Uganda - The challenge of growth and poverty reduction

Report No. 14313-UG Uganda The Challenge of Growth and Poverty Reduction June 30, 1995 Country Operations Division Eastern Africa Departnient Africa Region Document of the World Bank   Report No. 14313-UG Uganda The Challenge of Growth and Poverty Reduction JUNE 30, 1995 Country Operations Division Eastern Africa Department Africa Region Document of the World Bank  GOVERNMENT FISCAL YEAR July 1 - June 30 FY93 = July 1, 1992 to June 30, 1993 CURRENCY EQUIVALENTS Currency Unit: Ugandan shilling (U Sh) Interbank Market mid-rate: US$1.00 = U Sh 929 (April 1995) Bureau mid-rate for cash: US$1.00 = U Sh 935 (April 1995) Bureau mid-rate for travellers' cheques: US$1.00 = U Sh 924 (April 1995) ACRONYMS AND ABBREVIATIONS ADB African Development Bank BOU Bank of Uganda CIF cost, insurance and freight CMB Coffee Marketing Board COMESA Common Market for Eastern and Southern Africa CPI consumer price index DFCU Development Finance Corporation of Uganda DRC domestic resource costs EPADU Export Policy Analysis and Development Unit ESAF Enhanced Structural Adjustment Facility EU European Union FOB free on board FY fiscal year GDP gross domestic product HBS Household Budget Survey IBRD International Bank for Reconstruction and Development IDA International Development Association IHS Integratea Household Survey IMF International Monetary Fund IVA international value added LMB Lint Marking Board MAAIF Ministry of Agriculture, Animal Industries and Fisheries MFEP Ministry of Finance and Economic Planning MUV manufacturing unit value NGO nongovernment organization NTAE nontraditional agricultural exports ODA Overseas Development Association (U.K.) OECD Organization for Economic Cooperation and Development PAPSCA Program to Alleviate Poverty and the Social Cost of Adjustment PTA Preferential Trade Area QR quantitative restriction RC resistance council REER real effective exchange rate SSA Sub-Saharan Africa TOT terms of trade UCB Uganda Commercial Bank UCDA Uganda Coffee Development Authority UIA Uganda Investment Authority UIRA Uganda Revenue Authority USAID United States Agency for International Development VAT value added tax  COUNTRY DATA SHEET Page 1 of 4 General Area, land sq km 197,097 Population (1991) 16,671,705 Density (1991) per sq km 85 Socio-Econornc Indicators (1992/93) Women's share of credit Total percent 9.2 Rural " 13.6 Urban 7.3 Mean hours worked per day Men hours per day 7.0 Women 8.4 Women's share of land Total percent 26.0 Rural 28.7 Urban " 39.7 Social Indicators Mean births (1992/93) Rural of all women > 40 6.8 Urban 6.3 Health Infant mortality (1991) 0 - 11 months per 1,000 live births 122 12 - 59 months " 93 0 - 59 months " 203 Population per physician (1989) 23,000 Population per hospital (1992) 185,350 Education (1992/93) Literacy rate All Uganda percent, age 6 and over 61 Male " 75 Female 49 Urban " 86 Rural " 57 Primary school gross enrollment ratios Total % of relevant population 91 Male 99 Female " 83 Urban 103 Rural 90 Secondary school gross enrollment ratios Total % of relevant population 13 Male " 17 Female " 10 Urban 30 Rural " 11 Sources: 1992/93 IHS and Key Economic Indicators (MFEP), November 1994.  COUNTRY DATA SHEET Page 2 of 4 Gross National Product - FY94 Annual Growth Rates-- (% p.a., constant prices) US$ m % of GNP FY&8-FY94 FY92 FY93 FY94 GNP at market prices 3,995 100.0 6.1 2.2 10.0 5.2 GDPatfactorcost 3,755 94.0 6.0 3.6 8.6 5.1 Gross domestic investment 522 13.1 4.1 -6.9 4.0 7.8 Gross national savings 289 7.2 86.8 153.4 243.0 96.3 Current account balance -234 -5.9 -9.6 -16.6 -19.6 -39.9 Exports GNFS 248 6.2 8.9 17.1 -7.7 46.0 Imports GNFS 724 18.1 2.1 -2.7 9.1 1.5 GNP per capita - in US$ 218 Output, Employment and Productivity - FY94 -Value Added - - Value Added - -Labor Force - per Worker US$ m % mill. % US$ % Agriculture 1,842 49.0 .. Industry 539 14.3 .. Manufacturing 255 6.8 .. Services 1,375 36.6 .. Total 3,755 100.0 Government Finance UShm -% of GDPmp - FY94 FY90 FY94 Current receipts 363,881 6.8 8.2 Current expenditures 390,567 7.1 8.8 Current deficit -26,686 -0.3 -0.6 Capital expenditures 1/ 426,205 5.5 10.0 Continued 1/ Includes net lending.  COUNTRY DATA SHEET Page 3 of 4 Money, Credit and Prices FY90 FY91 FY92 FY93 FY94 In billions of U Sh outstanding, end of period: Money supply 94.4 138.6 237.0 338.0 448.7 Bank credit to public sector 9.2 12.9 57.2 40.0 -12.5 Bank credit to private sector 70.5 107.8 133.2 168.7 213.0 Percentage or index numbers: Money as % of GDP 2/ 6.8 7.5 8.5 8.6 10.1 Kampala CPI (Sept 1989 = 100) 110.1 137.1 194.8 250.1 269.6 (annual average) Annual percentage changes: Kampala CPI 45.4 24.6 42.1 28.4 7.8 Money supply, M2 57.0 46.8 71.0 42.6 32.8 Bank credit to public sector -65.2 40.2 343.4 -30.1 -131.3 Bank credit to private sector 67.5 52.9 23.6 26.7 26.3 Balance of Paymenits FY90 FY91 FY92 FY93 FY94 In millions of USS Exports GNFS 246 199 195 206 333 Imports GNFS 676 671 582 753 893 o/w Petroleum 78 87 57 53 64 Resource gap (deficit = -) -430 -472 -387 -547 -560 Factor service income, net -77 -58 -87 -49 -61 Net private transfers 78 81 136 241 304 Balance on current account -429 -449 -338 -355 -318 (excl. net official transfers) Net official transfers 153 262 206 259 250 Balance on current account -276 -187 -132 -96 -67 (incl. net official transfers) Capital account 244 84 7 85 173 Long-temi, net 215 122 38 127 179 Short-term, net 17 -36 -29 -18 -50 Errors and ommissions 12 -2 -2 -25 44 Overall balance -32 -103 -125 -12 106 Monetary movements 32 103 125 12 -106 Change in reserves 11 -15 -24 -38 -107 IMF transactions, net -1 52 22 10 18 Other 22 66 127 40 -16 2/ FY90 and FY91 money supply is M2. Beginning in FY93 M3, which includes forex accounts, is used. Continued  COUNTRY DATA SHEET Page 4 of 4 Merchandise Expons (Average FM90 - FY94) Value US$ m % of Total Coffee 128.8 67.9 Cotton 6.9 3.6 Tea 6.3 3.3 Other 47.6 25.1 Total 189.6 100.0 Rate of Exchange (Official. mid-point) FY90 FY91 FY92 FY93 FY94 U Sh 1.00 = USS 0.003 0.002 0.001 0.001 0.001 US$1.00 = U Sh 320 551 961 1202 1097 Ertemnal Debt, June 30, 1994 USS m Multilateral institutions 1,789 IMF 361 Bilateral, OECD 332 Bilateral. non-OECD 398 Commercial and other 112 Total outstmlding & disbursed 2,993 Net LTDebt Service Rado for FY94 4/ Percentage Multilateral institutions 23.7 IMF 20.4 Bilateral 3.1 Commercial and other 4.9 Total debt service 52.0 IRRD/IDA Lending. December 31, 1994 In miUlions qf USS IRD IDA Outstanding & disbursed 43 1,502 Undisbursed 0 756 Total outstanding including undisbursed 43 2,258 3/ Excludes IMF. 4/ Debt service as a percentage of exports of goods an services.  Acknowledgments This Country Economic Memorandum was prepared by a team led by task manager Ritva Reinikka (AF2CO). Team members included Federico Changanaqui, Mimi Klutstein-Meyer (AF2CO); Paul Armington (IECAP); Mohsen Fardi (AFRVP); Steven Jaffee (AF1AE); Simon Appleton, Arsene Balihuta, Paul Collier, Carsten Koch, Chris Milner, John McKinnon, Emmanuel Nabuguzi, Germina Ssemogerere (consultants). Additional material was prepared by James Coates and Tekola Dejene (AF2AE), while Mimi Klutstein-Meyer was responsible for the Statistical Annex. DANIDA, ODA, and SIDA financed a number of the consultants. The report was prepared under the general supervision of Peter Miovic, Lead Economist (AF2DR), Michael Carter, Chief (AF2CO) and Francis X. Colaco, Director (AF2), and benefited from comments from Shahid Yusuf, Lead Economist (AF2DR). The peer reviewers were Emmanuel Ablo (ESP), Lant Pritchett (PRDPH) and Jack van Holst Pellekaan (AFTHR). Technical support was provided by Roboid Covington, assisted by Lora Clarkson, Kathryn Rivera and Christian Villegas. The Government team was led by Damoni Kitabire (MFEP), Chairman of the Task Force for the report, and consisted of Mary Muduuli, Keith Muhakanizi, Allister Moon, Mark Henstridge, George Mugerwa, Tuan Nguyen (MFEP), Louis Kasekende, K.M. Agarwal (BOU), Margaret Kakande (PAPSCA), Francis X. Lubanga (Decentralization Secretariat), Sarah Kitakule (UMA) and Angela Katama (UIA). The report was discussed with the Government in June 1995. The team met with a number of donors and NGOs working in Uganda during the preparation of the report. A separate set of working papers on poverty in Uganda were prepared by Simon Appleton, Arsene Balihuta, Philippa Bevan, John McKinnon, Germina Ssemogerere and Achilles Ssewaya, financed by SIDA. The working papers are listed in the bibliography and are available in the World Bank Public Information Center, Washington DC.   CONTENTS EXECUTIVE SUMMARY ................................................................. i A. MACROECONOMIC POLICY AGENDA .............................................. ................... ii B. ACCELERATING GROWTH: INCENTIVES, EXPORTS AND INVESTMENT .................... I ..... iv C. RURAL INFRASTRUCTURE AND HUMAN RESOURCE DEVELOPMENT ........... .................. vi 1 MACROECONOMIC PERFORMANCE AND THE ROAD AHEAD .............................. 1 A. GROWTH, INV E STME NT AND SAVINGS .................................................................. 1 B. FISCAL AND MONETARY POLICY ................................................................. 6 C. EXCHANGE RATE MANAGEMENT AND TERMS OF TRADE SHOCKS ........... ................... 13 D. EXTERNAL AID AND MACROECONOMIC MANAGEMENT ................... ........................... 17 E. SUSTAINABILITY OF EXTERNAL DEBT ................................................................. 20 F MACROECONOMIC PROJECTIONS .................................................................. 2 1 2 ACCELERATING ECONOMIC GROWTH: INCENTIVES, EXPORTS AND INVESTMENT ................................................................. 25 A. PRiVATE RESPONSE IN EXPORTS, INDUSTRIAL PRODUCTION AND INVESTMENT: RECENT EVIDENCE ................................................................. 26 B. EFFECTIVE PROTECTION ................................................................. 3 3 C. HIDDEN SOURCES OF ANTIEXPORT BIAS ................................................................. 3 6 D. TRADE POLICY AGENDA ................................................................. 37 3 EXPORT RESPONSE AND INVESTMENT IN AGRICULTURE ................................. 39 A. PROSPECTS FOR TRADITIONAL CASH CROPS .............................................................. 40 B. DEVELOPMENT OF NONTRADITIONAL AGRICULTURAL EXPORTS IN 1988-94 ............... 42 C. INVESTMENT, ORGANIZATION AND INSTTUTIONAL SUPPORT .............. ....................... 46 D. EFFICIENCY, COMPETITIVENESS AND DEVELOPMENT IMPACT ............. ....................... 50 E. FUTURE PROSPECTS AND POLICY AGENDA ................................................................ 54 4 INFRASTRUCTURE AND HUMAN RESOURCES FOR GROWTH AND POVERTY REDUCTION ................................................................. 59 A. RURAL INFRASTRUCTURE FOR GROWTH AND POVERTY REDUCTION .......... ................ 60 B. EDUCATIONAL ATTAINMENT AND HEALTH ................................................................ 63 C. PUBLIC AND PRIVATE SECTOR ROLES IN SOCIAL SECTOR PROVISION ......................... 69 D. A WAY FORWARD IN HUMAN RESOURCE DEVELOPMENT .......................................... 72 ANNEX 1 POVERTY UPDATE ................................................................. 75 A. DISTRIBUTION OF WELFARE AND POVERTY ............................................................... 76 B. SOURCES OF INCOME ................................................................. 79 C. HOUSEHOLD EXPENDITURE ................................................................. 83 D. CHANGES IN POVERTY: EVIDENCED FROM HOUSEHOLD SURVEYS ......... ................... 84 E. DOMESTIC TERMS OF TRADE AND AGRICULTURAL PRODUCTION ................................ 87  ANNEX II MACROECONOMIC PROJECTIONS ....................................... 91 ANNEX ISg STATISTICAL ANNEX ....................................... 99 BIBLIOGRAPHY ....................................... 165 TEXT TABLES Table 1.1 Key Economic Indicators (National Accounts) Table 1.2 Key Economic Indicators (Public Finance) Table 1.3 Key Economic Indicators (Monetary Indicators) Table 1.4 Key Economic Indicators (Balance of Payments) Table 1.5 Liquidity Ratios Table 2.1 Investment and Export Shares of GDP Table 2.2 Composition of Merchandise Exports Table 2.3 Changes in Industrial Production Table 2.4 Composition of Planned and Estimated On-Ground Investment in UIA Monitored Projects: Manufacturing Sector Table 2.5 Fixed Investment, Construction and Trade Policy Table 2.6 Recent Evidence on Effective Protection Levels Table 2.7 Re-estimated Effective Rates of Tariff Protection Table 3.1 Nontraditional Agricultural Exports Table 3.2 Agribusiness Investments in Uganda Table 3.3 Estimated Revenue Share and Gross Earnings of Farmers and Fishermen, 1993 Table 3.4 Returns and Efficiency of Traditional and Nontraditional Crops Table 4.1 Educational Attainment Table 4.2 Child Mortality Table 4.3 Recurrent Expenditures Table A. 1 Distribution of Welfare Table A.2 Distribution of Population by Region and by Expenditure Quartiles Table A.3 Major Income Sources in Uganda Table A.4 Major Income Sources in Uganda (Urban/Rural) Table A.5 Agricultural Revenue Sources in Uganda Table A.6 Share of Major Commodity Groups in Household Budgets Table A.7 Gini Coefficients for Uganda TEXT FIGURES Figure 1.1 Progress in Economic Recovery and Stabilization Figure 1.2 Key Economic Indicators Figure 1.3 Gross and Net Aid as Shares of GDP Figure 1.4 Terms of Trade Effect, Aid Disbursement Differences and Net Effect .i.  Figure 2.1 Structure of Exports Figure 2.2 Financial Structure of Ugandan Finns Figure A. 1 Distribution of Rural/Urban Population by Expenditure Quartiles Figure A2 Crops and Agricultural Revenue Figure A.3 Domestic Terms of Trade Figure A.4 Agricultural GDP per Rural Person Figure A.5 Per Capita Food Production TEXT BOXES Box 1.1 The Impact of AIDS on Growth Box 1.2 Fiscal Decentralization Box 1.3 Improving Public Sector Management Box 2.1 Chronology of Trade and Exchange Rate Reforms, 1987-94 Box 2.2 Incidence of Import Duties Box 3.1 Reforms in the Coffee Sector Box 3.2 Technical Assistance for Nontraditional Export Development Box A. 1 Calculation of the Poverty Measure Box A.2 Poverty in Sub-Saharan Africa iii   EXECUTIVE SUMMARY 1. With a per capita income of about US$220, Uganda is one of the poorest countries in the world. Its weak economy and poor social indicators are the legacy of nearly 15 years of political turmoil and economic decline. Since 1987 the Government has been implementing an economic reform program supported by a large number of donors. The program aims to promote prudent fiscal and monetary management, improve incentives to the private sector, reform the regulatory framework, and develop human capital through investment in education and health. 2. Economic recovery and macroeconomic stabilization have been successful, and the pace of macroeconomic and institutional reforms has accelerated during the past three years. Per capita GDP has grown at the average rate of about 3 percent since 1987. However, the hard-won stability is precarious. Its continuation depends upon the ability to press ahead with recent macroeconomic policies. Furthermore, sustaining and accelerating economic growth and substantially reducing poverty will depend on developments on the real side of the economy. 3. Growth performance and recent improvements in coffee prices have led to a decrease in hardcore poverty. However, available data for 1992/93 show little change in overall poverty incidence. As traditional and emerging cash crops are as important an income source for the poor as for the better-off, liberalization of agricultural markets, which has substantially increased farmgate prices, has benefited both. 4. This Country Economic Memorandum takes stock of the outcomes of reforms in Uganda and defines the next generation of issues that Uganda must address in its medium- and long-term strategy for poverty reduction. The thrust of this strategy is the promotion of broad-based economic growth and increased investment in human resource development.' The report first analyzes the medium-term macroeconomic policy agenda with the objective of sustaining and strengthening macroeconomic stability which is a necessary condition for growth and poverty reduction. It then reviews the prospects for steady economic growth. Finally, a poverty update analyzes the status of and changes in poverty during the adjustment period. 5. Sustained growth requires increased private investment and strong export growth backed by higher public and private saving. In addition, physical and social infrastructure are necessary facilitating factors to complement private investment and provide human capital. Growth in Uganda is constrained by a number of factors which affect export development and private investment. The main constraints are poor infrastructure and weak institutions, a shortage of human capital, a weak financial sector, and remaining distortions in the incentive regime. Finally, the credibility of government policies needs to be progressively strengthened through the determined implementation of reforms. The I World Bank (1993), Uganda: Growing Out ofPoverty.  ii Executive Summary report focuses on the incentive regime, particularly on the antiexport bias, while other constraints and policies to overcome them will be analyzed from the viewpoint of promoting nontraditional agricultural exports, investment in rural infrastructure and human resource development. A. MACROECONOMIC POLICY AGENDA 6. Continue Tight Fiscal Policy. Uganda is currently well served by a tight fiscal policy which, with ongoing monetary deepening, keeps inflation relatively low. The traditional sources of monetary instability-monetization of the fiscal deficit and excessive overdraft facilities at the central bank-have been controlled and the quasi fiscal deficits checked. The policy of public expenditure restraint, which increases fiscal savings when foreign aid or tax receipts exceed the planned public expenditure level, acts as a powerful force for stabilization. As the Government is likely to receive once-and-for all revenues, such as funds accruing from divestiture of publicly owned assets or windfall tax revenue, it must ensure that such revenues do not result in expenditures that lead to unsupportable future claims on the budget. 7. Increase Public Revenue. During the past few years, fiscal deficits have been financed solely by grants and concessional foreign borrowing. One of the most critical issues for long-term macroeconomic stability is to increase public revenue. Otherwise, there is a risk of inflation which could discourage private investment, reduce capital inflows, and adversely affect poverty. Government must step up tax reform and extend the planning horizon of tax policy to at least the medium term. Tax reform should focus on three main issues: dismantling the dispersed system of duty, sales tax, and excise tax exemptions and replacing them with low, uniform rates; broadening the tax base, including the local revenue effort; and seeking to shift from a reliance on foreign trade taxes toward VAT and direct taxes. Improving the local revenue effort will require a substantial improvement in service delivery. This can be assisted by donors who can jump-start the process of improving services which in turn can lead to an improvement in the local tax effort. 8. Increase Public and Private Saving. Rapid growth could well start a virtuous circle of increased savings and investment which further support high growth. Increased public revenue would allow higher public savings, while rationalization of the tax system and its effective and fair implementation would promote private saving by firms. In order to increase overall private savings, financial sector reform is indispensable. Until now, reforms in the financial sector have been implemented unevenly and major new risks have emerged. The commercial banking system is in a precarious state: more than half of the banks made losses in 1994, and they have a large negative core capital. A number of banks are insolvent, including Uganda Commercial Bank (UCB). Aggregate nonperforming assets are in excess of 50 percent of total loans making much of banking activity nonviable. Banks lack financial discipline and administrative efficiency which has resulted in extremely high intermediation costs. These costs impose a significant burden on borrowers. The financial position of the Bank of Uganda is also untenable because of  Executive Summary ii foreign exchange and other past losses. The complexity of the problems, given the institutional capacity, calls for a focused approach. Immediate action is required on four fronts: privatizing UCB expeditiously; adopting a more aggressive approach in dealing with distressed private banks; strengthening the central bank; and adopting more prudent lending policies. 9. Management of the Coffee Boom. Successful management of external trade shocks keeps inflation low and the exchange rate stable. Booms and the way they are managed have also a direct impact on investment. Because coffee is an important source of income for the poor in the main coffee growing areas, boom management is linked to poverty reduction. Empirical evidence from other Sub-Saharan African countries suggests that the private sector typically saves a large part of transient income. Savings and investment can secure a sustainable increase in consumption. At the onset of the boom, savings tend to be in financial assets, in practice money and bank deposits. Subsequently, savings are likely to be invested so that the demand for assets would shift to real assets. 10. Given the private sector's likely response to the boom and the objective of avoiding unnecessary currency appreciation, the central bank must accommodate the private sector's increased demand for money by accumulating reserves. This policy has worked well in the current coffee boom: appreciation has been minimal, while inflation has been about 5 percent. Likewise, reserves can be decumulated when inflation shows signs of picking up - an indication that people have shifted from financial assets (money) to real assets. Export taxation, which was reintroduced in 1994 on coffee as a stabilization measure, could have a relatively high opportunity cost in terms of foregone private investment. In order to manage booms in the future, it is important to ascertain how the private sector in Uganda responds to windfall income. If the propensity to save is shown to be high in 1994-96, future stabilization may not require taxation apart from the central bank's intervention to accumulate and decumulate reserves. Financial sector reform is, however, important for boom management, since it would allow financial instruments other than money to become more important. 11. Future Borrowing Only on Highly Concessional Terms. Uganda faces a serious debt overhang. The solvency ratio, which is the net present value of debt over exports, based on the December 1994 stock of debt without new commitments, would decline from 450 percent before debt relief to 318 percent if the terms of the February 1995 Paris Club agreement are extended to all bilateral debt and some multilateral debt is prepaid. A country with a solvency ratio of higher than 300 is considered to be severely indebted. Although Uganda's ratio may be overstated because of under reported exports, its high level underlines the importance of further debt relief, rapid export growth, and borrowing on only highly concessional terms. If the debt strategy is fully implemented and export grow accelerates, the solvency ratio will fall below 150 by 2002. Since the prospects for further debt relief are limited, the critical determinants of debt sustainability are the terms of new financing and export growth.  iv Execufive Su B. ACCELERATING GRowTH: INCENTVES, EXPORTS AND INVESTMENT 12. Continue Improving the Incentive Regime. Future growth will, to a large extent, depend on export growth. Trade and foreign exchange reforms since 1987 have resulted in a substantial reduction in the antiexport bias. The effective rate of protection is a useful measure for assessing whether the reduction has been adequate. Using the current tariff structure, protection levels in Uganda turn out to remain quite high with respect to extra regional competition, ranging from well over 200 percent for a number of products sold in the domestic market to negative rates in export sales. On average, the effective rate of protection is around 90 percent in domestic sales and -16 percent in extra regional export sales. As PTA tariffs are lower, most industries are less protected in this market than in the domestic market. The average PTA rate of effective protection is more than 60 percent, however. Duty, excise tax and sales tax exemptions on imported inputs further aggravate these protection rates. Duty drawback schemes are designed to eliminate the negative effective rates of protection on exports. A scheme is available for Ugandan producers, but it needs to be made operational and effective. 13. Despite wide-spread exemptions, it is estimated that 37 percent of the cif value of imports are actually collected as import taxes; petroleum products represent two thirds of all customs duties collected. The ultimate incidence of high taxation of imports is shifted largely to Ugandan exporters, who as price-takers in their markets are unable to pass on these additional costs to consumers, as can those producers selling in the domestic market. Evidence from other countries shows that the share of import taxes being paid by exporters varies from about 50 to 90 percent. The highest incidence was in Colombia which had a similar structure of the economy as Uganda today, with a large share of coffee in total exports. 14. To reduce the antiexport bias the following measures are recommended: (i) reducing the level and dispersion of import taxes; (ii) abolishing the duty, excise and sales tax exemptions granted under the Tariff and Investment Codes, statutory instruments and on an ad hoc basis, and replacing them by low and uniform tariff rates; (iii) improving the operation of the duty drawback scheme and its extension to inputs not directly imported by the exporter in a simple, uniform and transparent manner, and (iv) shifting reliance from import taxes towards VAT and direct taxes during the next decade. 15. Export and Investment Response. The low level of private investment and the apparent lack of interest in export activities are worrying. Aggregate investment as a share of GDP has been lower in the 1990s than in the latter part of the 1980s. Furthermore, private investment has concentrated on import-substituting activities. According to a recent survey of a large number of domestic firms, only 8 percent of these firms' output was exported in 1995, mainly to regional markets, compared to 7 percent in 1991. However, there is also evidence of a distinct increase in nontraditional exports during the past few years. The remaining antiexport bias in the economy can go a long way in explaining the sluggish export response, magnified by the appreciating shilling in 1993-94.  Executve Summary v 16. Despite the sluggish investment response, there are some positive factors which may be able to improve the present trend. According to a 1993 survey of actual and potential foreign investors, for example, reform of the regulatory and incentive environment has made Uganda more attractive to investors than many other African countries. Nonetheless, the risk of policy reversal, political instability, and lack of infrastructure in power and telecommunications were perceived as major deterrents. Compared with Kenya, Uganda's greatest disadvantage was perceived to be in the labor market. Its shortage of skilled workers and management capacity reflects past neglect of education and the exodus of skilled labor. This calls for accelerating human resource development as a long-term solution. In the short term this process can be assisted by educated Ugandans returning from abroad and by on-the-job training of the work force. 17. The limits to attracting foreign investment-apart from returning Asians who have been allowed to repossess their expropriated properties-makes domestic private investment all the more important. Domestic firms see the constraints to their future operation and growth as different than those cited by their foreign counterparts. Domestic firms feel that their most severe obstacle is high taxation followed by the cost of and access to finance. The banking system-both commercial and investment banks-is only equipped to lend very small amounts for investment. The culture of nonrepayment is well- rooted, and the judiciary does not regularly permit lenders to foreclose on collateral. Loans are like equity in that they carry a high risk and are not recoverable. Ugandan firms report that 70 percent of their capital is self-financed. Hence, the economy needs to generate high private savings and profits in order to get investment rates up. In the next two years this should happen, to an extent, due to the coffee boom, although the investments of farmers might not be easily detected in the national accounts. 18. Support Nontraditional Agricultural Exports. Traditional cash crops are still the mainstay of Uganda's exports and revival of these industries has been a significant element in Government's effort to increase export revenue in the short termn. In the absence of investment in industrial exports, future growth would depend on nontraditional agricultural exports (NTAE). The prospects of future growth in the NTAE are good. Most important is the regional market for low-value staples, such as maize and beans, although the regional markets are volatile due to weather conditions and political uncertainty. Rapid growth is also expected in fish products and cut flowers. Export revenue from NTAE is anticipated to more than double between 1994 and 1998 to at least US$170 million by the latter year, provided product quality and farm-level and marketing efficiency can be increased. Expansion is also expected in pyrethrum, fresh fruits, vegetables and spices. During the past three years the total investment in nontraditional agribusiness is estimated at US$30 million which is still small compared to overall investment in the economy. Almost half of this investment is in fish processing. Of the total export revenue from non-traditional agriculture in 1993 (US$56 million), 56 percent accrued to farmers and fishermen, many of whom are poor. Maize and beans accounted for 78 percent of the all NTAE receipts by primary producers, while fishing was 7 percent and sesame 6 percent. Cut flowers represent only 0.5 percent of the total earnings of farmers from NTAE.  vi Executive Summary 19. Several policy measures to promote NTAE are suggested. First, measures to reduce the antiexport bias will have a positive impact on NTAE. Second, present land policies which adversely affect foreign investment in land-intensive activities should be reviewed. Third, a fisheries subsector analysis is urgently needed as existing and planned investment in the processing capacity, when in full use, would result in substantial overfishing. Fourth, there is an urgent need to improve handling facilities for fish and air cargo, to invest in the maintenance and construction of rural roads, to make distribution of improved planting material more effective and to strengthen efforts in export promotion, such as dissemination of market information, match-making between buyers and sellers, and improving product quality. C. RURAL INFRASTRUCTURE AND HUMAN RESOURCE DEVELOPMENT 20. Invest in Rural Infrastructure. Evidence from East and Southeast Asia suggests that provision of rural infrastructure has had a significant positive impact on growth and poverty reduction through increased agricultural output, productivity and development of off-farm activities in rural areas. As labor-intensive economic growth is a necessary condition for poverty reduction in Uganda as well, these lessons are useful for formulating future policies to accelerate growth and reduce poverty. 21. Market-determined incentives for agriculture and nonfarm activities are found to be necessary to induce a supply response, but they are not sufficient to maximize that response. Governments have a major role in the development of infrastructure, without which growth will not take off. Empirical evidence also shows that higher agroclimatic potential and natural resource endowments are associated with both a higher level of infrastructure investment and a stronger development response to additional infrastructure. To maximize the economic benefit, investment in infrastructure should be directed to areas with significant growth potential. 22. Experience from East and Southeast Asia also suggests that a coordinated package of rural infrastructure-roads, telecommunications, electrification, water supply and banking facilities-is vital for stimulating rural nonfarm activities such as agroprocessing, commercial enterprises to produce farm inputs, basic consumer goods and services. One of the most critical of all rural and production-related infrastructure is the rural road network. Rural roads are typically public goods best provided by the government but their construction and maintenance can be contracted out to the private sector. It is important that local people have a voice in making road investment decisions. In Asia decentralization of road investments and maintenance has resulted in increased utilization of local resources, better supervision of construction work and improved maintenance. In Uganda maintenance of the existing rural road network has been a major problem. Currently the responsibility for maintenance is being transferred from central to local government, which, hopefully, over time will improve the condition of these roads. 23. Good infrastructure can serve to attract financial infrastructure, while credit availability has a strong positive impact on off-farm activities and employment. As  Executive Summary vii indicated above, the financial sector in Uganda is currently undergoing a major restructuring program, including privatization of UCB. This may lead to a closure a large number of rural branches. Recognizing the importance of financial services to rural development, the Government has decided to carry out a study on the rural finance requirements immediately when the status of the branch network following privatization is known. The objective of the study is to determine a minimum set of locations where financial services should be available; institutional arrangements appropriate in providing these services, and whether a subsidy or an incentive scheme would be necessary to ensure that the minimum coverage of service will be available. 24. The poor derive indirect benefits from rural infrastructure to the extent it stimulates economic activity and increases the demand for local labor. To improve their direct access requires either reducing the cost of infrastructure (appropriate standards, low-cost and labor-intensive technology), or reducing the cost of using the infrastructure (low-cost transport services, for example). The poorest areas are in need of targeted investment in human capital and rural infrastructure to reduce hardcore poverty. 25. Increase Investment in Human Capital. Currently, earnings from off-farm employment and nonfarm enterprises contribute a relatively modest share to the income of rural dwellers rising from 12 percent among the poorest, to 27 percent of total earnings of the better-off. There was some progress in education even during the period of civil strife and economic mismanagement. Enrollment figures have increased. Figures from the 1992/93 Integrated Household Survey, which also include the private schools, suggest relatively high rates of gross enrollment, including primary gross enrollment as high as 91 percent (99 for males, 83 for females). However, these figures include an unknown proportion of older students and repeaters and hence the average attainment of children in primary education may be much less than they suggest. The figures also suggest that drop- out rates are high and there is evidence that they have increased over time. Of the primary cohort enrolled in 1986, 70 percent dropped out by P7 (only 10 percent in 1975). There is a significant gap between male and female enrollment. The paramount need is to address the quality of teachers and the availability of books. Communities are often more willing and able to pay for structures. 26. Nonetheless, the educational attainment of today's adult population in Uganda remains dismal. Combined with a poor health status, it is a serious hindrance for growth and poverty reduction. For instance, as many as 43 percent of those in the bottom expenditure quartile report having completed no level of formal schooling. Although literacy programs have not been proven to be great successes and strong support to primary education is considered the best policy to combat illiteracy, the Government should consider measures to improve adult literacy in the short term. 27. Health indicators in Uganda remain very poor. While Uganda compared well to other Sub-Saharan African countries in the 1960s, this is no longer the case. Economic decline certainly played a major part but improvement in some aspects of health are achievable at low cost and can be pursued now. Countries have achieved transformations  viii Executive Summary in life expectancy even when incomes were low and not growing particularly fast. Adult mortality is currently very high in Uganda and likely to increase for some time because of the high rates of HIV infection. Other major adult killers include malaria and tuberculosis, both of which are likely to be on the increase. Although curative treatment for the latter two can be effective, the poor are less able to get access to adequate treatment. Therefore, it is crucial to develop a cost-effective system of rural clinics. Some recent work has found that children who are malnourished are much more likely to have mothers who are also malnourished than children who are adequately nourished. This suggests that nutritional and health problems in children reflect a more pervasive problem in the household. 28. An analysis using the 1992/93 Integrated Household Survey data confirms the overwhelming importance of female education in reducing fertility and child mortality (203 per 1,000 births nationally), and also shows that measures of mothers' beliefs about health are independently important. In general, female education may raise incomes and increase women's bargaining power within the household, but the evidence suggests that its effects on mothers' understanding about health are the most important channel. In particular, it is instrumental in reducing the population growth rate. Uganda is characterized by relatively high rates of stunting among children (over 40 percent in the two lowest expenditure quartile), but low levels of wasting (around 7 percent), which points to chronic problems of nutrition in early childhood. 29. Fiscal data indicate a significant increase in the shares of actual spending going to social sectors, particularly education during the adjustment period. Actual spending by the Ministry of Education stood at 18 percent of the total recurrent expenditure in 1992/93. Raising salaries is a necessary condition for improved quality of social services. However, it is not a sufficient condition. Most observers agree that the ethos of public service has been damaged by the prolonged period of decline and both ethical and professional standards will need to be restored. 30. The public sector has a crucial role to play in both health and education. The volume of public and donor resources provided to these sectors should continue to rise. The AIDS epidemic increases drastically the need for palliative care and also poses an enormous challenge to preventive medicine and education. For this reason Uganda should aim at a higher share of health expenditure than the typical developing country. While the progress made so far is encouraging, the share of health in the recurrent budget should be well above 10 percent, which is considered reasonable for comparable countries. The balance of public resources should move further in favor of the primary sector, particularly in health. Tertiary medical care should be publicly supported only where the referral system is effective, so that the majority of the population has access to it when needed. 