighboring Kenya, Rwanda, Sudan, and Tanzania. Uganda has well developed ICT infrastructure. The country’s global system for mobile communications (GSM) footprint is exceptionally expansive, covering virtually the entire national territory except for the extreme northeast. The national fiber-optic backbone is also quite extensive (Figure 4d). Uganda, and the country is connected to the EASSy submarine cable via Kenya. Uganda has a few areas where irrigation is being practiced. However, by and large, the country’s agriculture is rainfed due to relatively high levels of precipitation. 9    Figure 4. Infrastructure in Uganda across most sectors is fragmented and in areas of high population density, 2005 a. Large parts of Uganda are not connected via roads b. Absence of a national grid in Uganda 10    c. Strong GSM footprint in Uganda d. Uganda is moderately endowed with water resources Source: AICD Interactive Infrastructure Atlas for Uganda, downloadable from http://www.infrastructureafrica.org/library/doc/661/uganda-interactive-infrastructure-atlas Note: GSM = global system for mobile communications. 11    Transport Figure 5. National and regional transport network in Uganda, 2005 a. National and regional road network 12    b. Uganda’s road network traffic Source: AICD Interactive Infrastructure Atlas for Uganda, downloadable from http://www.infrastructureafrica.org/library/doc/661/uganda-interactive-infrastructure-atlas Multimodal transport Achievements There are two major trading arteries that enable Uganda to better integrate with East Africa and obtain access to the sea via Mombasa and Dar es Salaam. The Northern Corridor provides international connectivity with Burundi, the Democratic Republic of Congo, Rwanda, South Sudan, and Kenya and connects Uganda to the coastal gateway of Mombasa. The Central Corridor provides connectivity with Burundi, Rwanda, Tanzania, and ultimately the alternative coastal gateway of Dar es Salaam. Of the two corridors, the Northern Corridor is the most frequently used for Ugandan freight, with Mombasa being the preferred gateway to the sea. 13    Over the last few years, the Uganda has made the Northern Corridor a strategic priority, making a concerted effort in the upkeep of certain segments of 650 km of the corridor within Uganda. Several sections of the road that were damaged are being rebuilt. Uganda has also received funds from the European Commission to upgrade the Northern Corridor. A feasibility study has been completed for the rehabilitation of the 150 km segment running from Mbarara to the Katuna border with Rwanda. The project will link 46 towns, trading centers, and villages (Nathan 2010). The trucking industry in Uganda and East Africa is relatively competitive and mature compared to that in West and central Africa. Freight transportation rates are determined by market forces rather than government regulations. The largest 20 professionalized trucking companies operate over 100 trucks each and serve 20 percent of East Africa’s road freight market , with the remainder being serviced by smaller firms. This size distribution is comparable to Europe and North America, which ensures a significant degree of competition since market share is not too heavily conocentrated with any one player. The largest Kenyan company owns a fleet of 600 trucks. These large companies obtain loads from long-term direct contracting and reach a much higher mileage than companies in other parts of Africa. Their yearly mileage on routes to Kampala can reach more than 100,000 km, which is much higher than the average mileage of trucks operating along the main transport corridors in Central Africa notably Douala to N’Djamena and Bangui(at most 60,000 km per year). Transport service quality in East Africa, including Uganda, is higher than in central or West Africa, with larger and more modern fleets. On average, transport prices are lower, especially services to Uganda (Teravaninthorn and Raballand 2009). Challenges Sections of the international corridor in Uganda are unevenly developed. Uganda plays an important role as a transit hub in East Africa, connecting landlocked countries such as Burundi, Rwanda, and South Sudan with coastal gateways in Kenya and Tanzania. Traffic volumes are substantial along all of these transit routes, particularly on the Northern Corridor into Kenya. But the condition of road infrastructure varies significantly across corridors. On the Northern Corridor, around 90 percent of the section linking the border town of Malaba to Kampala is in good condition. The onward connection to the border with South Sudan is of extremely poor quality, but major efforts are now underway to upgrade this corridor. On the Central Corridor, linking through to Kigali, only around 40 percent of the Ugandan section is in good or fair condition (see figure 6 and table 2). Uganda has made connectivity with Kenya an important strategic priority because it provides the main trading route for Ugandan goods, but apparently places less emphasis on connectivity with other hinterland countries in East Africa. 14    Figure 6. Roads connecting Uganda with Kenya along the Northern Corridor are of better quality than roads going south toward Rwanda and onward to the Central Corridor, 2005 a. Road quality along East African corridors b. Traffic along East African corridors Source: AICD Interactive Infrastructure Atlas for Uganda, downloadable from 15    http://www.infrastructureafrica.org/library/doc/661/uganda-interactive-infrastructure-atlas Table 2. Road conditions and traffic along portions of the Northern Corridor, 2005     Condition Type Traffic bands (vehicles per day) Corridors Good Fair Poor Unknown Paved Unpaved Unknown >300 300–1,000 >1,000 Unknown Mombasa to Nairobi to Kampala to Kigali to Bujumbura (Northern Corridor) 43.8 34.7 9.9 11.6 94.6 0 5.4 1.2 10.3 80.2 8.3 Rwanda 66.5 33.5 0 0 100 0 0 14.5 0 85.5 0 Uganda 6.9 34.6 10.1 48 77.5 0 22.5 0 21.8 78.2 0 Kenya 54.3 34.3 11.4 0 100 0 0 0 3.9 83.3 12.7 Burundi 45.2 4.2 0 0 100 0 0 0 70.3 25.6 4.2 Source: AICD analysis. The cost of moving freight in Uganda varies between typical East African rates of $0.09 on the routes to the coast, and much higher rates of $0.20 on inland routes toward South Sudan. Three reasons underlie the expensive freight tariffs for northbound traffic. First, road quality is extremely poor, which escalates the costs of moving freight. Second, the region is just emerging from conflict, and moving freight in risky environments is typically expensive. Third, trucking companies operating this route are unable to pick-up return freight, returning empty from South Sudan to Uganda, thereby significantly increasing the cost of transport services. Fourth, there seem to be monopolistic market conditions, due to the operation of cartels and interference by local chiefs. This leads to distortion of market prices, which in turn further discourages entry by new operators. The speed of Uganda’s road freight is close Table 3. Benchmarking Uganda’s regional network with African aggregates for to the African average, but worse on northbound regional corridors, 2005 routes. Along most of Uganda’s internal Road in good Implicit velocity ( km per Freight tariff (US cents per transport routes, surface transport moves at a condition (%) hour) tonne-km) pace of just under 20 km per hour (kmph), which is relatively good by African standards. But on the northbound routes into South Sudan the Western 72 6 8 effective velocity drops to 8 kmph when delays Central 49 6.1 13 are fully factored in (table 3). The slow effective Eastern 82 8.1 7 velocity of freight in Uganda can be explained Southern 100 11.6 5 by lengthy customs clearance processes and administrative and border crossing delays. Based Uganda 41 8.1–20 9–13 on estimates from 2008, East African trucking Source: Teravaninthorn and Raballand (2009) and World Bank staff estimates. companies have indicated that their trucks have to wait between 1 and 2 days at Malaba, which is the busiest and most-congested border crossing between Kenya and Uganda. Evidence from 2010 suggests that this delay was reduced significantly, but still 16    amounts to around 11 hours of wait time and another 4 hours to undertake all the customs clearance processes. Crossing the border from Uganda into Rwanda takes a similar amount of time, while crossing the Ugandan–South Sudanese border takes considerably longer, with delays ranging from 18 hours to 1 week (Nathan 2010; Yoshino 2011). Uganda further suffers from congestion and lengthy delays at its two sea gateways of Mombasa and Dar es Salaam. Long dwell times and port congestion problems at Mombasa, and more so in Dar es Salaam, adversely impact Uganda, which is landlocked and reliant on regional ports as gateways to the sea. Between the two options for Uganda, Figure 7: Moving freight within Sudan takes longer than moving longer than Figure 7. Moving freight from Mombasa to Kampala takes imports from Mombasa is the preferred port due to shorter Durban to Lusaka-from Durbancountries over a shorter distance, 2005 moving imports across three to Lusaka, distances and shorter dwell times. 1000 Time required to move Considering both port and road 800 freight (hours) related costs and delays, it is 600 possible to estimate the overall cost 400 and delay associated with Uganda’s 200 two coastal gateways: Mombasa and 0 Dar Es Salaam. These can be benchmarked against the North– South Corridor, which is southern Port Road transport Border Administrative Africa’s preeminent trading route. Source: AICD calculations based on Nathan (2010); World Bank (2008); and AICD ports The route from Lusaka to Durban performs database. significantly better than either of Uganda’s sea corridors even though it is 1,000 km Figure 8. Moving freight from Mombasa to Kampala takes longer than moving imports from Durban to Lusaka, over a shorter distance, 2005 longer and involves two border crossings instead of the single one on each of 500 Uganda’s two routes to the sea. The Costs per tonne to import total cost of moving freight from 400 freight (US $) Kampala to Mombasa along 300 Uganda’s Northern Corridor costs 200 twice as much per kilometer when 100 compared to the cost of importing 0 freight from Lusaka to Durban along Mombasa-Kampala Durban-Lusaka Dar es Salaam- Kampala the North–South Corridor, and the differential with respect to the Port Road transport Border Administrative Kampala to Dar es Salaam along Uganda’s Source: AICD calculations based on Nathan 2010, World Bank 2008, and AICD ports Central Corridor is even greater. The high database. costs can be attributed primarily to the high costs associated with the port as well as the relatively more expensive transport costs of moving along the Northern Corridor. Even with regards to costs, importing freight to Uganda via Dar es Salaam along the Central Corridor is far less competitive than the Nort-South Corridor (figure 8). Moreover, the journey from Kampala to Mombasa along the Northern Corridor takes 30 percent more time than the far longer journey from Lusaka to Durban, while the journey from Kampala to Dar Es Salaam along the Central 17    Corridor takes twice as long as the Lusaka to Durban route. Port delays at Mombasa are 8 days longer than at the Port of Durban, while customs clearance processes in Uganda add an additional day to the total travel time. Rail service on the Uganda to Kenya route, which runs parallel to the Northern Corridor road, offers lower costs but delays can be significant. The Rift Valley Railway Company connects landlocked Uganda to the port of Mombasa providing an alternative to road freight along the Northern Corridor. A comparison of this parallel road and rail corridors suggests that freight tariffs on the northern corridor are between $0.07 and $0.09 per tonne-kilometer, slightly more than the Kenya-Uganda railway tariff ($0.05 cents per tonne-kilometer). Nevertheless, the railway often encounters additional delays due to disrepair or other service disruptions.. Roads Achievements Road density in Uganda is rather high, with relatively high volumes of traffic. The classified road density at 365 km per 1000 km2 is four times the density of an average low-income African country. The paved roads carry twice as much traffic as those of low-income African peers, and indeed as much as Africa’s middle-income countries (MICs) (table 4). Table 4. Benchmarking Uganda’s roads, 2005 Indicator Unit Low-income, Uganda Middle- nonfragile income countries countries Classified road network density km/1,000 km2 of land area 88 360 278 Total road network density [1] km/1,000 km2 of land area 132 385 318 GIS Rural accessibility % of rural pop within 2 km from all-season road 25 26 31 Main road network condition [2] % in good or fair condition 72 87 86 Rural road network condition [3] % in good or fair condition 53 39 65 Classified paved road traffic AADT 1,131 2,460 2,451 Classified unpaved road traffic AADT 57 54 107 Primary network overengineering % of primary network paved with 300 AADT or less 30 12 18 Primary network underengineering % of primary network unpaved with 300 AADT or more 13 26 20 Perceived transport quality [4] % firms identifying transport as major business 28 22 18 constraint Source: AICD Road Sector Database on 40 Sub-Saharan African countries. Note: [1] Total network includes the classified and estimates of unclassified and urban networks. [2] Main network for most countries is defined as result of adding the primary and secondary networks. Uganda is only primary. [3] Rural network is generally defined as the tertiary network and does not include the unclassified roads. [4] Source: World Bank—IFC Enterprise Surveys on 32 Sub-Saharan African countries. 