31. User charges in both health and education are currently under discussion. In health, the Government's White Paper advocates the introduction of user charges, but the current policy is to leave the decision to the districts. There is a strong economic case for subsidizing health care and education in Uganda. However, public resources are extremely constrained. Hence for health, the decentralization of the decision about user charges to  Executive Summary ix the local level is appropriate. But user fees will only work if they are controlled by the local community and can be seen to improve the quality of services. Even then, too much should not be expected; user fees cannot replace public support. In education, targeting subsidies to vulnerable children in deprived areas is currently being considered. The government is also planning to target P4-P7 to reduce the number of drop-outs. 32. Ensuring the quality of social services offered by the private sector is an important government responsibility. Quality control can be achieved in the education sector by a well-administered examination system. In health, the limited information available to patients provides a case for giving priority to the importation of cheaper generic drugs. The most promising avenue for stopping the illicit diversion of public resources seems to be the active involvement of the district health committees. The authorities are acknowledging the role that can be played by traditional healers and seeking to educate and integrate them into the health system.   1 MACROECONOMIC PERFORMANCE AND THE ROAD AHEAD 1.1 With a per capita income of about US$220, Uganda is one of the poorest countries in the world. Its weak economy and its poor social indicators are the legacy of nearly 15 years of political turmoil and economic decline. Since 1987 the Government has been implementing an economic reform program supported by a large number of donors. The program aims to promote prudent fiscal and monetary management, improve incentives to the private sector, reform the regulatory framework, and develop human capital through investment in education, health and other social services. Economic recovery and stabilization have been successful; hard-won macroeconomic stability has been maintained for the past three years. The stability is precarious, however; continuation of good policies and further improvement are therefore required. 1.2 Improving macroeconomic policies and sustaining stability are, of course, only part of the larger development effort to build institutions and infrastructure and implement social policies needed for broad-based growth and poverty reduction. But experience from other countries shows that a stable macroeconomy is necessary to attract private investment and sustain the high growth rate required for rapid poverty reduction. To reduce fragility, macroeconomic policy in Uganda, must in the next few years: * Continue to maintain tight fiscal control. * Increase public revenue, including stepping up the tax reform. * Phase-out gradually import support from recurrent public finance. * Increase public and private saving. * Reform the financial sector. * Manage the coffee boom to maintain low inflation and a stable exchange rate and to accommodate the private sector's response to the boom. * Manage external debt by seeking further relief and by borrowing only at highly concessional rates. A. GROWTH, INVESTMENT AND SAVINGS 1.3 Growth. Investment is one of the most important elements of the growth process. Until recently Uganda's main sources of growth were recovering domestic consumption and, to an extent, regional demand and increasing capacity and land utilization. But the scope for expansion without a strong private investment response is likely to be limited. 1.4 Growth has picked up since 1987 but remains volatile and too modest, given the population growth rate, to substantially improve the living standards of most Ugandans in the near future. During 1993/94, real GDP growth slowed to about 5.4 percent compared  2 Macroeconomic Performance and the Road.Ahead with 8.5 percent in 1992/93 mainly reflecting lower agricultural growth.' GDP grew by an average of 5.8 percent per year from 1986/87 to 1993/94, a gain of about 2.9 percent per capita per year. Reflecting the present coffee boom, the preliminary estimate for GDP growth in 1994/95 is as high as 10 percent. However, real GDP is still well below the level enjoyed by Ugandans 25 years ago. 1.5 Agriculture, which makes up close to 50 percent of GDP, dominates the growth figures, employs more than 80 percent of the labor force and accounts for virtually all exports (Table 1.1). The industrial sector, which includes agro-based industries, such as coffee, cotton, sugar, food processing, tobacco, and beverages, as well as manufacturing Figure 1.1: PROGRESS IN ECONOMIC RECOVERY AND STABILIZATION GDP at MP Growth Rate Inflation 10 250 6 '~~~~~~~~~~~00 2 1 X o 100 0 50 -2 GDP . Agriculture Bureau/Official Rate Premium Net International Reserves 450 3.0 400 2.5 350 300 2.0 250 I L_1. J200I 150 I . 50I ~~~~~~~~~~~~~0.5 0 0.0 I 0 ~~~~~~~~~~~~~~~~0 E E o g t w x a g *co 0 9 Source: Statistics Department, MFEP, BOU, IMF and staff estimates. Note: Data are reported in fiscal years, MP refers to narket prices. National Accounts data are used based on the January 1995 revision by the Statistics Department, Ministry of Finance and Economic Planning.  Macroeconomic Perfornance and the RoadAhead 3 industries, produces mainly consumer goods for the domestic market and has been growing rapidly-between 7 and 19 percent a year since 1986/87-but from a very low base. The share of industry in GDP is around 13 percent. At about one third of GDP, the share of the service sector has not changed much over time. The nonmonetized economy, which is estimated to be around 30 percent of GDP, has grown slower than the monetized economy. 1.6 Investment. After the restoration of peace in 1986 investment recovered rapidly through 1989/90, driven by the rehabilitation of infrastructure and productive capacity. But investment as a share of GDP (at 1991 market prices) stagnated and then declined between 1991/92 and 1993/94 (Figure 1.2). Investment averaged around 20 percent of Figure 1.2: KEY ECONOMIC INDICATORS Fiscal Accounts Current Amcount Deficit 10 - Domestic Revenue 5 ~~~~~~~~~~~~~0 Afer Grants 0 -2 V -4 9Z -6 '~-8 Before Grants -lo ~~~~~~~~~~~-10I -0 Fiscal Deficit-2 before Grants -15- -14 1 a co a 9 a a co 9 9 a Savings and Investment Lending and Deposit Rates Lending Rates 16 40 14 Investment 35 12 30 1 0 - 6 25 8 20 Deposit Rates 6 4 Domestic Savings A ~~~~~~10 E2 -A 10 02 0 co V Source: Statistics Department, MFEP, BOU, 1M and staff estimates. Note: Data are reported in fiscal years, MP refers to market prices.  4 Macroeconomic Performance and the Road Ahead Table 1.1: KEY ECONOMIC INDICATORS (National Accounts) In Fiscal Years Indicator 1986 1990 1991 1992 1993 1994 (As % of GDP at current market prices) Gross domestic product (GDP) 100.0 100.0 100.0 100.0 100.0 100.0 Agriculture 54.4 53.0 49.0 47.8 47.7 45.4 Industry " 9.7 10.8 12.6 13.2 12.8 13.3 Services 29.9 30.3 32.4 33.4 33.4 33.9 Total consumption 2/ 94.5 99.0 100.3 100.5 101.2 98.9 Gross domestic investment 3/ 7.7 11.9 14.8 15.2 14.1 12.9 Public 2.0 4.1 5.7 7.0 7.5 7.2 Private (includes changes in stocks) 5.7 7.8 9.1 8.2 6.6 5.7 Exports (GNFS) 4' 11.3 6.0 6.1 7.2 5.5 6.1 Imports (GNFS) 4/ 13.6 16.9 21.1 22.9 20.8 17.9 Gross domestic savings 5.5 1.0 -0.3 -0.5 -1.2 1.1 (As % of GDP at constant 1991 prices) Gross domestic investment 3/ 12.5 15.7 16.2 14.6 14.0 14.4 Public 3.5 5.6 6.2 6.8 7.4 8.2 Private 9.0 10.1 10.0 7.8 6.6 6.2 (Real annual growth rates) GDP at market prices -0.3 6.1 4.7 3.2 8.5 5.4 Gross domestic income -1.7 3.4 3.7 2.4 8.6 4.4 Total consumption 2.0 5.9 3.3 4.6 4.9 3.1 Gross domestic investment 1.8 3.3 8.1 -6.2 4.0 7.8 "/ GDP components are estimated at factor cost; the discrepancy is attributable to indirect taxes. 21 Includes statistical discrepancy. 3' The Statistics Department has not yet published the public/private breakdown of gross domestic investment. Public investment is therefore estimated from the development budget. The figures may overestimate the share of public investment in total investment. 4' Goods and nonfactor services. Source: Statistics Department, MFEP. GDP in all of Africa in 1987-94, while the average in Uganda was around 15 percent. Investment in structures has increased, but the share of equipment and machinery has fallen precipitously since 1987/88. In short, Uganda has experienced a period of growth with only modest investment, possibly because the economy started far below the previous peak. The preliminary estimate for 1994/95 shows, however, a substantial increase in investment both in structures and in equipment and machinery.  Macroeconomic Performance and the RoadAhead 5 1.7 Saving is important to the growth process as excess investment over domestic saving can create inflationary pressure and aggravate balance-of-payments deficits. While increasing domestic private and public saving is extremely important, raising foreign savings can effectively jump-start investment in Uganda where both public and private assets were badly depleted during the extended period of economic mismanagement. Uganda's gross domestic savings stood at 5.5 percent of GDP in 1985/86. Since then domestic savings have fallen to between -1.2 and 1.1 percent (Figure 1.2 and Table 1.1). Preliminary data show an increase in domestic saving in 1994/95. As domestic saving has been low, Uganda has had to rely on foreign savings to finance domestic investment. In 1985/86 private and official transfers were only 2.2 percent of GDP, while in 1993/94 their share was 13 percent. 1.8 Structural imbalances in the economy must be further reduced to ensure that growth can be sustained (Figure 1.2). It is important to note, however, that the external and internal balances of the mid-1980s do not necessarily reflect good policies. Rather they indicate that almost no external source was willing to finance Uganda's budgets or imports at that time. Today the need to continue reform policies, on the one hand, and alleviate widespread poverty, on the other, warrant the use of foreign transfers to speed up economic recovery and development. These transfers inevitably produce fiscal and current account gaps, which are means of attaining higher growth and reducing poverty. However, these gaps cannot persist forever. The dependency of the current budget on counterpart funds generated by balance-of-payments support is, therefore, expected to be lessened by increasing domestic revenue. With a very small formal sector, increasing public revenue is a major challenge. Box 1.1: The Impact of AIDS on Growth Prospects for accelerating growth are likely to be adversely affected by the AIDS epidemic. A detailed analysis of this problem is beyond the scope of this report, but a few estimates of its impact on the economy are available. First, the World Health Organization projects that the number of HIV- infected people could increase to more than 1.9 million by 1998. It also projects that in 1993-98, 565,000 adults and 250,000 children will die from AIDS. Second, AIDS is not an illness that afflicts the poor only: HIV-prevalence is found to be higher in urban areas and among more-educated occupational groups in Uganda. Instead of the urban labor force growing from 400,000 to 1.1 million by 2010, it is estimated to reach only 740,000 because of deaths among workers between the ages of 35 and 50. Studies on the economic impact of AIDS are less conclusive. Nonetheless, private savings and investment, labor supply, and hence growth are likely to be adversely affected by the epidemic. In the hard-hit areas less land is under cultivation, farmers have shifted to less labor-intensive crops, interest in long-term planning and investments has fallen. Health expenditures are also likely to go up, but as resources for expansion are limited, the time required to care for sick family members may further reduce labor input and hence growth.  6 Macroeconomic Performance and the RoadAhead B. FISCAL AND MONETARY POLICY 1.9 The fiscal deficit increased from 4.2 percent of GDP in 1985/86 to 14.1 percent in 1991/92 and 11.6 percent in 1993/94 (Table 1.2). The Government has refrained from borrowing domestically since 1989/90, financing its expenditures with domestic revenue and external aid. (However, this policy was temporarily reversed in 1991/92.). Fiscal discipline has been the main contributor to price stability achieved during the past few years. 1.10 Public Revenue. One of the most critical issues for long-term macroeconomic stability is public revenue mobilization. Despite doubling the share of tax revenue in GDP in the early 1990s, it remains at less than 10 percent, and is well below the Sub-Saharan average of 18 percent. Public expenditure in Uganda was 18 percent of GDP in 1993/94, which is also below the Sub-Saharan average of 28 percent. Counterpart funds generated by quick-disbursing aid were worth U Sh 244 billion in the 1993/94 budget and covered more than 40 percent of total nonproject outflows - current expenditure, debt service, and settlement of arrears - while 90 percent of the development budget was externally funded. It is estimated that in 1994/95 counterpart funds were more than 30 percent of the total nondevelopmental outflow, while 84 percent of public investment is donor-funded. At the same time, the Government accumulated deposits vis-a-vis the domestic banking sector worth U Sh 27 billion in 1993/94. In 1994/95 the estimated fiscal savings are U Sh 99 billion. 1.11 In the long term it is important to reduce the dependence of Uganda's public sector budgets on external finance as such financing may not be permanently available and is inherently uncertain as donor resources and preferences change over time. Also, different donor requirements may limit the flexibility of public expenditure and cause additional costs or delays. Many inside and outside Uganda argue that aid creates a dependency that adversely affects both private behavior and public choice and may result in less than optimal economic performance and growth. All of these arguments call for increased contributions from domestic taxation to finance public spending. 1.12 At the same time Uganda can expect to benefit from continued aid inflows in the future because of its good economic performance, low level of per capita income, poor social indicators, low stock of productive assets, and high external debt service. Higher domestic revenue and maintenance of the current level of aid in real terms imply that the Government's share of GDP will go up unless external assistance increasingly finances private sector budgets in Uganda in the first round of their use. However, it may be difficult for multilateral and bilateral donors to directly finance the private sector as their operations have traditionally been geared to dealing with governments. 1.13 The revenue effort in Uganda is low for several reasons. First, the transition from reliance on subsistence and informal economic activity, to which the economy retreated during the long period of civil strife, has been relatively slow. Second, income levels are low and direct taxation of the large agricultural sector is limited. At the same time the  Macroeconomic Performance and the RoadAhead 7 Table 1.2: KEY ECONOMIC INDICATORS (Public Finance) In Fiscal Years Indicator 1986 1990 1991 1992 1993 1994 (as % of GDP at current market prices) Current revenues 6.4 6.8 7.4 6.7 7.1 8.2 Cwrent expenditures 7.9 7.1 7.1 11.6 8.2 8.8 Capital expenditures 2.7 5.5 7.3 9.0 10.0 9.5 Overall Deficit -4.2 -6.5 -7.8 -14.1 -12.1 -11.6 Budgetary Grants 1.1 1.5 3.8 7.0 7.9 6.5 Foreign borrowing, net 1.0 6.6 3.5 5.1 5.1 5.8 Domestic borrowing 2.1 -1.6 0.5 2.0 -0.6 -0.6 Source: MFEP. industrial and service sectors are small and hence formal employment is low. Third, revenue leakages are substantial because of exemptions, corruption, smuggling, and a virtual collapse of information and accounting systems. Fourth, Uganda has a poor tax paying culture, which will take time to change. As a result, taxes on international trade still contribute well over 50 percent of total revenue. The establishment of the Uganda Revenue Authority (URA) in 1991 introduced better incentives and facilities and thus improved tax administration and collection rates. But Uganda still has a long way to go to achieve the Sub-Saharan average in its revenue effort. 1.14 Tax Reform. Since 1987, the Government has introduced various measures to reform the tax system. The reforms have had several objectives. First, there is an attempt to widen the tax base by both increasing the number of taxpayers and by reducing widespread exemptions. By March 1995, the LURA had issued around 350,000 taxpayer identification numbers to individuals and more than 50,000 to businesses. Second, the reform aims to achieve better compliance through lower rates. In particular, the corporate tax rate has been reduced from 50 to 30 percent. Third, the reform aims at reducing reliance on taxation of foreign trade and move toward value added and direct taxes. In Ghana, for example, a VAT was recently introduced which rapidly increased inflation as many more firms than those eligible began to charge the VAT. This highlights the importance of adequate preparatory work prior to implementation of VAT. Relatively little has been achieved in the area of direct taxes in Uganda. The income tax share of total taxes has increased from 10 percent in 1988/89 to 14 percent in 1994/95. Still, 14 percent is a much smaller share than that in neighboring countries (although data problems in Tanzania and Ethiopia may bias the comparison). However, the implementation of VAT in Uganda, which is expected to become effective in July 1996, as well as universal income taxation requires further improvements in tax administration and education of the business community and the general public to achieve taxpayer compliance.  8 Macroeconomic Performance and the RoadAhead 1.15 Fourth, the reform attempts to reduce tax exemptions. Exemptions from duties and sales and excise taxes are granted on the basis of three different categories: the Second Schedule of the Tariff Code (including diplomatic), the Investment Code, and statutory instruments. The latter is the most important source of revenue loss. Reductions in the number of tax exemptions have not followed a consistent path, however. The duty payable on all industrial raw materials, for example, was suspended in 1987, only to be reintroduced in 1990 at the rate of 10 percent. In 1992 the import duty on raw materials was again abolished, only to be reimposed in the following year. In 1994 remission of the 10 percent duty was allowed for most raw materials not available locally. As a result almost no import duties (or sales taxes) are collected on imported inputs unless a domestic industry produces the good. In addition, exemptions are granted on an ad hoc basis. The Investment Code (1991) allows exemptions from import duties and sales taxes for imported machinery, equipment, and construction materials for practically all investments. All qualifying investors are exempt from the corporate tax, withholding tax, and dividend tax for three to six years. 1.16 Data on revenue by beneficiaries as a result of exemptions from import duties and sales taxes on non-oil imports are available for the first quarter of 1992/93.2 At an annualized rate the revenue loss is estimated to be 120 percent of the total revenue raised from import duties and sales taxes on non-oil imports. The largest revenue loss, 41 percent of the total revenue foregone, come from exemptions granted to foreign NGOs. This loss was followed by exemptions to donor-funded government projects (33 percent) and industry (22 percent). Of the total public revenue raised during the same year the estimated loss because of exemptions was 36 percent. In the case of donor-funded projects, the revenue loss is of course not real as the Government is usually the recipient of aid but the figure for foreign NGOs seems too high relative to other beneficiaries, which could be an indication of misuse of these exemptions. 1.17 In its 1995/96 budget the government announced a plan to reduce duty and tax exemptions across the board. It introduced a new 5 percent duty rate for raw materials. In addition, a number of changes to the Investment Code were announced which will reduce exemptions, and make the remaining ones more equitable. These are important steps forward in an effort to increase public revenue and improve the incentive regime. 1.18 Following the introduction of various tax measures over a number of years, an assessment of the tax system is necessary in order to chart out future reforns. Several issues require particular attention. As stated in the 1995/96 budget speech, the system of large-scale duty, sales tax, and excise exemption must be dismantled and replaced by low, uniform rates. Measures to broaden the tax base should be continued, including improving local revenue effort. In addition, the planning horizon of tax policy must be extended, at least to the medium term, and the reliance on foreign trade taxes ultimately shifted toward 2 For more recent information, which is qualitatively sirnilar to the data presented here, see Short, J. (1995), Assistance with Project Design, Private Sector Development Review of the Tax and Incentive Structure, ODA  Macroeconomic Performance and the RoadA head 9 a VAT and direct taxation. Removing most exemptions will improve the fiscal position, reduce abuse and the antiexport bias, and improve resource allocation. It is paramount that the revision of the Investment Code be completed as soon as possible. Cross-country evidence suggests that low rates without exemptions can do more to promote investment than the current scheme. Tax reform would benefit from a clear set of principles and objectives, preventing various interest groups from affecting tax policy in a stop-go manner. Expansion of the tax base is vital as raising tax rates would probably discourage private investment, which is primarily self-financed. The domestic revenue effort can, therefore, increase only gradually. Targeted annual improvement in public revenue requires a concerted effort from those responsible for setting and implementing tax policy. 1.19 Fiscal Decentralization. The central government's share in total government expenditure in Uganda is relatively high by international standards: 76 percent in 1992/93. The share of revenues collected by the center is even higher, only 5 percent of public expenditure were covered by local revenue. In 1990/91 only about one quarter of local revenue was spent directly on services. The rest went to administrative costs. Although revenue collection in a number of districts has been improving in the past few years, large annual fluctuations occur, indicating either that the capacity for resource mobilization varies or that the existing capacity is not exploited effectively. Any major improvement in local revenue effort requires that taxpayers perceive that service delivery has improved dramatically. Substantial improvement in the delivery of primary education could, for example, cause people to respect local government and lead to an improved local revenue effort. Donors can have a useful role in supporting improved service delivery which in turn will improve the local tax effort. 1.20 If service delivery is decentralized, revenue-raising responsibilities must be decentralized as well. Direct taxes, such as personal income and corporate taxes and taxes on wealth, are better administered by the central government. Property, general sales, and excise taxes and some natural resource taxes are suitable candidates for decentralization. Local authorities could also collect a centrally designed VAT. Finally, user charges for public services are a suitable local source of finance. Borrowing to cover local government operating deficits should not be permitted, but there should eventually be a mechanism to assist local government borrowing for capital projects. The broad guidelines for future assessment and collection of revenue at the local level are expected to continue to be determined by the center, mainly through the Local Government Finance Commission, yet to be established. 1.21 More generally, the inter-governmental fiscal arrangements that must be worked out in order to decentralize decision making and public service delivery can be classified according to: the extent to which services will be provided locally; the division of revenue- raising powers between central and local governments, including tax sharing and harmonization; the system of transfers and loan finance to bridge the gap between locally raised revenue and expenditures; the administrative, budgeting and monitoring framework; and local capacity building. So far the expenditure side and, to some extent, capacity  10 AMacroeconomic Performance and the RoadAhead building have received the most attention (Box 1.2). The Box 1.2: Fiscal Decentralization possibility of transferring the center's taxing decisions to The gradual process of fiscal decentralization in districts has not yet been Uganda began in 1993/94 when thirteen districts obtained a addressed' 3vote on the central government budget. They were, however, under the control of the line ministries during the first year. In 1994/95 an additional fourteen districts were 1.22 The ongoing decentraliza- permitted to have a vote, and the initial thirteen pilot tion process has at least two direct districts obtained a block grant. In 1995/96 the remaining links to fiscal policy and twelve districts "ill receive a vote, and the fourteen macroeconomnic stability. First, districts will receive a block grant. By 1996/97 all districts fiscal control may be harder to will be in the block grant system. Block grants are based on past expenditure levels. But this method may not be the maintain in the transition pefiod, best way to allocate funds in the long run. Hence, an while responsibilities within the equitable and transparent grant system based on the new decentralized administrative district's needs must be designed. system are being worked out in The most important services being transferred to practice. Second, decentralizing of the districts are primary education, primary health care, peracice. delivery can improvelocal feeder roads, and agricultural extension. Some local governments have been delegated responsibility for tax effort by increasing services, such as hospitals and secondary schools for which accountability and improving the central government provides additional funding. In service delivery. At present local practice only the recurent budget has been decentralized. capacity is extremely limited, l The development budget, which is funded mostly by caait is exrml li .itd external sources, is expected to remain with the central however, but in the long-term egovernament untir 1997/98 decentralization holds promise for g rural development. As the vast majority of the poor in Uganda live in rural areas, decentralization has a direct link to poverty reduction. 1.23 Monetary Policy. The key monetary aggregates have grown rapidly in recent years: broad money (M2) at an average annual rate of more than 40 percent since 1991/92, while the base money growth has varied from 80 percent to below 10 percent. Base money is currency in circulation and commercial banks' reserves at the Bank of Uganda, while broad money is currency and demand, savings and time deposits. The prime source of monetary growth has changed from increases in domestic credit to increases in net foreign assets. The ratio of broad money supply to GDP has almost doubled rising from 5 percent in 1991 to about 9 percent today. This level is still very low by international standards. 3 A number of local taxes are collected throughout Uganda. The graduated personal tax, for example, has wider coverage than most centrally collected taxes; hence it has potential for widening the tax base. Currently, the graduated personal tax rates are low. The infrastructure of the local tax administration must be built up working through the district Resistance Council (RC5) level and down the ladder to local authority. The base of the graduated personal tax could be strengthened toward a permanent income or wealth tax that covers fertile land and property as well. In urban areas assessment rates - property taxes - are another potential source of revenue enhancement since the land component of property is not being taxed at all.  Macroeconomic Performance and the RoadAhead 11 Box 1.3: Improving Public Sector Management Like a number of other countries in Sub-Saharan Africa, Uganda is presently redefining the role of Government, by dismantling controls and reforming institutions, such as the civil service, the financial sector, public enterprises and so on. Civil service reform has been relatively successful: the number of civil servants on the central government payroll has fallen from 320,000 to 150,000. Also, ministries and other government agencies have been restructured. A number of challenges still remain: monetizing in-kind benefits and ending the government provision of housing and transport to civil servants; phasing out salary "top-ups" relating to donor projects and ensuring that a "living wage" is achieved, which may require further downsizing; reviewing the structures and functions of ministries and agencies as the role of Government continues to be redefined; and decentralizing the administration. Rationalization of the public investment program, which has reduced the number of development projects from over 800 to around 160, is expected to be completed by the end of 1995/96. The adoption of a three-year budget framework should further improve planning of public expenditure. While marketing monopolies have been removed, the Government of Uganda continues to have a large parastatal sector which contributes 7-8 percent of GDP and formal employment but drains public resources much more than its share in production would warrant. Direct subsidies and foregone revenue from indirect subsidies to state enterprises, such as tax exemptions and preferential access to credit and guarantees, are estimated at US$180 million a year - about three times the government contribution to the development budget. Clearly this has to change. Unfortunately, the public enterprise reform and divestiture program have suffered from design problems and slow progress. The Government has overhauled its strategy recently to stress: effective financial control of all parastatals; faster speed of privatization; predictability of the divestiture exercise; and consensus-building among Ugandans on privatization. The reform is yet to produce the expected results but recent efforts are promising in view of achieving a much leaner parastatal sector and more efficient provision of services. 1.24 Since 1992/93 credit and fiscal management have improved substantially. Controls over domestic bank lending, apart from prudential controls, have been removed. Financial institutions are no longer obliged to lend to the Government; government borrowing takes the form of Treasury Bill auctions in which banks and nonbanks may take part. At present, Treasury Bills are being sold for purely liquidity management purposes. The Bank of Uganda has stopped direct loans to public enterprises, as well as excessive overdraft facilities for commercial banks. In addition, interest rates have been fully liberalized. Inflation control has been one of the main achievements (see Figure 1.1), as annual average inflation declined from 42 percent in 1991/92, to about 5 percent in early 1995. At the end of May 1995 inflation was 3 percent on an end-period basis. 1.25 Base money is the central bank's monetary liability. The main adjustments to base money have arisen from changes in net lending to the Government. Base money management is made more effective in Uganda because government expenditure is strictly limited by the availability of foreign aid and tax revenue, without domestic borrowing. Expenditure releases are also adjusted to assist monetary management bearing in mind monthly variations in price and exchange rate data and other macroeconomic indicators. Similarly, because of instability of the money multiplier, the central bank uses a broad range of economic indicators to guide its monetary policy. The central bank is less  12 Macroeconomic Performance and the RoadAhead Table 1.3: KEY ECONOMIC INDICATORS (Monetary Indicators) In Fiscal Years Indicator 1986 1990 1991 1992 1993 1994 Growth of M2(%) 10 57 47 54 42 33 Growth of Base Money (%) ... ... ... 80 20 43 M2/GDP (%) 10 7 8 8 8 9 Price Indices (1991 = 100) Merchandise exports 4 55 81 123 144 124 Merchandise imports 2 47 78 131 155 147 Merchandise terms of trade 242 117 104 94 93 84 Real interest rates .. 9.5 3.8 -19 24.7 -4.4 Average Annual Inflation (CPI;%) .. 45.4 24.6 42.1 28.4 7.8 GDP deflator 122.9 45.4 47.2 45.9 30.7 6.9 piona fipws, MPEp 91 -day Treasury Bill, end-year basis Source: BOU, Statistics Department, MFEP. willing to use its ability to change commercial banks' statutory reserves as it can have adverse effects on banks' profitability. The current cash reserve ratio is an average of 7.5 percent for demand and time deposits. 1.26 Summarizing, the traditional sources of monetary instability in Uganda, i.e. monetization of fiscal deficit, and excessive overdraft facilities at the central bank for commercial banks have been removed. Uganda is currently well served by a tight fiscal policy which, with ongoing monetary deepening, keeps inflation within single digits. Until instruments of indirect monetary control become more effective, the policy of public expenditure restraint which produces increasing fiscal savings at times when external resources are abundant acts as a powerful force for stabilization and will remain the main instrument for control over the growth of both base and broad money. Also, the Government has no need for Treasury Bill sales to finance its deficit. Interest on Treasury Bills sold with a view to deepening financial markets is an additional fiscal burden. 1.27 The Banking Sector. The prime task in financial market development is to create a solvent, efficient and competitive banking system, which will over the long run require interbank and secondary bill markets for liquidity management and portfolio choice. Uganda's good economic performance in recent years and future development prospects could be undermined by critical deficiencies in the financial system. Overall, the commercial banking system is in a precarious state. More than half of the fifteen commercial banks made losses in 1994 and have a large negative core capital of over U Sh 100 billion. A number of banks are insolvent, including Uganda Commercial Bank. Aggregate nonperforming assets are in excess of 50 percent of total loans (27 percent excluding Uganda Commercial Bank) making much of banking activity nonviable. Banks must adopt more prudent financial discipline. Intermediation costs are high (in excess of  Macroeconomic Performance and the RoadAhead 13 12 percent of interest bearing assets) because of administrative inefficiency and the high share of nonperforming loans. These costs impose a significant burden on borrowers. Finally, the financial position of the Bank of Uganda is untenable because of foreign exchange losses, and losses on past loans to the Government and public enterprises. 1.28 The complexity of these issues, given the institutional capacity, calls for a focused approach. Immediate actions are required on four fronts: privatizing Uganda Commercial Bank, finding a more aggressive approach to deal with distressed private banks, strengthening of the central bank including further restructuring and recapitalization so that it can manage the weaknesses in the banking system, and improving financial discipline. Uganda Commercial Bank will be put up for sale in "as is" condition through a merchant bank. At the same time, to meet the Government's objective of maintaining a minimal level of financial services in the rural areas that are served only by Uganda Commercial Bank, a rural finance study will be initiated to determine how the Government should intervene if the new owners do not want to maintain Uganda Commercial Bank's rural network. Among other actions, the Government must establish and aggressively enforce strict short-term targets for problem banks in key areas, such as capital adequacy, insider lending, and replacement of bank management and, where necessary, close institutions that fail to meet targets. Finally, an efficient deposit protection fund should be established to deal with potential bank closures. At the same time urgent institutional measures must be taken to address the problem of financial discipline, including establishing a credit information bureau and streamlining the judicial system to expedite legal recourse for debt collection. C. EXCHANGE RATE MANAGEMENT AND TERMS OF TRADE SHOCKS 1.29 Since 1987 Uganda has gradually moved from a system in which the central bank allocated foreign currency to a flexible foreign exchange system. The changes in exchange rate management include devaluations (1987-89), expansion of retention schemes for exporters (1988-89), and a real exchange rate peg (1990). An open general licensing scheme and a special import program were used during 1988-90 to allocate donor funds for imports. Nevertheless, the parallel market premium remained at around 100 percent. In 1990 the black market for foreign exchange was legalized by authorizing foreign exchange bureaus to trade in currencies without approval from the central bank. In 1992 a Dutch auction system was introduced for donor funds (the rate is determined by the lowest bid that exhausts the supply of currency in the auction). In November 1993 an interbank market replaced the auction, and all restrictions on international transactions were eliminated. 1.30 Until the end of 1991 the real effective exchange rate (REER) was depreciating strongly (by about 40 percent in 1990-91). It remained more or less stable until mid-1993 and then appreciated by more than 30 percent by June 1994. Since then the REER has depreciated slightly. Initially, after the introduction of the interbank market, the central bank intervened modestly by market smoothing, but since September 1994 the Bank of  14 Macroeconomic Performance and the RoadAhead Uganda has been actively accumulating foreign exchange reserves in response to the coffee boom. 1.31 External Trade and the Balance of Payments. Despite substantial liberalization, the ratio of exports to GDP (at current market prices) declined from 11 percent in 1985/86 to 6 percent in 1993/94, while the share of imports to GDP increased from 14 percent to 18 percent. The decline in the share of exports in GDP can be attributed to the low world price for coffee prior to June 1994, while the persistently low level of exports in GDP is likely to reflect the remaining antiexport bias (analyzed in chapter 2). The value of total merchandise exports was US$254 million in 1993/94 and is expected to rise to US$537 million by 1994/95 (to around 11 percent of GDP), reflecting the rise in the international price for coffee in June 1994 (Table 1.4). The value of imports of goods and nonfactor services stood at US$893 million in 1993/94 but is expected to increase by over 30 percent, to US$1,193 million in 1994/95. The gap between exports and imports has led to a sizable resource balance deficit. This deficit was partly offset by US$304 million of net private transfers in 1993/94. In 1994/95 private transfers are estimated at US$397 million. Table 1.4: KEY ECONOMIC INDICATORS (Balance of Payments) In Fiscal Years Indicator 1986 1990 1991 1992 1993 1994 1995* (USSm) Exports (GNFS) I/ 389 246 199 195 206 333 609 Merchandise (fob) 379 210 176 172 157 254 537 oiw coffee 360 159 127 117 99 172 402 Inports (GNFS) 1/ 446 676 671 582 753 893 1193 Merchandise (fob) 380 584 545 451 573 718 981 Current private transfers 101 78 81 136 241 304 397 Current account balance (excluding grants) 0 -429 -449 -338 -355 -317 -231 (including grants) 31 -276 -187 -132 -96 -67 -8 Overall balance 2.4 -44 -101 -121 -8 110 138 Gross reserves 86 35 50 73 112 219 386 in months of imports (GNFS) 2.3 0.6 0.9 1.5 1.8 2.9 4.0 Current account balance (incl. grants) (As % of GDP at current market prices) 0.08 -6.4% -5.6% -4.5% -2.9% -1.7% -5.7% Real exchange rate (1990=100) IFS (USS/LCU) 21 ... 