18    Uganda’s roads are on average in better condition compared to several East African countries (figure 9). Around 87 percent of Ugandan roads are in good or fair condition compared to only 72 percent of the roads in its low-income peers (see table 4 and figure 9). And when compared to its East African peers, Uganda boasts some of the best quality roads—although Uganda’s share of roads in good condition is relatively low, its share of roads in fair condition is exceptionally high. Figure 9. Main road network conditions in East Sub-Saharan Africa, 2005 Uganda Tanzania Ethiopia Kenya Sudan Eritrea 0% 20% 40% 60% 80% 100% Percentage Main Road Network Length Good Fair Poor Source: AICD Road Sector Database on Southern Sub-Saharan African countries. A number of recent efforts have aimed at strengthening road sector institutions. The Ministry of Works and Transport, which is responsible for policy formulation, leads and periodically formulates and updates the government’s National Transport Policy and Strategy (NTPS), which includes a Road Sector Development Program (RSDP). Following a long-term transitional arrangement that created the Road Agency in Formation Unit (RAFU), which is mostly externally funded, the government established the Uganda National Roads Authority (UNRA), which become operational in 2008. The UNRA is responsible for executing the road development and maintenance plans of national roads as well as projects financed by donors and development agencies. The Uganda Road Fund (URF) was legally established in 2008 as a Second Generation Road Fund and become operational only in 2010. The URF has private participation in its board and has been given the mandate to provide funding for maintenance on all roads. The legislation makes provision for road user charges including fuel levy, license fees, and others. However, the only source of funds applied to date have been appropriations by parliament from Ministry of Finance consolidated funds. This contravenes the principle of the URF and does not satisfy the intention of the Act. The finances applied to maintenance of the roads are not clearly related to road usage but are decided arbitrarily within the normal budget process. Challenges Over half the district (that is, rural or 0.40 US dollars per litre feeder) roads are in poor condition. 0.30 District roads connect rural areas to 0.20 markets, health centers, educational 0.10 19  0.00   Uganda Rwanda Kenya Tanzania Ethiopia Figure 10. Uganda significantly underspends on road maintenance, 2005 Source: AICD calculations. Implicit Levy Optimal Levy institutions, administrative centers, and other services and are the responsibility of the district governments. In 2008, 54 percent of the district roads were in poor condition (World Bank 2009b). Despite the higher than average road density in Uganda, the share of the population living within 2 km of an all-season road is no better than for other low-income African countries. Further while over half the rural roads in other low-income African countries are in good or fair condition, barely 40 percent of the rural roads in Uganda are in good or fair condition, highlighting the low accessibility of the rural areas. The road network in Uganda is highly fragmented. The main road networks originate from urban centers and connect surrounding areas. But connectivity between urban centers is limited—roads are either nonexistent or in poor condition. And a large portion of Uganda’s north and western central region, which are less dense in terms of population and have high incidence of poverty, are limited road connectivity (see figure 5a). Uganda is not devoting adequate resources to routine and periodic maintenance of the main infrastructure networks. Many countries in Africa have introduced road user charges—in the form of fuel levies—as a mechanism for funding road maintenance. Fuel levies in East Africa range widely from $0.03 to $0.20 per liter. Only in Kenya, however, is the fuel levy high enough to make a significant contribution to road maintenance funding. In Uganda, the optimal fuel levy is estimated to be around $0.18 per liter of fuel, while current spending levels on road maintenance are as low as just a few cents per liter of fuel. In fact, Uganda is one of the countries in Africa that has the largest divergence between actual and required spending on road maintenance (figure 10). Lack of safety on Ugandan roads is reaching alarming proportions. With rapidly growing motorization but only slightly improved road conditions, road accident fatalities in Uganda have increased dramatically over the last few years. The number of accidents has been growing at a rate of 6–7 percent per year, translating into a fatality rate of 81 per 100,000, double what is observed in Africa on average (World Bank 2009). Railways Achievements Uganda boasts one of the few binational railway systems in Africa connecting with Kenya. [[Please choose: “Uganda boasts one of the few bi-national railway systems in Africa, connecting the country with Kenya.â€? or “Uganda boasts one of the few bi-national railways systems that connects with Kenya.â€?]] The railway has been developed as an integrated operation between the two countries based on a partnership between the Ugandan Railway Company (URC) and Kenya Railway (KRC). This configuration smoothes the passage of goods across national borders and avoids the lengthy delays otherwise associated with switching of locomotives as freight is shifted from one national network to another. The URC network consists of four lines totaling 1,350 km of meter-gauge line, of which 259 km are currently being used under the binational concession with Kenya. The most heavily used URC link is the connection from Kampala to Malaba and the link between Kampala and the lake (Port Bell). Challenges 20    Figure 11. Uganda’s railways, like those of the rest of East Africa, are lightly used, 2005 Uganda’s railways recorded relatively high traffic by East 5 Million Traffic Units per route km African standards, though low in absolute terms. (figure 4 11). Uganda’s railway has been recording 0.8 million traffic units annually, above the East African regional average of 3 0.6 million, and well ahead of rail networks in Sudan and 2 Tanzania. Nevertheless, traffic flows on East African 1 railways are low relative to other regions of Africa, which are themselves lightly used by global standards.. 0 Sudan, SR Tanzania, TRC Kenya, KRC East Africa Central Africa West Africa Southern Africa North Africa Tanzania, TAZARA Uganda, URC Poor operational performance has made Uganda’s railways uncompetitive relative to roads. Uganda’s railways have recorded low labor productivity, locomotive productivity, and wagon productivity (table 5). The recent concession of the railways of both Kenya and Uganda did Source: AICD railways database 2009. not lead to immediate improvements in the performance of the system, with efficiency impeded by obsolete equipment, lack of adequate maintenance, and lack of spare parts. Competition from the road sector has further reduced the usage of Uganda’s railways. The lack of a strong marketing effort in the face of competition from the road sector has contributed to declining rail freight volumes. This was compounded by the liberalization of coffee transportation in 1990, removing the government mandate that the industry use rail transportation (World Bank 2005). Table 5. Performance of Ugandan railways, 2005 Labor Carriage Locomotive Wagon Passenger Freight yield productivity productivity productivity productivity yield Djibouti, CDE 12.5 3.1 Ethiopia/Djibouti, CDE 71 3,037 11 156 Kenya, KRC (RVRC) 203 1,159 24 218 3.8 0.6 Sudan, Sudan 77 329 9 225 Tanzania, TRC 259 3,264 25 583 4 1.6 Tanzania, TAZARA 352 2,770 13 551 3 1.1 Uganda, URC (RVRC) 156 9 144 Rail concessions 350 2,945 23 491 5 2 Source: AICD railways database. Note: Labor productivity = ‘000s traffic units per employee; locomotive productivity = millions of traffic units per locomotive; carriage productivity = ‘000s passenger-km per carriage; wagon productivity = ‘000s net tonne-km per wagon. Air transport Achievements Uganda’s efforts to liberalize the air transport market have increased international air traffic and boosted sector performance. In 2001, Uganda shut down its national flag carrier and opened up the market for liberalized traffic. After the initial drop in capacity, in 2007 a new carrier—Air Uganda—was 21    formed with financing from the Aga Khan Foundation. Traffic has grown significantly from a low of just under 1 million seats per year in 2004 to around 2.5 million seats estimated for 2009 (figure 12a). Connectivity has also recovered from around 10 city pairs in 2004 to some 20 city pairs estimated for 2009 (figure 12b). Uganda’s policy decisions have led to a healthy increase in international traffic volume, and present a case study on the positive impact of liberalization. Not only are outside carriers willing to service the country, outside investors are also willing to establish a regional carrier registered in Uganda. Since Uganda, like its neighbors Rwanda and Burundi, is a relatively small country, domestic service is minimal. Uganda’s airport infrastructure is also in reasonably good shape. As part of the Commonwealth meetings of heads of states in Kampala in 2007, a modern radar system was purchased for air traffic control, updating a virtually uncontrolled airport to more modern surveillance. Table 6. Benchmarking air transport indicators for Uganda and selected other countries, 20072 South Country Uganda Tanzania Rwanda Burundi Kenya Africa Traffic Domestic seats (seats per year) 70,980 1,871,255 n.a. n.a. 2,093,416 31,767,537 Seats for international travel within Africa (seats per year) 978,337 1,237,153 467,203 263,363 3,144,782 6,314,557 Seats for intercontinental travel (seats per year) 493,740 585,763 18,304 6,864 2,755,352 7,707,063 Seats available per capita 0.050 0.093 0.050 0.032 0.210 0.954 Herfindahl-Hirschmann Index—air transport market (%) 17.19 9.75 32.63 28.42 39.47 16.66 Quality Percent of seat-km in newer aircraft 73.2. 79.3 95.8 87.3 80.2 83.8 Percent of seat-km in medium or smaller aircraft 27.9 48.6 72.0 64.5 20.8 32.8 Percent of carriers passing IATA/IOSA Audit 0 33 0 0 11.1 33.3 FAA/IASA Audit Status No audit No audit No audit 0 Failed Passed Source: Bofinger 2009Derived from AICD national database (www.infrastructureafrica.org/aicd/tools/data). n.a. = Not applicable. Note: The Herfindhal-Hirschmann Index (HHI) is a commonly accepted measure of market concentration. It is calculated by squaring the market share of each firm competing in the market and then summing the resulting numbers. A HHI of 100 indicates the market is a monopoly; the lower the HHI, the more diluted the market power exerted by one company/agent. FAA = U.S. Federal Aviation Administration; IASA = International Aviation Safety Assessment; IATA = International Air Transport Association; IOSA = IATA International Safety Audit.  Uganda has benefited significantly from the increased air transport activity in East Africa, which is served by some of the leading air carriers in the continent. Uganda has benefited from its proximity to Kenya and Ethiopia and the strong regional airlines and regional hubs that have emerged in those                                                              2 All data as of 2007 based on estimations and computations of scheduled advertised seats, as published by the Diio SRS Analyzer. This captures 98 percent of worldwide traffic, but a higher percentage of African traffic is not captured by these data [[clarify this last clause]]. 22    countries. An origin-destination matrix of all flights in a week in East Africa shows that Uganda, after Tanzania, has the highest number of flights per week from Kenya and Ethiopia (figure 13). Uganda also benefits from frequent services provided by other international carriers such as Emirates. Figure 12. Evolution of seats and city pairs in Uganda (2001-2009) a. Seats b. City pairs 3,000,000 30 2,500,000 25 Number of seats 2,000,000 20 City Pairs 1,500,000 15 1,000,000 10 500,000 5 - 0 2001 2004 2007 2009 (Est) 2001 2004 2007 2009 (Est) Total Total International International Intercontinental excluding flights between NA and SSA Intercontinental Domestic Domestic Source: Bofinger 2009.Derived from AICD national database (www.infrastructureafrica.org/aicd/tools/data). Note: As reported to international reservation systems. NA = North Africa; SSA = Sub-Saharan Africa. Figure 13. All flights in one week in East Africa, 2007 Destination Tanzania Ethiopia Rwanda Uganda Burundi Kenya Sudan Burundi 7 8 20 7 Ethiopia 7 11 7 15 21 14 Kenya 7 11 15 34 87 39 Origin Rwanda 20 7 14 1 11 Sudan 12 17 4 Tanzania 7 48 6 Uganda 7 14 39 11 12 16 Source: Bofinger 2009. 23    Challenges Connectivity with Rwanda and to some extent Burundi, however, remains limited. Not only does Uganda have fewer flights to Rwanda and Burundi than to any other destination in East Africa, but the convenience and speed of air travel on these flights is significantly worse than on other routes due in part to long layovers on multi-stop flights (figure 14). Figure 14. Slow speed of service from Uganda to Rwanda and Burundi (kilometers per hour), 2007 Destination Tanzania Rwanda Ethiopia Uganda Burundi Sudan Kenya Burundi 460 410 296 512 Ethiopia 460 582 620 497 557 610 Kenya 350 582 363 298 275 436 Origin Rwanda 16 620 305 590 73 Sudan 572 330 513 Tanzania 662 193 661 Uganda 256 610 440 176 332 307 Source: Bofinger 2009. Resource constraints in Uganda pose a threat to air safety. Challenges are not due to the lack of professionalism in the Ugandan Civil Aviation Authority, which is dedicated to oversight, correct policy, and a high standard of service, but rather due to the size of the country and the limited resources available. This has led to a number of safety deficiencies that have been highlighted in the 2009 International Civil Aviation Organization (ICAO) audit. Some of the issues found, such as poor search and rescue capabilities, as well as weak accident investigations and resources for flight checks and ramp inspections, are regional in nature, and will be addressed in due course with the recent formation of the East African Civil Aviation Authority, an entity set up in the EAC with support from, among others, the U.S. Safe Skies Over Africa Program. 24    Water resources Figure 15. Water resources in Uganda, 2005 Source: AICD Interactive Infrastructure Atlas for Uganda, downloadable from http://www.infrastructureafrica.org/library/doc/661/uganda-interactive-infrastructure-atlas A significant share of Uganda’s territory is covered by fresh water lakes. Around 42,500 km2 (or 18 percent of the area) is covered by water in Uganda, due to the presence of major lakes such as Lake Victoria and Lake Albert. The country has 66 km3 of renewable water resources per year, equivalent to about 2,800 cubic meters (m3) per capita. The Nile basin is the most important river basin in the country. Rainfall ranges between 900 millimeters (mm) to 2,000 mm per year, depending on the region and the season of the year. Challenges Economic growth, population explosion, and growing urbanization are putting serious pressure on water resources. The annual population growth at 3.3 percent puts stress on water resources, both in the context of rapid urbanization and growing demand for food and associated irrigation needs. There is a need for clearly defined water rights to manage the competing needs of agriculture, water supply and industrialization. Irrigation Achievements Irrigation has been developed in areas of high agricultural yield. A very high percentage of Uganda’s land area is arable and being used for agriculture, albeit at a low level of intensity. In contrast to many other 25    African countries, there are only small pockets of high value agricultural land that have not yet been tapped (figure 16a). There are significant swathes of land where some degree of irrigation is practiced along the northern shores of Lake Victoria as well as in a northwesterly arc in more outlying areas. But even in these irrigated areas, less than 1 percent of the land is actually under irrigation. Figure 16. Uganda irrigation sector, 2005 a. Current Irrigation Area b. Potential (baseline scenario)     Source: Map on current area: AICD Interactive Infrastructure Atlas for Niger (www.infrastructureafrica.org). Map on irrigation potential: You 2008. Note: Baseline scenario was calculated assuming investment cost of $3,000 per hectare, a canal maintenance and water-delivery cost of 1¢ per cubic meter, on-farm annual operation and maintenance costs of $30 per hectare, and a discount rate of 12 percent. IRR = internal rate of return. 26    Table 7. Uganda's irrigation potential, 2005 Large-scale Small-scale Total Area Area Area Investment IRR increase Investment IRR increase Investment IRR increase Cutoff (%) $million % Ha $million % ha $million % ha 0 1035 2.4 530,522 3203 32.0 619,916 4239 18.4 1,150,438 6 36 6.9 18,498 2926 37.0 566,165 2962 36.0 584,663 12 0 0.0 0 2300 45.0 445,041 2300 45.0 445,041 24 0 0.0 0 687 72.0 133,009 687 72.0 133,009 Source: Derived from You and others (2009). Note: Water for irrigation can be collected in two ways: through large, dam-based schemes or through small projects based on the collection of run-off from rainfall. The investment costs of large-scale irrigation development reflect only irrigation-specific infrastructure, such as distribution canals and on-farm system development. The potential for small-scale irrigation is assessed not only on the basis of agroecological conditions, but also in terms of market access, since irrigation is typically viable only if the increased yields can be readily marketed. The unit cost for large scale projects is set at USD3000/ha and for small scale projects at USD2000/ha. Challenges Uganda can maximize its potential and achieve rates of return of at least 12 percent by developing small scale irrigation projects in a relatively small area, but at a high initial cost. Across most of Uganda’s territory, which covers over a million hectares in all, either large scale or small scale irrigation activity is economically viable (figure 16b; table 7). But if attention is limited to higher return irrigation schemes with internal rates of returns of at least 12 percent, the viable area shrinks to just under half a million hectares, but the average rate of return shoots up to 45 percent. This would be entirely composed of small- scale irrigation schemes on the eastern side of the country, as none of the large-scale irrigation schemes are capable of delivering returns above this threshold. However, the total investments needed to develop this area amount to a daunting $2.3 billion (table 7). Water supply and sanitation Achievements Developments in the water and sanitation sector have curtailed use of untreated surface water and reduced practices of open defecation. Use of untreated surface water halved between 1995 and 2006, falling from 28 percent to 13 percent. In fact, reliance on untreated surface water in Uganda is one-third of what is observed in low-income countries (LICs) in Africa. Similar progress was recorded in the sanitation sector. The practice of open defecation decreased from 20 percent to 12 percent between 1995 and 2006, and its rate of prevalence in Uganda is now only one-third of the average for other LICs and below the average of MICs (table 8). Most of the decrease in use of untreated surface water and reduction in open defecation was achieved between 1995 and 2001, although the rate of improvement has subsequently declined. 27    The reduced reliance on untreated surface water and reduced prevalence of open defecation is due primarily to an increased availability of intermediate water and sanitation options. In the case of water, there has been a rapid expansion in the use of stand posts and, in particular, wells and boreholes (even if only a fraction of these can be considered to supply safe drinking water). In the case of sanitation, there has been steady growth in access to both traditional and improved latrines. Indeed, as of 2006, the coverage of improved latrines at 69 percent is seven times greater than the average LIC in Africa (table 8). Due in part to relatively low rates of urbanization, there has been little if any increase in the coverage of higher end solutions, such as piped water and flush toilets; Uganda has achieved its noteworthy improvements in water and sanitation access by pragmatically focusing on intermediate lower cost solutions. Table 8. Benchmarking water and sanitation indicators in Uganda, 1995-2006 Low-income Middle-income Unit countries Uganda countries Mid-2000s 1995 2001 2006 Mid-2000s Access to piped water % pop 9.3 3.0 2.2 3.2 61.1 Access to stand posts % pop 17.1 4.6 7.6 9.8 22.1 Access to wells/boreholes % pop 39.3 64.2 75.5 73.5 4.8 Access to surface water % pop 34.2 28.0 14.9 13.4 10.9 Access to flush toilets % pop 4.7 1.4 1.5 1.1 47.7 Access to improved latrines % pop 18.3 64.9 67.0 69.0 33.7 Access to traditional latrines % pop 38.5 13.2 13.4 17.5 6.9 Open defecation % pop 38.3 20.3 17.8 12.0 11.0 Mid-2000s 1996 2001 2009 Mid-2000s Domestic water consumption liter/capita/day 51 41.0 39.1 41.3 196 Revenue collection % of total billings 94 47.9 51.9 99.0 99 Distribution losses % of production 35 64.5 47.5 35.8 29 Cost recovery % total costs 89 153 133 92 86 Operating cost recovery % operating costs 125 209 240 138 121 Connections per Labor productivity 176 45.1 91.4 148.9 203 employee Hidden costs % of total revenues 163 176 149 43 140 Scarce water Other developing Uganda resources regions U.S. cents per m3 2001 2006 Residential tariff 47 66 60 3–60 Nonresidential tariff 80 104 121 Source: Demographic and Health Survey and AICD water and sanitation utilities database (www.infrastructureafrica.org/aicd/tools/data). Access figures from Demographic and Health Surveys (1995, 2001, and 2006). 28    These improvements in access to improved water and sanitation services have propelled Uganda toward meeting the MDGs. Access to improved water increased from 48 percent to 66 percent in of the population between 1995 and 2006, while access to improved sanitation rose from 66 percent to 70 percent over the same period. As a result, Uganda has already met the MDG of 65 percent for improved sanitation, and is close to reaching goal of 72 percent for improved water. Box 1. Understanding the differences between the JMP and government data The AICD uses the Joint Monitoring Data (JMP) coverage statistics as the main source of access data on water supply and sanitation, and process under a standardize methodology to allow cross-country comparisons. These data might differ from that reported by governments. The JMP data are based on household surveys and therefore reported by users of the services, the government data is based on utility reports. This implies that there is a time lag between output data (provider) and outcome data (users). Moreover, household surveys capture clandestine use of water services, which are not conveyed in utility data. Other underlying factors explaining potential differences are the definition of what technologies constitute improved access to water supply and sanitation; and, the JMP’s use of several household surveys vis- à-vis the use of a single data point by several governments. Therefore, the conclusion on progress on MDGs might differ according to the data source used. Source: Adapted from AMCOW (2010). The performance of the urban water sector has been boosted by the remarkable improvements in the performance of the National Water and Sewerage Corporation (NWSC). The NWSC provides water supply and sewerage services in the 22 largest urban centers covering only 10 percent of the population in all. The improved performance is attributable to increases in revenue collection and a reduction in distribution losses. Revenue collection doubled from 48 percent of the bills in 1996 to 99 percent of the bills in 2009 (table 9). These rates exceed those of an average utility in LICs and are equivalent to the rates for utilities in MICs in Africa (table 8). Distributional losses also reduced significantly from 65 percent of production in 1996 to 36 percent in 2009. Despite the improvements, however, distribution losses at the NWSC as of 2009 were 16 percentage points higher than the benchmark for a well- performing water supply utility in Africa (table 9). The NWSC has also recorded impressive progress in labor productivity, with