100 76.7 69.9 72.7 ... * Provisional figures, MFEP I1 GNFS denotes goods and nonfactor services. 21 LCU denotes local curmncy units. An increase in USt/LCU denotes appreciation. Source: BOU and IMF  Macroeconomic Performance and the Road Ahead 15 1.32 In the last three years private transfers have become the most important financing source. Current private transfers capture foreign exchange bureau transactions, which cannot be identified in detail. They are assumed to include the proceeds from unrecorded nontraditional exports, direct foreign investment, transfers from Ugandans living abroad and expatriates living in Uganda, and aid provided by nongovernmental organizations (NGOs). For effective policy making the Government must identify the components of private transfers. For example, the nontraditional export response could turn out to have been stronger than indicated by official export data. 1.33 For the first time since 1986/87 the overall balance of payments showed a surplus of US$110 million in 1993/94. Gross reserves held by the central bank increased from US$219 million in June 1994 (about 2.9 months of imports) to US$386 million in June 1995 (about 4 months of imports). 1.34 Managing the Coffee Boom. The Ugandan economy is vulnerable to commodity booms and busts as its external balance continues to depend heavily on coffee. Proper management of external shocks is vital for macroeconomic stability. Currently, the Ugandan economy is experiencing a positive shock from temporarily high world prices for coffee. Management of this boom is a timely topic, but its importance extends beyond the present situation as booms are likely to occur in the future. Apart from stability, booms and the way they are managed have a direct impact on inivestment. As coffee is a relatively more important source of income for the poor than for the better-off in the main coffee growing areas, boom management is also linked to poverty reduction. 1.35 In order to quantify the magnitude of the boom, a counterfactual must be defined. The international price of coffee for the first half of 1994 and the 1993/94 volume are used. The windfall is estimated using the World Bank (January 1995) price forecasts and assuming an increase of 10 percent in coffee deliveries. The present value of the direct increase in income (the increase attributable to the rise in coffee prices) is estimated to be US$787 million, or 17 percent of GDP at factor cost in 1993/94. Assuming a reasonable GDP multiplier (somewhat below the Sub-Saharan average), the estimated indirect effect on income (resulting from higher output) would be US$315 million, or 7 percent of GDP. The total size of the boom (its net present value) is therefore 24 percent of GDP. Windfall income would thus be 6.6 percent of GDP in 1994/95, 5.7 percent in 1995/96, and 3.8 percent in 1996/97. The boom is expected to end by 1997/98 (windfall income in 1997/98 is estimated to be 0.9 percent of GDP). These figures show that the present boom is not a particularly large external shock in terms of GDP. But it-is more sizable if compared with the monetized economy, which is only 70 percent of GDP. 1.36 Assuming that both the Government and the private sector will increase their consumption only by an amount that is sustainable-that is, by an amount that can be maintained in the future-and assuming (for illustrative purposes) that the rate of return on investment is 10 percent, the Ugandan economy should save up to 70 percent of the windfall. At the onset of the boom these savings are likely to show up as an increase in the  16 Macroeconomic Performance and the RoadAhead demand for financial assets, in practice money and bank deposits. Subsequently, the savings are likely to be invested so that there is an increase in the demand for real assets. Ex ante, it was difficult to foresee whether the Ugandan private sector would prefer to hold shillings or foreign currency in the absence of any other financial assets. But the experience since June 1994 indicates that the private sector has indeed confidence in the shilling. The underlying inflation rate dropped sharply from 10.4 percent in May 1994 to 2.9 percent in September 1994, indicating that people increased their holdings of shillings (as initially there was no major accommodating increase in the money supply). Increased demand for money implies a temporary increase in seigniorage that accrues to the Government (or the central bank). At the same time merchandise imports have increased much more than initially expected. 1.37 Maintaining low inflation and a stable exchange rate are crucial for managing the macroeconomy during a boom. Two distinct forces pressure the exchange rate to appreciate. First, the shilling will appreciate if the private sector increases its real holdings of shillings. The central bank can help prevent this type of appreciation by accumulating reserves and increasing the nominal money supply. Second, the Dutch disease effect may rise, in which the inflow of foreign exchange causes the local currency to appreciate. The effect can be delayed by accumulating reserves, but when the real transfer to the economy occurs, the exchange rate will inevitably be affected because of the increased demand for-and therefore price of-nontradable goods. To avoid inflation, the price of tradable goods must go down, that is, the exchange rate must appreciate. It is difficult, however, to quantify the effect of the coffee windfall on the exchange rate in Uganda, partly because it is not clear which goods are internationally tradable. 1.38 Given the private sector's response to the boom and the objective of avoiding unnecessary currency appreciation, the central bank must accommodate the private sector's increased demand for money by accumulating reserves. The daily exchange rate and the monthly price level are the best available sources of information for implementing this policy. So far this policy has worked well-nominal appreciation between end-June 1994 and March 1995 was only 4 percent, while annual average inflation was less than 5 percent. Likewise, the central bank should decumulate reserves when inflation shows signs of picking up, an indication that people are shifting from financial assets (money) into real assets, including imports. In addition to holding reserves on behalf of the private sector, the central bank will temporarily hold the tax receipts from coffee exports on behalf of the Government. Apart from accumulating reserves as a macroeconomic policy instrument, the Government has a longer term objective of raising the overall level of reserves to create a more permanent buffer to enhance the economy's overall capacity to sustain external shocks. For future boom management the financial sector reform is essential so that the private sector has access to forms of savings other than just money. Similarly, having an efficient banking sector will be crucial for intermediating savings into investment.  Macroeconomic Performance and the RoadAhead 17 1.39 The Government reinstated a tax on coffee exports - at a constant rate of 32 percent above U Sh 1,100 per kg - as a stabilization measure in its 1994/95 budget.4 The tax was modified in the 1995/96 budget: a constant rate of 25 percent above U Sh 1,500 per kg. Determining the level of the tax was an unnecessarily long process, which created policy uncertainty in the market. The actual collection of the coffee tax started only in the beginning of 1995 and has not yet been fully effective. The main arguments in favor of the tax on coffee exports were the need to sterilize part of the inflow to prevent inflation and appreciation of the shilling. In the absence of financial instruments that could mop up excess liquidity from the market, a tax on coffee exports was seen as the only option. Eix ante, the risks of rapid inflation and appreciation of the shilling were high, which could have left all exporters, including the coffee sector, worse off. It was also feared that those who receive the windfall income from the boom would, in the absence of savings instruments, rapidly increase their consumption spending and demand for nontradable goods, so that the real exchange rate appreciates. 1.40 Empirical evidence from other Sub-Saharan African countries shows, however, that a transient rise in income may not necessarily result in a sudden increase in private spending.5 The private sector may prefer to increase its spending on a permanent basis and hence saves and invests a large part of the windfall income. It remains to be seen whether this is the case in Uganda. It is also widely acknowledged that an export tax is not an ideal stabilization measure for a number of reasons: first, all exports are already taxed implicitly by import taxes, which are high in Uganda. (This point is further elaborated in chapter 2). Second, a relatively high tax rate provides an incentive to smuggle to neighboring countries that do not have a similar tax, or to evade the tax by other means. In a competitive environment, as in the Ugandan coffee sector today, those who evade taxes can pay higher prices to coffee growers and hence outcompete those who pay taxes. There seems to be some evidence of that as farmgate prices have fallen little since the introduction of the tax. Finally, the tax may discourage coffee producers from investing in coffee. But investment is needed in Uganda as most coffee trees are old and yields are low. Therefore, for future trade shocks, it would be useful to analyze how the private sector in Uganda actually responded to the present boom. This would allow an assessment of the costs and benefits of an export tax as a stabilization measure in the future. D. EXTERNAL AID AND MACROECONOMIC MANAGEMENT 1.41 Official gross aid flows to Uganda totaled about US$550 million in 1993/94, more than twice the value of merchandise exports. As a share of GDP gross aid flows have undergone a fairly steep rise, from 2.7 percent in 1986/87 to 13.4 percent in 1993/94. The primary purpose of aid is to finance investment in physical and human capital, 4 Under this policy, the Government may receive as much as between 40 and 60 percent of the windfall from the coffee tax, from duties and excise and sales taxes on increased imports, from higher income taxation and from seigniorage when people increase their money holdings. S For empirical evidence of the private response to a coffee boom in Tanzania and Kenya, see Bevan and others (1990).  18 Macroeconomic Performance and the RoadAhead infrastructure and institutions. At present aid covers more than 80 percent of all public investment and a substantial share of other public outlays, such as recurrent expenditures and debt service. While having a strong positive effect on investment, growth and poverty reduction, large-scale external transfers impose an additional burden on macroeconomic management and may impact the economy's incentive structure. In 1993/94, for example, aid provided about 45 percent (35 percent in 1994/95) of all foreign exchange available to Uganda. Because only about 30 percent of imports are directly related to aid-financed projects, aid is likely to have an impact on the real exchange rate. However, it is not possible to quantify this influence because adequate data are not available. 1.42 As aid is an inflow of foreign exchange primarily to the public sector, the real exchange rate could appreciate by fostering an increase in public expenditures which increases the demand for and the price of nontradable goods. The resulting appreciation of the real exchange rate could diminish the attractiveness of producing tradable goods. As public revenue gradually increases, the government's objective is to phase out counterpart funds generated by import support from financing recurrent expenditures. 1.43 About 63 percent of all project aid disbursements and 52 percent of import support was supplied by multilateral donors. The largest contributor among the multilaterals is the International Development Association (IDA) followed by the European Union (EU). Denmark is the largest single bilateral donor on the project side providing 7 percent of project support. The United Kingdom supplied the most import support - 23 percent. Grants account for little less than half of total aid, and the rest is concessional loans. The share of grants has increased from 23 percent in 1986/87 to 46 percent in 1993/94. Figure 1.3: GROSS AND NET AID AS SHARES OF GDP The share of total import 16 support (loans and grants) 14 has risen from 28 percent in 12 1987/88 to 36 percent in l/ 1993/94. These numbers do 8 not include aid flows from 6 4 NGOs, which are included in 2 the balance of payments 2 ,,. under current private -2 - 984/85 19887 198819 1990/91 199293 transfers. Aid from NGOs has soared since 1990/91. ___Y_ Sairsc: BOL. Grass Aid .----*Net Aid The exact figure is not s______Bou __ -Gro___Aid_......_Net_Aid available, but some estimates Note: The data in the above graph are taken from the BOP put it at around US$125 statistics, which are not necessarily consistent with fiscal data. million a year.6, 6 Some of the larger NGOs in Uganda are Oxfam, Save the Children Fund, Care, Amrif, Acord, ActionAid and the Red Cross.  Macroeconomic Performance and the RoadAhead 19 1.44 The concept of net inflow of aid is more relevant from a liquidity point of view. Both net and gross inflows have had a fairly strong upward trend (Figure 1.3).7 Despite increasing aid flows, for most of the adjustment period, the negative impact of falling external terms of trade dominated the positive impact of increasing aid flows (Figure 1.4).8 Figure 1.4: TERMS OFTRADEEFFECT,AID DISBURSEMENT DIFFERENCES & NET EFFECT 200 150 100 50 0 '~-50 -100 -150 -200 ro - cc Ql 0 C4 en~ IT co 00 00 ac ~00 a, a, 01 4 cc a 6C Fiscal Years Source: BOU. E3TOT Effect EODA Disb Differences E3Net Effect Changes in a country's debt position apart from ordinary amortization, such as changes in arrears and exceptional financing, (consisting mainly of rescheduling or cancellation of debt) are also considered to be aid. 8 In order to capture the impact of the terms of trade (TOT) change for a given time period, the "TOT effect" is calculated. It is defined to be the change in the purchasing power equivalent of exports in terms of imports in 1991 US dollars. The change between period i and]j is Xj *TQTj - Xi TOTi, where X is exports in 1991 US dollars deflated by the MfUV. This value indicates how much compensation (in terms of imports) is needed to offset the TOT effect. The difference in net disbursements of Official Development Assistance (ODA) from all sources in 1991 US dollars is obtained to assess the change in extenal assistance. The change in assistance is compared with the change in import equivalents to obtain the net effect. Negative net effects may indicate that adverse TOT effects were not fully offset by increases in exteral aid. In that sense the country would be aunderfinanced," while positive net effects may imply "overfinancing".  20 Macroeconomic Performance and the RoadAhead E. SUSTAINABILITY OF EXTERNAL DEBT 1.45. As of December 1994, Uganda had US$3.2 billion in total external debt outstanding and disbursed (equal to about 80 percent of its GDP in 1993/94), which included around US$250 million in principal and interest arrears. These arrears were mainly to non-Paris Club bilateral creditors. Over 70 percent of total debt outstanding and disbursed was owed to multilateral institutions (including US$1.55 billion to IDA and US$342 million to the IMF). About 24 percent of the total external debt was owed to official bilateral creditors, half of which was owed to Paris Club creditors. Scheduled debt service obligations (including IIMF charges) in 1993/94 were equivalent to 52 percent of goods and services exports. Multilaterals accounted for more than half of the debt service payments that year (IDA debt service was 7.6 percent). 1.46. In 1992 the Government of Uganda adopted a well-articulated strategy for managing its debt. The strategy has five components: year-by-year rescheduling of eligible Paris Club bilateral debt from pre-June 1981 and maximum annual deferral of all Paris Club bilateral debt accumulated thereafter, write off or long-term rescheduling of all non- OECD bilateral debt, extension of bilateral balance-of-payments support to cover multilateral debt service payments, buyback of uninsured commercial debt, and virtual cessation of government or government-guaranteed external borrowing on all but highly concessional terms. Uganda has progressed in implementing this strategy: it has secured rescheduling from the Paris Club, most recently through application of a stock of debt operation on Naples Terms (although this translates only to a 3 percent reduction in the present value of total debt); some non-OECD bilateral debt has been rescheduled, although much remains untreated; IBRD debt has been fully paid, but African Development Bank (ADB) debt, though relatively small, is still uncleared; a buyback of unsecured commercial debt, financed by the Debt Reduction Facility for IDA-only countries and bilateral donors, was successfully completed; and Uganda has avoided almost all new nonconcessional borrowing. 1.47. Debt Sustainability. Projections indicate that scheduled debt service obligations in 1994/95-1995/96 would be halved and scheduled obligations in the next decade substantially lowered if several conditions hold: no further relief is forthcoming from the Paris Club, non-OECD bilateral creditors would grant Uganda relief comparable to that obtained from the Paris Club, ADB debt is covered by bilateral donors, Uganda continues to borrow only on highly concessional terms (except for very small amounts of nonconcessional borrowing), new official financing continues at its current level in real terms, and exports grow in real terms at around 7 percent per annum on average during 1994/95-2002/03 and 5.5 percent thereafter. Nevertheless, from 2004/05 onward, payments on the rescheduled official bilateral debt (Paris Club and non-Paris Club) become due, adding to Uganda's debt service obligations. Thus, despite progress with the debt strategy so far, Uganda's external debt situation remains tenuous. 1.48. Uganda's liquidity situation, as given by the liquidity ratio (debt service as a percentage of exports), shows that once all of the above debt relief measures are  Macroeconomic Performance and the RoadAhead 21 Table 1.5: LIQUIDITY RATIOS Actual Debt Projected Debt Service Obligations Service Obligations 1992/93 1993/94 1994/95 1996/97 1999/00 2004/05 2009/10 2013/14 Debt Service/Exports of G&S Before Debt Relief 83.4 52.0 23.6 28.2 28.9 17.5 13.0 12.6 After Debt Relief 83.4 52.0 11.9 18.7 17.2 18.2 14.0 13.7 Source: World Bank staff estimates. Note: Private transfers are excluded from exports; however, in Uganda's case, they are likely to include misreported export receipts. accounted for, the ratio will rise from 12 percent in 1994/95 to 17 percent in 1999/2000, and then attains levels of more than 15 percent until 2005/06, indicating of high indebtedness (Table 1.5). After 2005/06, the debt-service ratio is expected to fall below 15 percent. The share of IDA in debt service, while rising until 2010, should remain below 10 percent of projected exports throughout the period. 1.49 Uganda faces a serious debt overhang - implied by the solvency ratio, the present value of debt service obligations relative to the annual average of 1992/93-1994/95 export earnings. The solvency ratio, based on the December 1994 stock of debt and without new comrnitments, would decline from 451 percent before debt relief to 318 percent, assuming that the terms of the February 1995 Paris Club agreement on Uganda are extended to all bilateral debt, along with prepayment of some multilateral debt. A country with a solvency ratio higher than 300 is considered severely indebted. Although this ratio may be somewhat overstated because of underreported exports, its size underlines the importance of further debt relief, rapid export growth and favorable terms for future borrowing. If the debt strategy is fully implemented and export growth is relatively high, the solvency ratio should fall below 150 by 2002. Since there seem to be limited prospects for debt relief beyond what is assumed above, the critical determinants of debt sustainability are the terms of new financing and export growth. F. MACROECONOMIC PROJECTIONS 1.50 The macroeconomic projections for Uganda9 were prepared on the assumption that the Government will continue implementing fiscal and monetary policies in such a way that inflationary pressures are kept in check. It is also assumed that progress will be made on the structural reforms identified in the rest of this report, which would provide the basis for supply responses. Continuing satisfactory performance in stabilization and structural 9 The World Bank's macroeconomic Revised Minimum Standard Model Extended (RMSM-X) was used and adapted to the Ugandan economy. Detailed results are presented in Tables C1-C5 in the Annex.  22 Macroeconomic Performance and the RoadAhead reforms will also provide the basis for continuing support from the international donor community; 1.51 The model assumes that, given the substantial improvement in the terms of trade of Uganda, GDP will grow by about 7.0 percent in 1994/95 and 1995/96, by 6.5 percent in 1996/97 and by about 5.5 percent thereafter. After the coffee boom economic growth (which depends to a large extent on imports for investment) will be constrained by export growth. Total investment is projected to increase gradually from about 15 percent of GDP in 1994/95 to about 19 percent of GDP by 2002/03. Private investment increases from under 8 percent of GDP in 1994/95 to over 11 percent in 2002/03, and public consumption increases from under 8 percent of GDP to over 12 percent during the same period, reflecting a change in Uganda's expenditure composition away from private consumption towards private investment and public consumption. Private consumption increases in real per capita terms, but falls as a share of GDP. The increase in public consumption allows a sustainable increase in priority programs of the recurrent budget, such as education, health, agricultural research and extension, water supply and rural feeder roads. 1.52 The average annual inflation rates are projected at around 8 percent in 1994/95, and at around 5 percent thereafter. The Ugandan shilling is assumed to appreciate by about 15 percent in 1994/95 in nominal terms, remain constant in 1995/96 at about 930 shillings per dollar, and depreciate by about 5 percent in 1996/97 and by about 15 percent in 1997/98, returning to its pre-coffee boom level. After 1997/98 the real exchange rate is assumed to be constant; the nominal rate will adjust to compensate for domestic and external inflation differentials. 1.53 It is assumed that the current high commodity prices and the structural policy reforms implemented in the last few years will provide a boost to increase the volume of exports at 6 to 7 percent over the next few years. These optimistic assumptions are based on the fact that agricultural markets have been fully liberalized, price controls eliminated, processing plants have been or are being privatized and the monopoly of state marketing boards eliminated. The scenario assumes that Uganda will recover its previous (early 1970s) level of exports in its traditional exports (coffee, tea and cotton) during the next decade. Other exports are expected to increase as a share of total merchandise exports from 10 percent in 1994/95 to 24 percent by 2002/03. 1.54 Imports of goods and nonfactor services are based on the availability of external inflows (mainly exports, private transfers, foreign investment and foreign aid) and reserve targets in each year. In order to manage its external debt, Uganda has to limit future borrowing mostly to highly concessional terms. It is assumed that aid disbursements are maintained in real terms throughout the period, and that the public sector will contract no more than US$15 million dollars of new nonconcessional loans per year. Real annual growth rates of imports are low after the coffee boom reflecting the more moderate availability of foreign exchange, but pick up after 1997/98 to about 5 to 5.5 percent.  Macroeconomic Performance and the RoadAhead 23 1.55 The large gap between exports and imports leads to substantial resource balance deficits, which initially decline to about 9 to 9.5 percent in 1994/95 to 1996/97, but increase thereafter to about 11 to 12 percent of GDP. Under more normal conditions, this deficit would be unsustainable and risk a balance-of-payments crisis. However, an abrupt reduction in the trade deficits (i.e. aid) could be harmful for medium-term growth in Uganda, which requires external inflows to accelerate investment in infrastructure and human resource development. 1.56 The results from the scenario underline the fragility of the macroeconomic stability and the need to deepen the structural adjustment over the medium term--in particular, in the areas of public sector reform, improved financial sector performance and improved incentives to exporters. Inaction would increase the potential for a balance-of-payments crisis and high inflation.   2 ACCELERATING ECONOMIC GROWTH: INCENTIVES, EXPORTS AND INVESTMENT 2.1 Macroeconomic stability is a necessary but not a sufficient condition for growth. Future growth in Uganda depends primarily on developments on the real side of the economy. Sustaining and accelerating growth in a small open economy like Uganda requires a strong and diversified export sector, as domestic demand and few commodities prone to large price fluctuations cannot sustain high growth rates in the future. Another important ingredient for future growth is increased private investment in productive capacity, backed up by higher public and private saving. In addition, physical and social infrastructure are necessary facilitating factors to complement private investment and provide human capital. 2.2 Growth in Uganda is constrained by a number of factors which affect export development and private investment. The main constraints are poor infrastructure and weak institutions, lack of human capital, including high illiteracy rates and lack of technical and managerial skills, a weak financial sector, and remaining distortions in the incentive regime. Finally, there is a perceived lack of policy credibility which can only change over time, provided reform policies are continued. This chapter focuses mainly on the incentive regime, while other constraints and policies to overcome them will be analyzed further in chapter 3 with a view to promoting nontraditional agricultural exports, and in chapter 4 regarding rural infrastructure and human resource development. 2.3 Since the launching of the Economic Reform Program in 1987 the Government of Uganda has been implementing policies, with the support of donors, to address the above constraints. In particular, it has taken important steps to liberalize the economy and shift incentives in favor of the tradable sector and to promote private sector development. The Government also continues to rehabilitate infrastructure and institutions, direct more public funds towards agricultural research and extension, health services and education, and so on. However, due to a long period of economic decline with hardly any investment, insufficient maintenance, collapse of standards and many institutions and shrinking of the formal sector, resource requirements to overcome the above constraints are huge. In addition, many of the reforms have taken time to gain momentum so that, despite progress in a number of areas, most of the constraints to long-term growth are very much present. 2.4 As to the outcomes of the reforms, overall GDP growth (about 3 percent per capita on average) has been better than private response in exports and investment. As growth is dominated by agriculture, occasional droughts have increased the volatility of growth performance. The present coffee boom will temporarily boost growth rates in 1994-96. Until now growth has largely been driven by economic recovery (i.e. a gradual increase in the share of marketable and formal activities, and rehabilitation of  26 Accelerating Economic Growth: Incentives, Exports and Investment infrastructure), increased domestic demand and, to a lesser extent, fortuitous regional demand. Exports seem to have not yet responded in the aggregate to improved incentives. However, there are encouraging signs in nontraditional agricultural exports (NTAE) but, as yet, no sign of emerging industrial exports. Aggregate investment remains also low. Its share of GDP has actually declined after the first two years of rehabilitation in 1986-87. A lag in response can be expected, but the decline in aggregate investment is a worrying trend. The composition of investment has also shifted from equipment and machinery to structures, while most private investment has been in the import-substituting sector and rehabilitation of the existing capacity. 2.5 The rest of the chapter investigates the reasons behind the sluggish response in exports and private investment, particularly in export-oriented activities, to trade and exchange rate liberalization and other economic reforms implemented since 1987. It also identifies constraints for promoting exports within the region (Preferential Trade Area, PTA) and outside the region. One of the main findings is that, although substantially reduced since 1987, there is still an antiexport bias embedded in the incentive regime. This policy bias arises because of high effective rates of domestic protection and dependence of public revenue on import taxation. In an economy like Uganda, the ultimate incidence of import taxation falls largely on exporters who are price-takers and cannot shift their higher costs onwards. Domestic producers instead have more market power and are hence able to pass on at least part of the additional costs. Policy measures are urgently required to reduce this bias as export growth is vital for Uganda's future growth which is in danger of eventually stagnating if producers continue to rely on domestic demand alone. A. PRIVATE RESPONSE IN EXPORTS, INDUSTRIAL PRODUCTION AM INVESTMENT: RECENT EVIDENCE 2.6 One of the overall aims of the economic program in Uganda has been to promote nontraditional exports by reforming both export and import policies. These reforms have been gradually introduced since 1987 (Box 2.1). The removal of explicit export taxes (associated with a nonunified exchange rate regime) and import liberalization did not occur until 1990, making this year the earliest point at which to observe changes in trade, production, and investment pattems. To the extent that producers believe the reforms to be credible and long-lasting, one would anticipate, after an appropriate response lag, a significant increase in the relative incentive to produce for the export market, especially in the more profitable nontraditional sectors. An improvement in incentives should be reflected in production and trade changes in sectors demonstrating a genuine comparative advantage or export potential. Also, investment should move away from the formerly highly protected import substitutes and toward exports. 2.7 Export Response. Despite a substantial liberalization of external trade and the exchange rate system since 1987, particularly since 1990, the ratio of Uganda's exports to GDP (at current market prices) fell from 11 percent in 1985/86 to 6 percent in 1993/94.10 10 Only the recorded, rather than actual trade response can be reported. The two may diverge for two reasons: the presence of unrecorded trade arising from smuggling and underinvoicing, and the  Accelerating Economic Growth: Incentives, Exports and Investment 27 Box 2.1: Chronology of Trade and Exchange Rate Reforms, 1987-94 1987 Dual trade licensing system introduced. Exemptions on raw materials and capital goods suspended. 1988 Some protective tariffs (sugar, soap) raised. Open general license scheme for imports implemented. 1989 Retention account scheme for export earnings introduced. 1990 Export licensing system replaced with certification system. Forex bureau/parallel foreign exchange market legalized. Duty exemptions on raw materials reintroduced. 1991 Import licensing system replaced with certification system. Investment Code introduced. 1992 Foreign exchange auction market created. Tariff structure rationalized (10 to 50 percent range). Several duties on raw materials abolished. Tax on coffee exports abolished. Coffee marketing board's monopoly removed. 1993 Unified interbank foreign exchange market/floating exchange rate. Surrender of coffee exports receipts waived. Special import surcharges on Kenyan imports applied. Harmonized commodity coding system for imports introduced. System of trade documentation reformed; preshipment requirements introduced. Cross Border Initiative to promote regional trade introduced. 1994 Tariff structure (10 to 30 percent range) further rationalized. Import duties on some raw materials suspended. Tax on coffee exports reintroduced. The ratio will bounce back to the 1985/86 level in 1994/95 because of the high world price for coffee. At constant prices exports have remained between 6 and 9 percent of GDP since 1985/86 (Table 2. 1). misrecording of reported trade. Both appear to be significant problems in Uganda. The extent of unrecorded trade is difficult to quantify, though it is likely to have declined as a result of export and import liberalization. Differences in tax arrangements and the ease of admninistration in the formal and informal sectors will affect the amount of unofficial trade. These differences in the incentive to record are also likely to affect the accuracy of trade information compiled from foreign exchange requirements/receipt sources and that from customs sources. (The substantial variations in export values recorded in different sources are illustrated in Statistical Annex Table H11.2.) In addition, it is likely that current private transfers include earnings from nontraditional exports.  28 Accelerating Economic Growth: Incentives, Exports and Investment Table 2.1: INVESTMENT AND EXPORT SHARES OF GDP In Percent Investnent/GDP Exports/GDP Investments/GDP Exports/GDP (Current prices) (Constant prices) 1985/86 7.7 11.3 12.5 8.3 1986/87 9.3 6.6 16.8 7.7 1987/88 10.3 6.0 18.7 7.3 1988/89 10.3 6.7 16.1 7.3 1989/90 11.9 6.0 15.7 7.3 1990/91 14.8 6.1 16.2 6.4 1991/92 15.2 7.2 14.6 7.2 1992/93 14.1 5.5 14.0 6.2 1993/94 12.9 6.1 14.4 8.6 1994/95* ... 11.1 ... 7.5 Source: Statistics Department, MFEP. * estimate 2.8 The composition of exports is sensitive to changes in the world price of coffee (Figure 2.1). In addition, there is evidence of a distinct increase in importance of nontraditional agricultural exports (which is discussed in more detail in chapter 3). Theshare of manufactures in total exports increased slightly in 1992 and 1993, but manufactured exports contributed a relatively (and absolutely) small share (Table 2.2). There is some suggestion of a shift away from machinery and transport equipment (two activities for which Uganda does not have a comparative advantage) toward exports of basic and miscellaneous manufactures. But the disaggregated data indicate that manufactured exports are made up of a relatively large number of products sold in small quantities to neighboring countries. This type of exporting is more likely to be explained Figure 2.1: STRUCTURE OF EXPORTS Before the Coffee Boom Dming the Coffee Boom 1990/91-1993/94 1994/95 Nonfactor Nonfactor Services Services 16% 10% Non- 13% Coffoee Non- 46% tracdtional 18% ~~~~CoffeeOhe 62% 5 Other 20%  Accelerating Economic Growth: Incentives, Exports and Investment 29 Table 2.2: COMPOSITION OF MERCHANDISE EXPORTS (in percent) Shares of Total Exports 1/ Shares of Manufactured Exports Trad. Agr. t Non-Trad. Agr. & Manuf. 41 Chemicals Basic Machinery & Misc. Primary Goods 31 Manuf. Transport Manuf. Equip. 1989 90.9 7.6 1.3 2.3 7.6 85.3 4.8 1990 80.3 18.3 1.3 9.8 27.7 52.2 10.3 1991 72.1 21.6 1.3 8.5 25.3 54.4 11.8 1992 74.2 23.7 2.1 9.5 21.1 46.3 23.2 1993 67.5 28.3 4.3 - - - - Source: Background to the Budget, 1994-95, MFEP, and EPADU for 1993 estimates. Includes SITC 9 (goods not classified by kind). 2/ Coffee, tea, tobacco and cotton. 3/ SITC 0-4 less traditional exports. 4V srrc 5-8. by idiosyncratic factors or distortions, possibly of a transitory nature, than by genuine comparative advantage. Much greater product concentration is expected, judging from the experience of other developing countries that have moved from traditional activities to exporting manufactures to extraregional markets, particularly industrial markets. 2.9 Industrial Production Table 2.3 CHANGES IN INDUSTRIAL Response. Industrial production PRODUCTION has increased in each year since (In Percent) 1987, but at a decreasing rate Industrial Sector 1987-93 1987-90 1990-93 since 1990 (Table 2.3). In four Food processing 146 75 41 sectors the rate of increase Of Tobacco and beverages 71 55 10 production was higher in 1990- Textiles and clothing -7 16 -20 93-chemicals, bricks and Leather and footwear -32 -25 -9 cement, steel and steel products, Timber, paper and printing 138 84 30 and miscellaneous, which Chemicals, paint and soap 239 84 85 includes vehicle accessories Bricks and cement 165 54 71 Steel and steel products 159 8 140 electrical products, and plastic Miscellaneous 271 81 105 products. (That production of All items 114 56 38 these goods has increased is Source: Background to the Budget, 1994-95, MFEP. evidence that Uganda has limited Kenya's access to its markets.) Given Uganda's level of technologies and local resources, these should be import-substituting activities, for which there may be some opportunity for interregional, but not for significant extraregional exports. Indeed, the growth of production in these sectors does not seem to be driven by exports. For example, exports of chemicals and plastics, positive in 1987, had fallen to zero by 1992, while exports of electrical products increased in nominal terms by only a small amount between 1987 and 1992. Even in the case of steel and steel products the total value of exports was still very small in 1992.  30 Accelerating Economic Growth: Incentives, Exports and Investment 2.10 Investment Response. As shown in Table 2.1 above, the published data do not show either an aggregate export or investment response to the reform program as yet. Indeed, the investment and export-to-GDP ratios have been lower on average in 1990-94 than in 1987-90. Sufficient information is not available on the composition of total investment, however, including the breakdown of total investment in the national accounts into private and public. Currently the latter is estimated from the public investment program and the formner is derived as a residual. The sectoral composition of private investment can only be inferred from Uganda Investment Authority (UIA) data on planned and "estimated on the ground" investment, which accounted for about 10 percent of total investment in the economy during 1991-94 (Table 2.4). The low level of private investment is probably caused partly by limited public investment in infrastructure. Removal of the implicit subsidy which imported capital goods enjoyed during the long period of overvalued exchange rate may be another factor that adversely affects investment in machinery and equipment. The remaining antiexport bias, perceived high non-commercial risk and insufficient scale of production to yield externalities to investors are also likely to explain the observed slowness of response. Table 2.4: COMPOSITION OF PLANNED AND ESTIMATED ON-GROUND INVESTMENT IN UIA MONITORED PROJECTS: MANUFACTURING SECTOR (In Percent) Shares of Total Manufacturing Planned Estimated On-Ground xnplementation Ratio (Licensed/on-ground) Food processing 26.7 29.6 0.37 Tobacco and beverages 6.3 9.1 0.48 Textiles and clothing 18.4 1.0 0.02 Leatherandfootwear 3.0 1.2 0.13 Timber, paper and printing 5.4 4.0 0.24 Chemicals, paint and soap 21.1 39.7 0.63 Bricks and cement 5.1 1.4 0.09 Steel and steel products 7.4 10.4 0.47 Miscellaneous 6.5 3.7 0.19 Source: Based on end-July 1994 data supplied by UIA. 2.11 Most of the post-1991 investment has gone into the manufacturing sector, which accounts for more than 70 percent of the on-ground investment. Ugandan manufactures are largely import substitutes, but around 40 percent of manufacturing investment has been agro-based. Some of the food processing activities are nontraditional export activities. The overall picture in 1991-94, however, is not one of investment being directed toward export-oriented activities. This observation is confirmed by a recent survey of a  Accelerating Economic Growth: Incentives, Exports and Investment 31 large number of domestic firms." Only 8 percent of these firms' output was (reported to be) exported in 1995 - mainly to regional markets - compared with 7 percent in 1991. In line with the production changes in this period, a significant proportion of on-ground investment has gone to the chemical and steel subsectors, while recorded exports of chemicals fell to zero by 1992. 