connections per employee more than tripling from 45 connections per employee in 1996 to 148 connections per employees in 2009; this still falls short of the benchmark of 200 connections per employee for a well-run utility in Africa, however. In 2005 a free connection policy was introduced to allow the poorest customers to access utility water. Since then the number of the NWSC’s connections has almost doubled, rising from 123,046 connections in 2005 to 225,932 in 2009. Nevertheless, cost recovery is still a substantial challenge for the NWSC. Costs have increased substantially in recent years, yet systematic adjustments of water tariffs have not been undertaken. Thus, although the NWSC’s revenues cover operating cost, they do not cover capital costs (table 8). Capital costs have been financed by the government through aid from donors. Hidden costs as a percentage of the NWSC’s revenues have registered an impressive decline during the decade ending 2009. In 2009 hidden costs were around 65 percent of the NWSC’s revenues compared to 243 percent in 1999. In 1999, under-pricing of water, large distributional losses, and revenue collection issues were responsible for the large hidden costs (figure 17b). Despite progress in the NWSC’s performance, under-pricing of water still needs to be tackled to reduce the inefficiencies of the NWSC. In monetary terms, hidden costs have remained more or less stagnant at around $30 million a year. The 29    NWSC records amongst the lowest hidden costs when compared to other East African countries (figure 17b). Table 9. Evolution of operational indicators associated with NWSC, Uganda, 1999- 2009 Water System Collection ratio Average total Average Total hidden Total hidden delivered losses cost effective tariff costs costs (million (%) (%) (US$/m3) (US$/m3) (US$ (% revenues ) m3/year) million/year) 1999 46 48 76 1.18 0.45 30 243 2000 46 43 80 0.93 0.45 22 141 2001 47 43 85 0.93 0.45 22 131 2002 47 40 92 0.94 0.45 21 113 2003 51 39 92 0.88 0.47 20 107 2004 55 38 98 0.95 0.50 23 85 2005 58 34 89 0.99 0.53 26 88 2006 58 30 90 1.01 0.58 25 76 2007 61 33 92 1.18 0.81 25 59 2008 64 34 92 1.44 0.91 36 66 2009 69 36 99 1.22 0.76 32 65 Source: Derived from Briceño-Garmendia, Smits, and Foster (2009). Figure 17. Impressive reduction of hidden costs in Uganda, 1999-2009 a. Evolution of hidden costs in the NWSC b. Hidden costs of selected water utilities 250 250 Percentage of the revenues Percentage of the revenues 200 200 150 150 100 100 50 50 0 0 Tanzania Ethiopia Kenya Sudan Uganda Uganda (2009) (2005) Collection inneficiencies Under-pricing Losses Collection Inefficiencies Underpricing Losses Source: Derived from Briceño-Garmendia, Smits, and Foster (2009). 30    The NWSC’s progress over the last 15 years can largely be attributed to the introduction of a system of internal performance contracts implemented in 2004. In 1998 the government reformed the utility’s management structure, and granted a concession to a private operator for the water distribution, billing, and collection in Kampala. The NWSC continued serving secondary cities and towns, where it established area performance contracts to remunerate local managers based on results. This model was successful at reducing nonrevenue water and increasing collection ratios in the areas under the NWSC management, but significant change was not achieved in Kampala. Following the end of the concession, the system of internal performance contracts was extended to Kampala operations in 2004, yielding better operational results. Since 2004 the combined effect of better performance indicators and increasing revenues (table 9) contributed significantly to the reduction in the hidden costs (figure 17a). A similar approach based on performance contracts has been successfully adopted for small towns not served by the NWSC. The implementation of these performance agreements between the line ministry and town water supply authorities, which encourage the engagement of private operators in the operation and management of the water supply, has allowed Uganda to attract private participation into the sector while improving the quality of services and customer satisfaction. In 2008 the government started signing output based aid contracts with these private operators to design, build, and operate water systems. Under this scheme 961 connections have been completed (out of 2000 planned), 450 yard taps verified benefiting 8,100 people, and in some towns the service is to be provided with no subsidy. As of 2010, 20 private operators were running 72 water systems in small towns. Challenges Uganda registered virtually no progress in access to safe forms of water supply between 2001 and 2006, compounded by challenges of growing population rates. Due in part to relatively low rates of urbanization, access to piped water has remained stagnant since 1995, and stands at barely one-third of the average for African LIC peers. Only 0.3 percent and 0.7 percent of the national population was gaining access per year to piped water and stand posts, respectively, between 2001 and 2006 (figure 18a). Expansion in water supply has not been able to keep pace with growth in population, which grew at 2.9 percent nationally and 3.5 percent in urban areas. The slow progress in access to piped water and stand posts, as well as the predominantly rural population, is also responsible for the relatively low level of per capita water consumption. The domestic water consumption per capita per day in Uganda did not change between 1996 and 2009, and at 41 liters is equivalent to the rate in African LICs and a third of the rate in African MICs. 31    Figure 18. Expansion in access to water and sanitation has not keep pace with population growth and increases reliance on untreated surface water and open defecation, 2001-2006 Population gaining access per year between 2001–06 a. Water b. Sanitation 6 6 5 5 Population  gaining access per year (%) Population  gaining access per year (%) 4 4 3.5 3.5 3 3 2.9 2.9 2.8 2.8 2 2 1 1 0 0 National Urban Rural National Urban Rural â€?1 â€?1 â€?2 â€?2 Piped Water Standposts Flush Toilets Wells/Boreholes Surface Water Improved Latrines Annualized Growth Traditional Latrines Source: WHO (2010) from the Demographic and Health Surveys 2001 and 2006. Power Achievements In the late 1990s, the Government of Uganda undertook a comprehensive power reform program that placed the power sector under private management operating on commercial principles. The sector has subsequently been unbundled, legal and regulatory reforms have been introduced, and the operation of the main generation and distribution assets has been turned over to the private sector under long-term concession agreements. There has been a doubling of generation infrastructure over the last few years. Following a serious drought and resulting power supply crisis in the mid-2000s, Uganda has made serious efforts both to expand its power generation assets and diversify its mix to become less reliant on hydropower. Generation capacity increased from 280 megawatts (MW) to 568 MW between 2005 and 2009. Despite this increase, generation capacity in 2009—at 18 MW per million of population—remained somewhat lower than the average for the African LIC peer group. But the Bujagali hydropower project will begin to come on stream during 2011 but will not be fully operational until 2012 (EIU 2011). With the additional 250 MW that will be available, capacity is expected to increase to 25 MW per million people, higher than in LIC peers. Although Uganda’s generation portfolio has moved from a predominantly hydro-based 32    system in 2005 to a more balanced hydro-thermal system in 2009 (EIA 2009), Bujagali will skew the generation portfolio once again toward hydropower. Challenges Access to power in Uganda is very limited. As of 2009, only 9 percent of the population had access to power, less than a third of the rate in other low-income African countries and a fraction of the rate in resource-rich countries. Uganda’s access rates are more or less equal to access rates in Malawi, amongst the lowest in Africa. Access to electricity in urban areas is also limited. Even in urban areas, only 50 percent of the population has access to power compared to 86 percent in other LICs. In rural areas, only 5 percent of the population has access to power compared to 12 percent in LICs, falling short of Uganda’s national rural access target of 10 percent (table 10). Table 10. Benchmarking Uganda’s power infrastructure, 2006 Low-income, Middle- Resource- Uganda nonfragile income rich countries countries countries Access—national 2009 % population 9 33 50 46 Access—urban 2009 % population 50 86 100 100 Access—rural 2009 % population 6 12 33 28 Access—capital city 2009 % population 60 81 81 89 Installed generation capacity MW 568 651 36,971 4,105 MW per million Installed generation capacity people 18 20 799 43 Emergency generation capacity MW 100 46 0 0 Self-generation capacity MW 37 17 30 13 Firms that find power a constraint for business % of firms 45 52 31 56 Firms with own generator % of firms 29 41 18 63 number per Outages, number, annually year 132 124 71 174 Outages, value lost % of sales 10 6.5 1.6 7 Collection rate, reported by utility, electricity % of billing 94 92 91 70 Cost-recovery ratio, historical % 67 89 85 97 US cents per Revenue per unit kWh 15 14 13 13 System losses % generation 39 24 20 52 Total hidden costs % revenue 103 69 0 168 Source: Access to power (national) is based on information in 2009 and taken from World Energy Outlook, 2010; Access to power in rural areas taken from EIU (2011). Note: All data for 2006 unless indicated otherwise. 33    Uganda’s economy has suffered terribly from unreliable power supply during drought periods, notably in the mid-2000s. Episodes of weak hydrology and associated power cuts have tended to hobble business activity and competitiveness and consequently hinder growth. An enterprise survey undertaken at the height of the drought in the mid-2000s found that around 45 percent of firms cited power as a major constraint to doing business reporting over 130 outages per year and 55 days spent without power (World Bank 2006). As a result, firms relied on generators to self-supply as much as 30 percent of their power needs, and nonetheless lost 10 percent of their sales due to Figure 19. Power outages are a drag on GDP inadequate power supply. As of 2006, firms had put in place 37 MW of self-generation capacity. Due to the high price of diesel (see below), the cost of self-generation of power, at $0.46–$1.44 per kilowatt-hour (kWh), is two to six times more expensive than grid-based electricity. As a result, private investment in physical capital may be constrained by the high costs of poor infrastructure (World Bank 2006). Over time, the lack of reliable power is a drag on economic growth. In 2007, 5 percent of Uganda’s GDP was shaved off due to erratic power supply, amongst the highest in the continent (figure 19). Although the situation has improved since the height of the 2005 drought, reliability issues remain a concern and the system is still vulnerable to drought periods. Ugandan power customers, including firms, see their competitiveness affected due to extremely expensive power generation costs. Historic total production power costs in Uganda are $0.24 per kWh (figure 20). These costs are amongst the highest in Africa; they Figure 20. Extremely high costs of power production in Uganda would be typical for 45 40 Power Production costs (US cents smaller thermal power 35 systems rather than 30 25 hydropower. Though 20 per KWh) Uganda has access to 15 10 hydropower, that 5 0 resource is subject to Rwanda Tanzania Botswana DRC Zambia Malawi Madagascar Cote d'Ivoire Uganda Benin Cape Verde Angola Kenya Namibia Lesotho Mozambique Ethiopia South Africa Cameroon Congo Chad Ghana Nigeria Niger Senegal Mali Burkina Faso periodic droughts and calls for thermal backup, which is very costly due to the very Source: Derived from Shkaratan and Briceño-Garmendia (2008); based on data from World Bank (2010a). high and escalating price of diesel Note: DRC = Democratic Republic of Congo. (table 11). This became a particular problem during the drought of the mid-2000s when 100 mega-watts of emergency diesel-based generation capacity was contracted to offset 34    power shortages, leading to a huge escalation in sector costs. The situation was later exacerbated by delays in the commissioning of Bujagali hydro-power project, and the volume of short-term leased capacity has risen to 170 mega-watts further inflating costs. Diesel prices in East Africa have been traditionally higher than many other countries in southern and West Africa; in the case of Uganda, the prices are higher still, reflecting both the high costs of importing oil and the not insignificant transportation costs ($0.08 per tonne-km) for transporting oil along East African corridors. Table 11. Diesel prices in Uganda are amongst the highest in Africa Diesel prices ($ per liter) Cost of power production ($ per kWh) 2004 2006 2008 Ethiopia 8.4 42 62 89 Ghana 12 43 84 90 Kenya 14 76 98 114 Nigeria 15 45 66 113 Rwanda 17 99 108 137 Tanzania 14 87 99 130 Uganda 24 88 101 122 Source: GTZ 2009. The average tariff at $0.16 fails to recover the high costs of power production. Uganda’s power tariffs had remained fairly steady at around or just below $0.10 per kWh in the early 2000s. Tariffs were increased in 2006 to generate more revenue for the cash starved power sector following the drought and increased reliance on emergency power generation, reaching $0.18 per kWh in the late 2000s. Despite these increases, domestic tariffs only covered about two-thirds of the costs of power production in 2010 (World Bank 2010a). Figure 21. Relatively high tariffs for power in Uganda, 2006 50 45 US cents per KWh 40 35 30 25 20 15 10 5 0 Madagascar Kenya Ghana Botswana Mozambique DRC Niger Tanzania Zimbabwe Botswana Senegal Malawi Zambia Burkina Faso Mali Chad Cape Verde Uganda Rwanda Benin Cote d'Ivoire Namibia Lesotho Ethiopia Liberia Nigeria South Africa Cameroon Congo, Rep. Source: Derived from Shkaratan and Briceño-Garmendia (2008) and World Bank (2010a). [[Should this be 2010b?]] Note: DRC = Democratic Republic of Congo. 