2.12 Increased private Table 2.5: FIXED INVESTMENT, CONSTRUCTION investment is critical for AND TRADE POLICY future growth. There is Indices at 1991 Constant Prices some empirical evidence GDP at MP Exchange Fixed Structures Equipment from other countries that Premium private investment in machinery and equip- 1985/86 100 100 100 100 100 ment has the strongest 1986/87 104 246 137 130 145 correlation with high 1987/88 113 227 168 160 178 growth rates. 12 For 1988/89 120 107 159 159 160 Uganda this result would 1989/90 127 65 161 167 155 suggest that the current 1990/91 133 24 168 182 150 suggstruction u , 1991/92 137 9 162 189 129 construction boom, 1992/93 149 2 163 205 112 though a positive 1993/94 157 2 179 231 116 development and a sign Source: Statistics Departments, MFEP and BOU. of increased confidence, Note: The exchange rate premium is the parallel (bureau) rate over the may not produce high official rate. growth rates that are sustainable. As shown in Table 2.5, the share of machinery and equipment in investment has fallen quite dramatically since 1987/88. Also, Uganda's low international credit ratings, may preclude substantial inflows of foreign investment in the near future.'3 Hence in the medium-term growth is likely to depend more on the recovery of domestic investment. 2.13 Despite the sluggish investment response to date, there are some positive factors which may be able to improve the present trend. According to a 1993 survey of actual and potential foreign investors, for example, reform of the regulatory and incentive environment has made Uganda more attractive to investors than many other African countries. Nonetheless, the risk of policy reversal, political instability, and lack of power and telecommunications infrastructure were perceived as major deterrents.14 Compared 11 The World Bank and the Uganda Manufacturers Association (1995). 12 DeLong, B. and L. Summers (1991). 13 The average rating of the Institutional Investor International for low-and middle-income countries was 35 in 1993 (100 is risk-free). For Sub-Saharan Africa it was 15.3 and for Uganda it was 7.3, an improvement of only 2.0 points since 1987. Another credit rating company, Dun and Bradstreet International, shows a somewhat brighter picture by rating Uganda 4d on a scale of l(a-d) to 7. Uganda is on par with Ghana and ranked the 10th best of the 23 African countries that were rated. 14 World Bank (1994c).  32 Accelerating Economic Growth: Incentives, Exports and Investment with Kenya, Uganda's greatest disadvantage was perceived to be in the labor market. Its shortage of skilled workers and management capacity reflects past neglect of education and the exodus of skilled labor. This calls for accelerating human resource development as a long-term solution. In the short term, this process can be assisted by educated Ugandans returning from abroad and by promoting on-the-job training of the work force. 2.14 The limits to attracting foreign investment - apart from returning Asians who have been allowed to repossess their expropriated properties - makes domestic private investment all the more important. Domestic firms see the constraints to their future operation and growth as different than those cited by their foreign counterparts. Domestic firms feel that the most severe obstacle is high taxation followed by the cost of and access to finance. The banking system - both commercial and investment banks - is only equipped to lend very small amounts for investment. The culture of nonrepayment is well- rooted, and the judiciary does not regularly permit lenders to foreclose on collateral. Loans are like equity in that they carry a high risk and are not recoverable. 2.15 However, even in industrial economies about 80 percent of investment is financed from retained earnings. Ugandan firms report that 70 percent of their capital is self- financed (Figure 2.2). Corporate taxation is the policy which most directly affects profits. At the same time, it is inevitable for the future macroeconomic stability that the share of public revenue in GDP has to increase. In order not to overburden the small formal enterprise sector and adversely affect private investment, tax rates do not have much room to go up. Hence the increase in public revenue, which can be gradual at best, must come from expanding the presently small tax base. Despite the importance of retained earnings, the banking sector needs to be able to provide loans for investment and working capital at reasonable interest rates, mobilize savings and smooth the impact of commodity booms by Figure 2.2: FINANCIAL STRUCTURE OF UGANDAN FIRMS 12% l 32 % 111 Commercial Banks 5 % 0~~ Development Banks 3 Foreign Sources 2% 03 Famidly/Friends . . . . . . . . . . . . . tro,2 Fl ed 3% U~~~ Suppliers 2% H~~~E Conmunity/Group Savings i.,:-.-. : . '.'. .'.E' ..''' .'.'. .-.-'.-.''' .. .. _2 1% .. ..... ..... .. .. ..... . it; - i* Other Enterprises ...... /..: ............. E O ther 70% 13~~~~~~~~~~~~~E Own Capital Source: WB and UMA 1995 Private Enterprise Study.  Accelerating Economic Growth: Incentives, Exports and Investment 33 providing farmers and entrepreneurs a way to accumulate financial savings prior to making investment decisions. As seen in chapter 1, the financial sector continues to perform extremely poorly, and slow reform efforts are a serious impediment to private economic activity, investment, and growth. B. EFFECTIVE PROTECTION 2.16 As seen above, there has been a substantial liberalization of the trade and foreign exchange regimes and reduction in the antiexport bias, involving exchange rate unification, retention of export earnings, elimination of most quantitative restrictions, and some rationalization and reduction-of tariffs (Box 2.1). To investigate whether there has been an effective and adequate reduction in the antiexport bias, it is useful to examine the pattem of incentives, captured by the effective rates of protection"5 across different activities and markets (Tables 2.6 and 2.7) 16 2.17 The effective rate of protection varies considerably across sectors and products. This variation is not uncommon where there is a mixture of tariffs and quantitative restrictions, pervasive duty exemptions and administrative discretion, and variation in local value-added (at international prices) across activities. Indeed, some products show negative rates of effective protection in Maxwell Stamp's (1993) data. Again, this result is not unusual; it might be explained by downward pressure on nominal protection induced by smuggling, regional competition, or the relative unimportance of local sales (true of 5 This measure captures the net protection accorded to a particular stage of production. It allows for both the protective or subsidizing effect of tariffs on competing final imports and for the disprotecting or taxing effect of tariffs on intermediate inputs or raw materials used in this stage of production. For example, assume that a 30 percent import duty applies to imports of a final consumer good, while local producers of the final good pay a 10 percent (t1) duty on an imported input which makes up 50 percent of the pre-tax cost of product, (a,j). In other words, the value added is 50 percent. The nominal rate of protection (tj) in the absence of any quantitative restrictions is, therefore, 30 percent but the effective rate of protection is 50 percent, i.e. the percentage increase in the net price of the final good. For this simple case of one good j the formula for effective protection (ej) is: ej = I-aij Note the ej increases as aij increases even if tj and t, are constant. Thus for this same pattern of nominal tariffs, a lower value-added activity, i.e. aij = 80 percent would be subject to an effective rate of protection of 110 percent. Similarly, if the domestic producer is exempted from tariffs on intermediate inputs, as often is the case in Uganda, the effective rate of protection increases from 50 to 60 percent. 6 The two sets of values reproduced in Table 2.6 are not directly comparable, since one gives product level estimates and the other averages across a sample of products in each sector. There are also differences in the estimates because of the differences in the means used to estimate nominal protection by the two studies. The Louis Berger study uses only scheduled tariffs to estimate nominal protection, which will overstate protection, for example, where exemptions or smuggling is important and understate protection where QRs are present. The Maxwell Stamp methodology is more ambitious and based on domestic and import price comparisons.  34 Accelerating Economic Growth: Incentives, Exports and Investment Table 2.6: RECENT EVIDENCE ON EFFECTIVE PROTECTION LEVELS MaxweDl Stamp (1993) 1/ Louis Berger (1993) 21 Product % Sector % Electronic asmembly 38.2 Steel products 68.0 Electrical assembly 57.4 Engineering V.A. <o Brewing 166.8 Paper, packaging, printing 90.0 Clothing 77.3 Wood and related products V.A. <0 Dairy products -23.0 Agro-processing 39.0 Fish processing -9.3 Paint 61.0 Footwear 32.8 Plastics 53.0 Grain milling 101.1 Textiles and clothing 75.0 Horticulture -20.0 Leather and leather products 6.0 Leather -2.1 Beverages 92.0 Light engineering 147.6 Misc. manufacturing 19.6 Paints 435.4 Paper products 17.3 Plastic goods 20.0 Soft drinks 49.8 Spirit. V.A.<o Sugar -8.7 Tea and coffee -2.0 Textiles -40.0 Tmrmber processing 1.3 Tobacco products 3563.3 Tires 14.9 1t Against extra-regional (non-PTA) competition in the domestic market using estimates of nominal protection resulting from both tariffs and QRs (1992 data). (Altermative estimates based on scheduled tariffs and rates of import duty collection are also reported in the study). 2/ As in (1) except using scheduled tariffs (pre-July 1992) as indicators of nominal protection. V.A. <0 Indicates negative value-added at world prices. most export sectors). Similarly, for primary and agricultural activities that involve little processing, the escalation of the tariff structure may mean that some inputs are more highly taxed than their outputs. Overall, however, the average rates of protection in domestic sales of around 60 percent are not out of line with rates of protection found in many other developing countries at a comparable stage of industrialization and trade liberalization.17 But these countries should not necessarily be considered a standard of 17 The earlier studies biased the measurements downward somewhat. The Louis Berger (1993) study does not capture the effects of quantitative restrictions, while the Maxwell Stamp (1993) study uses regionallKenyan prices as the proxy for world prices when measuring nominal protection. Clearly, the measurement of nominal protection in a world of quantitative restrictions, differential tariffs from PTA and non-PTA sources, smuggling, tariff evasion, duty exemptions, and quality differences between local and imported goods, is problematic - there is no precise or unique methodology for its measurement. But competition from regional imports does not mean that there is little or no protection against extraregional imports. The regional (PITA) market is itself protected against extraregional imports. The common or lowest trade barriers against extraregional imports which  Accelerating Economic Growth: Incentives, Exports and Investment 35 Table 2.7: RE-ESTIMATED EFFECTIVE RATES OF TARIFF PROTECTION (In Percent) In Domestic Sales In Export Sales From Extra-Regional From PrA Extra-PTA Markets Competition Competition Electronic assembly 47.8 47.8 -27.4 Electrical assembly 68.9 32.4 -4.2 Brewing 166.9 166.9 -24.3 Clothing 219.9 98.9 -38.2 Dairy products 23.6 -10.3 -48.7 Fish processing 110.9 95.9 -9.4 Footwear 35.6 18.2 -1.5 Grain milling 281.8 185.7 -25.9 Horticulture 24.3 24.3 -21.1 Leather 60.8 15.5 -2.2 Light engineering 77.2 34.1 -9.1 Misc. manufacturing 53.1 29.3 -23.6 Paints 181.2 130.4 -5.2 Paper products 36.5 5.0 -26.5 Plastic goods 34.9 16.3 -2.4 Soft drinks 75.3 75.3 -18.8 Sugar 34.0 10.7 -17.4 Teaandcoffee 41.1 41.1 -2.0 Timber processing 99.2 42.9 -0.9 Tobacco products 265.7 265.7 -10.7 Tires 19.3 16.9 -10.3 Unweighted average 93.2 63.9 -15.7 These are approximations given the methods used to derive the 'average technologies' and given the ability to only crudely match products with product ranges in the tariff schedule. This is particularly so in the case of the PTA tariffs. achievement. What is important is how the incentives for import-substitution affect export promotion in Uganda. 2.18 The above levels of effective protection imply a significant bias in favor of import substitution and against exports. Since tariffs and quantitative restrictions do not benefit export sales and since there is no compensating export subsidization, effective protection levels in export sales will either be zero, if there is no taxation of inputs, or negative if there is. However, the biases, particularly the antiexport bias, should be lower in 1994 than in the studies based on 1992 data because trade policy has been further liberalized. apply across the region, are likely to define the level of protection. Support for this interpretation is provided by an analysis of the shares of intermediate inputs (measured at world prices) implied by the estimates of effective protection report in Table 2.6.  36 Accelerating Economic Growth: Incentives, Exports and Investment Reforms include reduced coverage of the negative list and the narrowing of the spread of tariffs between final and intermediate imports. 2.19 Revised Estimates of Effective Protection. After revisiting the rates of effective protection, we find that effective protection is still high in Uganda. The average rate of effective protection against extraregional competition is calculated to be greater than 90 percent (Table 2.7). However, this figure is upwardly biased in those sectors where smuggling is pervasive and where PTA competition is most intense. It is downwardly biased where transportation costs provide natural protection against extraregional imports. But such caveats about precision should not obscure the fact that there is a substantial degree of antiexport bias in the present tariff schedule. The bias is especially pronounced for low value-added manufacturing activities. In these activities even relatively modest escalation of tariffs on intermediate and final goods translates into high rates of effective protection. This tendency is exacerbated by the current practice of granting widespread exemptions from duties and sales tax on imported raw materials and also other goods. C. HIDDEN SOURCES OF ANTIEXPORT BiAS 2.20 Uganda's antiexport bias is found in the implicit rather than explicit taxation of exports (except for coffee exports, which are also explicitly taxed). The bias takes two conceptual forms: relative and absolute taxation. Absolute taxation is evidenced by consistently negative rates of effective protection in export sales. For example, directly imported raw materials and intermediate inputs may be subject to tariffs and other border taxes. Duty drawback, which would offset such input tariffs, is available to Ugandan producers. However, the scheme has not operated effectively (even though it was recently strengthened following criticism that funds were not available to support the arrangement). 2.21 Relative taxation is likely to arise from the indirect price-raising effect of import barriers: higher prices of goods not directly imported by exporters (such as petroleum products), higher prices of locally produced but protected inputs, and higher priced nontradable inputs. In other words, exports are implicitly "taxed" by import barriers. Exporters in Uganda are more handicapped by high-cost inputs than producers selling to the domestic market because exporters are price-takers in international markets. Producers selling to domestic markets, on the other hand, have a greater ability to recover such high costs by passing them on (at least partly) to consumers. This disadvantage, which cannot be alleviated by a conventional drawback mechanism, constitutes a hidden tax that is a disincentive to export production. 's 2.22 The implicit taxation of exports can also be explained by the impact on the exchange rate. Trade barriers cause the value of foreign exchange earnings to fall with 18 Empirical estimations for a number of Latin American countries indicate that the proportion of import taxes paid by exporters vary from 53 percent in Uruguay to 90 percent in Colombia (Clements and Sjaastad 1984).  Accelerating Economic Growth: Incentives, Exports and Investment 37 import demand. This drop is equivalent to an appreciation of the shilling.'9 In Box2.2: IncidenceofImportDuties Uganda the policy discussion has been Import taxes are shifted to the export sector because more concerned with appreciation ultimately export earnings can only be used to arising from increases in the foreign purchase imports. If a kilo of coffee trades for ten exchange supply attributed to aid, bars of soap on the world market and there is a 20 private inflows, and coffee exports. percent import duty on soap, then within Uganda a Regardless of the case appreciation kilo of coffee only buys eight bars of soap (the other Regardless thadable cadse apriceiato two bars accrue to the Government as an import means that tradable goods prices are duty). If the coffee sector bought only nontradables lower in domestic currency terms than then its offer of a kilo of coffee is worth only eight they would be relative to nontradables (if bars of soap to the nontradable sector, and so the no appreciation had taken place). In coffee sector will receive nontradables worth only other words, domestically produced eight bars of soap: the incidence of the extra import importables and exports suffer alike. But duties falls on the coffee sector no matter what it importables are "compensated" to the purchases. extent that they enjoy protection. D. TRADE POLICY AGENDA 2.23 Reduction of the Antiexport Bias. The average rate of effective protection remains at more than 90 percent because of a cascading tariff structure, widespread exemptions on raw materials and intermediate goods, and low levels of value added. Despite widespread exemptions, around 37 percent of the c.i.f. value of imports is collected as import taxes. The antiexport bias that results from the incidence of import taxes is attributable to exporters' inability to pass their additional costs onto their clients. In other words, the ultimate incidence of import taxation falls, to a large extent, on those who earn foreign exchange-agricultural exporters in particular. 2.24 In order to reduce the antiexport bias, the Government should expeditiously abolish most exemptions from duties, sales taxes and excise taxes on imported inputs and lower the tariffs and other remaining restrictions on final goods imports. In the long run the Government must move from international trade taxes toward direct taxes and VAT. The revision of the Investment Code should also be completed without delay. 2.25 Apart from the remaining antiexport bias, macroeconomic policies are now less constraining to private sector development, investment, and export growth. But a whole range of microeconomic barriers continue to deter investors and prevent investment from becoming more productive and efficient. To promote domestic competition and efficiency, all firms must be treated alike. More than 70 percent of domestic firms surveyed in 1995 complained about unequal treatment in tax exemptions. 2.26 The recent appreciation of the nominal and real exchange rates (in 1993-94) has been a concern to policymakers and exporters as it is a disincentive on export growth and 19 Krueger, Schiff, and Valdes (1991).  38 Accelerating Economic Growth: Incentives, Exports and Investment diversification. At present these concerns have dissipated as the nominal and real exchange rate have remained fairly stable since mid-1994. The effect of this constraint depends on the extent and duration of the appreciation. In Uganda the industrial sector is small. Appreciation cannot therefore crowd out large amounts of manufactured exports. Much of the capacity in this sector is oriented toward local markets, and there is not much evidence of an increase in export-oriented investment. If the appreciation persisted, however, export diversification would most likely be delayed. 2.27 Regional and Global Export Promotion. In 1993, fourteen countries in Eastern and Southem Africa and the Indian Ocean agreed to implement outward-oriented regional trade liberalization and integration under the Cross Border Initiative. The initiative, which is supported by the IMF, the European Union, the African Development Bank, and the World Bank, focuses on eliminating nontariff barriers, harmonizing tariffs based on a low and simple structure, and harmonizing investment policies and incentives. Internal tariff reduction (ongoing under COMESA agreements) would be matched by reductions in external tariffs with a view to avoiding trade diverting increases in tariffs. In March 1995 the countries endorsed a "road map" to undertake the tariff reductions and harmonizations by 1998. The initiative allows subgroups of countries to form customs unions. In this context Uganda has indicated its intention, jointly with Kenya and Tanzania, to revive East African cooperation by establishing a secretariat in Arusha, Tanzania and by beginning to form a customs union in the region. The Cross Border Initiative emphasizes creating a low external tariff structure as part of a sustainable extraregional export strategy. 2.28 Discriminatory regional liberalization may allow Uganda to increase its exports of industrial goods (as a result of trade creation or diversion). To the extent that this policy fosters regional import substitution that is less costly than domestic import substitution, it is an improvement in efficiency. But discriminatory regional liberalization risks sustaining or introducing new barriers to the promotion of extraregional exports. Among Uganda, Kenya, and Tanzania (the countries forming a customs union), Uganda has the lowest external tariffs. Thus the relative disincentive against exporting outside of the free trade area would remain, and would be higher if a common external tariff structure was negotiated that was higher than Uganda's current tariffs. This increase is possible given the incentive for producers in the highly protected economies to lobby for the retention of current protection levels. Thus discriminatory regional liberalization risks frustrating one of Uganda's key reform objectives: export promotion. There is much less risk of nondiscriminatory trade liberalization frustrating regional export promotion: exports that are competitive outside the region will be competitive within the region. 2.29 This analysis argues that regional liberalization of trade is not an adequate substitute for extraregional trade liberalization in Uganda. An early commitment to a low common external tariff structure (ideally lower than Uganda's current tariff structure) would reduce the risk of costly trade diversion and would lower antiexport bias. Once committed to common external tariffs, Uganda's ability to affect discrimination and reverse its antiexport bias (in extraregional trade) would be seriously constrained.  3 EXPORT RESPONSE AND INVESTMENT IN AGRICULTURE 3.1 Over the 1971-1985 period, Uganda's agricultural sector was badly disrupted by the country's political and military turmoil and insecurity of market activities relative to subsistence farming and the breakdown of infrastructure and support services. While total food crop production was maintained, this period witnessed the virtual collapse of the country's cotton, tea, sugar and tobacco industries. Among major agro-industries, only coffee survived the period of turmoil without a large decline in output. As a result, by the late 1980s, coffee accounted for more than 95 percent of Uganda's agricultural exports and 90 percent of its total merchandise exports. In the past few years, the costs and risks of such a high degree of export concentration have been graphically illustrated. The collapse of international coffee prices during the late 1980s and early 1990s was a major factor in the deterioration of Uganda's balance of payments, debt-servicing ratio, and increased dependence on international financial assistance. As a result, there has been growing attention given to the prospects and support for nontraditional exports, especially for agricultural products. Indeed, over the past four to five years Uganda's nontraditional agricultural exports (NTAE) have grown rapidly, eclipsing the dominance of coffee in foreign exchange earnings, and making a contribution to employment, income generation and private sector development within the country. 3.2 This chapter focuses on the prospects for Uganda's agricultural exports as the main source of growth, particularly nontraditional agricultural exports. Based upon existing data, enterprise surveys, and subsector studies, as well as the results of field work in Uganda, this chapter: (i) reviews the development of NTAE over the 1988 to 1994 period; (ii) examines patterns of investment, organization, and institutional support for NTAE during this period; (iii) provides a summary analysis of various indicators of NTAE competitiveness, efficiency, and development impact; (iv) assesses the future prospects for Ugandan NTAE development; and (v) recommends policies and areas for public support. While the importance of coffee, cotton and tea for the generation of foreign exchange has declined due to low world prices and competition from NTAE, they still represent the mainstay of Uganda's current exports. Revival of these industries has been a significant element in Government's effort to increase export revenue in the short term. A brief summary of the future prospects of these crops therefore precedes the analysis of NTAE. A. TRADITIONAL CASH CROPS 3.3 Coffee is the largest source of export revenue for Uganda, although its share has declined to around 65 percent of merchandise exports in recent years. About 85 percent of Uganda's coffee exports are robusta. They constitute about 15 percent of world trade in this type of coffee. Coffee output has oscillated between 100,000 and 150,000 tons over  40 Export Response and Investment in Agriculture Box 3.1: Reforms in the Coffee Sector 1990/91 Separating the regulatory and trading functions of the Coffee Marketing Board (CMB), dividing it into two new institutions, Uganda Coffee Development Authority (UCDA) and Coffee Marketing Board Ltd., and removing CMB's monopoly in the export of coffee. At present there are well over 100 coffee exporters in Uganda. 1991 Transferring crop financing functions for the coffee sector from the Bank of Uganda. Removing controls on producer prices, processing and export margins, allowing farmers' price and other margins to be determined by market forces. A floor price remained for exports. 1992 Reducing implicit taxation of coffee exports, by exchanging coffee proceeds at the bureau exchange rate, removing export taxes. 1993 No longer requiring exporters to surrender proceeds to the Bank of Uganda. 1994 An export tax was reimposed in the wake of the coffee boom. 1995 Abolition of the export floor price for coffee. the past 10 years, well below the 200,000-ton average of the early 1970s. Incentives to improve quality and productivity had deteriorated under a restrictive regime of monopoly exports, high taxation and inefficient support services. In order to redress this situation, the Government launched a market liberalization program in 1990 which has brought about significant change (Box 3.1). 3.4 The liberalization of the coffee market coincided with the sharp decline in world coffee prices. Although it was a difficult time to introduce new policies, liberalization nevertheless helped in sustaining coffee sector performance, including exports under adverse market conditions. The liberalization policy has had the following effects: * Farmers are now paid promptly and, despite low international prices (before June 1994), real producer prices have almost doubled since 1989. * Farmer now have an incentive to tend existing coffee trees and to plant high yielding varieties. This will hopefully reverse the current decline in productivity and exports, as well as enhance quality. * Export prices fetched by Ugandan coffee (relative to average international prices) have improved, and some new markets have been penetrated. * Efficiency and cost effectiveness at all levels of the marketing chain have improved, enhancing Uganda's competitive position in the world coffee market.  Export Response and Investment in Agriculture 41 3.5 However, the principal structural problem in the coffee sector continues to be low production and farm level productivity. In spite of improvements in farmers' incentives, coffee deliveries remain low. The neglect and poor management during the 1970s also contributed to deterioration in the productivity of coffee trees. Many of the coffee trees are over 40-50 years old and have reached the end of their economic life. The program to increase productivity and raise quality includes measures to increase the replacement of: (i) the aging robusta trees using the new clonal varieties which are high yielding, disease- resistant and produce a crop of a better quality; and (ii) old arabica trees with new stock. 3.6 The current productivity of robusta nurseries, operated by the Government is low due to inadequate budgetary support and lack of appropriate technology and know-how. The Government nurseries cannot cope with the demand. At prevailing market prices, however, operation of a nursery should be commercially viable. To facilitate private replanting efforts for robusta coffee, a two-pronged strategy is recommended: (i) confirming clonal suitability, i.e. disease-resistance and quality of the existing six robusta clones, (ii) improvement of nursery technology. An important impediment to the expansion of arabica production is the susceptibility to disease of the current varieties. The cost of combating disease, and raising yields to reasonable levels is excessive. The introduction of new, disease-resistant varieties, which are available elsewhere in Africa and South America, should be a priority. 3.7 Cotton. The cotton sector in Uganda collapsed in the early 1970s, due to the disruption of the ginning industry by the Amin government. From 470,000 bales of lint, production declined to some 30,000 bales in 1980, increased and then declined again, before picking up to its current level of around 40,000 bales. Many cotton farmers shifted to growing foodcrops. The problems facing the industry included the disruptions caused by civil war, the takeover of the ginneries (mostly privately owned) by the cooperative unions in the early 1970s which encountered difficulties in financing and managing these enterprises, and the centralized management of pricing and export activities by the monopoly Lint Marketing Board (LMB). Farmers' incentives for production were eroded by predatory pricing policies, delays in making payments, and constant overvaluation of the exchange rate. 3.8 In a series of adjustments which parallel the efforts in the coffee sector, the Government has removed the LMB's monopoly on export marketing, and established a Cotton Development Organization to monitor developments in the sector, and promote its interests. Ginning enterprises are being restructured, introducing new ownership and management where required, and reducing the often overwhelming debt burden. A series of measures are underway to improve seed production and distribution, access to credit by farmers, and strengthen the research and extension effort designed to improve the productivity and quality of this crop. 3.9 However, the actions taken so far are not sufficient to attract private sector participation and to encourage production by smallholders. There is a "wait and see" attitude to investment in cotton. Marketing and processing inefficiency, shortage of inputs,  42 Export Response and Investment in Agriculture and the lack of hand tools, oxen and mechanical power for opening up land are the major problems that cotton farmers, who often are poor, are faced with. To reverse these adverse conditions, restructuring of the ginning industry, including debt relief arrangements, has to be completed expeditiously. 3.10 Tea exports have rebounded dramatically in recent years. Exports have risen from 2,000 to 3,000 tons of made tea per annum in the late 1980s to some 10,000 tons in 1993. A major recent accomplishment in the tea sector includes the repossession of tea estates by their former owners. This has put in place the incentives for further investment and rehabilitation. Moreover, tea factories and estates held by the parastatal Agricultural Enterprise Ltd. have recently been sold to a private company, and government shares in joint venture companies have also been divested. The ownership of some of the factories catering to smallholder tea producers is gradually being transferred to the smallholder farmers themselves. 3.11 The resolution of these long-standing issues would facilitate the resumption of growth in the tea sector over the next few years, despite less positive prospects at present in the intemational markets. There are also problems that require urgent action. The smallholder tea farms are only gradually being rehabilitated. Smallholder factories that were abandoned have not been replaced or rehabilitated. Poor tea crop management, combined with poor handling and transport of green leaf tea, and poor factory facilities and quality control have become major causes for the steady decline in tea export prices. Therefore, actions are required to improve farm yields, product quality and factory efficiency. B. DEVELOPMENT OF NONTRADITIONAL AGRICULTURAL EXPORTS IN 1988-94 3.12 As shown in Table 3.1, Uganda's NTAE increased from only US$1.4 million to more than US$75 mnillion between 1988 and 1993. Befitting Uganda's excellent and varied natural resource base, NTAE have taken varied forms, including: * Low-value food staples: maize, other cereals, beans sold in the regional market; * Fish and animal products: fresh and frozen Nile perch fillets, animal skins, and other animal by-products sold in Europe, the Middle East, and to neighboring countries; * Spices and high-value industrial crops: vanilla, chilies, ginger, pyrethrum, silk cocoons, and cocoa sold in Europe, the Middle East, and Japan; * Oilseeds: sesame seed sold in Europe, the Middle East, and Japan, and groundnuts, and soybeans sold in the regional market; * Horticultural crops: roses, vegetables, and pineapples sold in Europe, and bananas sold in the regional market; and * Timber and woodproducts, sold in Europe.  Export Response and Investment in Agriculture 43 Table 3.1: NON-TRADITIONAL AGRICULTURAL EXPORTS FOB Value, In Millions of US$ Actual Projectd 1988 1989 1990 1991 1992 1993 1994 199S 1996 1997 1996 Maize * 0.22 3.26 4.19 3.89 19.88 35.00 34.00 40.00 44.00 48.00 (36.48) Other cereals 0.06 0.06 0.16 0.56 0.58 2.20 1.80 2.00 2.20 2.40 2.40 Beans * 2.69 2.51 4.15 4.28 12.47 16.00 17.50 18.00 19.50 21.00 (15.08) Fish 0.26 0.74 1.39 5.31 6.49 8.97 14.00 24.00 36.00 40.00 42.00 Hides/skins 0.37 6.10 6.17 4.41 4.06 5.96 5.00 6.00 6.50 7.00 7.50 Sesame * 1.01 5.23 10.52 6.48 2.75 1.50 1.50 1.75 3.50 4.10 Vanilla * * * 0.18 0.17 0.39 0.56 1.10 1.80 2.60 3.50 Other spices 0.12 0.18 0.12 0.32 0.31 0.47 0.30 0.50 0.65 0.85 1.00 Cocoa beans * * 0.50 0.37 0.28 0.71 0.85 0.75 0.75 0.75 0.75 Fruit/vegetables 0.58 0.53 0.95 0.60 0.41 0.66 0.80 1.25 2.75 4.00 6.00 Timber .. 0.71 0.86 0.36 0.12 0.50 1.00 1.25 1.50 2.00 2.25 Groundnutr/soybeans .. 0.04 0.08 0.12 1.12 0.84 0.75 0.75 0.75 0.75 0.75 Roses/other cut flowers .. * * * 0.21 3.00 9.00 12.00 15.00 18.00 Pyre&irum e e * * * * 1.50 3.10 4.90 6.50 Silk/cocoons * * * * * 0.01 0.08 0.75 1.70 2.30 2.75 Total NTAE 1.39 12.28 21.23 31.09 28.19 56.02 80.64 101.85 129.45 149.55 166.50 (75.23) Total trad. agr exports 271.40 270.60 151.80 140.60 116.70 127.10 Total all agr exports 272.79 282.88 173.03 171.69 144.89 183.12 (202.33) % share ofNTAE 0.5 4.3 12.3 18.1 19.5 30.6 (37.2) Source: Agricultural Secretariat and staff calculations. 3.13 While consisting of a broad array of individual products, Uganda's NTAE are presently dominated in value terms by a limited number of items: the most important are maize (48 percent of the total value in 1993), beans (20 percent), fish products (12 percent), and hides/skins (8 percent). Trade for all the other commodities totals less than USS10 million, with trade in high-value spices, horticultural crops, and other specialty products not exceeding US$2 million. 3.14 Table 3.1 also illustrates the erratic pattern in the trade development for most NTAE. The initial jump (1988 to 1989) can be largely attributed to the development of (unprofitable) barter deals involving exports of hides and skins and to the formal recording of previously unrecorded informal regional trade in low-value staples. The second jump (1989 to 1991) was due to a short-term surge in sesame seed exports, and to growth in the maize and fish product trade. The most recent jump (1992 to 1994) was primarily due to a large increase in maize and bean exports. Of the above commodities, only in the case of fish products has there been a steady increase in trade levels over this period. For all other commodities, trade levels have either been erratic or have remained insignificant to  44 Export Response and Investment in Agriculture date. As will be discussed below, exogenous shocks have strongly influenced NTAE development thus far, while the development of trade in high-value and specialty commodities has featured an extended gestation period. 3.15 During the period considered, several investments, policies, and reforms enacted by the Government of Uganda have helped to facilitate the development or revival of NTAE. These measures have included: * The rehabilitation of infrastructure, particularly of primary and secondary roads; * The reform of the foreign exchange regime, including the licensing of private foreign exchange bureaus and the provisions for foreign exchange accounts; * The depreciation of the Ugandan shilling from U Sh 400 per US$1 in 1988 to a peak of 1,240 per US$1 in April 1993; * The liberalization of agricultural markets and prices, first in the domestic market for food crops (1988) and later in the export of these crops (1990) and of traditional export crops (1991); - The enactment of a new Investment Code and the creation of the Uganda Investment Authority (UIA) which assist new investors; * The simplification of export and cross-border trade procedures; and T The Government's encouragement of former Ugandan Asians to return to the country through assistance in reclaiming their properties and businesses. 3.16 Most of these measures have reduced the barriers to entry by small-to-medium- scale agro-enterprises and have reduced the transaction costs associated with investment and trade. However, the general (and erratic) patterns of NTAE in recent years have been as or even more importantly influenced by various exogenous factors, with both positive and negative effects. Among the most significant of these exogenous factors have been: * The 1990-91 drought in Sudan which, together with that country's overvalued exchange rate and political turbulence, created a short-term vacuum in the international sesame market; * The Iraqi invasion of Kuwait and the subsequent Gulf War which led to an increase in petroleum prices and hence air-freight and road freight rates, and to disruption in trading channels, affecting Uganda's exports of hides, skins, ginger, and sesame; * Recent political uncertainty in Kenya which has led some Kenyan entrepreneurs to invest in Uganda; * Events in Rwanda which initially in 1991-92 resulted in a drop in cross-border trade and the bankruptcy of many traders, and then later in 1993-94 provided enormous opportunities for Ugandan supplies of low-value foods to international relief agencies; and  Export Response and Investment in Agriculture 45 * The severe drought faced by Kenya (and parts of Uganda) in 1993-94 which expanded opportunities for profitable cross-border trade. 3.17 Both the sesame trade in the early 1990s and the more recent maize and beans boom have had 'gold rush' characteristics, including a sudden increase in demand, the entry of many new traders, a rapid and large increase in price, only to be followed by a subsequent collapse in prices and the bankruptcy of many of the new and already established firms. In the case of sesame, the basis for the short-lived Ugandan 'gold rush' was a serious drought in 1990-91 in Sudan, then a leading supplier to the Middle East and European markets. The drought, combined with the overvaluation of the Sudanese currency and the political and economic isolation of Sudan due to its stance during the Gulf War, created a shortfall in the international sesame market and a big opportunity for Uganda. Between 1990 and 1992, the price of Ugandan sesame seed doubled to nearly US$700 per ton (f.o.b. Mombasa). This stimulated a 40 percent increase in sesame plantings and brought about the increased commercialization of what had been largely a subsistence or locally traded crop. During these boom years there was much discussion about sesame becoming a leading export crop alongside coffee. This confidence led traders to continue paying farmers high prices in 1993, despite evidence that Sudan was returning to the market. The 1993 Sudanese crop turned out to be a record crop, reducing international prices and driving down the export prices for the less favored Ugandan commodity by one half This, together with the appreciation of the Ugandan shilling, resulted in substantial losses for sesame traders, with many going out of business. 3.18 In the case of maize and beans, cross-border trade had gone on for many years, with actual product flows depending upon supply and demand conditions and relative exchange rates in particular years. While the number of refugees in East Africa increased sharply during the late 1980s and early 1990s, international relief agencies did not procure staple foods in Uganda because of its then overvalued exchange rate (increasing the costs of supplies) and the difficulties encountered in securing reliable supplies. The initial upheaval in Rwanda weakened the maize and beans trade as many Ugandan traders were not paid by their Rwandan counterparts. In 1993, new opportunities emerged. Kenya experienced a major drought, leading it to import some 5.8 million bags of maize. Large quantities of maize were supplied from Uganda, through formal and especially informal channels with Kenyans participating in this trade on both sides of the border. 1993 also witnessed a large increase in the food requirements of international relief agencies to service Rwandan refugees. In 1993, the World Food Programme alone purchased 100,000 tons of commodities in Uganda, the bulk of which was maize and beans. Much of Uganda's officially recorded exports of maize and beans was based on the purchases and supply systems of the relief agencies. 3.19 The Ugandan deliveries to the relief agencies were not based on well organized supply channels. Many individuals simply tendered bids for supply contracts and upon approval, went out to procure the necessary crop. Some traders did not understand the tendering process, making low bids with the assumption that they could bargain the price  46 Export Response and Investment in Agriculture upward after a tender was accepted. With the appreciation of the Ugandan shilling, many successful bidders were forced to choose between defaulting on their contracts or incurring large losses. Many bankruptcies occurred. As a result, the membership of the Uganda Grain Exporters Association dwindled from 25 in 1993 to only 6 by mid-1994. The survivors have been larger firms, with more secure financing, a diversified product line, and a better crop procurement network. 3.20 Uganda has experienced several, smaller short-term booms in NTAE which proved not to be sustainable. For example, a spurt of exports of fresh pineapples in 1988 and 1989 was rendered unprofitable by a rise in air-freight rates. The emergence of a trade in fresh and dried ginger was sidetracked by the Gulf War and by the financial and technical problems experienced by the major exporter association. Various attempts to develop an export trade in dried chilies have shown initial promise, only to sputter during implementation. Among higher-value products, there has been an extended gestation period for getting production and post-harvest operations at a level which would enable the penetration of international markets. Small quantities have been exported and a sizable breakthrough is close for several commodities. Much of the past activity has consisted of 'learning by doing' and tapping into donor financial and technical assistance. A lack of cooperation between new entrants into various commodity fields has prolonged the learning process. C. INVESTMENT, ORGANIZATION AND INSTITUTIONAL SUPPORT 3.21 Investment in NTAE. The sustainability of Uganda's NTAE and the future competitiveness of the different subsectors in the international commercial environment will depend, to a considerable degree, on the level and effectiveness of investment in land, plant and equipment, human capital, and technology. Through 1991, actual investment in nontraditional agricultural production, processing, and trade was very small, with little private investment in commodity cleaning and storage facilities, minimal investment in food processing, and with most of the emergent fish processing companies and most spice/silk/horticultural companies operating with very rudimentary facilities. In the last three years, however, there has been considerable investment in new facilities and in the upgrading of prior establishments. 3.22 Based on information available from the Uganda Investment Authority, supplemented by information obtained from a few firms not registered by UIA, it is estimated that between July 1991 and July 1994, US$30.4 million was invested in land, buildings and equipment for NTAE production, processing and trade. This should be regarded as a minimum figure as it primarily captures investments by UIA-registered firms and does not include many small-scale investments, particularly in artisanal fishing and in on-farm investments in post-harvest facilities. During the past three years, there has also been investment in traditional agribusiness industries, especially in sugar production and processing. 3.23 As Table 3.2 indicates, the largest amount of recent NTAE investment has occurred for fish processing. Thirteen such investments have taken place (involving nearly  Export Response and Investment in Agriculture 47 US$14 million), either for the Table 3.2: AGRIBUSINESS INVESTMENTS IN construction of new, modern UGANDA factories or for the up-grading July 1991 to July 1994 of existing facilities to meet EU Number Value of NTAE standards. Most of this new of Investmnt lvestma investment has been undertaken Projects (percet) by foreign or joint venture NontradiuionalAgribusiness 63 30.44 100.0 companies. A majority of the Fish proeessing 13 13.96 45.9 operating fish processors have Flowers/horticulture 7 3.87 12.7 some Kenyan (Asian) Edible oil processing 10 3.44 11.3 participation, this being Poultry production/feeds 3 2.34 7.7 stimulated by the political Hides, skins, leather 3 2.19 7.2 uncertainty there and by Produce trading 5 1.34 4.4 Kenya's comparatively poorer Grain milling/processing 6 1.14 3.7 Kenya's coprtveypoe Fruitlvegetable processing 2 0.79 2.6 access to the Lake Victoria Fruitg/aba s0 fishery resoue Dairying/abattoir 7 0.55 1.8 fishery resources. While Vanilla/silk/pyrethrum 4 0.54 1.8 previously the fish processing Savmiling 3 0.28 0.9 industry absorbed considerably Traditional Agribusiness 11 45.84 less than its allocated quota of Sugar processing 2 43.69 60,000 tons per year, Coffee processing 5 1.51 investments made in the past Tea production 4 0.64 two years are likelytoincr eTotal AUl Agribusiness 74 76.28 two years are likely to increase Source: Uganda Investment Authority, supplemented with data from the processing capacity of the from selected non-registered companies. industry to over 100,000 tons per year, a figure just below the total fish landings from Lake Victoria for all consumption and market purposes in recent years. Until a better understanding of the present state and future sustainability of the Lake Victoria fisheries resource base is acquired, further investments in fish processing in the lakeshore and Kampala areas (but not necessarily on other lakes) should be discouraged, except for investments geared toward modernizing existing facilities to meet EU standards. 3.24 Investments in cut flower and other horticultural ventures have ranked second in aggregate value. Seven such ventures are already in some stage of implementation, while several others have reached advanced planning stages. As in the case of fish processing, investment in horticulture has exhibited something of a 'herd' pattern, with a few initial investments having a demonstration effect, leading others to replicate. Both Ugandan and foreign capital have been invested, with most individual ventures being undertaken by corporate groups which have multiple business interests in Uganda. Such corporate structures have facilitated their access to term financing and have helped to bear the costs and risks of such start-up ventures. The emergent horticultural export industry has thus far relied heavily on expatriate management services and on contractual links tying together technical advice and marketing services. Thus far, Uganda has piggybacked on the Kenyan cut flower industry, utilizing varieties of roses which have been grown successfully in Kenya, and recruiting Kenyan flower farm supervisors to become farm managers in Uganda.  48 Export Response and Investment in Agriculture 3.25 A number of small-to-medium-scale investments have been undertaken in the areas of grain milling, edible oil extraction, dairy production and processing, and poultry production. These ventures are geared toward the domestic market and, as such, are not examined here. At least among officially registered companies, there has been only modest investment thus far in produce marketing infrastructure, including warehouses, vehicles, produce cleaning machines, etc. There exist many unused facilities of the Produce Marketing Board. Those in good condition should be leased or sold to the private sector. 3.26 Some limited investment has been directed toward high-value specialty products, including vanilla, silk, and pyrethrum. Both for vanilla and silk, emergent entrepreneurs and farmers have been provided technical and/or financial support from donor-supported programs. Probably the most significant assistance has come through the USAID-funded Agricultural Nontraditional Export Promotion Project (ANEPP) under which several entrepreneurs were provided with technical and matchmaking services as well as grants for business plan development, management services etc. Under the project, extension support was provided to vanilla growers and a program of research station and field trials for a range of fruit, vegetables and cut flowers was initiated. In the case of pyrethrum, an international consulting company has made their first African agribusiness venture. The original idea was to organize pyrethrum production in western Uganda and have the flowers processed in Rwanda under contract. However, with the disarray in Rwanda, the company is now investing in a pyrethrum processing facility which should come on line in 1995. 3.27 The organization of the different NTAE subsectors is quite varied. Given the country's agrarian structure, it is not surprising that primary production is dominated by smallholder farmers. This applies to low-value as well as high-value commodities. The main exception is cut flower production where multihectare operations under shaded netting is the emerging trend, although there is some interest in exploring possibilities for outdoor, lower cost flower production. Fish catches are by artisanal fishing crews with only one trawler licensed to catch fish on a large scale. 3.28 In most NTAE subsectors the 'vertical' linkages between primary producers and downstream processors and traders have yet to fully develop, resulting in inefficiencies in the supply chain and uncertainty. Among the high-value and specialty crops, various forms of contract farming are beginning to emerge, filling, in part, a vacuum created by relatively weak systems of rural finance, agricultural extension and material input supply in many locations. These contracting systems, however, are not yet as advanced as those in place for tea (involving 10,300 growers) or tobacco (23,000 growers). Weak intermediation between farmers and the contracting firms has been common. Attempts to use cooperatives as intermediary institutions have frequently been unsuccessful due to poor management and conflicts of interest (i.e. for vanilla, chilies, ginger and tobacco). At present, the most effective contracting scheme among NTAE is that for pyrethrum. This involves some 3,500 farmers in the Kabale area, organized around collection centers, with  Export Response and Investment in Agriculture 49 the lead company providing a team of extension agents. This firm maintains a long waiting list of farmers wanting to join the scheme. 3.29 In the case of fish there are some cases of fishermen being financed (for equipment) by processing companies, although this is not widespread. More common are repeat trading arrangements in which fishermen give particular companies the right of first refusal for each consignment. Generally, however, the bulk of the fish procured by the processing companies is auctioned off on the beaches. The vertical linkages in the maize, beans and sesame trades are even weaker with little or no direct contact between formal sector exporters and the primary producers. Physical and cash insecurity contribute to this, but so do the poor condition of feeder roads, the weak liquidity of many produce traders and other factors. Purchases are made on a cash basis, and virtually no support is provided by traders to farmers in terms of technical advice and inputs procurement. As competition and quality standards increase, this is likely to change and will expand the outgrower scheme once its processing factory comes on line. 3.30 It is important to highlight several other dimensions of NTAE commodity system organization in order to understand the current state and likely future evolution of NTAE in Uganda. These are as follows: * The maize and beans export trade has a dualistic structure, comprising: (i) a small number of Kampala-based companies who are financed from off-shore sources, have warehouses and produce cleaning and packaging equipment, and trade in an array of exportable and imported commodities; and (ii) large numbers of part-time, small-scale traders operating in small towns or rural areas, typically without proper produce storage and cleaning facilities. These two groups do not and largely cannot compete with one another. The Kampala-based firms channel most maize and beans sales through the relief agencies and cannot compete on a price basis with the smaller traders whose sales are largely informal and cross-border. Most of the smaller traders are no longer eligible for relief agency tenders or are discouraged by a system of bid- bonding, whereby their tender bids are accompanied by a 5-10 percent deposit which is forfeited should they be unable to fulfill successful tenders. * In both the vanilla and silk industries there are two rival groups which have not cooperated with one another, experimenting with different approaches to production and seeking different sources of technical and other support. In the case of vanilla this rivalry has proven to be dysfunctional for the industry as farmers are receiving different and inconsistent technical messages, the prices paid to farmers have been bid up to a level which is not sustainable, and the scramble for available supplies has led to the harvesting and sale of immature beans. * In several commodity fields production and/or trade associations have been established. Most have not yet provided much practical support to their  50 Export Response and Investment in Agriculture members or developed into cohesive entities. Their future development is critical, however, as there are many services which the public sector cannot be expected to provide and will be beyond the means of individual firms. * Until now, Ugandan-based NTAE firms have had little or no involvement in the international marketing of their commodities and products. Uganda's cut flowers are sold to brokers who put them on the Dutch auctions. Brokers also handle the bulk of Uganda's fish exports. Uganda's cocoons are sold to the same firm which supplies silkworm eggs. Other high-value NTAE are similarly contracted with single overseas companies. As product quality improves, the Ugandan firms will need to develop marketing strategies to penetrate new markets and distribution channels. 3.31 Institutional support to NTAE has been limited and not especially effective. Although the recent restructuring of government ministries and agencies has removed the most obvious anomalies, there is still a need for further rationalization of activities of the Ministry of Agriculture, Animal Industries and Fisheries (MAAJF), the Ministry of Industry and Trade, the Ministry of Finance and Economic Planning and the Agricultural Secretariat of the Bank of Uganda, the latter being responsible for policy analysis and formulation. MAAIF is perceived by the private sector as being weak. In some cases (i.e. vanilla, pyrethrum, silk), the Ministry has been ambivalent if not antagonistic to the private promotion of smallholder production. Much of the analytical attention and direct support to NTAE has thus occurred outside of MAAIF. Donor-funded initiatives, as with ANEPP and several EU-funded activities have sought to address some of the existing technical, financial and marketing difficulties, but on a selective and largely ad hoc basis. In 1995, several years since the initial takeoff of NTAE, Uganda still lacked a private or public institution which provided effective support services to producers, traders, and/or processors on a self-sustaining basis. D. EFFICIENCY, COMPETITIVENESS AND DEVELOPMENT LMPACT 3.32 Most NTAE subsectors are still in an initial stage of development and it is too early to make firm judgments about their long-term competitiveness and developmental impact. Uganda's recent success in agricultural export diversification must be regarded as fragile since in general its NTAE have been characterized by low or uneven product quality, low rates of production and post-harvest productivity, relatively wide gross marketing margins, and high rates of failure among individual firms. 3.33 Uganda has thus far not developed a reputation for high quality products. Both maize and beans from Uganda are considered to be of poor quality in Kenya. Uganda's hides and skins are considered of poor quality as they are dried on the ground and frequently get imbedded with sand and dirt. Much of the fish reaching Uganda's fish factories is of mediocre quality, enabling the processing of only a second or third grade product. This is reflected in the prices obtained in Europe which are no better than domestically produced frozen cod fillets. A large proportion of Uganda's silk production  Export Response and Investment in Agriculture 51 is of non-exportable second grade, while its exports presently obtain prices well below those of the established suppliers. Uganda's sesame seed is not a high-value confectionery product and is an inferior substitute to Sudan's product. Initial supplies of Ugandan roses to the Dutch auctions received prices in the lower half of their price range for particular varieties. On the other hand, the quality of Ugandan vanilla is considered to be very high, and commercial tests have shown the country's pyrethrum to have a high pyrethrum content. 3.34 Productivity levels in most, if not all, NTAE subsectors are presently quite low. The recent increases in maize, beans and sesame production have been due to area expansion rather than productivity gains, with yields lagging behind other African countries with less favorable agro-ecological conditions. Labor shortages, the widespread practice of inter-cropping, and the very limited uptake of improved varieties are contributing factors. Post-harvest losses for these crops are also high in Uganda. Smallholder vanilla bean yields are also well below achievable levels. The silk industry presently achieves very low germination rates for silkworm eggs (i.e. 50 to 60 percent) due to an absence of proper egg treatment and storage facilities. High rates of fish spoilage and contamination occur due to the absence of refrigeration facilities and the poor landing facilities on shore. Rates of spoilage are reportedly high in the fresh fruit and vegetable export trade. 3.35 The Share of Primary Producers. Uganda's NTAE subsectors currently feature high marketing margins between the farmgate or fish landing site and the point of export. As can be seen from Table 3.3, the share of farmers and fishermen in the final f.o.b. value is equivalent to or less than that provided to Uganda's coffee, tobacco and cotton producers despite the fact that many of the nontraditional exports undergo less processing or preparation work after harvest and prior to export. Though requiring further analysis, the contributing factors to such high gross marketing margins are likely to include very high transport costs (especially for lower value commodities) due to high fuel prices, the high spoilage rates for perishables, the payment of official and unofficial fees at the district level and at borders, and high overhead costs due to the underutilization of facilities (i.e. fish processing factories, vanilla curing facilities and grain storage facilities). For some crops, another factor is the limited competition among farmgate buyers due, in part, to the poor condition of feeder roads. 3.36 Based on an analysis of the price/cost chains for different commodities, it is estimated that the total gross earnings accruing to farmers and fishermen of NTAE were equivalent to US$31.4 million in 1993 (Table 3.3). The greatest proportion of these earnings went to producers of maize and other cereals (US$15.5 million), beans (US$9 million), fish (US$2.2 million) and sesame (US$1.8 million). For all the other NTAE combined, farmer gross revenues were about US$3 million. Such earnings are not insignificant, especially when considering the returns to producers of long-standing export crops. For example, in 1993 the estimated payments to farmers for tea, cotton and tobacco were only US$9.1 million in aggregate. Reflecting low international prices in 1993, Uganda's coffee producers received payments amounting to US$53.3 million.  52 Export Response and Investnent in Agriculture Table 3.3: ESTIMATED REVENUE SHARE AND GROSS EARNINGS OF FARMERS AND FISHERMEN, 1993 Estimated Share of FOB Estimated Gross Value Accrued to Earnings of Farmers/Fishennen Farmers/FishenDen (Percent) (US$ m) Nontraditional Exports 31.35 Maize and other cereals 40 15.47 Beans 60 9.05 Fish 25 2.24 Sesame 65 1.79 Hides/skins 10 0.60 Groundnuts/soybeans 65 0.55 Spices 55 0.47 Cocoa beans 63 0.45 Fruits/vegetables 50 0.33 Timber 50 0.25 Roses 75 0.15 Traditional Exports 62.40 Coffee 50 53.35 Tobacco 61 4.29 Tea 30 3.34 Cotton 62 1.42 Source: Based on data provided by the Agricultural Secretariat, Bank of Uganda, and interviews of traders and processors. 3.37 Despite the deficiencies mentioned above, the available evidence suggests that many of the nontraditional export crops and products generate very favorable returns to farmers in comparison with traditional food and industrial crops, and that some NTAE have a higher international value added per hectare and a lower domestic resource cost ratio than major traditional crops. These comparisons are provided in Table 3.4 below. The first two columns compare private returns, i.e. farm-level output/input ratios and returns to family labor, while the last two columns compare domestic resource costs (DRC) and intemational value added (IVA). Farmer retums and national IVAs are especially high for high-value spices, horticultural crops, and industrial crops. The low- value NTAE (i.e. maize, beans and sesame) have farmer returns and IVAs which are no better (or worse) than traditional food and export crops. 3.38 The limited available farm survey work indicates that nontraditional export crops provide a supplementary income to farmers, although in some cases--as with vanilla in Mukono district, pyrethrum in the Kabale area, and among mulberry silk producers in Bushenyi district--these crops are emerging as a leading source of income. Survey work indicates that farmers are using this income for a variety of purposes including land purchase, home construction and repair, school and medical fees, consumer good purchases and farm improvements.  Export Response and Investment in Agriculture 53 Table 3.4: RETURNS AND EFFICIENCY OF TRADITIONAL AND NONTRADMONAL CROPS Farm-Level Returns to Domestic International Output/Input Family Labor Resource Value Added Ratio Cost Ratio (US$/man-day) (US$/ha) March 1994 March 1994 June 1994 June 1994 Traditional Crops Coffee, unimproved 1.17 1.14 0.18 2,953 Coffee, improved 1.40 1.87 Tea 0.99 0.86 0.91 3,408 Flue-cured tobacco 1.21 1.51 0.68 1,356 Cotton, hoe 0.57 0.39 0.81 459 Cotton, ox-plow 1.11 1.10 0.69 961 Matooke (banana) 1.42 2.00 n.a. n.a. Nontraditional Crops Vanilla 6.62 7.74 0.55 9,574 Passion fruit 5.73 14.78 n.a. n.a. Silk 2.24 9.92 0.69 3,824 Pineapple 2.52 3.82 n.a. n.a. Ginger 1.37 2.09 0.68 1,420 Pyrethrum 1.30 1.32 0.77 n.a. Chilies 1.27 1.25 0.27 1,471 Groundnuts 1.10 1.07 0.56 608 Maize, unimproved 1.10 1.03 0.38 661 Beans, unimproved 1.08 1.01 0.63 363 Sesame 1.04 0.93 0.86 196 Note: Domestic Resource Cost Ratio is the ratio of value added at domestic prcies to that at world prices. Source: Agricultural Secretariat, Bank of Uganda. 3.39 Table 3.4 indicates that at the exchange rate of U Sh 940 per US$1 Uganda has a comparative advantage in the production and trade of many nontraditional crops and products as illustrated by domestic resource cost ratios well below unity. However, the hike in the international coffee price and consequent pressures on the Uganda shilling to appreciate further has raised concerns about the competitiveness and continued profitability of trade in many nontraditional and traditional export commodities. Analysis by the Agricultural Secretariat indicates that most of Uganda's NTAE remain economically profitable at an exchange rate of U Sh 900 per US$1, although in some cases just barely. At such an exchange rate, however, the profit margins for traders are slim or nonexistent for many commodities and this puts downward pressure on the prices they are prepared to pay farmers and fishermen.  54 Export Response and Investment in Agriculture E. FUTURE PROSPECTS AND POLICY AGENDA 3.40 The prospects for future growth in Ugandan NTAE are good. For most commodities, demand will not be a constraining factor. Regional market demand for low- value staples will remain favorable given Kenya's emerging structural deficit in maize and beans and the continued need for food imports in neighboring countries as a result of political instability. Capturing a large and secure share of the Kenyan market will require an improvement in product quality and a reduction of costs at the farm level and in the marketing chain. As the Rwandan situation normalizes and relief agency activities decline and then altogether cease, Uganda should be able to maintain its level of maize and bean exports through growing formal and informal sales to Kenya, provided the latter will stick to the liberalization of its maize imports. 3.41 In the next few years, thanks to recent investments rapid growth can be expected in Uganda's exports of fish products and cut flowers. The European and broader international market for cut flowers continues to expand and can easily absorb (at remunerative prices) the increased quantities of flowers expected from Uganda. Demand will not be a constraint for Ugandan silk cocoons and pyrethrum if high quality standards are achieved. The world vanilla market may soon be oversupplied, although Uganda can carve itself a niche at the upper quality end of the market. Studies by the Export Policy Analysis and Development Unit (EPADU) of the Ministry of Finance and Economic Planning suggest that there is a limited range of fresh fruits and vegetables for which Uganda can compete in the European and Middle Eastern markets. With an improvement in product quality, Uganda can achieve modest gains in its exports of sesame seed, hides and skins, chilies and other spices and herbs. 3.42 Table 3.1 includes projections for Ugandan NTAE through 1998. These are based on information provided by the private sector for high-value industrial, horticultural and other commodities and on assumptions about the development of the Kenyan market. The table shows that NTAE are projected to more than double between 1994 and 1998 to reach over US$166 million by the latter year. The largest increases in trade are expected from fish products, maize, beans and cut flowers, although expansion is also expected in the trade of pyrethrum, fresh fruits and vegetables and several spices. Maize and beans trade involves uncertainty due to weather conditions both in Uganda and the neighboring countries as well as political developments in the region. This uncertainty means volatility in exports, which is difficult to predict, however. To realize the export and growth potential of NTAE, Ugandan producers, traders and processors must increase the quality of their products and increase farm-level productivity and marketing efficiency. To do so, apart from measures suggested in the previous chapter for reducing the antiexport bias, concerted effort is needed to address a number of infrastructural, technical, financial, and human resource constraints, as detailed below. Most of these constraints apply to other productive sectors as well. 3.43 Physical Infrastructure. Deficiencies in physical infrastructure increase risks and costs and contribute to problems of low product quality. While Uganda has a considerable  Export Response and Investment in Agriculture 55 road network, the majority of this network, feeder roads, are in very poor condition and serve as a major bottleneck in the movement of produce. At present few exporters use rail services because of their unreliability and cumbersome procedures, especially within Kenya. Uganda's telephone services are also unreliable and are extremely expensive. Electricity services are relatively inexpensive, yet are erratic, creating problems for processing operations and those requiring the refrigeration of raw materials and finished products. As the existing stock of infrastructure can increase only gradually, improving management of the available facilities is therefore important. There is a lack of proper landing sites along Lake Victoria creating conditions whereby fish can be contaminated by sand, dirt, and pathogenic bacteria. There is a virtual absence of pre-cooling and cold chain facilities for perishable commodities. While the existing air cargo handling facilities at Entebbe International Airport are antiquated and small, these will soon be expanded and upgraded through donor funding. 3.44 Technology Development and Dissemination. While measures are being taken to revive agricultural research and extension, this will be a long-term process. Traditional export industries, such as coffee, cotton and tea, developed their own research and advisory services over the years as has a private company for tobacco. Official research for most high-value and specialty NTAE has either been nonexistent or has been very rudimentary and dependent upon short-term donor financing. In the case of sesame, the varieties in use date to 1970 and have not been maintained by breeders. In some cases, individual private companies have done their own research and developed their own farmer advisory services. They have also distributed planting materials. Otherwise, a commercial seed industry has been slow to develop, with seeds for food crops either being saved from the prior year's crop or obtained from district agricultural officers. Relatively few farmers plant improved varieties of maize and beans, and high-quality sesame planting seed is virtually not available. Low educational attainment and the high illiteracy rate are a hindrance to dissemination of extension messages and adoption of improved technology. The Government should consider an outreach program to improve literacy in Uganda and hence enhance growth prospects in agriculture. 3.45 Resource, Production and Market Information. There is considerable uncertainty regarding the present state of the fisheries resource base, the catch potentials, and the long-term ecological and economic consequences of changes in this resource base. There is need to conduct a fisheries subsector analysis, reviewing the available resource base, the existing domestic market and factory raw material requirements, issues related to fisheries policies, the water hyacinth problem, infrastructure investment requirements, etc. At present a study is being carried out on the resource base alone. Official estimates of national and regional production of maize and beans vary widely depending upon institutional source, generating problems for traders to make accurate investment and trading decisions. Great uncertainty also exists regarding food crop demand, complicating the marketing task of primary traders and farmers. Exporters have had difficulty accessing information on overseas market opportunities, prices, and quality and other standards and regulations. Uganda's institutional capacity for export promotion is presently weak, while enterprise development suffers from unnecessary  56 Export Response and Investment in Agriculture regulation and red tape. UIA could have a useful role in suggesting ways to streamline requirements for industrial and business development. 3.46 Based on prior experience in Uganda as well as in other countries, it is not obvious that the necessary export promotion functions can be best provided by a public organization. This may be particularly true for Uganda's major NTAE, including the regional trade in low-value food staples and international trade in high-value specialty commodities. Commodity or industry associations may be better placed to undertake the promotion work. The restructured Export Promotion Council should develop ways to collaborate with such associations in special country or commodity campaigns. 3.47 Finance. Most small traders lack access to finance to enable them to develop seasonal working inventories of crops and to invest. Commercial banks have little capacity and interest to provide long-term capital, especially to new enterprises and those engaged in relatively risky ventures. Only a small minority of nontraditional product exporters have obtained loans under the Bank of Uganda supported Export Refinance Scheme or Export Credit Guarantee Scheme due to the cumbersome procedures involved and the lack of strong incentives for commercial banks to lend through these schemes. A venture capital fund, managed by the DFCU, has provided long-term finance to several NTAE operations, although these have been primarily large-scale investments in fish processing and cut flower production. Ongoing assessments of the status of rural financial markets should consider the special requirements of NTAE farmers. 3.48 Processing and Other Agribusiness Skills. At present, very few of the managers or senior supervisory staff have training in modem food processing. This is especially important in the fish processing industry where there is a need to move rapidly to the Hazard Analysis and Critical Control Points method of production to meet EU standards. More generally, agribusiness management skills are not widely developed in Uganda. An effort to step up skills and on-the-job training is hence called for. 3.49 Policy Analysis. There is need to rationalize policy analysis, preferably in one place, with greater attention given to improving the database concerning NTAE trade and the costs, profitability and division of income from different commodities. Further analysis is needed on the constraints on regional trade and investment cooperation as this has significant potential for Uganda's export development. 3.50 Land. For foreign investment in NTAE, existing legislation which prohibits acquisition of agricultural land is a major bottleneck. The government committee which has been set up to review the draft Tenure and Control of Land Bill (1990) recommends that only citizens should be allowed to own rural land, whereas noncitizens could gain access to agricultural land through leasing arrangements. The Constitutional Assembly is currently discussing this (and other) recommendations. Foreign investors wishing to obtain land in an urban area require the consent of the Minister of Land, Housing and Urban Development. In practice, these titles seem to be granted relatively easily.  Export Response and investment in Agriculture 57 3.51 Donor Assistance. The new Box 3.2: Technical Assistance for IDEA project supported by USAID is Nontraditional Export Development obviously central to the medium term development of certain NTAE. It is a Additional support for nontraditional agricultural complex project, whose success and exports will be provided under a five-year, USAID- sustainability will depend upon the funded Investment in Developing Export Agriculture staff involved, the linkages Project (IDEA). The project will address gaps in caliber of market and technical information, help to strengthen made with MAAIF research and agribusiness management skills, and help Ugandan extension pertaining to low-value traders and processors develop links with foreign (export) food crop technical support, buyers (and potential investors) and strengthen their and the extent to which commodity ties with local farmers. The project will feature an and industry associations can be array of technical assistance mechanisms and provide direct support to exporters of both low- and strengthened to take on support (and high-value agricultural commodities/products. regulatory) functions in their Under the project, entrepreneurs could benefit from respective areas. It is important that customized technical assistance, participation in attention be given under the project market tours, and grants to finance feasibility studies to enhancing product quality and or otherwise "jurnp start" export activities. The to enhancing product quality and project will also fund applied farm research work on marketing system development for selected commodities, strengthen local university the low-value staples, where the training in post-harvest management, horticulture, potential payoffs are likely to be more and marketing, and strengthen market widespread than for some of the more information/intelligence systems. An Agribusiness exotic, high-value commodities. The Development Center (ADC) will be created as a businesses must be enabled to chart temporary, autonomous project implementation unit. The ADC will be staffed with five expatriate and five their own strategies and find their local professionals. own solution to problems. In order to get the most benefit out of the project's matching grant funds and test the seriousness of prospective exporters, the beneficiaries should be asked to contribute at least 25 percent of the costs for feasibility studies, market tours, training programs, technical assistance, etc. Where grant funds are to be provided to "jump start" export activities, these should help defray certain fixed entry costs (developing markets contacts), yet not finance variable cost items (i.e., seeds, packaging materials). Otherwise, entrepreneurs will be unable to judge the actual (or even potential) profitability of the activity, weakening the scope for sustainability.   