35    The financial performance of the sector is further undermined by Uganda’s exceptionally high system losses. System losses in Uganda stood at 35-40 percent in the late 2000s. This is way above the LIC benchmark of 24 percent and about four times the best-practice benchmark of around 10 percent (table 10). High system losses have resisted even the introduction of private management within the sector. Decrepit metering systems and outmoded billing software are partly responsible for the problem, which has been exacerbated by burgeoning illegal connections following the tariff increases since 2006. The one area where financial performance has clearly improved has been in revenue collection. In 2005 collection of power bills was around 84 percent. This increased significantly to 94 percent in 2009, slightly higher than the average for LICs in Africa (table 10). The financial burden of hidden costs has increased over time, shaving off as much as $230 million in revenues in 2009 or around 1.5 percent of Uganda’s GDP. The absolute value of hidden costs continued to grow even in the aftermath of the drought, largely due to the surging demand that increased from around 1,000 gigawatt-hours (GWh) per year in 2006 to 1,500 in 2009. As of 2009, system losses drained $116 million from power sector revenues, while mispricing of power, though worse in prior years largely due to exchange rate fluctuations, resulted in losses of $103 million in 2009 (table 12). In an attempt to bolster sector finances, the government has provided direct budgetary subsidies to the sector, partly funded by donor contributions. These direct subsidies have continued to grow from $107 million in 2006 to $351 million in 2010 (World Bank, forthcoming). In share of revenue terms, the burden of the hidden costs has decreased over time but is still high. Hidden costs in 2000 stood at around 300 percent of sector revenues, reached a low point of around 50 percent of sector revenues in 2003 before the drought, escalated back to 130 percent of revenues at the height of the drought in 2006, and have since declined only slightly to around 100 percent. In 2009 the burden associated with underpricing and system losses was almost equally split at 51 and 46 percent of revenues respectively (figure 22a). Uganda’s hidden costs, though not the highest when compared to other East African countries, are still a major burden on the utility (figure 22b). In the longer term, Uganda has the potential to become an exporter into the East African Power Pool. While Uganda’s historic power production costs have been very high due to growing reliance on thermal power, these costs could be expected to fall in the long-term should Uganda complete the development of its hydro-power potential. Looking ahead, simulations suggest that Uganda’s long run marginal costs could drop toward $0.12 per kWh, about half the level of historic costs, as Uganda develops more of its hydropower resources (figure 23). While Uganda’s hydropower potential is not on a par with major potential producers such as Ethiopia or the Democratic Republic of Congo, it is nonetheless significant and could be competitive in the East African regional context. If regional power trade were to develop unfettered in East Africa, Uganda could emerge as a significant hydropower exporter with the possibility to develop some 550 MW of export oriented hydropower, requiring some 500 megawatts of inter-connectors in support (Rosnes and Vennemo, 2009). A one-time investment of $145 million would be needed to develop this infrastructure, yielding an estimated return of 16 percent. Under such a scenario, Uganda would end up exporting about 50 percent of its domestic power consumption. 36    Table 12. Large hidden costs at associated with the power sector in Uganda, 1998-2009 Implicit Power System Collection Cost recovery Average Average Total hidden Total hidden billings losses Ratio benchmark Revenue effective tariff costs costs (GWh/year) (%) (%) (US$/kWh) (US$/kWh) (US$/kWh) (US$ million/year) (% revenues) 1998 865 36 81 0.09 0.08 0.08 153 249 1999 876 42 81 0.08 0.08 0.07 167 287 2000 1094 36 81 0.07 0.07 0.06 207 308 2001 1019 41 81 0.08 0.08 0.10 174 227 2002 1139 41 81 0.08 0.08 0.09 199 212 2003 1252 35 81 0.08 0.08 0.09 48 52 2004 1226 41 81 0.08 0.07 0.10 56 61 2005 1139 43 86 0.13 0.08 0.09 120 122 2006 1043 38 85 0.20 0.12 0.12 162 134 2007 1204 40 93 0.23 0.17 0.18 159 74 2008 1345 39 90 0.26 0.18 0.16 277 115 2009 1483 40 94 0.24 0.15 0.17 234 103 Source: Briceño-Garmendia, Smits, and Foster 2009; World Bank 2008 and 2010a. Note: kWh = kilowatt-hour; GWh = gigawatt-hour. Figures 22a and 22b. Hidden costs in revenue terms decreased between 1998 and 2005 but are on the higher side relative to several neighbors 350 Malawi Hidden costs as a share of Hidden costs as a share of revenue (%) 300 Botswana 250 Tanzania revenue(%) 200 Uganda 150 Ethiopia 100 DRC Congo 50 Kenya 0 Rwanda 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 0 50 100 150 200 250 Unaccounted Losses Under-Pricing Collection Inefficiencies Losses Underpricing Collection Inefficiencies Source: Briceño-Garmendia, Smits, and Foster 2009; and World Bank 2008 and 2010a. [[Remove hyphen from under-pricing in figure.]] Note: DRC = Democratic Republic of Congo. 37      Figure 23. Long-run prospects look promising for Uganda 30 US cents per kWh 25 20 15 10 5 0 Total costs, Revenue Effective tariff LRMC trade LRMC trade historical expansion stagnation Source: Rosnes and Vennamo 2009; World Bank 2008 and 2010. Note: LRMC = long-run margin costs. Information and communication technologies Achievements Uganda has made notable progress in telecommunications, particularly through mobile networks, outperforming LICs in this area (table 13). Mobile penetration has risen from less than one percent in 2000 to 28 percent by 2009, consistent with what is observed in low-income African countries. This level of access is higher than the penetration rate due to shared usage in households and public mobile phone facilities. Furthermore, there are no infrastructural barriers to mobile access, with the Uganda Communications Commission (UCC) reporting that mobile cellular signals covered 100 percent of the population by December 2008b (UCC 2009). This is a major achievement compared to the LIC benchmark of only 56 percent. Meanwhile, in 2006 (the latest year available), the Uganda Bureau of Statistics (UBOS) reported that almost half of inhabitants already had access to telephone facilities (UBOS 2006), and the number of public pay telephones has increased more than 30 times since 2000 to almost 100,000 by 2009. 38    Table 13. Benchmarking ICT indicators Access 2000 2008 2009 Low-income countries GSM coverage % population under signal 16 100 100 56 International bandwidth Bits/person 0.08 16 61 24 Internet Users/100 people 0.2 7.8 8.4 4.6 Landline Subscribers per 100 0.3 0.5 0.6 4.6 people Mobile phone Subscribers per 100 0.6 26.7 28.3 28.5 people Prices Price of monthly mobile basket US$ 9.7 8.3 10 Price of monthly fixed-line US$ 13.3 11.3 9.8 basket Price of monthly fixed US$ 300 300 102 broadband Price of a call to the United US$ 0.26 0.22 States per minute Price of an inter-Africa call per US$ 0.63 0.31 minute Source: Adapted from UCC, UTL, MTN, and World Bank ICT At-a-Glance.   Uganda was an early telecommunication sector reformer. It introduced a private cellular operator in 1994, created the industry regulator UCC in 1997, licensed a second national operator in 1998, and privatized the incumbent Uganda Telecommunications Limited (UTL) in 2000 (ITU 2001). It has progressively introduced competition in the mobile sector with five operators providing service by 2009. It has also created a technology neutral streamlined licensing process. Inflow of foreign investment in Uganda, particularly from companies that are involved in more than one country, has contributed to connectivity and service enhancement. Collaboration over mobile roaming and fiber optic connectivity between Rwandatel and Uganda Telecom has been facilitated by common ownership. These multi-country networks have provided beneficial regional roaming arrangements (box 2) Box 2. Cooperative private sector development of fiber-optic infrastructure in Uganda As of 2009, Uganda’s telecommunications market had five mobile operators and several ISPs. MTN and UTL are the two national fixed line operators and are also significant mobile operators. Both companies also have operations in Rwanda and thus have a common interest in establishing a communications link across the border from Uganda to Rwanda. In 2007 MTN constructed a fiber-optic cable from Kigali, Rwanda, to the border with Uganda. The company also recently announced a deal with its competitor UTL to jointly develop the fiber-optic network on the Uganda side—a good example of competing operators forming a cooperative arrangement to lower the costs of developing fiber-optic networks outside major urban areas. But such an arrangement raises concerns for the market in Rwanda since the only fiber optic connection to the country will be jointly controlled by the only two network operators in Rwanda. Such concerns may ease as more licenses are issued in Rwanda and competition grows. Source: World Bank 2009a. 39    Uganda has gained access to the EASSy submarine cable via Kenya.. Up to 2009 there were in any case no international submarine connections in East Africa. Since then, three systems connecting East Africa have been launched. Uganda has gained access to these systems via domestic fiber-optic backbones to the Kenyan border for onward connectivity to submarine cable landing stations in Mombasa. This access to abundant bandwidth quadrupled Uganda’s international Internet capacity between 2008 and 2009 and increased the number of bits per second per person from 16 to 61 (figure 24a). Challenges The overall performance of the ICT sector is impeded by factors external to the industry. Factors such as high service taxes, low levels of electrification, and a landlocked geography raise the level of ICT prices making service unaffordable for many. Although the prices of fixed and mobile telephone services are close to those in the peer group, the prices of broadband services in Uganda are more than three times as high as in the average LIC in Africa. Uganda has Africa’s highest rate of taxes applied to telecommunications services (GSMA 2009). In addition to the value added tax (VAT), mobile phone users also have to pay an additional excise tax. While these taxes have benefited the government budget—the communications sector was the largest contributor to government revenue in the 2009 fiscal year (UCC 2010)—they raise service prices affecting mobile take-up and use. Studies indicate that reducing the excise tax would lead to a higher mobile subscription level that would in turn generate more VAT revenue for the government and offset the loss from excise taxes (UCC 2007). Very low levels of electrification—reported as 9 percent of households in 2009—impacts ICT take-up since users find it difficult to recharge mobile handsets or power ICT equipment such as computers. It also inhibits network roll-out and results in higher costs since providers must resort to higher priced alternatives such as diesel fuel to power base