4 INFRASTRUCTURE AND HUMAN RESOURCES FOR GROWTH AND POVERTY REDUCTION 4.1 Experiences from East and Southeast Asian countries highlight the vital role of rural infrastructure and basic literacy and numeracy for rural development and sustainable growth. This chapter analyzes first these cross-country experiences, and summarizes lessons for Uganda. Second, the chapter assesses the availability of human resources for growth by examining the current educational attainment and the health and nutritional status of the population as well as discusses government's role in provision and financing social services. 4.2 In addition, rural infrastructure development and education are necessary for reducing poverty, which, in Uganda, is wide-spread and predominantly rural. For this reason reduction in poverty has to be based on a strategy for broad-based, environmentally sustainable agricultural development. Extension services play a crucial role in intensification of farming. This chapter seeks to show that, in order to raise rural incomes, policies should go beyond agriculture and foster the development of off-farm enterprises, the improvement of local infrastructure, education and health services, and the strengthening of local government. In particular, investments in education and health, apart from their direct impact on the quality of life, are vital contributions to the process of productivity change, income growth and specialization in the rural economy. 4.3 East and Southeast Asian countries-for example Indonesia, Malaysia, Thailand and China-have achieved rapid reductions in rural poverty in recent decades through a process of substantial economic growth. This growth has been based initially on labor-intensive agriculture combined with investment in human capital which has increased labor productivity. Rising rural incomes boosted consumer demand and strengthened demand- supply linkages to rural nonfarm activities, such as agroprocessing, industries producing farm related products and basic consumer goods and services. Rural-urban migration also had a (relatively small) role in poverty reduction. Agricultural incomes and hence consumer demand were initially boosted by green revolution technology which smallholders were able to adopt. Provision of rural infrastructure had also a significant role. 4.4 Currently, earnings from off-farm employment and non-farm enterprises contribute a relatively modest share to the income of rural dwellers rising from 12 percent among the rural poor, to 27 percent of total earnings of the better-off. While the development of off- farm enterprises is likely to be demand-constrained, these businesses can provide a significant multiplier effect to improvements in agricultural earnings. Estimates of the multiplier effects of agricultural growth on economic activities in the surrounding areas  60 Infrastructure and Human Resources for Growth and Poverty Reduction range from around 1.5 in Africa to around 1.8 in India and Malaysia.20 Off-farm activities received a boost in Uganda during the years of the "economic war" under the Amin regime, and during the early 1980's, when severe shortages of foreign exchange, and the paralysis affecting the large import substitution industries producing tools, household goods, furniture and other items caused production to increase in businesses at regional and district centers. A. RURAL INFRASTRUCTURE FOR GROWTH AND POVERTY REDUCTION21 4.5 The provision of rural infrastructure has had a significant positive impact in many emerging Asian economies on growth and poverty reduction through increase in agricultural output, productivity and development of off-farm activities in rural areas. Market-determined incentives for agriculture and nonfarm activities are found to be necessary to induce a supply response but they are not sufficient to maximize the response. To do so, governments also needed intervene where markets failed, particularly in the areas of infrastructure. Similarly, infrastructure alone cannot induce economic growth but its absence is likely to constrain it. Empirical evidence also shows that agroclimatic potential and natural resource endowments influence both the level of infrastructure investment and the development response to additional infrastructure. In the areas of low potential, or where policy environment has not been favorable to private economic activity, the supply response to investment in infrastructure has been minimal. These are important lessons for Uganda's policy of liberalizing agricultural markets and for its strategy of rural infrastructure investment aimed at growth and poverty reduction. Recent changes in agricultural markets have to be continued, including restructuring of some of the processing industries and reduction in regulation of business development, supported by increased investment in rural infrastructure. 4.6 Studies of rural India, for example, show that a substantial part of the variation in availability of infrastructure is attributable to differences in agroclimatic potential.22 Nevertheless, road density was also a significant independent variable in explaining variation in aggregate agricultural output, and greater than the effect of price changes. Furthermore, commercial banks were shown to locate in areas with good agroclimatic potential and good infrastructure. Access to banking facilities had a positive impact on a number of things. Another study concludes that credit availability was associated with a modest increase in agricultural output and rural wages; with a large increase in the demand for fertilizer and in nonagricultural employment; an increases in the use of draft power (animal and mechanic); but a modest reduction in agricultural employment.23 Most importantly, credit availability had a strong positive impact on more profitable off-farm activities and employment. 20 Haggblade and Hazell (1989). 21 Goldstein, E. (1993). 22 Binswanger (1992) and Binswanger et al (1993). 23 Binswanger and Khandher (1992).  Infrastructure and Human Resourcesfor Growth and Poverty Reduction 61 4.7 Experience from East and Southeast Asia also suggests that a coordinated package of rural infrastructure-roads, telecommunications, electrification, water supply and banking facilities-is vital if agricultural growth is to succeed in stimulating rural nonfarm activities such as agroprocessing, commercial enterprises to produce farm inputs, basic consumer goods and services. China has probably been the most successful in implementing the strategy of providing a full package of rural infrastructure. This was possible through an unusual degree of administrative and fiscal decentralization, which empowered local government to take control of the provision and financing of the infrastructure. Taiwan (China) grew fast thanks to Japanese investment which produced a strong agricultural sector, extensive transport infrastructure and a base of literacy.24 Integrated rural development projects of the 1980s often failed to address the fiscal incapacity of local governments which diminished their potentially useful role, while central governments resisted delegation of control and financial resources to local levels, including independent resource generation. The ongoing decentralization in Uganda has so far assigned many of the maintenance functions to local authorities but the investment program is still in the central control. Similarly, the issue of decentralization of taxation authority, which seems to be an important element in successful provision of rural infrastructure elsewhere, has not yet been addressed. 4.8 The poor derive indirect benefits from rural infrastructure to the extent it stimulates economic activity and increases the demand for local labor. To improve their direct access requires either reducing the cost of infrastructure (appropriate standards, low-cost and labor-intensive technology), or reducing the cost of using the infrastructure (low-cost transport services, for example). As elsewhere in Africa, Asia and even in many cases in Latin America, the poor in Uganda tend to reside in areas of low agricultural potential, are largely illiterate, and lack basic infrastructure and social services. For the hard-core poor, access to social services and development of human capital are shown to be of the highest priority. Social sector investments tend to have a greater impact on income in the poorest regions than infrastructure investments, while the reverse is true in the better-off areas. However, a study of Bangladesh shows that infrastructure has a profound effect on the incomes of the poor.25 Although in Uganda, where poverty is extremely wide-spread, efficient, broad-based economic growth is the best means of lifting a large number of people from poverty, there are (and should be) targeted subsidies to poor areas, such as the Northern Reconstruction Project supported by IDA and other donors, to ensure provision of a minimum infrastructure for those who are likely to be left behind in the growth process. 4.9 Rural Roads. Perhaps the most critical of all rural production-related infrastructure is the rural road network. Rural roads are typically public goods best provided by the Government but their construction and maintenance can be contracted out to the private sector. It is important that local people have a voice in making road 24 Brautigam (1994). 25 Ahmed, R. and M. Hossain (1990).  62 Infrastructure and Human Resources for Growth and Poverty Reduction investment decisions. In Asia decentralization of road investments and maintenance has resulted in increased utilization of local resources, better supervision of construction work and improved maintenance. Apart from bicycles, rural Ugandans do not own many means of transport. Particularly women walk vast distances when performing their household duties or marketing their produce. Assessing the transport needs of the poor can only happen at the local level which requires decentralized planning and implementation and willingness to consider paths, trails and tracks as legitimate infrastructure investment. Credit facilities for transport investments tend to be even more limited than those available for agricultural production. 4.10 The problem with rural roads is that they tend to be either over- or under- designed. The former is often the case when high standards and capital-intensive methods are used in construction, while the latter is the case when they primarily perform as public works programs for short-term employment generation. Again, these lessons are useful for Uganda where responsibilities for the maintenance of rural roads are being decentralized and the involvement of local contractors in construction will increase. 4.11 Rural feeder roads in Uganda cover about 20,000 km, and consist mainly of earth or gravel roads. While they are often at least indirectly linked to the main road network, their use is very much location- and user-specific. Maintenance continues to be the main problem of this network, which in the future, could be alleviated by the ongoing administrative and fiscal decentralization. The central government's strategy proposes that 14,000 km will be brought to a fair level of accessibility by 1996. There is, however, no clear assessment what the appropriate size of the network should be but clearly its present condition is far from being satisfactory. 4.12 Other Infrastructure. One of the main findings of the studies of East and Southeast Asia is that areas with development potential need the full "package" of roads, electrification, telecommunications, financial services and water supply to get the full benefit of infrastructure investment. Furthermore, rural electrification has been found to have little impact on agriculture, but had a significant impact on the development of agroprocessing industries and farm services. Rural electrification does not, on its own, induce the development of rural enterprises, but the more developed an area is, the greater the impact of rural electrification is likely to be. 4.13 Rural Finance. The absence of a viable rural financial market is another constraint to the development of the rural economy. As shown above, availability of rural infrastructure attracts financial infrastructure. In Uganda, the financial sector is currently undergoing a major restructuring including privatization of the largest bank, Uganda Commercial Bank (UCB). This may lead to the closure of a large number of rural branches. Recognizing the importance of financial services to rural development, the Government has decided to carry out a study on the rural finance requirements immediately when the status of the branch network following privatization is known. The objective of the study is to determine a minimum set of locations where financial services should be available; institutional arrangements appropriate in providing these services; and  Infrastructure and Human Resources for Growth and Poverty Reduction 63 whether a subsidy or an incentive scheme would be necessary to ensure that the minimum coverage of service will be available. B. EDUCATIONAL ATTAINMENT AND HEALTH 4.14 Education. Educational attainment by the population over 16 years of age is a crucial factor in determining a nation's medium-term growth path. In East Asia and elsewhere recent studies have shown that universal primary education has been a significant factor contributing to high growth rates and substantial reduction in poverty. Evidence on the importance of education in determining economic well-being varies somewhat between countries in Sub-Saharan Africa. In Uganda, recent studies find strong benefits of education for household welfare in urban and rural areas in all regions of the country. However, in Uganda no schooling at all (no level completed) was reported by 43 percent of those in the bottom expenditure quartile nationwide while over 18 percent of the population in the top expenditure quartile reported no schooling (Table 4.1). 4.15 In spite of the dismal picture of educational attainment in Uganda, there has been some progress, even during the period of economic decline. Enrollment figures have increased (see the Statistical Annex for gross enrollment rates).26 Earlier enrollment figures available for Uganda were based on Ministry of Education surveys, which included only schools supported by the public sector. Figures from the 1992/93 Integrated Household Survey (IHS), which also include private schools, suggest much higher gross enrollment rates, including primary enrollment as high as 91 percent (99 percent for boys, 83 percent for girls). However, these figures include an unknown proportion of overage pupils and repeaters, and thus children's average attainment in primary education is likely to be much less than they suggest. The urban gross enrollment rate is 1.03 while the rural rate is 0.90. For the bottom expenditure quartile, the gross rate is 0.77, while that for the top quartile is 1.07.27 4.16 Drop-out rates are high and evidence from the 1992/93 IHS shows that they have increased over time. Of the primary cohort enrolled in 1986, 70 percent dropped out by P7 (females 75 percent males 64 percent). In 1975 only 10 percent dropped out by P7. Of the 1986 entering class who reached P7 and sat the Primary Leaving Examinations only 40 percent achieved admission to secondary school. For the top expenditure quartile, the gross enrollment rate for the secondary level is 24 percent while for the bottom quartile it is only 6 percent (Table X.8 in the Statistical Annex). In 1986 only 16 percent of students entering secondary dropped out. By 1991, 47 percent were dropping out in the same 26 In many countries net enrollment, which counts only children within the target age group as enrolled, is preferred. The proportion of children between 7 and 13 years of age in school in Uganda is 70 percent nationally, while urban net enrollment is 78 percent and rural 69 percent. Net enrollment for girls is 67 percent and that for boys is 73 percent. 27 See also Balihuta, A.M. and G. Ssemogerere, 1994, The Determinants of Access to Education and Their Implications for Poverty Alleviation in Uganda: An Analysis of the Integrated Household Survey Data 1992/93 and Related Studies, Working paper for the Uganda Country Economic Memorandum, World Bank Public Information Center, Washington, D.C.  64 Infrastructure and Human Resources for Growth and Poverty Reduction period of time. In short, more children may be entering school than before, but a higher proportion are dropping out. 4.17 Enrollment varies very strongly across geographical regions. For instance, Karamojong has very low enrollment (12 percent for females and 32 percent for males in Kotido). Children from poor families have lower enrollment rates than others. However, economic factors may not be the most important. In an analysis of the 1989/90 Household Budget Survey, it has been found that poverty was not significant in determining attendance once other variables including the educational attainment of the household head were included.28 4.18 There are very strong gender differences in enrollment in Uganda as in other African countries. Although most Ugandan children enter primary school, it is estimated that only 48 percent of boys and 29 percent of girls complete the primary cycle. There are a number of reasons for gender differences. First, parents have different aspirations for girls and boys. For instance, the Women's Needs Survey found that mothers value education for the daughters because it will make them better mothers rather than help them find employment. The employment most mentioned for girls was being a nurse, which was extremely unlucrative at the time. Secondly, there is some evidence in other East African countries that married daughters are less likely than married sons to remit cash income to their parents. While daughters do provide physical care and help for elderly parents, education may not be seen as so important for this. Both these reasons relate to parental demand and are hard for policy to address directly, but there are also supply-side factors militating against female education which could be addressed more easily. Girls who get pregnant in school, for example, are required to drop out and are not allowed to re-enroll at the same school after delivery. 4.19 The Education White Paper (1992) proposed that when fees were removed from primary education, attendance should become compulsory. However, compulsory school attendance for all children of the relevant age requires the cooperation and participation of parents and guardians. Even if coercive means were adopted it is unlikely that universal attendance would be achieved given the costs and the need for labor. 4.20 Differentials in education relate to quality as much as quantity. School facilities are run down mostly from poor construction and lack of maintenance. Between 1980 and 1990 there was a 114 percent increase in the number of primary school teachers and the number of government aided primary schools rose from 4,300 in 1980 to 8300 in 1992. The proportion of untrained teachers rose from 42 percent in 1982 to 49 percent in 1992. The majority of trained teachers are found in urban or pefi-urban areas. Only 15 percent of textbooks and instructional materials are provided by the Government. Most of the available materials are outdated. The 1989 school census showed that 15 percent of schools had a library but most of these libraries did not have any books. A recent study of 28 Kakande and Nalwadda (1993).  Infrastructure and Human Resources for Growth and Poverty Reduction 65 Table 4.1: EDUCATIONAL ATTAINMENT Percentage of Population over 16 Years of Age No Level PI to P4 P5 to P7 Sl to S4 S5 to S7 Further Proportion Completed Literate 16 to 25 years 19.4 25.8 37.8 14.4 1.5 1.0 73.7 26 to 35 years 27.8 21.1 31.2 12.6 1.3 6.0 67.1 36 to 45 years 36.7 23.4 24.4 9.7 0.4 5.4 57.6 46 to 55 years 52.4 21.5 15.4 7.3 0.2 3.2 42.3 Over 55 years 69.7 19.5 7.1 2.0 0.0 1.7 29.3 Male 20.6 25.6 33.1 14.7 1.5 4.6 74.7 Female 45.1 20.7 23.9 7.8 0.5 2.0 49.0 Urban 11.4 13.5 33.0 25.9 4.4 11.7 85.8 Rural 36.9 24.5 27.5 8.7 0.4 1.9 57.4 Expenditure quartiles: Bottom 43.1 24.2 24.9 6.3 0.5 1.0 50.2 Lower Middle 34.7 22.4 29.0 10.9 0.6 2.4 60.1 Upper Middle 26.9 21.9 31.5 14.8 1.2 3.7 68.5 Top 18.4 16.6 28.5 22.3 2.9 11.3 78.8 Source: Calculations from the 1992/93 Integrated Household Survey. Note: Literacy means reading and writing. education in Kibale showed that nearly all the primary schools in the district do not have enough classrooms and that the state of existing building is very poor. Many lessons take place outside under trees, especially at lower primary level. 4.21 Literacy. The ability to move into more remunerative off-farm employment, to adopt more productive but more risky and complex agricultural technology, or to make a successful transition to an urban livelihood is closely linked to literacy and to levels of education. In a review of the characteristics of the rural population across districts in Uganda, adult literacy correlates positively with low levels of poverty. On its own, adult literacy explains some 46 percent of the variation in the district poverty index. Accelerated growth in the next few years can only come from those who are now between 16 and 55 years of age but of whom a large number are illiterate and therefore unable effectively to receive extension messages, initiate local business development, and so on (Table 4.1). Although experiences from literacy programs have not been too positive in general and hence universal primary education is considered the first-best policy option, the Government should seriously consider outreach programs to attack illiteracy nationwide. This should be done without delay in order to equip Ugandans with basic literacy and numeracy skills to be better able to participate in and bring about the growth required for poverty reduction.  66 Infrastructure and Human Resources for Growth and Poverty Reduction 4.22 Health. Health indicators in Uganda are very poor. Uganda compared favorably to other Sub-Saharan African countries in the 1960s, but has since dropped in standing. While other countries progressed, Uganda stagnated. Although economic decline certainly played a major part in this decline some aspects of health can be improved at low cost and do not need to wait for further economic recovery. For example, other countries have raised life expectancy even when incomes were low and not growing particularly fast. 4.23 Although there are data on morbidity, clinical data suffers from sample selection problems, and survey data are inaccurate (respondents' reporting of their health has a strongly subjective element). Recent mortality data also suffer from underreporting. This analysis therefore concentrates on two measures that are relatively robust: anthropometric indices of children and the mortality ratio of children of surviving mothers. 4.24 The 1991 Census estimates of life expectancy are based on the reported mortality of children of surviving mothers, with appropriate adjustments. They suggest that health indicators have improved little if at all since the 1960s (Table X. I in the Statistical Annex). Nationally infant mortality is 122 per 1,000 births, while child mortality (under five years) is 203 per 1,000 births. The expenditure-based regional poverty profile is confirmed by child mortality data-Kampala, one of the wealthier regions, has the lowest child mortality rate, while Kitgum in the north has the highest rate. But Mbarara, which is relatively wealthy in terms of household expenditure, has a higher child mortality rate than the national average. As shown below, educational attainment may at least partly explain this finding. 4.25 The diseases that Table 4.2: CMLD MORTALITY cause death are not clearly (aio of children who have died) understood by surviving relatives who are often too Mother's Age sensitive when asked. < 20 21-25 26-30 31-35 3640 > 40 However, data are Location: available on the causes of Rural 0.12 0.15 0.18 0.20 0.20 0.31 death in clinics. These data Urban 0.09 0.11 0.13 0.15 0.17 0.27 suggest that malaria, Expenditure quartiles: diarrhea, and measles are Bottom 0.13 0.17 0.17 0.19 0.19 0.33 the major killers of Lower-middle 0.15 0.13 0.16 0.19 0.20 0.32 children. To analyze the Upper-middle 0.07 0.17 0.19 0.20 0.19 0.30 pattern of child mortality, Top 0.11 0.13 0.16 0.19 0.20 0.30 the proportion of children Matemal education: who have died but were None 0.10 0.17 0.20 0.21 0.22 0.34 born to surviving mothers Some primary 0.11 0.15 0.16 0.20 0.18 0.25 is used. This indicator has Some secondary 0.04 0.08 0.11 0.09 0.14 0.11 some limitations; fo r Some further 0.00 0.03 0.07 0.05 0.08 0.09 example, it is likely to omit many cases of pediatric Source: Calculations from the 1992/93 IHS Aman bcauses of tpedirc Note: The above calculations use the proportion of children, AIDS because mothers who have since died, born to surviving mothers.  Infrastructure and Human Resourcesfor Growth and Poverty Reduction 67 who pass AIDS to their children are likely to die themselves. Also the age of the child at death is not known. But, it has the advantage of allowing the analysis of mortality across the whole child population. 4.26 An important finding from the analysis of the 1992/93 Integrated Household Survey data is that mortality is drastically lower for children of educated mothers; it is somewhat lower, but not dramatically so, for the economically better off (Table 4.2). But, even the top expenditure quartile suffers from significant child mortality. There is also a big difference between urban and rural areas: children of urban mothers have a much better chance of survival. 4.27 A multivariate analysis confirms the overwhelming importance of women's education in reducing child mortality and shows that measures of mothers' beliefs about health are independently important29. In general, education may raise incomes and increase women's bargaining power within the household, but the evidence strongly suggests that its effects on mothers' understanding about health are most important. Other studies have revealed a number of beliefs that influence child health, including beliefs about children's feces, the practice of excising "false teeth," and the role of oral rehydration therapy. This body of work implies that in order to improve child health in Uganda, the level of public understanding about health must be raised. While education is an effective way of accomplishing this, less-costly methods can be used at the same time. China, for example, achieved a great deal by delivering a few very simple health messages to its population through the media and political institutions. 4.28 Although adult mortality is an extremely serious issue in Uganda, data are harder to obtain. There is no doubt that adult mortality is very high and likely to increase because of the high rates of IRV infection. A serious effort has been made to inform people about the AIDS epidemic, and data from the 1992/93 IHS show that almost everyone in Uganda has heard of the disease, although not everyone understood it completely. Other major adult killers include malaria and tuberculosis-both of these are on the increase and are more likely to be transmitted in crowded living conditions. Both can be treated quite effectively, but the poor are less able to have access to adequate treatment. 4.29 Caring for the ill imposes a large cost. Because much care is given within the household and because the productive value of women's time is often overlooked, it is easy to discount the large amount of resources already being absorbed by care for the sick. Most cost estimates assume that the sick require hospital treatment and arrive at frightening and unfeasible numbers. While the costs incurred in providing domestic care is not known, they are probably high in relation to total household income. Studies of health expenditure have revealed that transport is a major problem. One of the attractions of the traditional sector is the proximity of healers.30 29 McKinnon (1995). 30 Wamai (1993), a study of the determinants of patient compliance with tuberculosis regimes, find that transport costs were a crucial constraint for poor patients in Kampala.  68 Infrastructure and Human Resourcesfor Growth and Poverty Reduction 4.30 Nutrition. Stunting (low height for age) and wasting (low weight for height) are the two most commonly used indicators of protein energy malnutrition among children. These markers mirror society's state of deprivation-they result from lack of food and exposure to illness. Recent evidence indicates that the effects of even moderate levels of protein energy malnutrition can be devastating. More than 56 percent of all deaths of children under five years are caused by effect of malnutrition on infectious diseases. In other words childhood diseases such as measles, diarrhea, or acute respiratory infection are more fatal to those children who have moderate protein energy malnutrition compared with those who do not. The future well-being of malnourished children is likely to be severely compromised. Longitudinal studies indicate that children who were stunted in their preschool years are likely to perform poorly in primary schooling and are likely to earn much less when they join the labor force. Thus, the economic benefits from improving nutrition at an early age are substantial. 4.31 Uganda is characterized by relatively high rates of stunting, but low levels of wasting (Tables X.3, X.4, and X.5 in the Statistical Annex). In the lowest expenditure quartile 44 percent of children are stunted, while in the top quartile 37 percent suffer from stunting. The figures for wasting are 7.3 percent and 3.8 percent, respectively. The age distribution of malnutrition is very marked: after about six months children suffer wasting, and their height-for-age begins to suffer. After the age of two wasting is no longer a problem (indeed, for children older than four years, Uganda's level of wasting falls within international reference standards), but height-for-age remains low. In other words children experience nutritional deprivation during early childhood, and these episodes lead to permanently reduced stature. 4.32 Nutritional deprivation may come from food shortage in the household, inappropriate methods of food preparation for young children, or episodes of illness. The fact that older children are not likely to suffer from wasting (even in the drought year of 1992/93), suggests that diseases (which are most severe for newly weaned children) and poor food preparation may be more important than food shortages.3" Low expenditures are important in determining wasting but not stunting. 4.33 Because stunting is more prevalent in Uganda and because disease is a major contributor to stunting, disease probably plays as important a role in mass child malnutrition as does access to food. Hence what is needed is an integrated strategy that addresses health and nutritional issues jointly. 4.34 Adult nutrition has not been as extensively studied as child nutrition. However, some recent work has found that children who are malnourished are much more likely to have mothers who are also malnourished than children who are adequately nourished. This suggests that nutritional and health problems in children reflect a more pervasive problem in the household. 31 Jitta and others; McKinnon (1995).  Infrastructure and Human Resources for Growth and Poverty Reduction 69 C. PUBLIC AND PRIVATE SECTOR ROLES IN SOCIAL SECTOR PROVISION 4.35 The Rationale for Public Involvement. In addition to primary education, there are very good reasons for public involvement in the health sector. First, many preventive measures have the character of a public good. Some areas such as immunization and AIDS control are receiving attention in Uganda but others, such as malaria control need more attention. Second, treatment of communicable diseases (which are currently causing most of the deaths in the country) has positive externalities, because a person who is cured cannot transmit the illness to another. Moreover, partial treatment such as short courses of drugs has strong negative externalities. Resistance to anti-malaria drugs and antibiotics is emerging as a major health problem in Uganda. Third, the death of one family member can have catastrophic effects on surviving members. Uganda is of course unusual in the extent of adult mortality. Finally, the failure of insurance markets means that people cannot insure themselves against their possible needs for major medical expenditure. 4.36 The care of an AIDS patient can be very expensive. This argument is illuminated by the recent Health Expenditure Survey32 which found that few households had savings available for health expenditures and that strategies involved the sale of subsistence crops, short-term borrowing, and the sale of cash crops. Sales depend on seasonality and a ready buyer; access to borrowing depends on friendship and reciprocity networks. Land sales were also found, particularly where education was low. 4.37 The arguments discussed above give a rationale for public subsidy and regulation but not necessarily for public provision. However, the ability of the public sector to regulate the quality of the private sector is very limited in Uganda. It would also be very difficult to ensure that subsidies to private health actually reached the patient. The authorities already face a considerable challenge in controlling quality and eliminating illegal charges within the public sector. Hence the most realistic way of improving the health services available to most Ugandans is the improvement of facilities within the public sector. This needs to be combined with improving the information available to patients in both sectors. In education, many of the same arguments apply. In particular, education is a very effective way of conferring an asset (human capital) on children which, unlike land, cannot be expropriated. 4.38 Another important public sector role is the enforcement of standards. In the health sector, there has been much public controversy about the presence of large amounts of expired drugs. Where advice is provided so much by people in shops (mostly not qualified pharmacists) it is in practice very difficult to regulate prescription practices. In addition it has been found that even in the public sector pharmacists practices leave much to be desired. In education, national examination bodies provide quality control. Nutrition and sanitation may also be subject to government regulation. In colonial times households were required to build latrines and there is evidence that this is still enforced in some areas. 32 Barton and Bagenda (1993).  70 Infrastructure and Human Resourcesfor Growth and Poverty Reduction 4.39 The Incidence of Public Expenditure. The decline in health services during the period of political instability caused a movement into the private sector.33 People are more likely to use the private than the public sector. Use of public facilities is more frequent among the poorer households than among others. This suggests that public facilities, rightly or wrongly, are perceived as inferior (another reason for the pattern may be that charges are lower but queues longer at public facilities and the better-off pay to save time). Survey data on the "informal" health sector are likely to be under-reported. Most communities do report having a traditional healer accessible, which suggests that demand for their services is considerable. In addition self-treatment is extensive, including the collection of herbs, the use of purchased drugs and even the domestic administration of injections. 4.40 A significant part of education is privately financed and managed. However, much publicly managed education has a considerable private component of both management and financing, as schools often charge fees greatly in excess of the statutory fees. Fees are used to supplement teachers' salaries and developmental activities. In 1991 for secondary schools 74 percent of developmental expenditure and 56 percent of recurrent expenditure were provided by parents. 4.41 The fiscal data indicate a significant increase in the shares of spending going to health and education during structural adjustment (Table 4.3). It should also be noted that some important recurrent costs are included in the development budget because they are mainly donor-financed, including the Expanded Programme of Immunization and the Essential Drugs Programme. Nonetheless, government expenditure on education, for example, remains at about 2 percent of GDP, whereas 5 percent of GDP is more typical for Sub-Saharan African countries. Furthermore, public expenditure per student is skewed towards beneficiaries at the higher levels of the system. 4.42 However, much of this increase in recurrent expenditure has been devoted to paying increased salaries to teachers and health workers. These increases should help improve the quality of education and health services. The central government has limited capacity to monitor the spending actually occurring in health facilities. In future, with much primary spending decentralized, the center's capacity to achieve further increases in the shares of spending on primary health and education will be dependent on the cooperation of the districts, or on the ability to control districts' decisions. 4.43 The expenditure-based definition of poverty is used to examine incidence of expenditure in two ways using the 1992/93 IHS data (Tables X. 14-X. 16 in the Statistical Annex). First, the proportion of people in each expenditure quartile who are receiving the service is calculated. Second, the proportion of people receiving the services who are in 33 Table X.14 in the Statistical Annex shows the use of health facilities in the last thirty days as reported in the 1992/93 IHS.  Infrastructure and Human Resourcesfor Growth and Poverty Reduction 71 Table 4.3: RECURRENT EXPENDITURES 1988/89 1989J90 1990191 1991/92 1992/93 In Millions of U Sh: Ministry of Education 8,576 11,237 16,439 36,361 38,204 Ministry of Health 1,846 3,439 4,832 9,943 12,064 Mulago Hospital 583 1,057 1,548 3,028 4,341 Makerere 1,266 2,212 2,763 6,361 7,270 Percentage Shares: Ministry of Education 16.8 12.7 16.1 17.7 18.0 Ministry of Health 3.6 3.9 4.7 4.8 5.7 Mulago Hospital 1.1 1.2 1.5 1.5 2.1 Makerere 2.5 2.5 2.7 3.1 3.4 Source: Uganda Computing Services Note: Thc above data do not include the health and education departments within the Ministry of Local Government. Actual data for these departments are not readily available; however, from the budgeted estimates, approximately 1.5% for the earlier years to about 4.5% for the later years could be added. each quartile is obtained. The first gives an intuitive sense of how likely poor people are to receive public services, while the second shows the distributional impact of subsidies to these services. In primary education, for example, children in the bottom expenditure quartile go disproportionately to the government-financed and/or managed schools, while both non-profit and commercially run primary schools have their pupils from better-off families. In health services, the poor make about as much use of public outpatient facilities as the nonpoor. Hence, subsidy to these services is received about as much by the poor as by the nonpoor. For subsidies in education, the story is similar. However, poor children have lower enrollment than others, while poor families have a higher proportion of children than others. These two effects balance out so that roughly the same proportion of people are in publicly-financed schools in all expenditure groups. 4.44 Existing Policy Initiatives. The Education White Paper (1992) rightly makes the following recommendations: * changing the structure of primary-junior secondary-senior secondary from 7-4-2 years to 8-3-2 years to allow for increased teaching of vocational subjects. * the possibility of parents or guardians paying in kind (materials, labor or food), rather than cash. * adequate facilities for girls in post-primary institutions to allow for balanced enrollment-head or deputy head of all educational facilities should be a woman and there should be accelerated registration and training of female teachers, tutors, and lecturers.  72 Infrastructure and Human Resources for Growth and Poverty Reduction * The Education Policy Review Commission recommended that Government should allocate at least 20 percent of recurrent budget to education. Local government should raise resources for education through taxation. The paper also discusses the following points which need further review: * abolishing government charges for primary tuition at a rate of one level per year. This was recently discussed by the Constituent Assembly and rejected as an item in the constitution. The issue now being discussed is when to grant free primary education in terms of need, and whether district administrations and Government should provide bursaries to some of the most needy and deserving children. * schooling should be strongly oriented towards vocational preparation-it should be prevocational in upper primary and vocational at secondary level. 4.45 In health, the Three Year Health Plan Frame and the White Paper on Health Policy Update and Review outline a strategy, involving concentrating on the most cost-effective ("essential") interventions, increased government funding, and cost-sharing. The Ministry of Health has identified an "Essential Health Package for Uganda," including malaria control, maternal and child health, family planning, immunization services, and control of sexually transmitted infections. While these principles remain in place, decisions on cost- sharing have been decentralized. The executive control of district health committees are being increased and all the districts have been required to produce health plans. The central authorities have urged the prioritization of primary and preventive care. This has been a long-standing recommendation for both health and education but little has been achieved in the actual shifting of spending toward primary services. It is felt that the decentralization is increasing the transparency of the sector and will make abuses more difficult. However, public confidence in the health profession remains to be restored. D. A WAY FORWARD IN HUMAN RESOURCE DEVELOPMENT 4.46 As argued above the public sector has a crucial role to play in both health and education. The Government of Uganda recognizes this and is committed to increasing the resources available for health and education. Despite improvements, the volume of public resources provided to these sectors remains low and should continue to rise both in real terms and proportionately. 4.47 The AIDS epidemic increases drastically the need for palliative care and also poses an enormous challenge to preventive medicine and education. For this reason Uganda should aim at a higher share of health than the typical developing country. While the progress made so far is encouraging, a share of health in the recurrent budget of 8 percent  Infrastructure and Human Resourcesfor Growth and Poverty Reduction 73 is not sufficient for Uganda. The balance of public resources should move further in favor of the primary services. Tertiary medical care should be publicly supported only where the referral system is effective so that the majority of the population has access to it when needed. This is a major area of policy reform in Uganda. 4.48 There are a number of illnesses, such as malaria, AIDS and tuberculosis, where preventive measures are badly needed. Government and NGOs have begun to focus AIDS education on those in the "window of hope" aged between 5 and 15, a group with little AIDS. However, the distinction between preventive and curative care is less clear-cut than often thought: cure of a tuberculosis patient reduces the risk that they will infect someone else. Moreover, only a medical system which offers curative care will win the trust of patients. Once this trust exists, preventive care can be pursued by offering advice in the course of curative treatment. The real need is therefore to improve both preventive and curative primary care (for those diseases which are affordably treatable), often using the same institutions to do both. 4.49 Given the high rates of child mortality, discussion of health in developing countries has focused on programs of maternal and child health. In Uganda, there is a paramount need to improve adult health. This involves both the prevention and cure of disease and the better treatment of accidents and disability. Similarly, adult education requires much greater attention. Some preventive actions are cheap. For instance, the media and the local government structure could be used to spread messages about health. Evidence from the 1992/93 IHS suggests that the Resistance Council network is so far little used for this. 4.50 Raising salaries is almost certainly a necessary condition for improved quality of social services. However, it is not a sufficient condition; many observers agree that the ethos of public service has been damaged by the prolonged period of economic decline and both ethical and professional standards will need to be restored. 4.51 In education, the main problem is the high number of drop-outs and repeaters, probably due to the low quality of education, rather than inadequate numbers of school places. The problem has become more serious over time. The paramount need is to improve the quality of teachers and the availability of books. In 1992 the Government launched a Primary Education Reform Program, supported by USAID and the World Bank, with these objectives in mind. (A mid-term review of the USAID supported aspects of the program is being carried out in 1995.) With a well-trained and well-monitored cadre of teachers and an adequate supply of textbooks other constraints such as physical facilities and curriculum would be far easier to address. There is a significant gap between male and female enrollment but not such a large difference in access to health care. In both sectors, however, much could be done to make the services more user-friendly for women. Officials in health and education need to be alerted to the aspects of service provision which militate against full female participation. 4.52 All the above concerns can conceivably be helped by decentralization. However, this cannot be taken for granted, although local committees may be in a better position to  74 Infrastructure and Human Resourcesfor Growth and Poverty Reduction enforce honest accounting and conscientious professional practice than an official in an under-resourced central ministry. However, many observers are concerned that the standards of district authorities vary, from very good to very poor, and that in some cases the districts may actually take less equitable decisions than central government. The central government should therefore clearly enunciate a set of minimum standards of service provision which the districts are expected to achieve, with some sanctions available for authorities who fail to achieve the standards. 4.53 User charges in both health and education are currently under discussion. In health, the White Paper advocated the introduction of user charges, but the current policy is to leave the decision to the districts. Despite a strong economic case for subsidizing health care and education in Uganda, public resources are extremely constrained. Hence for health, the decentralization of the decision about user charges to the local level is sensible, as user fees are likely to work effectively in improving services if they are controlled by the local level. 4.54 In education, it is worth considering targeting subsidy to deprived areas and to vulnerable children within the area. The Government is also planning to target P4-7 to reduce drop-outs. This suggests that it sees education as a merit good rather than a vehicle for redistribution. Some schools are already spontaneously remitting fees from poor children but it is not thought to be an extensive practice. Also, experience in other countries suggests that the authorities should focus on providing textbooks and training teachers as high priorities. Communities are often more willing and able to pay for structures. Because of externalities, it is important to get the most able people into secondary and tertiary education and therefore to offer scholarships to this end. Older students should not be discriminated against. 4.55 Ensuring review of the quality of social services offered by the private sector is an import government responsibility. Quality control can be achieved in the education sector by a well-administered examination system. In health, the limited information available to patients provides a case for giving priority to importation of cheaper generic drugs. It is known that many doctors work in both sectors. Unfortunately, the effect of prohibiting this practice might well be to worsen the already serious brain drain. The most promising avenue for stopping the illicit diversion of resources seems to be the active involvement of the district health committees. The authorities are acknowledging the role that can be played by traditional healers and seeking to educate and integrate them into the health system.  ANNEX I POVERTY UPDATE   ANNEX 1 POVERTY UPDATE 1. Poverty has many dimensions. At the personal level, people may be deprived of adequate nutrition, good health, or education. Socially, people may be denied human rights, citizenship, or access to social networks. Cultural values and beliefs may make some people disadvantaged, while a lack of political voice or physical insecurity impoverishes others. Economic factors, such as low incomes, few assets or little access to markets or public services, can force people into poverty. Poverty is also dynamic: households and people move in and out of poverty over time, even seasonally. Some people are more vulnerable to poverty than others; a single incident, such as a cattle raid in eastem Uganda, can start a downward spiral. 2. This annex examines the status of and changes in poverty in Uganda. It focuses mostly on poverty defined in economic terms. (Social indicators related to health, nutrition, education, and so on are discussed in chapter 4). The principal new source of data on poverty since the previous Country Economic Memorandum, Growing Out of Poverty (which is also a poverty assessment on Uganda) is the 1992/93 Integrated Household Survey, which will be used here. This information is supplemented by other primary data and secondary sources. Although important, issues such as variability and vulnerability cannot be adequately addressed in this report, but several noneconomic aspects of poverty are discussed in a background paper for this report.' 3. The main findings of this annex are: * Poverty has not yet fallen substantially in Uganda, but hard-core poverty has been reduced. * The poor are predominantly rural; the east and the north are the poorest regions. * The poor grow proportionately the same amount of cash crops as the nonpoor and proportionately more coffee in the central region. * Domestic terms of trade for cash crops have improved because of liberalization. This change has benefited the poor as well as the nonpoor. * Emerging export demand for a number of food crops has led to a prompt supply response, similarly benefiting the poor as well as the nonpoor. * Production of other food crops has stagnated in the absence of a major boost in demand and because of inefficient technology. * The urban-rural gap has widened slightly. Bevan P. and A. Sseweya (1995), Understanding Poverty in Uganda: Adding a Sociological Dimension, a working paper on poverty in Uganda for the CEM, available at request from the World Bank Public Information Center, Washington, D.C.  76 Annex I Poverty Update * Women-headed households are not poorer than other households. A. DIsTRIBuTIoN OF WELFARE AND POVERTY 4. The measure of welfare Table A.1: DISTRIBUTION OF WELFARE used is the ratio of household expenditure per adult equivalent Welfare measure to the poverty line. The cut-off Distribution percentiles (highest value in each percentilefa point separating the poor and the 99% 4.643 nonpoor is thus one (Box A.1 95% 2.510 describes the derivation of the 90% 1.916 welfare measure). According to 75% 1.289 61% 1.000 this measure, 61 percent of 50% 0.850 Ugandans are classified as poor 25% 0.559 (Table A.1). The median 10% 0.381 expenditure in each of the four 5% 0.300 quartiles is very close to the mean, I % 0.193 except in the top quartile, in Mean and median values of the welfare measure which the mean is driven upward within quartiles by several very high observations. Quartile Mean Median The highest expenditure in the Qi 0.40 0.41 ninety-ninth percentile is 4.6 times Q2 0.70 0.70 Q3 ~1.05 1.03 greater than the poverty line, Q3 2.18 1.77 while the highest expenditure in the seventy-fifth percentile is only a Welfare measure = household expenditure per adult 1.3 times that of the poverty line. equivalent/poverty line. The poorest 10 percent of the population consume barely more source: Calculationsfromthe1992/93JHS. than one-third of the amount consumed by people at the poverty line.2 5. Choosing a poverty line is always somewhat arbitrary, especially in a country like Uganda where malnutrition is not primarily a result of food shortage at the household level. In addition, as available expenditure data are less than perfect, the relative picture is more reliable than the absolute one. Using expenditure quartiles allows us to see the relative picture and allows for more differentiation beyond poor and nonpoor. Because poverty is widespread, the characteristics of these two groups tend to be very similar as many people above the poverty line are only slightly better-off than those below it. But absolute measure is needed for intertemporal comparisons. The rest of the chapter will refer to the bottom quartile as the ultra poor and the two lowest quartiles as the poor. 2 The average household size in the 1992/93 Integrated Household Survey is 4.8 people per household, which is 3.9 in terms of adult equivalent. This finding is in line with the 1991 population census.  Annex 1 Poverty Update 77 Box A.1: Calculation of the Poverty Measure The poverty measure used here is the ratio of total household expenditure per adult equivalent to a regional poverty line. The numerator and the denominator of this measure are defined as follows. The Numerator. First, total expenditure is estimated for each household. This total includes the imputed value of home-produced food and owner-occupied dwellings. Then the size of the household is defined in adult-equivalents. Because children consume less than adults, they are given less weight in the adjusted measure of household size. The scale used is based on measures of nutritional requirements: 1 Age 0-11 mths 1 2 3-4 5-6 7-9 10-11 12-13 14-15 16-17 18+ Weight .27 .37 .45 .52 .62 .70 .73 .80 .88 .95 1.00 The Denominator. The poverty line is based on a food price index. First, the cost of 2,200 calories from a given food basket is calculated in each region for urban and rural households for a two- month period. This is the food poverty line. The basket is held constant across the country but regional price differences are taken into account. It may be possible to achieve the calorie level by substituting to cheaper crops (as people do in the north), but it is assumed that such substitution is itself a symptom of poverty and that people would prefer the more expensive crops if they could afford them. This gives a food poverty line. Essential nonfood expenditures are then added, based on the consumption of nonfood items of the households whose total expenditures are equal to the food poverty line. 'Since children are particularly at risk, it may be argued that their weights should be higher than those used here. However, most of the results are probably not very sensitive to the choice of equivalence scales, the main exception being the relationship between demographic structure and poverty. Source: Method adapted from Ravallion and Bidani (1994). 6. The Rural-Urban Gap. Rural households are poorer than urban households on average FORU ALEBYE ENINF1I.UJI (Figure A. 1). This finding holds even when rural expenditures are 60 deflated by rural prices (which is are lower than urban prices) and 40 the equivalence scales used make * 30 a strong adjustment for children 2O.. (rural households have more l0 children than urban households). I'0 If these adjustments were not Bsan LOW LWr Tcp made, the urban-rural difference Mce Mtue would be even more Q O pronounced.3 Twenty-seven s* PAW oU 3 However, the existence of the urban-rural gap in the labor market has been challenged by some authors recently (Jamal and Weeks 1993). While these data do not tell anything about the labor market, they do show that an urban-rural gap exists in terms of welfare.  78 Annex I Poverty Update percent of the rural and only about 11 percent of the urban population are in the lowest quartile, while 22 percent of the rural population and 49 percent of the urban population fall into the top quartile. The population is fairly evenly distributed among the four quartiles in rural areas, whereas in urban areas most of the population are in the two upper quartiles. (Gini coefficients are given in Table A.7). 7. The western and the central regions of Uganda are relatively better-off than the north and east, even though the west suffered a drought at the time the survey was carried out (Table A.2). The western region may have so far been less affected by AIDS than the central region, which may help to explain its relative affluence despite the drought. 8. The north is very poor. This result is somewhat magnified by the choice of the poverty line which is constructed using a national basket of goods so that a constant share of different goods in spending is assumed across different rural areas.4 The crops most important in the north are relatively cheap, and thus one could argue that a given amount of spending buys more in terms of welfare. To some extent different crops simply reflect different climatic conditions. However, in Uganda some of the differences in crops consumed reflect relative prices and consumer incomes. An example is the widespread substitution of cassava for matooke in the central region in recent years. 9. A clear pattern Table A.2: DISTRIBUTION OF POPULATION BY REGION also emerges in the AND BY EXPENDITURE QUARTILES distiibution of poverty In Percent across districts (see the Region Statistical Annex). The Central Eastern Western Northern relative affluence of Kampala (85 percent of Expenditure Quartiles: 100 1(X 100 100 the population falls into Bottom 17 29 18 39 the two upper quartiles) Lower middle 22 27 23 29 and Mbarara (73 percent Upper middle 27 25 28 18 in the two upper Top 34 19 31 13 quartiles) and the poverty of Karamojong, Source: Calculations from the 1992/93 Integrated Household Survey. that is, the Kotido and Moroto districts (86 percent and 70 percent in the two bottom quartiles, respectively) stand out very clearly, as does the relative poverty of Kitgum (91 percent in the two lowest quartiles). Kitgum has been badly affected by civil unrest. 10. On average the poorest are households with older heads. This may partly explain why the heads of poorer households are typically less educated. Similarly better-off households tend to have heads whose parents were more educated. For example, among the most affluent quartile a third of household heads had literate mothers, while among the poorest the proportion was less than 10 percent. On average, poorer households are 4 Following Ravallion and Bidani (1994).  Annex I Poverty Update 79 markedly larger, as measured by the number of adult equivalents. They also tend to have a higher proportion of dependents, both young children and other adults. 11. Female-Headed Households. Contrary to the earlier findings, female-headed households do not seem to be poorer in expenditure terms than other households in Uganda. Data from some other Sub-Saharan African countries show a similar result. One reason is remittances from a migrant husband. Households with more than one woman are, however, markedly poorer than others, a sign of the effects of polygamy. Again, there may be a third factor underlying this result, such as polygamy being more prevalent in poorer areas. While a more or less equal proportion of households in each expenditure quartile are female-headed, disaggregation by the marital status of the head of household reveals that households headed by widows are common in poorer quartiles. The opposite is true of other types of female-headed households, such as divorced women. 12. Although female-headed households as a group are not poor when assessed by consumption or income, they are disadvantaged on several social indicators, with lower school enrollment for girls, higher mortality and lower usage of curative health care. One consequence of these gender differentials is that female-headed households are markedly less educated than their male counterparts. More than half of the female heads had received no schooling compared to less than a quarter of their male counterparts. B. SOURCES OF INCOME 13. The 1992/93 Integrated Household Survey (IHS) is the first source to provide micro-level data on income in Uganda. As expected, agriculture accounts for most of the Table A.3: MAJOR INCOME SOURCES IN UGANDA Quartile Bottom Lower Middle Upper Middle Top ALL OF UGANDA 100.0 100.0 100.0 100.0 Earned income 69.5 78.0 80.1 86.5 Agriculture 53.4 56.1 53.4 38.3 Business 8.1 10.3 14.2 27.0 Employment 6.4 9.9 11.1 19.7 Government employment 2.1 4.2 4.6 9.6 Private employment 4.3 5.6 6.5 10.1 Residual earned income 1.5 1.8 1.4 1.4 Unearned income 30.5 22.0 19.9 13.5 Rent 2.8 1.6 1.9 1.9 Remittances 21.2 16.4 14.9 9.7 Transfers 0.7 0.1 0.2 0.1 Dowry 3.9 2.4 1.7 1.1 Inheritance 1.9 1.5 1.3 0.8 Source: Calculations from the 1992/93 Integrated Household Survey.  80 Annex I Poverty Update Table A.4: MAJOR INCOME SOURCES IN UGANDA (Urban/Rural) Quartile Bottom Lower Middle Upper Middle Top URBAN 100.0 100.0 100.0 100.0 Earmed income 70.0 77.2 75.3 86.1 Agriculture 17.9 15.8 9.9 5.7 Business 19.3 27.9 29.4 42.8 Employment 29.3 31.0 33.9 36.3 Government employment 8.3 10.2 11.4 16.5 Private employment 21.0 20.8 22.6 19.8 Residual earned income 3.5 2.6 2.1 1.2 Unearned income 30.0 22.8 24.7 13.9 Rent 5.2 3.0 5.0 3.7 Remittances 22.0 16.0 18.0 9.4 Transfers 0.3 0.2 0.3 0.1 Dowry 1.5 1.3 0.4 0.3 Inheritance 1.0 2.3 1.0 0.5 RURAL 100.0 100.0 100.0 100.0 Earned income 69.4 78.2 81.1 86.7 Agriculture 57.3 62.5 62.4 58.6 Business 6.9 7.5 11.1 17.2 Employment 3.9 6.5 6.4 9.4 Government employment 1.5 3.3 3.2 5.3 Private employment 2.5 3.2 3.2 4.1 Residual earned income 1.3 1.7 1.2 1.5 Unearned income 30.6 21.9 19.0 13.3 Rent 2.6 1.4 1.2 0.8 Remittances (private) 21.1 16.4 14.2 9.9 Transfers (government) 0.8 0.1 0.2 0.1 Dowry 4.2 2.6 2.0 1.5 Inheritance 2.0 1.4 1.3 1.0 Source: Calculations from the 1992/93 Integrated Household Survey. Note: The quartiles are defined with reference to the national population: the cut-off points for each quartile are the same for all regions. Thus, the poorest quartile in the northern rural region will include more than 25 % of the northern population, and the poorest quartile in urban areas will include less than 25 % of the urban population. income of the poor and the nonpoor (Table A.3). In urban areas agriculture is also a significant source of income for those in the bottom quartile (Table A.4). Within rural areas, dependence on agriculture does not vary markedly with economic well-being. Instead, poorer people depend more on unearned income, while more affluent people have higher nonagricultural incomes. Remittances account for more than one-fifth of the total income of the poorest people. This dependence suggests that Uganda has an informal welfare system, with more affluent households transferring resources to less prosperous ones. Remittances are an important source of income for all expenditure groups. This informal welfare system is therefore more complex than simply a case of the better-off remitting to the poor. It would be possible to calculate the net transfers received in each quartile from the 1992/93 IHS, but these calculations are beyond the scope of this report.  Annex I Poverty Update 81 Table A.5: AGRICULTURAL REVENUE SOURCES IN UGANDA Quartile Bottom Lower Upper Top Middle Middle Crops 95.0 94.9 95.2 92.4 Grains 26.3 21.3 19.4 15.9 Maize 8.6 7.8 7.4 7.1 Rice 1.1 1.2 1.3 1.0 Millet 8.4 7.1 6.1 4.8 Sorghum 7.4 5.0 4.0 2.9 Other 0.9 0.2 0.6 0.1 Grains Matooke and tubers 41.4 45.2 49.4 52.4 Matooke 8.6 12.7 18.0 21.4 Sweet potatoes 15.2 15.5 13.8 15.0 Cassava 16.2 15.5 15.8 14.3 Other tubers 1.4 1.5 1.8 1.7 Pulses, beans and nuts 17.5 18.5 17.0 16.0 Beans 8.6 10.1 10.0 9.6 Peas 0.8 0.5 0.3 0.3 Groundnuts 4.8 4.5 4.2 4.1 Cow peas 0.2 0.4 0.2 0.2 Simsim 2.2 2.4 1.6 1.4 Other pulses, beans and nuts 0.8 0.7 0.7 0.4 Fruit 2.2 2.2 2.2 2.2 Sugar cane 0.3 0.2 0.1 0.2 Other fruits 2.0 2.1 2.1 2.0 Vegetables 1.4 1.4 1.2 1.3 Onions 0.1 0.2 0.2 0.2 Other vegetables 1.3 1.1 1.1 1.1 Cash crops 5.9 6.1 5.8 4.5 Coffee 3.7 3.8 3.4 3.0 Cotton 1.6 1.2 1.6 0.9 Tea 0.0 0.1 0.1 0.2 Tobacco 0.5 1.0 0.6 0.3 Other cash crops 0.1 0.1 0.1 0.1 Other crops 0.3 0.2 0.1 0.1 Animal revenue 5.0 5.1 4.8 7.6 TOTAL 100.0 100.0 100.0 100.0 Source: Calculations from the 1992/93 Integrated Household Survey. Note: This table reports average household shares. Agricultural revenue includes crops grown for own consumption valued at producer prices. Revenue is reported rather than income because costs were not disaggregated. 14. Food crops account for about 90 percent of total income earned from agriculture, including home consumption (Table A. 5). This reliance is partly a legacy of the retreat to subsistence since 1972, prompted by insecurity and low producer prices. The main difference between the poor and the nonpoor with respect to food crops is that the poor rely more on cassava, millet, and sorghum, and the nonpoor depend on matooke. This  82 Annex I Poverty Update distinction is partly caused by regional differences: matooke can only be grown in the relatively fertile banana belt around the central and western regions; sorghum and millet are generally grown in the poor areas of the north and east. Outside the rural northern region the nonpoor receive more income from animal husbandry, possibly reflecting the risky nature of investments in relatively lumpy assets such as cattle. The reversal of this pattern in the north reflects the existence of poor pastoralists in that area. 15. Although cash crops account for a very Fte A2: CROPS AND AGRICLULJRAL REVENUE small share of average Es agricultural incomes (5 70% Ceater We to 6 percent in 1992/93, when the price of coffee No was low), they are 50% equally important for the poor as for the nonpoor. , 40% Coffee is the most important cash crop. In 3 the rural central region, t20% where it is most Ol_ commonly grown, coffee 10% accounts for nearly 15 +l percent of the 0% a o a CY aC oC agricultural revenue of m E m F m - m - people in the poorest = Bol "'m Q=We TQ = Top lrme Qutie quartile compared with 6 Soue 1Cain nblooe *Cassava 1 Cash percent for people in the 0 highest quartile (see Statistical Annex Table IX.3). The share of cash crops was at a low point in the survey year because of the low international price for coffee; if the survey had been carried out in 1994/95, it would have indicated a much higher share of traditional cash crops in agricultural revenue. 16. The finding that the poor grow proportionately more coffee than the better-off may seem counterintuitive to those more familiar with countries like Cote d'Ivoire, Ghana and Kenya, where coffee producers tend to be relatively wealthy. However, several factors help to explain the relatively high share of coffee in poor people's incomes. Historically, coffee was adopted by many smallholders. Where it is still grown, it is usually on a small scale. Coffee trees last many years and require little attention, so poor farmers may have little incentive to uproot them. Nonetheless, traditional forms of coffee are relatively unprofitable in Uganda, especially prior to liberalization of the coffee sector. Consequently, larger and more progressive farmers are likely to have moved out of coffee and into more remunerative activities. Indeed, one route by which the post-1987 economic reforms are likely to have benefited the poor is through the trade-liberalizing devaluation which brought much higher prices for exportables. Another route is the liberalization of internal and external marketing of both cash and food crops.  Annex I Poverty Update 83 17. Despite the collapse in world coffee prices since liberalization, the domestic relative producer price increased considerably. The domestic terms of trade calculated for cash crops and food crops show this clearly (Figure A.3). This relative price change benefited the poor in the coffee growing areas because of their higher dependence on coffee. Cash crop income may have accrued more to men than to women, exacerbating intra-household inequality. Household level data unfortunately do not allow us to document this effect. C. HOUSEHOLD ExPENDITURE 18. The poor are much less involved in the market than the nonpoor (Table A.6). While the share of total food spending is more or less constant across the three bottom quartiles and falls only a little for the top quartile (suggesting that the income elasticity of food expenditure is only slightly less than one), the share of home-produced food is much higher for the poor. 19. People in the bottom quartile buy 41 percent of their total food consumption from outside of the family farm, while this share is 53 percent in the top quartile. As might be expected, matooke is more popular with the nonpoor, whereas maize and cassava are important items for the poor. Meat, but not fish, behaves as a luxury good, reflecting the relative abundance of fish in Uganda (see Statistical Annex Table IX.4). Wealthier urban households spend more on education than do their rural or poorer urban counterparts. Table A.6: SHARE OF MAJOR COMMODITY GROUPS IN HOUSEHOLD BUDGETS Expenditure Quartiles All Urban Rural Bottom Lower Upper Top Middle Middle SHARE OF TOTAL SPENDING 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Food, kind 31.1 5.9 39.8 37.5 37.7 37.2 35.1 Food, cash 32.9 46.6 28.2 29.8 30.0 31.0 25.2 Nondurables 3.5 3.6 3.4 4.1 3.7 3.7 3.3 Semi-durables 18.3 26.4 15.5 18.1 17.4 16.3 19.5 Durables 1.9 2.8 1.6 0.8 1.1 1.2 2.7 Health 4.2 3.6 4.5 3.6 4.0 4.2 4.5 Education 5.0 8.5 3.8 4.1 3.8 4.1 5.9 Miscellaneous 3.0 2.6 3.2 2.1 2.3 2.3 3.8 MEAN SHARE ACROSS HOUSEHOLDS Food, kind 37.1 8.4 41.7 40.2 39.9 39.2 31.3 Food, cash 31.1 51.6 27.8 27.8 28.7 30.4 35.6 Nondurables 3.8 3.9 3.9 4.1 4.0 3.6 3.5 Semi-durables 17.6 23.4 16.7 18.9 18.0 16.8 17.1 Durables 1.2 1.6 1.2 0.7 1.0 1.1 1.9 Health 3.6 3.7 3.6 3.2 3.5 3.8 3.9 Education 2.8 5.0 2.5 3.0 2.6 2.6 3.1 Miscellaneous 2.6 2.3 2.7 2.1 2.3 2.3 3.5 Source: Calculations from the 1992/93 Integrated Houwehold Survey. Notes: Semi-durables includes ervices, rent and fuel. Shares of expenditure can be calculated in two ways as the share of total spending, or as the averge of the share across households. Tbe first measure weights better-off households more because they constitute a larger share of total spending.  84 Annex I Poverty Update 20. The unusually high share of food in total expenditure across quartiles could indicate reporting bias in the survey data. However, when disaggregating the population in a different way, the share of food in total expenditure shows a more normal pattern, i.e. declines at the upper end: for the poorest 86 percent the share of spending on food is around 68 percent, for the next 10 percent it is 65 percent, and for the rest (4 percent) it is 51 percent. D. CHANGES IN POVERTY: EVIDENCED FROM HOUSEHOLD SURVEYS 21. Data from two household surveys are available for Uganda: the 1989/90 Household Budget Survey, an expenditure survey carried out mainly to revise the consumer price index, and the 1992/93 Integrated Household Survey, which contains much more information than just expenditure data. A comparison of these surveys shows that there has been a dramatic fall in household expenditure. Using alternative price deflators and correcting for sampling differences do not change the basic result. But a large increase in poverty does not seem plausible, given production and other data from the same period. A closer investigation of the two surveys reveals that the 1992/93 survey suffers from systematic underreporting of expenditure; the survey design switched from a detailed list of prompting consumption items bought during the thirty days immediately prior to the interview to an open format expenditure questionnaire with minimum prompting. Therefore, it is not possible to draw any firm conclusions about changes in absolute poverty from the two surveys. However, the rest of the survey, which is the first nationally representative household survey of Uganda, provides a rich source of socio- economic information about households. In addition, it includes a small-scale establishment and household enterprise survey as well as a community survey. 22. Relative Poverty. We can, however, assess what has happened to relative poverty. Ignoring changes in the mean household expenditure per capita, we ask: what has happened to the distribution around these means? Two poverty lines are chosen for illustrative purposes: two-thirds of the mean household expenditure and one-third of the mean, and they are applied to both surveys separately. 23. Using the two-thirds of the mean expenditure poverty line and not adjusting for price variation, we find that 39 percent of the population were poor in 1989/90, while 44 percent were poor in 1992/93. However, when the seven districts not surveyed in 1989/90 are excluded, the figure for 1992/93 is only 40 percent. In other words, there is no evidence of a change in relative poverty. Taking the poverty line of one-third of the mean and applying it to both surveys shows a fall in hard-core poverty from 11.6 percent to 9.4 percent. Adjusting for regional price variation should give more accurate insight into welfare changes. However, the adjustments do not alter our earlier conclusions (no change in relative poverty broadly defined and a slight fall in relative hard-core poverty). Still, poverty may have fallen in absolute terms. 24. These headcount measures are rather insensitive to changes in the welfare of the poorest. The poverty gap measure may therefore be preferable. It measures the difference between the expenditure of those falling below the poverty line and the poverty line itself.  Annex 1 Poverty Update 85 The poverty gap is calculated for each household and aggregated to give a measure of the total proportional shortfall in expenditure. The national poverty gap remains the same when using the two-thirds of the mean expenditure poverty line, and falls when using the one-third of the mean expenditure poverty line. These measures seem to confirm that broad poverty did not change during 1989/90-1992/93, while hard-core poverty fell. But it is important to keep in mind that it is not possible to determine whether the absolute mean expenditure of the poor increased or decreased between the two surveys; we can only determine what happened to the distribution around the mean. 25. Inequality. Using the data on household expenditures per adult equivalent, Gini coefficients are constructed for the population (Table A.7). Overall, Uganda's income distribution is more equitable than that in Kenya, for example, where the Gini coefficient for rural areas was 0.49 (0.35 in Uganda) and the coefficient for urban areas was 0.45 (0.44 in Uganda) in 1992. 26. Gini coefficients indicate Table A.7: GINI COEFFICIENTS FOR UGANDA that inequality has risen slightly in Uganda. They also show a 1989 1992 1992 excl. 7 widening urban-rural gap Districts (evidenced by a higher national value of the Gini coefficient than Nominal Expenditures the weighted average of urban and National 0.377 0.409 0.405 rural coefficients) and increased Urban 0.373 0.439 0.436 inequality within urban areas, Rural 0.364 0.352 0.344 while within rural areas inequality has been reduced. These results are consistent with the analysis of National 0.368 0.383 0.379 relative poverty, that is, hard-core Urban 0.371 0.439 0.439 poverty seems to have fallen. They Rural 0.364 0.353 0.346 are also robust (remain qualitatively the same) to controls Source: Calculations from the 1992/93 IHS. for price variation, as indicated by the expenditure figures deflated by regional poverty lines. Deflating by poverty lines does, however, reduce the size of the increase in inequality since allowing for price differences narrows the rural-urban gap. 27. These results have some plausibility. According to national accounts estimates, nonagricultural sectors have grown more during 1989-92 and have benefited urban residents more. Furthermore, this growth may have increased inequality within the urban sector by providing more opportunities for the better-off and by attracting poor migrants.  86 Annex I Poverty Update Box A.2: Poverty in Sub-Saharan Africa A recent World Bank report5 summarizes the status and changes in poverty in Sub-Saharan Africa. Despite the generally poor economic performance and high and increasing incidence of poverty, the link between good macroeconomic policies and lower levels of poverty is evident. Even more evident is the link between a deteriorating macroeconomic framnework and a high incidence of poverty. Countries which have deteriorating macroeconomic policies indicated an increase in the percentage of people living on less than US$1 a day. The wealthier Sub-Saharan African countries, with GNP per capita in excess of US$460, generally perform better with respect to all key poverty indicators. In the middle income group (US$288 to US$459), a number of social indicators, though not all, are better than in the lower income group. For all key social indicators, without exception, the worst performer is always a country from the poorest income group, and the best performer is always one from the wealthier group. Primary enrollment rates, for example, reach an average of 107 percent in the wealthier group, while in the middle income group and low income group the figures are 74 and 61 percent, respectively. The corresponding figures for female enrollment are 100, 63 and 51 percent. Access to health services in the richer group is 74 percent of the population but only 46 and 49 percent for the middle and poorest group, respectively. The majority of the poor live in rural areas where households are larger, adult migration increase dependency ratios and access to education is more limited than in urban areas. However, urban poverty is growing rapidly. There are serious difficulties in measuring change in poverty in Africa. Few countries are able to provide estimates of income or expenditure distributions for two or more periods in time. In some countries for which such data exist, the timing of one or more of the surveys may be inappropriate if the reference year is atypical, say a drought year. In addition, methodology, sampling and definitions used in surveys are not consistent which make the comparison difficult. The latter is particularly evident in the case of Uganda. Something can be said, however, for Sub-Saharan Africa as a whole, i.e. there has been a small increase in the overall percentage of the population living in poverty since 1985. Due to the growing size of the overall population, there are substantially more people living in poverty now than in 1985. The picture that emerges from those countries where household survey data exist over time, is an ambiguous one. Overall economic indicators stagnated, yet social indicators improved, especially long-term indicators such as life expectancy, child mortality, adult literacy and access to safe water. On the other hand, while the change in the number of people living below the international poverty line is insignificant in the middle and low-income countries, access to health services in the latter two groups has actually fallen, while in all the three income groups there has been no change in primary enrollment. World Bank (1994), Status Report on Poverty in Sub-Saharan Africa 1994. The Many Faces of Poverty, Technical Department, Africa Region.  