stations. Table 14. ICT pricing trends for EAC countries, 2005–10 (US$) 2005 2006 2009 2010 Monthly prepaid mobile basket Kenya 14.60 15.93 7.36 7.36 Rwanda 11.64 11.31 6.16 5.39 Tanzania 13.46 10.40 9.32 9.28 Uganda 8.08 9.60 8.32 8.32 Monthly postpaid fixed basket Kenya 10.42 14.23 — — Rwanda 4.84 7.69 — — Tanzania 12.43 10.82 — 9.65 Uganda 12.96 12.49 — 10.25 ADSL monthly service charge Kenya — 220.44 37.51 37.51 Rwanda — — 86.38 86.38 Tanzania — 38.87 29.74 29.74 Uganda — 300.00 300.00 300.00 40    Prices of internet services remained high in Source: AICD. Uganda as of 2010. Reduction in prices would Note: EAC = East African Community. boost Uganda’s already relatively high Internet — = Not available. penetration and foster the development of ICT services and IT-enabled exports, helping the country reduce the gap with higher performing peer countries (figure 24a). Fixed broadband pricing has shown little traction and digital subscriber line (DSL) tariffs remain high given the limited number of wired telephone lines. High-speed wireless networks on the other hand offer more attractive tariffs and will drive Uganda’s Internet progress.3 Prices are expected to fall following Uganda’s connection to the EASSy undersea cable Figure 24. Uganda’s Internet market, 2008-2009 a. Internet service trends, users, 2000–09 b. Internet service trends, COMESA, 2008–09 9.0 70 25 1600 International internet bandwidth 8.0 1400 International internet bandwidth 60 20 7.0 1200 50 Internet users 6.0 15 1000 Internet users 5.0 40 800 4.0 10 600 30 3.0 400 20 5 2.0 200 10 1.0 0 0 0.0 0 Madagascar Kenya Ethiopia Rwanda Sudan Swaziland Uganda Mauritius Zambia 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Internet users (per 100 people) Internet users (per 100 people) International Internet bandwidth (bits per second per person) International Internet bandwidth (bits per second per person) Source: AICD. Note: COMESA = Common Market for Eastern and Southern Africa. Financing Uganda’s infrastructure To meet its most pressing infrastructure needs and catch up with developing countries in other parts of the world, Uganda needs to expand its infrastructure assets in key areas (table 15). The targets outlined below are purely illustrative, but they represent a level of aspiration that is not unreasonable. Developed in a standardized way across African countries, they allow for cross-country comparisons of the affordability of meeting the targets, which can be modified or delayed as needed to achieve financial balance.                                                              3 For example the UCC reported that in June 2009, mobile accounted for 92 percent of all Internet subscriptions. See UCC (2009). 41    Table 15. Illustrative investment targets for infrastructure in Uganda Economic target Social target Install fiber-optic links to neighboring capitals and submarine Provide universal access to GSM signal and public broadband ICT cables. facilities. Develop additional 445,041 hectares of economically viable Irrigation n.a. small scale irrigation. Develop 1,258 MW of new generation capacity and 537 MW Increase electrification to 27.2 percent (100 percent urban and Power inter-connectors (no-trade scenario). 15.1 percent rural). Achieve regional (national) connectivity with good quality 2- Provide rural road access to 27 percent of the highest-value Transport lane (1-lane) paved road. agricultural land, and urban road access within 500 meters. Achieve Millennium Development Goals, clear sector WSS n.a. rehabilitation backlog. Source: Mayer and others 2009; Rosnes and Vennemo 2009; Carruthers, Krishnamani, and Murray 2009; You and others 2009. Note: WSS = water supply and sanitation; ICT = information and communication technology; GSM = global system for mobile communications. n.a. = Not applicable.    Meeting these illustrative infrastructure targets for Uganda would cost $1.4 billion per year over a decade. Capital expenditure would account for 85 percent of this requirement. The power sector has the highest spending needs and will require an estimated $0.4 billion per year; the water and sanitation sector has the second-highest spending needs at about $0.3 billion per year to meet the MDGs. Around $0.2 billion per annum will be required to meet needs in each of the ICT, irrigation, and transport sectors (table 16). Table 16. Indicative infrastructure spending needs in Uganda, 2006–15 US$ million per year  Sector Operations and Capital expenditure maintenance Total needs ICT 143 18 161 Irrigation 231 1 232 Power (nontrade) 390 57 447 Transport 137 84 221 WSS 293 56 348 Total 1,194 216 1,410   Source: Mayer and others 2009Rosnes and Vennemo 2009; Carruthers, Krishnamani, and Murray 2009; You and others 2009. Derived from models that are available online at www.infrastructureafrica.org/aicd/tools/models.  Note: WSS = water supply and sanitation; ICT = information and communication technology.    42    Infrastructure spending needs amount to around 16 percent of GDP. This is somewhat lower than for other countries in East and southern Africa (figure 25). Investment would absorb around 14 percent of GDP, about the same level of effort China made on infrastructure during the mid-2000s. Figure 25. Uganda Republic’s infrastructure spending needs in the regional context, share of GDP, 2006-2015 Estimated infrastructure spending needed to meet targets, as percentage of GDP SSA LICâ€?Fragile LICâ€?NoFragile SADC Resourceâ€?Rich MIC Congo, Dem. Rep. Zimbabwe Ethiopia Central African Republic Kenya Uganda Capex O&M South Africa Botswana % of GDP 0 10 20 30 40 50 60 70 Source: Mayer and others 2009; Rosnes and Vennemo 2009; Carruthers, Krishnamani, and Murray 2009; You and others, AICD 2009. Derived from models that are available online at www.infrastructureafrica.org/aicd/tools/models. Note: WSS = water supply and sanitation; ICT = information and communication technology.  Uganda already spends a sizable $1 billion per year to meet its infrastructure needs with a mix of public and private funds (table 17). About 65 percent of the total spending is allocated to capital expenditure and 35 percent to operating expenditures. About half of existing spending is channeled to the power sector. Operating expenditure is entirely covered from budgetary resources and payments by infrastructure users. Unusually, Uganda relies heavily on the private sector to fund as much as 40 percent of total capital spending on infrastructure. As in most countries, ICT attracts the largest share of private investment in infrastructure. But in contrast to many other countries, the private sector also invests significantly in Uganda’s power, transport and even water infrastructure. The second most important source of funding for infrastructure investment in Uganda is overseas development assistance (ODA), which supplies 33 percent of total funding and is directed mostly to power, transport and water. As is rarely the case in Africa, ODA and private participation in infrastructure (PPI) flows to the water and sanitation sectors in Uganda are broadly comparable. Third, about 26 percent of capital expenditure is funded by federal and district governments and state-owned enterprises (SOEs). Non–Organisation of Economic Co-operation and Development (non-OECD) financiers account for only around 5 percent of capital spending; their presence is most pronounced in the water and transport sectors. 43    Table 17. Financial flows to Uganda’s infrastructure, 2001-2009 US$ millions per year O&M Capital expenditure Public Non-OECD Total Total Public sector sector ODA financiers PPI CAPEX spending ICT 0.3 0.3 2 0 128 130 130 Irrigation 0.1 0.1 0 0 0 0 0.2 Power 226 71 88 0 65 224 451 Transport 81 81 75 2 22 180 261 WSS 37 18 47 3 41 109 147 Total 345 170 213 5 256 644 989 Source: Derived from Foster and Briceño-Garmendia (2009). Note: O&M = operations and maintenance; ODA = official development assistance; PPI = private participation in infrastructure; CAPEX = capital expenditure; OECD = Organisation for Economic Co-operation and Development; WSS = water supply and sanitation; ICT = information and communication technology. Existing infrastructure spending in Uganda amounts to around 11.3 percent of GDP (figure 26). Uganda devotes a relatively high share of its GDP to infrastructure compared to many other LICs in Africa. Relative to its peers, Uganda invests twice as much in power infrastructure and comparable or slightly smaller amounts on ICT, transport, and water infrastructure (figure 27). All infrastructure sectors receive at least as much or more private finance than other peer low-income African countries.   Figure 26. Uganda’s existing infrastructure spending is quite high, 2001-2009 SSA LICâ€?NoFragile MIC LICâ€?Fragile Resourceâ€?Rich Zimbabwe Ethiopia Uganda Kenya Central African Republic Botswana Capex O&M South Africa Congo, Dem. Rep. % of GDP 0 5 10 15 20 Source: Derived from Foster and Briceño-Garmendia (2009). Note: LIC = low-income country; MIC = middle-income country; SSA = Sub-Saharan Africa; GDP = gross domestic product; O&M = operations and maintenance; CAPEX = capital expenditure  44    Figure 27. Uganda’s pattern of capital investment in infrastructure differs from that of comparator countries, 2001-2009 Investment in infrastructure sectors as percentage of GDP, by source 3.0 Uganda LIC-Non-Fragile 2.0 % of GDP 1.0 0.0 Public ODA Non-OECD Private Source: Derived from Briceño-Garmendia, Smits, and Foster (2009). Note: Private investment includes self-financing by households. ODA = official development assistance; OECD = Organisation for Economic Co-operation and Development; ICT = information and communication technology; GDP = gross domestic product; WSS = water supply and sanitation; LIC = low-income country.  How much more can be done within the existing resource envelope? Inefficiencies in Uganda divert as much as $307 million in resources (table 18). By far the largest source of inefficiencies is the power sector, where underpricing and distribution losses each hemorrhage more than $100 million a year. The same types of inefficiencies are also pronounced in the water sector, but the volume of resources involved is much smaller at under $40 million in total. Another significant issue is underexecution of capital budgets in the transport sector, leading to losses of $24 million a year. Table 18. Uganda’s potential gains from greater operational efficiency, 2001-2009 US$ million  ICT Irrigation Power Transport WSS Total Under-recovery of costs — n.a. 103 n.a. 21 124 Overstaffing n.a. — 8 — 5 13 Distribution losses — — 116 — 11 127 Undercollection — n.a. 15 n.a. 0 15 Low budget execution 0 0 1 24 2 27 Total 0 0 243 24 39 307 Source: Derived from Foster and Briceño-Garmendia (2009). Note: WSS = water supply and sanitation; ICT = information and communication technology.  — = Not available. n.a. = Not applicable. Underpricing of utility services is a significant problem for Uganda, although this problem is even more serious among Uganda’s peers. Mispricing of power costs Uganda about $103 million each year, or around 0.7 percent of the country’s GDP. It is estimated that the average total cost of producing electricity 45    has been $0.24 per kWh historically in Uganda, while the average effective tariff stood at $0.15 as of 2009. While the underpricing of power remains a macroeconomically significant issue in Uganda, the problem is even more pronounced in Uganda’s peer group of other LICs in Africa (figure 28). In the water sector, average tariffs charged by NWSC stand at $0.76 per m3 versus an estimated benchmark tariff of $1.20 per m3 for full recovery of both operating and capital costs. The consequent macroeconomic burden of undercharging for water services—at 0.1 percent of GDP—is significantly lower than that for power, and again comparatively lower than for the peer group. Figure 28. Underpricing of power and water in Uganda is comparatively less burdensome, 2001-2009 Financial burden of underpricing, as percentage of GDP 1.5 Percenatage of GDP 1.0 0.5 0.0 Power Water Uganda LIC-Non-Fragile Source: Derived from Briceño-Garmendia, Smits, and Foster (2009). Note: GDP = gross domestic product; LIC = low-income country. Because of inequitable access to power and water services in Uganda, subsidized tariffs are highly regressive. Close to 100 percent of those that have electricity or piped water connections belong to the top 20 percent of the expenditure distribution; such connections are non-existent for poorer households (figure 29). Only the richest quintile has access to piped water. Most of the poorest quintile still rely on untreated surface water. This distribution of connections virtually guarantees that any price subsidy to piped water services will be extremely regressive. 46    Figure 29. Consumption of infrastructure services in Uganda is highly differentiated by budget, 2001-2009 a. Mode of water supply, by income quintile b. Prevalence of connection to power grid among population, by income quintile 100% 40% 35% 80% 30% % population % population 60% 25% 20% 40% 15% 20% 10% 0% 5% Q1 Q2 Q3 Q4 Q5 0% Piped water Stand posts Q1 Q2 Q3 Q4 Q5 Power Wells/boreholes Surface water Source: Banerjee and others 2009. Note: Q1—first budget quintile, Q2—second budget quintile, and so on.   Figure 30. Electricity and water subsidies that reach the poor, 2006 a. Electricity b. Water Nigeria Senegal Gabon CAR Congo Gabon Côte d'ivoire Congo Cape Verde Nigeria Kaduna Togo Togo DRC Sao Tome Nigeria FCT Senegal Cameroon Cameroon Côte d'ivoire Mozambique Niger Ghana Chad CAR Cape Verde Guinea Burundi Malawi Blantyre Burundi Ghana Burkina Guinea Chad Uganda Malawi Malawi Lilongwe Uganda Burkina Rwanda Rwanda 0 0.5 1 0 0.2 0.4 0.6 0.8 1 Omega Omega     Source: Banerjee and others, 2009. Note: Omega is a measure of distributional incidence, or the share of subsidies received by the poor as a percentage of their share in the population. The higher the value of omega, the better the distributional performance of the subsidy. Values of omega below 1 denote a regressive subsidy and values above 1 denote a progressive subsidy. CAR = Central African Republic; DRC = Democractic Republic of Congo 47    Cost-recovery tariffs do not look to be affordable for the majority of the population in Uganda; but more so for the relatively affluent minority with access to services. With a cost-recovery tariff of $0.24 per kWh and a monthly subsistence consumption of 50 kWh, the associated utility bill would come to $12 per month. Based on the distribution of household budgets in Uganda, monthly utility bills at these levels would be affordable by only 10 percent of the population (figure 31). Similarly, a bill for subsistence consumption of 10 m3 of water would come to $12 per month. A more limited level of subsistence consumption of 25 kWh per month for power and 4 m3 per month for water—which is capable of meeting the most basic needs—would cost $6 and $5 per month respectively, but would still only be affordable to barely half of the population. Nevertheless, it is important to recall that access to power and piped water services in Uganda at present is very limited and largely confined to the top quintile of the budget distribution. As a result, among those that have access to the service today the majority should be able to afford a subsistence level of consumption of these services. Affordability will become a serious issue as Uganda accelerates coverage of utility services, however. (Given that this analysis is based on the 2002 Household Expenditure Survey, the affordability situation is likely to have improved significantly in the meantime given sustained economic growth.) Figure 31. Affordability in Uganda worse than in other low-income countries, 2002 100 Share of urban households whose utility bill would be less  80 than 5 percent of the monthly household budget 60 40 20 0 2 4 6 8 10 12 14 16 Monthly utility bill (US$) Uganda LIC Average cost of power is 6 USD/Month per 25 kwh or 12 USD/Month per 50 kwh subsistence  consumption Average cost of water is 4.88 USD/Month per 4 m3 or 12.2 USD/Month per 10 m3 subsistence  consumption Power costâ€?recovery tariff is 0.24 USD/kwh Water costâ€?recovery tariff is 1.22 USD/m3   Source: Banerjee and others 2009. Note: LIC = low-income country; kWh = kilowatt-hour. Operational inefficiencies of power and water utilities cost Uganda a further $155 million a year, equivalent to 1.11 percent of GDP. The annual value of inefficiencies in the power sector, at $139 million, is substantially higher than for the water sector, at $16 million. The burden of utility inefficiencies in Uganda is somewhat higher than for the benchmark countries in the power sector, but lower in the water sector (figure 32). The Uganda Electricity Distribution Company Limited (UEDCL) suffers from high system losses and low collection efficiency. Uganda’s 2009 distributional losses of 39.8 48    percent are four times the best practice 10 percent benchmark, resulting in $116 million in potential savings. Another $15 million per year could be saved by raising bill collection efficiency from 94 to 100 percent. Distributional losses are the driver of operational inefficiencies in the water sector. Uganda could avoid this cost by reducing nonrevenue water losses from 2009’s 36 percent level, to the 20 percent benchmark of a well-functioning utility. Bill collection, on the other hand was close to 99 percent in 2009. Figure 32. Uganda’s power and water utilities burden of inefficiency, 2001-2009 a. Uncollected bills and unaccounted losses in the power sector, b. Uncollected bills and unaccounted losses in the water sector, as a as a percentage of GDP percentage of GDP 1.000 0.20 Percenatage of GDP Percenatage of GDP 0.800 0.15 0.600 0.10 0.400 0.05 0.200 0.000 0.00 Uganda LIC-Non-Fragile Uganda LIC-Non-Fragile Collection inefficiencies Unaccounted losses Collection inefficiencies Unaccounted losses   Source: Derived from Briceño-Garmendia, Smits, and Foster (2009).   Annual funding gap Uganda’s infrastructure funding gap amounts to $425 million per year, or about 5 percent of GDP, once efficiencies are captured. In contrast to many of its peers, Uganda does not seem to face a significant funding gap for power or transport. In the power sector, this is mainly as a result of the substantial efficiency gap, as well as the potential for reallocating expenditure within the sector from operating to capital expenditure. The largest funding gap is to be found in the water and sanitation sector(table 19). Overall, Uganda’s infrastructure funding gap looks manageable relative to its GDP and compared to funding gaps found in other LICs in Africa. Table 19. Funding gaps by sector US$ millions ICT Irrigation Power Transport WSS Total Spending needs (161) (231) (447) (221) (348) (1,409) Existing spending* 130 0 281 218 147 776 Reallocation potential within sectors 0 0 166 3 0 169 Efficiency gains 0 0 243 24 39 307 Funding gap (31) (231) - - (163) (425) Source: Derived from Foster and Briceño-Garmendia (2009). 49    Note: Potential overspending across sectors is not included in the calculation of the funding gap, because it cannot be assumed that it would be applied toward other infrastructure sectors. — = Not available. *traced to needs. What else can be done? Broadly speaking there are three alternative ways to close the infrastructure funding gap. The first is to raise additional finance. The second is to find most cost-effective ways of meeting the infrastructure targets. The third is to lengthen the time period needed to reach the targets, beyond the ten years assumed in this analysis. Uganda’s prospects for raising the volumes of additional infrastructure funding needed look quite hopeful for a number of reasons. Once efficiency gains are fully captured there would likely be surplus spending in the power sector that could potentially be reallocated toward sectors with funding gaps. Looking ahead, Uganda’s new-found oil wealth will in due course boost fiscal revenues part of which could be allocated to close the infrastructure funding gap. This gives Uganda an important new source of funding, which – however – should not become a pretext for overlooking efficiency issues. Furthermore, Uganda has been one of the most successful African countries at attracting private finance to the infrastructure sectors, and not only into telecommunications. It is unclear whether this track record suggests that even more could be done, or whether it rather signals that all of the most relevant opportunities have already been tapped (figure 33). Figure 33. Numerous African countries capture more private investment than Uganda 3.5 3.0 2.5 2.0 % GDP 1.5 1.0 0.5 0.0 Power ICT Transport Water Source: Private Participation in Infrastructure Database, 2010 . Note: GDP = gross domestic product; ICT = information and communications technology.  Continuing the existing strategy of relying on lower-cost technologies could somewhat reduce the funding gap for water and sanitation, but only to a modest extent. Meeting the MDGs for water supply and sanitation with lower-cost technologies than those that have been used to date (entailing greater reliance on stand posts, boreholes, and improved latrines) could reduce the associated price tag from $348 million to $329 million each year. But the savings, at just under $20 million are relatively small, reflecting the fact that Uganda has already gone a long way toward adopting lower-cost technologies, and the impact on the sectoral and global infrastructure funding gap would be modest. 50    Simply focusing on stemming inefficiencies, could greatly accelerate the achievement of infrastructure targets. Even if it were not possible to close the funding gap any further, simply by capturing the identified inefficiencies Uganda could still meet the postulated infrastructure targets within a 20-year period, even at current levels of spending. Without stemming inefficiencies, however, the existing resource envelope would not suffice to meet power infrastructure targets in the medium term. References and bibliography This country report draws upon a wide range of papers, databases, models, and maps that were created as part of the Africa Infrastructure Country Diagnostic. All of these can be downloaded from the project Web site: www.infrastructureafrica.org. For papers go to the document page (www.infrastructureafrica.org/aicd/documents), for databases to the data page (www.infrastructureafrica.org/aicd/tools/data), for models go to the models page (www.infrastructureafrica.org/aicd/tools/models), and for maps to the map page (www.infrastructureafrica.org/aicd/tools/maps ). The references for the papers that were used to compile this country report are provided in the table below. General AICD (Africa Infrastructure Country Diagnostic). 2010. “East Africa’s Infrastructure: A Regional Perspective.â€? Africa Region, World Bank, Washington, DC. Banerjee, Sudeshna, Quentin Wodon, Amadou Diallo, Taras Pushak, Helal Uddin, Clarence Tsimpo, and Vivien Foster. 2009. “Access, Affordability, and Alternatives: Modern Infrastructure Services in Africa.â€? AICD Background Paper 2, Africa Region, World Bank, Washington, DC. Foster, Vivien, and Cecilia Briceño-Garmendia, eds. 2009. Africa’s Infrastructure: A Time for Transformation. Paris and Washington, DC: Agence Française de Développement and World Bank. www.infrastructureafrica.org. World Bank. 2006. Beyond Recovery: Investment and Behavior Change, for Growth. Country Economic Memorandum., Volume 1: Summary and Recommendations. Washington, DC: World Bank. World Bank and IFC (International Finance Corporation). 2006. Enterprise Survey. Uganda Country Profile. Washington, DC: World Bank. Adam and Bevan 2003, Garber 2004, Same 2008 Financing Briceño-Garmendia, Cecilia, Karlis Smits, and Vivien Foster. 2009. “Financing Public Infrastructure in Sub- Saharan Africa: Patterns and Emerging Issues.â€? AICD Background Paper 15, Africa Region, World Bank, Washington, DC. 51    Growth Calderón, César. 2009. “Infrastructure and Growth in Africa.â€? Policy Research Working Paper 4914, World Bank, Washington, DC. Escribano, Alvaro, J. Luis Guasch, and Jorge Pena. 2010. “Assessing the Impact of Infrastructure Quality on Firm Productivity in Africa.â€? Policy Research Working Paper 5191, World Bank, Washington, DC. Yepes, Tito, Justin Pierce, and Vivien Foster. 2009. “Making Sense of Africa’s Infrastructure Endowment: A Benchmarking Approach.â€? Policy Research Working Paper 4912, World Bank, Washington, DC. Information and communication technologies Ampah, Mavis, Daniel Camos, Cecilia Briceño-Garmendia, Michael Minges, Maria Shkaratan, and Mark Williams. 2009. “Information and Communications Technology in Sub-Saharan Africa: A Sector Review.â€? AICD Background Paper 10, Africa Region, World Bank, Washington, DC. Gillwald, Alison, and Christoph Stork. 2008. “Towards Evidence-based ICT Policy and Regulation: ICT Access and Usage in Africa.â€? www.researchictafrica.net/index.php/ria-publications. GSMA (GSM Association). 2009. Taxation and the Growth of Mobile in East Africa., London ITU (International Telecommunication Union). 2001. The Internet in an African LDC: Uganda Case Study, International Telecommunications Union, Geneva Mayer, Rebecca, Ken Figueredo, Mike Jensen, Tim Kelly, Richard Green, and Alvaro Federico Barra. 2009. “Connecting the Continent: Costing the Needs for Spending on ICT Infrastructure in Africa.â€? AICD Background Paper 3, Africa Region, World Bank, Washington, DC. UBOS (Uganda Bureau of Statistics). 2006. Uganda National Household Survey 2005/2006. Kampala UCC (Uganda Communications Commission). 2007. Review of Sector Taxation Policies and Determining the Elasticity of Penetration and Price of the Various Telecommunication Services in Uganda. Kampala— ——. 2009a. Status of the Communications Market—December 2008. Kampala ———. 2009b. A Review of the Post and Telecommunications Market 2008/09. Kampala ———. 2010. Status of the Communications Market—December 2009. Kampala World Bank. 2009a. Information and Communications for Development 2009: Extending Reach and Increasing Impact. Washington, DC: World Bank. Irrigation Heidecke, Claudia. 2006. Development and Evaluation of a Regional Water Poverty Index for Benin. IFPRI Discussion Paper 145, International Food Policy Research Institute. Washington DC Svendsen, Mark, Mandy Ewing, and Siwa Msangi. 2008. “Watermarks: Indicators of Irrigation Sector Performance in Africa.â€? AICD Background Paper 4, Africa Region, World Bank, Washington, DC. 52    You, L., C. Ringler, G. Nelson, U. Wood-Sichra, R. Robertson, S. Wood, G. Zhe, T. Zhu, and Y. Sun. 2009. “Torrents and Trickles: Irrigation Spending Needs in Africa.â€? AICD Background Paper 9, Africa Region, World Bank, Washington, DC. Power Eberhard, Anton, Vivien Foster, Cecilia Briceño-Garmendia, Fatimata Ouedraogo, Daniel Camos, and Maria Shkaratan. 2008. “Underpowered: The State of the Power Sector in Sub-Saharan Africa.â€? AICD Background Paper 6, Africa Region, World Bank, Washington, DC. EIA. 2009. International Energy Statistics, United States Energy Information Administration, Washington, DC EIU. 2011. Uganda Country Report, Economist Intelligence Unit, London Foster, Vivien, and Jevgenijs Steinbuks. 2009. “Paying the Price for Unreliable Power Supplies: In-House Generation of Electricity by Firms in Africa.â€? Policy Research Working Paper 4913, World Bank, Washington, DC. GTZ. (Deutsche Gesellschaft für Internationale Zusammenarbeit), 2009. International Fuel Prices 2009, 6th edition. Eschborn, Germany. Keener, S., and S. G. Banerjee. 2005. “Ghana: Poverty and Social Impact Analysis of Electricity Tariffs.â€? ESMAP Technical Paper 088, World Bank, Washington, DC. Okure, Eng. Dr. Mackay A. E. 2008. EAC Strategy to Scale up Access to Modern Energy Services: Uganda Country Report and Implementation Workplan. Mimeo, Kampala. Rosnes, Orvika, and Haakon Vennemo. 2009. “Powering Up: Costing Power Infrastructure Spending Needs in Sub-Saharan Africa.â€? AICD Background Paper 5, Africa Region, World Bank, Washington, DC. Tallapragada, Prasad, Maria Shkaratan, Ada Karin Izaguire, Jaakko Helleranta, Saifur Rahman, and Sten Bergman. 2009. Monitoring Performance of Electric Utilities. Washington, DC: World Bank. World Bank. 2010a. “Performance of the Uganda Power Sector (comprising of UEGCL, UETCL, UEDCL and Umeme).â€? Mimeo, World Bank, Washington, DC. ———. 2011a. “Electricity Development Project for Uganda.â€? Project Appraisal Document, World Bank, Washington, DC, May 31, 2011. World Energy Outlook. 2010. The Electricity Database. International Energy Association, World Energy Outlook Database. www.worldenergyoutlook.org/database_electricity10/electricity_database_web_2010.htm. World Bank, forthcoming, “Uganda Strategic Review of the Electricity Sectorâ€?, Mimeo, Poverty Reduction and Economic Management, Africa Region, World Bank, Washington DC. Transport Bofinger, Heinrich C. 2009. “An Unsteady Course: Growth and Challenges in Africa’s Air Transport Industry.â€? AICD Background Paper 16, Africa Region, World Bank, Washington, DC. 53    Bullock, Richard. 2009. “Off Track: Sub-Saharan African Railways.â€? AICD Background Paper 17, Africa Region, World Bank, Washington, DC. Carruthers, Robin, Ranga Rajan Krishnamani, and Siobhan Murray. 2009. “Improving Connectivity: Investing in Transport Infrastructure in Sub-Saharan Africa.â€? AICD Background Paper 7, Africa Region, World Bank, Washington, DC. Gwilliam, Ken, Vivien Foster, Rodrigo Archondo-Callao, Cecilia Briceño-Garmendia, Alberto Nogales, and Kavita Sethi. 2008. “The Burden of Maintenance: Roads in Sub-Saharan Africa.â€? AICD Background Paper 14, Africa Region, World Bank, Washington, DC. Kumar, Ajay, and Fanny Barrett. 2008. “Stuck in Traffic: Urban Transport in Africa.â€? AICD Background Paper 1, Africa Region, World Bank, Washington, DC. Ocean Shipping Consultants, Inc. 2009. “Beyond the Bottlenecks: Ports in Africa.â€? AICD Background Paper 8, Africa Region, World Bank, Washington, DC. Teravaninthorn, Supee, and Gaël Raballand. 2009. “Transport Prices and Costs in Africa: A Review of the Main International Corridors.â€? AICD Working Paper 14, Africa Region, World Bank, Washington, DC. World Bank. 2005. “East Africa Trade and Transport Facilitation Project.â€? Project Appraisal Document, World Bank, Washington, DC, December 27, 2005. ———. 2009b. “Transport Sector Development Project.â€? Project Appraisal Document, World Bank, Washington, DC, November 2009. World Bank 2009. Uganda Transport Sector Development Project. Project Appraisal Document. November 12, 2009. Washington DC Yoshino, Yutaka. 2011. Behind the recent growth of the South Sudan's cross-border regional trade with Uganda. Mimeo Washington DC Water supply and sanitation AMCOW (African Ministerial Conference on Water). 2010. Regional Synthesis Report, Country Status Overviews on Water Supply and Sanitation 2010. Led by the World Bank–administered Water and Sanitation Program (WSP) in collaboration with the African Development Bank (AfDB), the United Nations Children’s Fund (UNICEF), and the World Health Organization (WHO), Addis Ababa Azuba, Chris, Josses Mugabi,and Yogita Mumssen 2010. “Output based AID for Water Supply in Uganda: Increasing Access in Small Towns.â€? OB Approaches Series, Note No. 35, July 2010, Global Partnership for Output Based Aid, Washington DC. Banerjee, Sudeshna, Vivien Foster, Yvonne Ying, Heather Skilling, and Quentin Wodon. 2008a. “Cost Recovery, Equity, and Efficiency in Water Tariffs: Evidence from African Utilities.â€? AICD Working Paper 7, World Bank, Washington, DC. 54    Banerjee, Sudeshna, Heather Skilling, Vivien Foster, Cecilia Briceño-Garmendia, Elvira Morella, and Tarik Chfadi. 2008b. “Ebbing Water, Surging Deficits: Urban Water Supply in Sub-Saharan Africa.â€? AICD Background Paper 12, Africa Region, World Bank, Washington, DC. IBNET (The International Benchmarking Network for Water and Sanitation Utilities). 2009. www.ib-net.org/. WHO (World Health Organization) Joint Monitoring Program (JMP). 2010. “Uganda Estimates for the Use of Improved Drinking-Water Sources.â€? www.wssinfo.org/resources/documents.html. ———. 2010b. “Uganda Estimates for the Use of Improved Sanitation Facilities.â€? www.wssinfo.org/resources/documents.html. Keener, Sarah, Manuel Luengo, and Sudeshna Banerjee. 2009. “Provision of Water to the Poor in Africa: Experience with Water Standposts and the Informal Water Sector.â€? AICD Working Paper 13, World Bank, Washington, DC. Marin, Philippe, William Muhairwe, Silver Mugisha, and Josses Mugabi 2010. “Internal Delegation Contracts for Water in Uganda.â€? Gridlines Series, PPIAF, Note No. 55, World Bank, Washington, DC, June 2010. Morella, Elvira, Vivien Foster, and Sudeshna Ghosh Banerjee. 2008. “Climbing the Ladder: The State of Sanitation in Sub-Saharan Africa.â€? AICD Background Paper 13, Africa Region, World Bank, Washington, DC. Other Nathan Associates. 2010. “Definition and Investment Strategy for a Core Strategic Transport Network for Eastern and Southern Africa.â€? Preliminary draft report prepared for the World Bank, Washington, DC. Teravaninthorn, Supee, and Raballand Gael. 2009. Transport Prices and Costs in Africa: A Review of the Main International Corridors. Washington, DC: World Bank. World Bank. 2008. Doing Business 2009: Comparing Regulation in 181 Economies. Washington, DC: World Bank. ———. 2010b. “Agricultural Technology and Agribusiness Advisory Services.â€? Project Appraisal Document, World Bank, Washington, DC, May 26, 2010. World Bank 2011a. Uganda’s Transition to an Oil Economy: Fiscal Decentralization and Local Development in the Producing Areas. Mimeo. Washington DC ———. 2011b. “Uganda Demography and Economic Growth in Uganda.â€? Draft version, World Bank, Washington, DC. WEF (World Economic Forum). 2007. “Competitiveness and Information and Communications Technologies in Africa.â€? In Africa Competitiveness Report 2007, ed. World Economic Forum, Geneva       55    About AICD and its country reports   This study is a product of the Africa Infrastructure Country Diagnostic (AICD), a project designed to expand the world’s knowledge of physical infrastructure in Africa. The AICD provides a 2006 baseline against which future improvements in infrastructure services can be measured, making it possible to monitor the results achieved from donor support. It also offers a solid empirical foundation for prioritizing investments and designing policy reforms in Africa’s infrastructure sectors. The AICD is based on an unprecedented effort to collect detailed economic and technical data on African infrastructure. The project has produced a series of original reports on public expenditure, spending needs, and sector performance in each of the main infrastructure sectors, including energy, information and communication technologies, irrigation, transport, and water and sanitation. Africa’s Infrastructure— A Time for Transformation, published by the World Bank and the Agence Française de Développement (AFD) in November 2009, synthesized the most significant findings of those reports. The focus of the AICD country reports is on benchmarking sector performance and quantifying the main financing and efficiency gaps at the country level. These reports are particularly relevant to national policy makers and development partners working on specific countries. The AICD was commissioned by the Infrastructure Consortium for Africa following the 2005 G8 (Group of Eight) summit at Gleneagles, Scotland, which flagged the importance of scaling up donor finance for infrastructure in support of Africa’s development. The first phase of the AICD focused on 24 countries that together account for 85 percent of the gross domestic product, population, and infrastructure aid flows of Sub-Saharan Africa. The countries are: Benin, Burkina Faso, Cape Verde, Cameroon, Chad, Côte d’Ivoire, the Democratic Republic of Congo, Ethiopia, Ghana, Kenya, Lesotho, Madagascar, Malawi, Mozambique, Namibia, Niger, Nigeria, Rwanda, Senegal, South Africa, Sudan, Tanzania, Uganda, and Zambia. Under a second phase of the project, coverage was expanded to include as many of the remaining African countries as possible. The data collected under the first phase of the project covered the period 2001 to 2006, while that collected under the second phase covered the period 2001 to 2008. Consistent with the genesis of the project, the main focus is on the 48 countries south of the Sahara that face the most severe infrastructure challenges. Some components of the study also cover North African countries so as to provide a broader point of reference. Unless otherwise stated, therefore, the term Africa is used throughout this report as a shorthand for Sub-Saharan Africa. 56    The World Bank has implemented the AICD with the guidance of a steering committee that represents the African Union (AU), the New Partnership for Africa’s Development (NEPAD), Africa’s regional economic communities, the African Development Bank (AfDB), the Development Bank of Southern Africa (DBSA), and major infrastructure donors. Financing for the AICD is provided by a multidonor trust fund to which the main contributors are the United Kingdom’s Department for International Development (DFID), the Public-Private Infrastructure Advisory Facility (PPIAF), Agence Française de Développement (AFD), the European Commission, and Germany’s Entwicklungsbank (KfW). A group of distinguished peer reviewers from policy-making and academic circles in Africa and beyond reviewed all of the major outputs of the study to ensure the technical quality of the work. The Sub-Saharan Africa Transport Policy Program and the Water and Sanitation Program provided technical support on data collection and analysis pertaining to their respective sectors. The data underlying AICD’s reports, as well as the reports themselves, are available to the public through an interactive Web site, www.infrastructureafrica.org, that allows users to download customized data reports and perform various simulations. Many AICD outputs will appear in the World Bank’s Policy Research Working Papers series. Inquiries concerning the availability of data sets should be directed to the volume editors at the World Bank in Washington, DC.       57  Â