Annex I Poverty Update 87 E. DOMESTIC TERMS OF TRADE AND AGRICULTURAL PRODUCTION 28. In the absence Figure A3: DOMESTIC TERMS OF TRADE of adequate, comparable microdata to measure the 120. change in absolute poverty 100 . . over time, it is useful to look at domestic terms of trade and production and con- i 0 0 sumption patterns to get 6 some idea of how different 50 -. l-.-l -j groups have fared during S; ' . ' ' . a adjustment (Figure A.3),6 Fisc Yer The real farmgate prices for Sure istic pt, MFEShCrop?.FoodCrop TlAgncu cash crops and food crops have behaved very differently during this period. The relative price for traditional cash crops was very low until the early 1990s mainly because of low international commodity prices and a monopolistic and inefficient market structure. In the early 1990s, the trend was radically reversed. This reversal can be attributed to the liberalization of the cash crop sector, mainly coffee, as the world prices for cash crops continued to be very low. As opposed to cash crops, the relative price of food crops appears to have been quite stable between 1985/86 and 1989/90 but declined by 15 percent during 1990/91, remaining at the lower level, except for a small peak in 1992/93 (resulting from the drought). It is not possible to determine how much adjustment has contributed to the modest fall in food prices; the restoration of peace and security are also important factors in increasing the supply of food crops to the market. Nonetheless, the shift in relative prices in favor of cash crops can clearly be attributed to adjustment measures in the coffee sector. 29. A change in the incentives faced by smallholders is a necessary first step toward successful rural development. The fall in food prices observed in the data means that the relative prices of other rural economic activities are going up. This rise is necessary to shift resources toward more profitable activities, such as cash crops, nontraditional exports, and off-farm activities. Nontraditional exports and off-farm activities have much higher returns, but are more complex and risky. Currently the top expenditure quartile earns 27 percent from off-farm activities while the bottom quartile earns only 12 percent from these activities. Therefore, a decline in food prices is only a necessary condition for a shift in resource allocation; sufficient conditions include year-round access to food through the market for rural development to take-off. This transition may not to through the market and improved technology. 6 The domestic terms of trade are defined for food crops, as the ratio of their price index to the price index of nonfood goods and services, and for cash crops as the ratio of their price index to the price index of nonfood goods and services. The use of food and nonfood CPI yields similar results to the GDP deflator.  88 Annex I Poverty Update 30. Adjustment seems to have contributed to a shift in the incentive structure to the right direction for sustainable rural development to take-off. This transition may not have been harmful to the poorest, as they appear to be net buyers of food7. This result is not as implausible as it might at first appear: the poor receive substantial remittances from others and rely on cash crops just as much as other groups-or more in the case of coffee in the central region. Poverty has not necessarily been reduced by falling food prices, but rural incentives, which have moved in the right direction and without directly making the poor worse-off. However, incomes are still low, and access to quality social services, particularly education and health, remains extremely limited. 31. Examination of per Fgure AA: AGRCULTURAL GD FM capita production figures RURALPESON (for the rural population) 80 shows that production of commonly grown cereals, 75 pulses, and oil seeds increased substantially - 70 during 1987-92: maize by 11 percent, beans by 5 percent, a and sesame by 17 percent. 65 These three crops contribute 19 percent of the agricultural 60 - i I i E I i E I E income for the bottom 1983514 1985/86 1987/88 1989/90 1991&2 1993I94 quartile in rural areas. The gains came mainly from SDnrce: SatikicstDept,MFE. increasing the area under cultivation. The importance of these crops in exports has also increased during the period. Root crops and matooke, on the other hand, did not show a similar per capita increase: production of matooke increased very little, while that of cassava fell slightly, and sweet potato was stagnant. As these three crops represent 40 percent of agricultural (imputed) income, the net effect on production per person, although likely to be positive, is small. 7 Overall, the poor rely more heavily on subsistence than the nonpoor, and many poor households are both sellers and buyers of food crops during a given year. This makes it difficult to assess the poor's net position. Preliminary analysis of expenditure and income patterns reveals, however, that the poorest (bottom quartile) in Uganda may be net buyers of food. More specifically, the rural-urban breakdown shows that 18 percent of the income of the urban poor come from food crops, while 43 percent of their expenditure are spent on them. Hence, the urban poor are net buyers and have benefited from the recent decline in the relative price of food crops. For the rural poor food crops provide 47 percent of their income, while they spend 54 percent on food crops. Therefore, the rural poor seem also to be net buyers of food crops and hence have benefited from the (modest) fall in their relative price. However, due to differences in the structure of the income and expenditure parts of the surey and prices applied (farmgate prices in income vs. market prices in consumption), more work is required to establish the robustness of this finding.  Annex I Poverty Update 89 Figure A.5: PER CAPITA FOOD PRODUCTION 1,600 1,4C0 1,200 8'000 600- 400 200 0~~~~~~~~~~~01 ~ 0 0 @0 @0 @ S: MPEP. - - - - - - - e' " Sou=e: MFEP. 32. According to the data available from the Agricultural Secretariat (Bank of Uganda), the real price of frequently purchased agricultural inputs, such as seed, chemicals, hand tools, and so on, either decreased or increased only slightly during 1989- 94. As a result, the cost of producing a unit of output has not increased. Unfortunately, Uganda's agriculture is low input-low output type so that reduced input prices have not had much of an impact on production.   ANNEX II MACROECONOMIC PROJECTIONS The data in the following tables are presented in fiscal years, with 1990 meaning 1989/90 or July 1, 1989 to June 30, 1990. Date in constant prices use calendar year 1991 as the base year. The projections for the four sectors-public, private, external and monetary-are presented within a consistency framework. Consequently, since 1993/94 is treated as a projected year by the model, some data may differ from published statistics.  I  Uganda Key Indicators Table Annual Growth Rate 5-year Rates/Indicators Main Macro Aeareaates 92 93 94 95 96 97 84-89 90-94 94-99 GDP 3.2 8.5 5 4 7 0 7 0 6.5 3 3 5 5 6.3 GDPpercapitau/ -0.5 52 77 40 40 35 0.5 2.2 3.3 Investment -6.9 4.0 2.7 364 176 130 123 1.1 14.3 Consumption 2.6 10 5 8.3 5.9 3 7 3 8 3 3 6.4 4 4 Consumption percapita/a -1.1 7.1 10.7 2.9 0.8 0.8 0.5 3.1 14 ExportsGNFS 17.1 .77 23.8 4.2 7.1 7.6 04 50 66 Imports GNFS -2.7 9.1 219 17 0 1.5 1.3 7 6 61 41 ICOR .. 2 8 2.9 Import Elasticity -0.9 1.1 4.1 2 4 0 2 0 2 2.3 1.1 0.6 Debt/Liauidity Indicators (M) 90 91 92 93 94 95 96 97 99 2003 Current Account/GDP .9 9 -13.4 -14.1 -12 1 -8.9 -4.5 -3.9 -4.2 -6 3 -8 0 Overall Budget Balance/GDP -5.8 -7 2 -14.2 -11 1 -11 3 -7 2 -6 5 -5.8 -6.6 -6.4 Interest Due/XGS 0.0 0.0 0.0 2.6 17.3 7.3 66 72 8.1 7.5 Repayment Due/XGS 45.6 65.: 116.0 66.2 36.6 11.6 11.3 13 3 17 2 16 8 Total Debt Service Due/XGS 45.6 65.5 116.0 68.8 53.9 18.9 17.9 20.6 25 4 24.4 DOD/GDP 54.6 77.2 91 4 81.7 74.0 59.6 58.2 57.3 61 4 53 9 DOD/XGS 1404.9 1841.5 2448.7 1705.2 962.6 523.8 535.1 599 8 703 9 680 8 Gross Reserves (mos. imports) I i 2 2 4 5 6 7 7 4 Financinv Plan Period Averages (USS, millions) 1990-91 1992-94 1995-97 Official capital grants 207 250 229 Private Investment 3 4 1 0 NetLongTermBorrowing 169 139 229 All other capital flows 34 82 -81 Total financing/b 416 429 387 /I Calculated using IECSE population series. /b Total financing - -(CAB + Change in reserves.)  92 Annex II Macroeconomic Projections Uganda NadonalAccoutnts CI Page 1 actual eutimats proiection 1990 1991 1992 1993 1994 1995 1996 17 1998 19o 2003 A. In Current Prices (bil. LCUS) GDPat marketprices 1387.5 1848.1 2782.5 3947.6 4448.8 5134.4 5773.8 6480.5 7178.7 7952.2 11974.5 NetindirectTaxes 80.1 119.5 156.7 244.5 288.5 399.7 483.9 582.6 567.7 679.4 1225.0 GDP at Factor Cost 1307.4 1728.6 2625.8 3703.1 4160.3 4734.6 5289.9 5897.9 6611.0 7272.9 10749.5 Agriculture 736.0 905.5 1329.3 1881.1 2020.3 2371.4 2597.0 2844.1 3114.7 3411.1 49066 Industry 150.4 224.8 367.7 505.3 591.2 764.3 882.7 1019.6 1163.6 1328.4 2267.9 ofwhich Manufacturing 74.6 103.1 170.6 229.6 279.7 375.9 438.2 510.7 595.2 693.7 1280.0 Services 420.9 598.3 928.8 1316.7 1548.9 1599.0 1810.2 2034.1 2332.8 2533.4 3575.0 Resource Btiance -151.3 -278.1 -438.3 -605.7 -660.8 .486.0 -503.5 -573.7 -767.0 -866.4 -1386.8 Imports(GNFS) 234.4 390.7 637.5 821.7 990.8 1054.1 1092.6 1151.6 1375.5 1510.6 2278.7 Exports(GNFS) 83.1 112.6 199.2 216.0 330.1 568.1 589.1 577.8 608.5 644.2 891.9 Total Expenditure 1538.8 2126.2 3220.8 4553.2 5109.6 5620.4 6277.3 7054.2 7945.7 8818.6 13361.3 Consumption 1373.5 1852.8 2797.0 3995.4 4536.4 4850.2 5324.6 5900.7 6617.7 7331.6 11091.3 Government 141.3 194.0 394.1 495.0 327.0 401.5 470.6 543.1 658.5 777.9 1477.0 Private 1232.2 1658.8 2402.9 3500.4 4209.4 4448.7 4854.0 5357.5 5959.2 6553.6 9614.3 Gross Domestic lnvestment 165.2 273.4 423.8 557.9 573.2 770.2 952.7 1153.5 1328.1 1487.1 2270.0 Govemment 57.5 105.1 196.0 296.5 423.4 382.3 436.7 493.6 553.5 584.3 934.1 Private 108.6 162.0 230.0 252.3 149.8 387.9 516.0 659.9 774.6 902.8 1336.0 Total fixed investmnent 166.1 267.1 426.0 548.8 573.2 770.2 952.7 1153.5 1328.1 1487.1 2270.0 Total investment in stocks -0.9 6.3 -2.1 9.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Domestic Savings 13.9 -4.7 -14.5 -47.8 .87.6 284.2 449 2 579.8 561.1 620.7 883.2 + Net Factor Income (NFY) -24.6 -32.1 -83.6 -58.8 -66.7 -39.1 -20.3 -22.2 -50.9 -32.5 -54.9 +NetCurrentTransfers(NCT) 24.9 44.3 56.2 199.5 333.1 294.3 299.2 321.0 378.8 397.7 483.4 -National Savings 14.3 7.6 -41.9 93.0 178.7 539.4 728.1 878.6 889.0 985.8 1311.8 Gross National Product 1362.9 1816.0 2698.9 3888.8 4382.1 5095.3 5753.5 6458.3 7127.9 7919.7 119196 Gross National Disposable Income 1387.8 1860.4 2755.1 4088.3 4715.2 5389.6 6052.7 67793 7506.6 83174 124030 B. shares of GDP (current prices) GDP at market prices 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Net Indirect Taxes 5.8 6.5 5.6 6.2 6.5 7.8 84 9.0 79 8.5 10.2 Agriculturevalueadded 53.0 49.0 47.8 47.7 45.4 46.2 45.0 43.9 43.4 42.9 41.0 Industry value added 10.8 12.2 13.2 12.8 13.3 14.9 15.3 15.7 16.2 16.7 18.9 of whichManufacturing 5.4 5.6 6.1 5.8 6.3 7.3 7.6 79 8.3 8.7 10.7 Services value added 30.3 32.4 33.4 33.4 34.8 31.1 31.4 31.4 32.5 31.9 29.9 Resource Balance -10.9 -15.0 -15.8 -15.3 -14.9 -9.5 -8.7 -8.9 -10.7 -10.9 -11.6 Imports(GNFS) 16.9 21.1 22.9 20.8 22.3 20.5 18.9 17.8 19.2 19.0 19.0 Exports(GNFS) 6.0 6.1 7.2 5.5 7.4 ll.l 10.2 8.9 8.5 8. 1 7.4 Total Expenditure 110.9 115.0 115.8 115.3 114.9 109.5 108.7 108.9 110.7 110.9 111.6 Government consumption 10.2 10.5 14.2 12.5 7.4 7.8 82 8.4 9.2 9.8 12.3 Private consumption 88.8 89.8 86.4 88.7 94 6 86.6 84.1 82.7 83.0 82.4 80.3 Government investment 4.1 5.7 7.0 7.5 95 7.4 7.6 7.6 7.7 7.3 7.8 Private investment 7.8 8.8 8.3 6.4 3.4 7.6 8.9 10.2 10.8 11.4 11.2 Gross Domestic Savings 1.0 -0.3 -0.5 -1.2 -2.0 5.5 7.8 8.9 7.8 7.8 7.4 Gross National Savings 1.0 0.4 -1.5 2.4 4.0 10.5 12.6 13.6 12.4 12.4 11.0 Gross National Product 98.2 98.3 97.0 98.5 98.5 99.2 99.6 99.7 99.3 99.6 99.5 Gross National Disposable Income 100.0 100.7 99.0 103.6 106.0 105.0 104.8 104.6 104.6 104.6 103.6 Memorandum items- Price indices (%/6 change) GDP deflator 45.4 27.2 45.9 30.7 6.9 7.9 5.1 5.4 5.0 5.0 5.0 Consumerpriceindex 45.4 24.6 42.1 28.4 7.8 7.5 5.0 5.0 7.4 5.5 5.1 Totai GDP(millioncurrentUSS) 4,341.1 3,354.7 2,896.0 3,284.7 4,053.9 5,504.2 6,189.7 6,616.4 6,373.3 6,898.7 9,387.5 Conversionfactorused(LCU/lSS) 319.6 550.9 960.8 1201.8 1097.4 932.8 932.8 979.5 1126.4 1152.7 1275.6 Per capita gross national product 261 261 261 270 .. .. .. .. (Atlas method: in 1987 USS, in calendar years)  Annex 1I Macroeconomic Projections 93 Uganda NVationalAccounts Cl Page 2 actual estimate nroiection 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2003 C. In Constant 1991 Prices (bil. LCUs) GDP at market prices 2073.2 2170.8 2239.7 24305 2561 8 2741.1 2933.0 3123.6 3295 4 34766 43069 GDP at Factor Cost 1929.6 2033.6 21064 22871 23865 2518.1 2677.0 2832.0 30233 31676 3851.7 Agriculture 1040.1 1069.0 1056.9 11572 1176.9 1233.4 1286.4 1341.7 13994 14596 17273 Industry 2374 261.4 290.5 312.4 351.8 406.1 446.7 491.4 5336 5798 8120 of which Manufacturing 84.8 84 8 84.8 84.8 973 116.8 129.6 143.8 159 7 177 2 269 1 Services 652 1 703.2 758.9 8175 857.9 878.7 943.9 998.9 10902 1128.2 13124 Resource Balance -346.0 -362.5 -325.0 .381.7 -462.7 -565.2 -562.9 -557.2 -554 8 -578 9 -720.8 Imports (GNFS) 496.7 501.1 487.3 531.5 648.1 758.3 769.7 779 7 792 6 831 5 10300 Exports (GNFS) 150.7 1385 162.2 1498 185.4 193.1 206.9 2226 2378 2526 309.3 Total Expenditure 2419.2 2533.3 2564.8 2812.2 3027.7 3312.5 35009 36845 38530 4058.2 5031.1 Consumption 2093.5 2181.1 2236.9 2471.3 2677.5 28349 2939.1 30496 31858 3346.7 41375 Government 220.3 213.9 265.2 236.0 293.7 357.0 395.2 427 1 482.3 540.3 8383 Private 1873.2 1967.2 1971.7 2235.2 2397.7 25094 25858 2672.1 27686 2887.1 34613 Gross Domestic Investment 325.8 352.2 327.8 341.0 350.2 477.6 561 7 635.0 667 2 711 5 893 6 Government 115.3 134.4 151.2 179.9 202.3 100.7 86.0 68.0 60.2 38.4 734 Pnvate 214.0 208.1 178 5 151.9 138 5 364 2 460.7 550.0 589 2 654 1 796 3 Total fixed investment 329.2 342.5 329.7 331.9 340.8 464.8 546.7 618.0 649.4 692.5 869 7 Total investment in stocks -3.5 9.8 -1.9 9.1 0.0 00 00 0.0 00 00 00 Terms oftrade (TT) effect 25.4 5.9 -100 -10.0 305 215.6 208.2 1687 1129 1020 939 Gross domestic income 2098.6 2176.7 2229.8 2420.5 2592.2 2956.6 3141.1 3292.3 3408 2 35786 4400 8 Domestic saving (TT adjusted) 5.2 -44 -7.2 -50.8 -85.3 121.7 202.0 2427 2225 231 9 263 3 D. Annual arowth rates (1991 grices) GDP at market prices 6 1 4.7 3.2 8 5 5.4 70 7.0 6 5 5 5 5.5 5 5 Agnculture 5.4 2.8 -1.1 95 1.7 48 4.3 43 43 43 43 Industry 6.6 101 11.2 75 12.6 154 10.0 100 86 87 89 of which Manufacturing 0.0 0.0 0.0 00 147 200 110 11.0 110 110 110 Services 6.8 5 6 6.2 7 7 7.5 6 6 89 7 6 5 6 5.5 5.2 Imports (GNFS) -3.0 09 -2.7 9 1 21.9 170 1.5 13 1 7 49 55 Exports (GNFS) 5.7 -8.1 17.1 -77 238 42 7.1 76 68 6.2 53 Total Expenditure 4.1 4.7 1.2 9.6 7.7 9 4 5 7 5 2 4.6 5.3 55 Consumption 4.2 4 2 2.6 10.5 8 3 5 9 3.7 3 8 4 5 5.1 55 Investment 3.3 8.1 -6.9 40 2.7 364 176 130 5.1 6.6 5.5 Gross domestic income 3.4 3.7 2.4 8.6 71 14.1 6.2 4 8 3.5 50 5.4 Gross domestic saving -74.6 -185.6 62.5 607.6 679 -2427 659 202 -83 43 3.9 Per Canita arowth rates: Per capita GDP (mp) 3.1 1.8 -0.5 5.2 77 4.0 4.0 3.5 25 25 25 Per capita total consumption 1.3 1.3 -1.1 7.1 107 2.9 08 0.8 15 21 2.5 Per capita private consumption 0.4 2.1 -34 9.9 96 1.7 0 l 0.4 07 13 1.7 E. Period Average Indicators 1984-89 1989-94 1994-99 Marginal national saving rate -0.2 0.1 0.3 Incremental capital-output ratio . 2 8 2.9 Import elasticity 2.3 1 1 06  94 Annex II Macroeconomic Projections Uganda Expwrty and Imonrts C2 actual estimate orolection 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2003 A. Value in Current Prices (USS millions) Total Merchandise Exports (FOB) 210 176 172 157 230 537 555 509 454 467 581 Primuy products 159 127 130 114 176 482 494 440 376 379 439 CP.X.BEV.COFFEE 159 127 117 99 152 454 458 394 317 307 336 CP.X.OAGRI.COTTON 0 0 8 10 6 4 9 17 27 39 65 CP.X.BEV.TEA 0 0 5 4 7 9 t 1 14 16 16 20 CP.X.FOOD.FISH 0 0 0 0 12 14 15 16 16 16 19 Manufactured goods 0 0 0 0 0 0 0 0 0 0 0 Othergoods 51 49 42 44 54 55 61 69 78 88 141 Total Merchandise Imports (CIF) 584 545 445 534 727 936 955 949 985 1,054 1,438 Food 0 0 0 0 46 60 62 61 70 80 96 Other Consumer Goods 0 0 0 0 97 117 S0 45 -20 -93 -43 POLandOtherEnergy 91 91 91 91 68 77 80 8I 95 112 145 Intermediate Goods n.e.i. 0 0 0 0 300 368 386 386 449 527 649 Primary Goods 0 0 0 0 82 101 106 106 123 144 178 ManufacturedGoods 0 0 0 0 218 267 280 280 326 383 471 Capital Goods 0 0 0 0 216 314 348 377 392 429 591 B. Value In Constant 1991 Prices (USS millions) Total Merchandise Exports (FOB) 194 166 182 174 205 217 235 256 276 295 366 KP.X.BEV.COFFEE .. .. .. KP.X.OAGRI.COTTON .. .. KP.X.BEV.TEA YP.X.FOOD.FISH Manufactures .. .. .. Other Expor.. .. .. ... .. . TotalMerchandiselmports(CIF) 614 551 436 517 650 774 774 771 784 821 1,017 Food .. .. .. Other Consumer Goods .. .. POL and Other Energy .. . .. Intermediate Goods n.e.i. .. .. Primary Goods . .. Manufactured Goods .. .. Capital Goods .. .. Memorandum Items: Export volume growth rte 25.0 -14.5 9.9 -4.4 17.8 5.7 8.2 8.8 7 8 6.9 57 Importvolumegrowthnmte(CIF) 1.4 -10.2 -20.9 18.7 25.7 19.0 0.0 -0.3 1.6 4.7 5.5 C. Price Indica (1991 - 100) Merchandise Export 108 106 94 90 112 247 236 199 165 158 159 Merchandise Import 95 99 102 103 112 121 123 123 126 128 141 MerchandiseTermsofTrmde 114 107 92 87 100 204 191 162 131 123 112 D. Non-Factor Services (indices base 1991 - 100) Exports ofNFS - price index 49 48 43 41 41 42 43 44 45 46 47 lmponsofNFS- price index 98 102 106 107 95 95 99 96 99 102 104  Annex II Macroeconomic Projections 95 Uganda Balance of Payments (millions ef USS) C3 actual estimate oro*ection 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2003 Total Exportsof GNFS 246 199 195 206 301 609 632 590 540 559 699 Merchandise (FOB) 210 176 172 157 230 537 555 509 454 467 581 Non-Factor Services 36 23 23 49 71 72 76 81 87 92 119 Total ImportsofGNFS 676 671 576 718 903 1,130 1,171 1,176 1,221 1,310 1,786 Merchandise (FOB) 584 545 445 534 727 936 955 949 985 1,054 1,438 Non-Factor Services 92 126 131 184 176 194 216 226 236 256 348 Resource Balance -430 -472 -381 -512 -602 -521 -540 -586 -681 -752 -1,087 Net Factor Income -77 -58 -87 -53 -61 -42 -22 -23 -45 -28 -43 Factor receipts -77 -58 -87 -49 11 17 42 43 22 43 44 Factor Payments 0 0 0 4 72 59 63 65 67 71 87 Total Interest DUE (scheduled) 0 0 0 4 54 46 45 46 47 49 56 Interest Paid 22 20 87 54 54 46 45 46 47 49 56 Due but not paid -22 -20 -87 -50 0 0 0 0 0 0 0 OtherFactorPayments 0 0 0 0 18 14 19 19 21 22 31 NetprivateCurrentTransfers 78 81 59 166 304 316 321 328 336 345 379 Current Receipts 78 81 59 166 304 316 321 328 336 345 379 of which workers' remittances 0 0 0 0 0 0 0 0 0 0 0 Current Payments 0 0 0 0 0 0 0 0 0 0 0 Net official current transfers 0 0 0 0 0 0 0 0 0 0 0 Current Account Balance -429 -449 -410 -399 -359 -247 -241 -281 -390 435 .751 Official capital grants 153 262 224 277 250 225 229 234 240 246 271 Private investment (net) 6 1 2 4 5 5 9 15 19 23 57 Direct Investmnent 6 1 2 4 5 5 9 15 19 23 57 Portfolio investment 0 0 0 0 0 0 0 0 0 0 0 Net LT Borrowing 215 122 92 145 180 259 235 193 235 246 328 DisbursementsperDRS 360 195 163 232 294 331 311 277 333 349 453 LT Repayments (scheduled) 77 92 125 104 114 73 76 84 98 104 125 Principal repaid 64 58 125 104 114 73 76 84 98 104 125 Due but not paid 13 34 0 0 0 0 0 0 0 0 0 Other long-term inflows (net) -68 19 54 18 0 0 0 0 0 0 0 Adjustments to Scheduled debt service -9 14 -87 -50 0 0 0 0 0 0 0 DebtServicenotpaid 10 14 -115 -52 31 11 0 0 0 0 0 Reduction in arears/prepayments(-) 19 0 -28 -2 31 11 0 0 0 0 0 Other Capital Flows (net) 55 13 180 51 14 -78 -90 -75 -10 35 32 Net Short-Term (ST) Capital 24 -39 -35 -26 -38 -79 -79 -60 -10 25 20 Capital Flows n.e.i. 6 7 8 9 0 0 0 0 0 10 12 Errorsandomissions 25 45 207 68 52 2 -11 -15 0 0 0 Change in net intem'l reserves 10 37 -2 .29 -90 -164 -142 -86 -94 -115 63 (- indicates increase in assets) Memorandum Items: Total Gross Reserves, of which 35 50 73 112 301 486 645 741 773 829 700 Total Reserves minus gold 35 50 74 112 301 486 645 741 773 829 700 Gold (at year end London price) 6 7 2 2 0 0 0 0 0 0 0 Total Gross Reserves in months M I 1 2 2 4 5 6 7 7 7 4 Exchange rates Annual Average(LCU/USS) 320 551 961 1202 1097 933 933 979 1126 1153 1276 Atendyear(LCUIUSS) 400 700 1166 1199 1015 933 956 1053 1140 1166 1292 Index real av X-Rate (1990 =100) 100.0 76.7 69.9 72.7 IFS Current Account Balance as % GDP -9.9 -13.4 -14.1 -12.1 -8.9 -4 5 -3 9 -4 2 -6 1 -6.3 -80  96 Annex II Macroeconomic Projections Uganda External Debt Stocks and Flows (milions of USS) C4 Page 1 actual estimate projection 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2003 A. Gross Disbursements Public & Publicly Guaranteed 360.0 195.0 163.4 231.5 294.0 331.3 310.9 277.3 333.2 349.3 453.4 a Multilateral 220.0 148.0 153.0 195.5 235.0 246.1 244.2 218.0 249.5 260.2 325.0 of which IDA 175.0 138.0 146.0 137.0 188.0 186.1 169.2 161.0 165.4 163.5 214.7 of which IBRD 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 b. Bilateral 88.0 39.0 9.4 32.0 58.0 73.7 51.8 44.3 68.7 74.1 113.4 Privatecreditors 52.0 8.0 1.0 4.0 1.0 11.5 15.0 15.0 15.0 15.0 15.0 of which bonds 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Non-Guaranteed 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Total Long-Term Disbursements 360.0 195.0 163.4 231.5 294.0 331.3 310.9 277.3 333.2 349.3 453.4 Net Short-Term Capital 23.5 -38.8 -34.7 -25.7 -38.2 -79.3 -79.0 -60.0 -10.0 25.0 20.0 [Mf Purchases 42.0 89.0 55.0 28.0 27.5 46.9 56.2 65.6 0.0 0.0 0.0 Total Disburs. (LTlINF+ST) 425.5 245.2 183.7 233.8 283.3 298.9 288.1 282.9 323.2 374.3 473.4 B. Amortizations Public & Publicly Guaranteed 64.0 58.0 125.4 104.1 114.0 72.8 76.2 84.4 98.0 103.5 125.1 a Multilateral 20.0 20.0 63.4 65.1 55 0 35.0 31.0 31.0 34.0 33.0 62.5 of which [DA 1.0 2.0 2.0 4.0 5.0 10.0 10.0 10.0 12.0 14.0 33.0 of which rBRD 5.0 6.0 5.0 8.0 7.0 6.0 3.0 2.0 2.0 0.0 0.0 b. Bilateral 19.0 16.0 20.0 16.0 470 31.8 34.3 39.3 50.2 54.1 46.6 Private creditors 25.0 22.0 42.0 23.0 12.0 6.0 10.9 14.1 13.8 16.4 15.9 of which bonds 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Non-Guaranteed 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Total Long-Term Amortizations 64.0 58.0 125.4 104.1 114.0 72.8 76.2 84.4 98.0 103.5 125.1 IMF Repurchases 43.0 37.0 34.0 18.3 9.8 25.8 38.7 55.8 61.4 60.0 42.0 Total Amortizations (LT+IMF) 107.0 95.0 159.4 122.4 123.8 98.6 114.9 140.2 159.4 163.5 167.1 C. Net Disbursements Public & Publicly Guaranteed 296.0 137.0 38.0 127.4 1800 258.5 234.8 192.8 235.2 245.8 328.3 a. Multilateral 200.0 128.0 89.6 130.4 180.0 211.1 213.2 187.0 215.5 227.2 262.4 of which IDA 174.0 136.0 144.0 133.0 183.0 176.1 159.2 151.0 153.4 149.5 181.7 of which IBRD -5.0 -6.0 -5.0 -8.0 -7.0 -6.0 -3.0 -2.0 -2.0 0.0 0.0 b. Bilateral 69.0 23.0 -10.6 16.0 11.0 41.9 17.5 5.0 18.5 20.0 66.8 Private creditors 27.0 -14.0 -41.0 -19.0 -11.0 5.5 4.1 0.9 1.2 -1.4 -0.9 of which bonds 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Non-Guaranteed 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Total Long-Term Net Disb. 296.0 137.0 38.0 127.4 180.0 258.5 234.8 192.8 235.2 245.8 328.3 Net Short-Term Capital 23.5 -38.8 -34.7 -25.7 -38.2 -79.3 -79.0 -60.0 -10.0 25.0 20.0 Netuseof MFCredit -1.0 52.0 21.0 9.7 17.7 21.1 17.5 9.8 -61.4 -60.0 -42.0 Total net Disburs. (LT+IMF+ST) 318.5 150.2 24.3 111.4 159.5 200.3 173.3 142.6 163.8 210.8 306.3 D. Interest Public & Publicly Guaranteed 22.0 20.0 78.0 47.0 52.8 42.0 40.9 42.1 43.4 45.7 53.9 a. Multilateral 16.0 14.0 40.0 25.0 25.0 18.0 19.2 20.5 21.5 23.3 32.8 of which IDA 4.0 60 8.0 90 10.0 12.0 13.2 13.5 152 16.1 21.7 of which IBRD 3.0 2.0 2.0 2.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 b. Bilateral 4.0 3.0 14.4 8.0 230 23.0 20.1 18.8 18.3 18.3 16.9 Private creditors 2.0 3 0 23.6 14.0 4.8 1.0 1.6 2.8 3.6 4.1 4.3 of which bonds 0.0 0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Pnvate Non-Guaranteed 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Total Interest on Long-Term Loans 22.0 20.0 78.0 47.0 52.8 42.0 40.9 42.1 43.4 45.7 53.9 Interest on Short-Term Debt 5.0 5.0 5.0 4.0 0.0 0.0 0.0 0 0 0.0 0.0 0 0 IMF Charges 14.0 12.0 4.0 2.0 1.0 3.5 3.6 3.7 3 5 3.2 2.1 Total Interest (LT+IMP+ST) 41.0 37.0 87.0 53.0 53.8 45.5 44.5 458 46.9 48.9 56.0  Annex II Macroeconomic Projections 97 Uganda Erternal Debt Stocks and Flows (millions of USJ) C4 Page 2 actual estimate oroiection 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2003 E. External Debt Public&PubliclyGuaranteed 2097.0 2257.0 22730 2328.0 2560.7 2821.6 3124.7 3307.3 3544.1 38673 4886.0 a. Multilateral 1152.0 1350.0 1426.0 1611.0 1826.5 2048.1 2322.3 2508.3 2722.8 2948.0 3972.1 of which IDA 816.0 9400 1159.0 1267.0 1425.0 1606.1 1765.3 1916.3 2069.7 2219.1 2912.4 of which IBRD 34.0 29.0 26.0 19.0 12.0 6.0 3.0 2.0 0.0 0.0 0.0 b. Bilateral 653.0 811.0 651.0 663.0 685.0 725.0 742.8 732.0 749.7 847.8 845.5 Pnvate creditors 292.0 96.0 196.0 54.0 49.2 48.5 59.6 67.0 71.6 71.5 68.5 a. Bonds 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 40 4.0 4.0 Prvate Non-Guaranteed 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Total Long-Term DOD 2097.0 2257.0 2273.0 2328.0 2560.7 2821.6 3124.7 3307.3 3544.1 3867.3 4886.0 Short-Term Debt 28.0 40.0 44.0 10.0 77.3 77.3 77.3 77.3 773 77.3 773 Use of IMFCredit 245.0 294.0 330.0 344.0 361.1 382.1 399.7 409.5 348.2 288.2 98.0 TotalDOD(LT+IMF+ST).of which: 23700 2591.0 2647.0 2682.0 2999.1 3281.0 3601.7 3794.1 3969.6 4232.8 5061.3 Principal Arrears 184.0 362.7 426.4 195.9 173.4 162.8 162.8 162.8 162.8 162.8 162.8 InterestArrears 10.0 15.0 182.8 83.9 77.3 77.3 77.3 77.3 773 77.3 77.3 F. Debt and debt Burden Indicators: Total debt service (mil USS) 148.0 132.0 246.4 1754 177.6 144.1 159.4 186.0 206.2 212.5 223.1 Interest (LT+ST+ IMF) 41.0 37.0 87.0 53.0 53.8 45.5 44.5 45.8 469 48.9 56.0 Principal (LT + IMF) 107.0 95.0 159.4 122.4 123.8 98.6 114.9 140.2 1594 163.5 167.1 For total DOD and Total debt service (TDS): DOD/E.xports (GNFS + WR) ratio 1404.9 1841.5 2448.7 1705.2 962.6 523 8 535.1 599.8 705.8 703.9 680.8 DOD/GDP 54.6 77.2 91.4 81.7 74.0 59.6 58.2 57.3 62.3 61.4 53.9 TDS/Exports (GNFS + WR) ratio 87.7 93.8 227.9 111.5 57.0 23.0 23.7 29.4 36.7 35.3 30.0 EBRD exposure indicators: IBRD Debt Service/Public DS 9.3 10.3 3.4 6.6 4.8 6 1 2.6 1.6 1.4 0.0 0.0 Pref Creditor DS/Public DS 81.4 83.3 27.0 28.7 20.3 50.8 58.5 67.2 66.5 62.5 552 lBRD DS/Exports (XGS+ WR) 4.7 5.7 6.5 6.4 2.6 1.1 0.4 0.3 0 4 0 0 0.0 Country Share in IBRD Portfolio .. .. .. .. 0.0 0.0 0.0 0.0 0.0 0.0 0.0  98 Annex II Macroeconomic Projections Uganda Public Finance (bit LCUs) C5 actual estimate pro&ection 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2003 Total Current Revenues 95 137 186 281 366 510 619 752 784 956 1763 Direct taxes 9 14 24 41 53 76 101 130 159 189 322 Indirecttaxes 77 114 150 219 289 400 484 583 568 679 1225 Ondomesticgoodsandservices 38 52 71 64 86 117 144 243 302 382 766 On international trade 39 62 79 154 203 282 339 340 266 298 459 Non-Tax Receipts 8 9 12 22 25 34 35 39 57 87 216 Total Current Expenditures 98 131 323 323 442 496 554 631 748 891 1595 Interest on extemal debt 8 17 81 57 52 35 34 37 45 48 63 Interest on domestic debt I 1 9 13 9 6 -5 -3 -9 11 I Transfers to private sector 0 0 0 0 53 53 53 53 53 53 53 Transfers to other NFPS 0 0 0 0 0 0 0 0 0 0 0 Subsidies 0 0 0 0 0 0 0 0 0 0 0 Consumption 90 112 233 254 327 401 471 543 658 778 1477 Wagesandsalaries 13 24 48 63 84 124 158 195 263 327 665 Other consumption 77 88 185 191 243 277 312 348 395 451 812 Budgetary Savings -4 6 -137 -42 -76 14 65 121 36 65 168 Capital Revenues 0 0 0 0 0 0 0 0 0 0 0 Total Capital Expenditures 77 139 258 395 426 384 439 496 555 586 936 Capital transfers 0 5 9 1 3 2 2 2 2 2 2 Budgetary fixed investment 77 134 250 394 423 382 437 494 553 584 934 Overall balance (- = deficit) -80 -132 -396 -437 -502 -371 -373 -374 -520 -521 -768 Sourcesoffinancing(+) 80 132 396 437 502 371 373 374 520 521 768 OfficialCapitalGrants 20 70 195 314 275 210 213 229 270 283 346 External Borrowing (net) 92 65 142 201 157 174 159 141 230 273 368 Monetary System Credit (net) -17 4 44 -17 -53 -70 -25 -77 185 5 42 Other Domestic Borrowing (net) -15 -7 14 -60 123 57 26 81 -166 -40 12 Shares of GDP at current Prices Currentrevenues 6.8 74 6.7 7.1 8.2 9.9 10.7 11.6 10.9 12.0 14.7 Current expenditures 7.1 7.1 11.6 8.2 9 9 9.7 9.6 9.7 10.4 11.2 13.3 Budgetasy savings -0.3 0.3 -4.9 - 1.1 -1.7 0.3 1.1 1.9 0.5 0.8 1.4 Capital revenues 0.0 0.2 0.3 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 Capital expenditures 5.5 7.5 9.3 10.0 9 6 7.5 7.6 7.6 7.7 7.4 7.8 Overall Balance (- = deficit) -5.8 -7.2 -14.2 -11.1 -11.3 -7.2 -6.5 .5.8 -7.2 -6.6 -6.4 Official capital grants 1.5 3.8 7.0 7.9 62 4.1 3.7 3.5 3.8 3.6 2.9 Extemal Borrowing (net) 6.6 3 5 5 1 5.1 3.5 3.4 2.8 2.2 3.2 3.4 3.1 Monetary System Credit (net) -1.2 0.2 1.6 -04 -1.2 -1.4 -0.4 -1.2 2.6 0.1 0.4 OtherDomesticBorrowing(net) -1.0 -0.4 0.5 -1.5 2.8 1.1 0.5 1.2 -2.3 -0.5 0.1 Government Debt (DOD at the end of the vear) Extemal Debt in billions of LCU 704 1428 2544 3223 2347 2370 2695 3149 3649 4077 5650 External Debt in millions oftUSS 2202 2592 2648 2682 2312 2541 2818 2991 3202 3496 4372 Debt To Monetary Sys. (LCU mil) 9 13 57 40 -13 -83 -109 -185 0 5 87 Other Domestic Debt (LCU mil) . . 129 182 208 289 123 82 -55 Total Govemment debt .. .. .. . 2464 2469 2794 3253 3772 4165 5683 Total Govt debt as percent GDP .. 55 48 48 50 53 52 47 Tax burden indicators Ml. Direct taxes/ GDP 0.7 0.8 0.8 1.0 1.2 1.5 1.7 2.0 2.2 2.4 2.7 lndir taxes on domestic G&S / GDP 2.7 2.8 2.6 1.6 1.9 2.3 2.5 3.7 4.2 4.8 6.4 IndirtaxesondomG&S/privConsu 3.1 3.1 30 1.8 2.0 2.6 3.0 4.5 5.1 5.8 8.0 taxes int'l tradelmerch imports 20.9 20.8 18.4 24.1 25.4 32.3 38.1 36.5 24.0 24.5 25.0  ANNEX III STATISTICAL ANNEX   COUNTRY DATA SHEET TABLE 1.1 General Area, land sq km 197,097 Population (1991) 16,671,705 Density (1991) per sq km 85 Socio-Economic Indicalors (1992/93) Women's share of credit Total percent 9.2 Rural " 13.6 Urban " 7.3 Mean hours worked per day Men hours per day 7.0 Women " 8.4 Women's share of land Total percent 26.0 Rural " 28.7 Urbani 39.7 Social Indicators Mean births (1992/93) Rural of all women > 40 6.8 Urbani 6.3 Health Infant mortality (1991) 0 - 11 months per 1,000 live births 122 12 - 59 months " 93 0 - 59 months " 203 Population per physician (1989) 23,000 Population per hospital (1992) 185,350 Education (1992/93) Literacy rate All Uganda percent, age 6 and over 61 Male " 75 Female 49 Urban " 86 Rural 57 Primary school gross enrollment ratios Total % of relevant population 91 Male " 99 Female " 83 Urban " 103 Rural " 90 Secondary school gross enrollment ratios Total % of relevant population 13 Male 17 Female 10 Urban " 30 Rural 11 Sources: 1992/93 IHS and Key Economic Indicators (MFEP), November 1994.  100 AnnexIII StatisticalAnnex THE 1991 POPULATION AND HOUSING CENSUS TABLE 1.2 Final Results Percentage Region & District Total Male Female Urban Rural Urban CENTRAL Kalangala 16,371 9,929 6,442 1,376 14,995 8.4 Kampala 774.241 377,225 397,016 774,241 0 100.0 Kiboga 141,607 72,538 69,069 5,277 136,330 3.7 Luwero 449,691 224,399 225,292 36,531 413,160 8.1 Masaka 838,736 415,552 423,184 77,196 761,540 9.2 Mpigi 913,867 455,703 458,164 137,126 776,741 15.0 Mubende 500,976 254,081 246,895 34,541 466,435 6.9 Mukono 824,604 413,580 411,024 98,735 725,869 12.0 Rakai 383,501 189,082 194,419 14,869 368,632 3.9 Totals 4,843,594 2,412,089 2,431,505 1,179,892 3,663,702 24.4 EASTERN Iganga 945,783 461,079 484,704 44,002 901,781 4.7 Jinja 289,476 143,336 146,140 80,893 208,583 27.9 Kamuli 485,214 237,513 247,701 8,262 476,952 1.7 Kapchorwa 116,702 58,577 58,125 4,604 112,098 3.9 Kumi 236,694 112,719 123,975 11,749 224,945 5.0 Mbale 710,980 355,803 355,177 60,298 650,682 8.5 Pallisa 357,656 173,836 183,820 2,927 354,729 0.8 Soroti 430,390 209,530 220,860 46,274 384,116 10.8 Tororo 555,574 273,220 282,354 63,657 491,917 11.5 Totals 4,128,469 2,025,613 2,102,856 322,666 3,805,803 7.8 NORTHERN Apac 454,504 222,854 231,650 5,783 448,721 1.3 Arua 637,941 307,679 330,262 26,712 611,229 4.2 Gulu 338,427 166,318 172,109 38,297 300,130 11.3 Kitgum 357,184 172,640 184,544 15,327 341,857 4.3 Kotido 196,006 92,481 103,525 9,702 186,304 4.9 Lira 500,965 247,607 253,358 27,568 473,397 5.5 Moroto 174,417 80,061 94,356 12,981 161,436 7.4 Moyo 175,645 85,054 90,591 8,787 166,858 5.0 Nebbi 316,866 152,093 164,773 23,943 292,923 7.6 Totals 3,151,955 1,526,787 1,625,168 169,100 2,982,855 5.4 WESTERN Bundibugyo 116,566 57,816 58,750 9,215 107,351 7.9 Bushenyi 579,137 279,543 299,594 Hoima 197,851 99,547 98,304 4,616 193,235 2.3 Kabale 417,218 197,695 219,523 29,246 387,972 7.0 Kabarole 746,800 369,818 376,982 36,954 709,846 4.9 Kasese 343,601 167,672 175,929 39,892 303,709 11.6 Kibaale 220,261 109,756 110,505 2,408 217,853 1.1 Kisoro 186,681 86,406 100,275 7,485 179,196 4.0 Masindi 260,796 131,936 128,860 14,352 246,444 5.5 Mbarara 798,774 394,101 404,673 Ntungamo 289,222 139,083 150,139 Rukungiri 390,780 187,885 202,895 12,985 377,795 3.3 Totals 4,547,687 2,221,258 2,326,429 157,153 2,723,401 3.5 UGANDA Totals 16,671,705 8,185,747 8,485,958 Source: Statisticts Departnent, MFEP.  Annex.IlI StatisticalAnnex 101 POPULATION AND LITERACY BY RURAL-URBAN DISTRIBUTION TABLE 1.3 Age 10 and Over RURAL URBAN TOTAL Percent Percent Percent District Literate Total Literate Literate Total Literate Literate Total Literate Apac 155,010 294,870 53% 2,841 3,938 72% 157,851 298,808 53% Arua 182,108 405,732 45% 11,861 18,647 64% 193,969 424,379 46% Bundibugyo 27,257 70,256 39% 3,367 6,346 53% 30,624 76,602 40% Bushenyi 194,911 359,646 54% 7,541 9,806 77% 202,452 369,452 55% Gulu 93,707 204,937 46% 19,252 27,293 71% 112,959 232,230 49% Hoima 71,477 127,873 56% 2,518 3,174 79% 73,995 131,047 56% Iganga 268,940 586,305 46% 20,386 28,823 71% 289,326 615,128 47% Jinja 82,634 136,036 61% 46,979 56,281 83% 129,613 192,317 67% Kabale 122,418 245,573 50% 14,334 20,228 71% 136,752 265,801 51% Kabarole 218,629 457,770 48% 19,466 26,028 75% 238,095 483,798 49% Kalangala 8,160 11,481 71% 794 964 82% 8,954 12,445 72% Kampala 485,036 548,455 88% 485,036 548,455 88% Kamuli 125,588 311.382 40% 3,814 5,546 69% 129,402 316,928 41% Kapchorwa 38,972 72,255 54% 2,099 3,107 68% 41,071 75,362 54% Kasese 88,899 190,123 47% 19,010 27,110 70% 107,909 217,233 50% Kibale 69,188 137,468 50% 1,149 1,568 73% 70,337 139,036 51% Kiboga 48,986 90,368 54% 2,756 3,503 79% 51,742 93,871 55% Kisoro 34,625 107,558 32% 2,305 4,839 48% 36,930 112,397 33% Kitgum 88,635 233.183 38% 7,369 11,075 67% 96,004 244,258 39% Kotido 12,229 119,120 10% 2,962 6,325 47% 15,191 125,445 12% Kumi 62,829 154,329 41% 5,074 7,943 64% 67,903 162,272 42% Lira 152,636 313,908 49% 14,376 20,627 70% 167,012 334,535 50% Luwero 157,230 272,726 58% 18,537 24,329 76% 175,767 297,055 59% Masaka 297,260 493,519 60% 42.217 51,230 82% 339,477 544,749 62% Masindi 81,895 163,169 50% 8,952 10,756 83% 90,847 173,925 52% Mbale 236,032 435,239 54% 30,044 41,578 72% 266,076 476,817 56% Mbarara 255,772 499,939 51% 26,339 32,266 82% 282,111 532,205 53% Moroto 8,154 103,738 8% 4,701 8,760 54% 12,855 112,498 11% Moyo 49,559 112,575 44% 4,268 6,175 69% 53,827 118,750 45% Mpigi 358,634 506,433 71% 79,956 91,534 87% 438,590 597,967 73% Mubende 171,420 303,855 56% 18,835 22,704 83% 190,255 326,559 58% Mukuno 281,870 476,761 59% 49,939 64,366 78% 331,809 541,127 61% Nebbi 88.793 194,827 46% 10,069 16,476 61% 98,862 211,303 47% Ntungamo 87,190 185,994 47% 1,548 1,930 80% 88,738 187,924 47% Pallisa 108,866 233,973 47% 1,185 1,899 62% 110,051 235,872 47% Rakai 129,269 243,017 53% 8,230 10,155 81% 137,499 253,172 54% Rukungiri 136,024 243,266 56% 6,873 9,071 76% 142,897 252,337 57% Soroti 118,485 265,324 45% 21,031 31,210 67% 139,516 296,534 47% Tororo 165,633 329,409 50% 30,873 43,858 70% 196,506 373,267 53% Total: 4,879,924 9,693,937 50% 1,058,886 1,309,923 81 % 5,938,810 11,003,860 54% Source: The 1991 Population and Housing Census, Statistics Department, MFEP. Note: The literacy data presented here are different to those derived from the IHS owing to difference sources.  102 Annex lll StatisticalAnnex POPULATION AND LITERACY BY SEX DISTRIBUTION TABLE 1.4 Age 10 and Over MALE FEMALE TOTAL Percent Percent Percent District Literate Total Literate Literate Total Literate Literate Total Literate Apac 102,274 145,333 70% 55.577 153,475 36% 157,851 298,808 53% Arua 131,546 201,169 65% 62,423 223,210 28% 193,969 424,379 46% Bundibugyo 20,330 37,993 54% 10,294 38,609 27% 30,624 76,602 40% Bushenyi 111,595 175,530 64% 90,857 193,922 47% 202,452 369,452 55% Gulu 73,549 113,421 65% 39,410 118,809 33% 112,959 232,230 49% Hoima 41,945 66,213 63% 32,050 64,834 49% 73,995 131,047 56% Iganga 167,311 296,438 56% 122,015 318,690 38% 289,326 615,128 47% Jinja 71,295 95,652 75% 58,318 96,665 60% 129,613 192,317 67% Kabale 76,668 123,056 62% 60,084 142,745 42% 136,752 265,801 51% Kabarole 138,649 238,208 58% 99,446 245,590 40% 238,095 483,798 49% Kalangala 5,720 7,968 72% 3,234 4,477 72% 8,954 12,445 72% Kampala 244,190 268,174 91% 240,846 280,281 86% 485,036 548,455 88% Kamuli 74,721 153,886 49% 54,681 163,042 34% 129,402 316,928 41% Kapchorwa 25,934 37,997 68% 15,137 37.365 41% 41,071 75,362 54% Kasese 64,374 105,675 61% 43,535 111,558 39% 107,909 217,233 50% Kibale 41,177 69,380 59% 29,160 69,656 42% 70,337 139,036 51% Kiboga 29,144 48,784 60% 22,598 45,087 50% 51,742 93,871 55% Kisoro 23,978 49,637 48% 12,952 62,760 21% 36,930 112,397 33% Kitgum 68,299 116,219 59% 27,705 128,039 22% 96,004 244,258 39% Kotido 11,425 58,007 20% 3,766 67,438 6% 15,191 125,445 12% Kumi 41,056 75,765 54% 26,847 86,507 31% 67,903 162,272 42% Lira 112,919 164,487 69% 54,093 170,048 32% 167,012 334,535 50% Luwero 94,225 147,950 64% 81,542 149,105 55% 175,767 297,055 59% Masaka 176,201 268,745 66% 163,276 276,004 59% 339,477 544,749 62% Masindi 56,412 88,851 63% 34,435 85,074 40% 90,847 173,925 52% Mbale 150,876 239,572 63% 115,200 237,245 49% 266,076 476,817 56% Mbarara 161,241 262,235 61% 120,870 269,970 45% 282,111 532,205 53% Moroto 9,005 49,411 18% 3,850 63,087 6% 12,855 112,498 11% Moyo 35,131 56,545 62% 18,696 62,205 30% 53,827 118,750 45% Mpigi 224,597 298,070 75% 213,993 299,897 71% 438,590 597,967 73% Mubende 104,207 166,577 63% 86,048 159,982 54% 190,255 326,559 58% Mukuno 178,832 272,182 66% 152,977 268,945 57% 331,809 541,127 61% Nebbi 66,426 99,683 67% 32,436 111,620 29% 98,862 211,303 47% Ntungamo 50,838 88,792 57% 37,900 99,132 38% 88,738 187,924 47% Pallisa 66,226 113,117 59% 43,825 122,755 36% 110,051 235,872 47% Rakai 73,865 124,277 59% 63,634 128,895 49% 137,499 253,172 54% Rukungiri 77,068 119,837 64% 65,829 132,500 50% 142,897 252,337 57% Soroti 87,810 142,324 62% 51,706 154,210 34% 139,516 296,534 47% Tororo 116,979 182,606 64% 79,527 190,661 42% 196,506 373,267 53% Total: 3,408,038 5,369,766 63% 2,530,772 5,634,094 45% 5,938,810 11,003,860 54% Source: The 1991 Population and Housing Census, Statistics Department, MFEP. Note: The literacy data presented here are different to those derived from the IHS owing to difference sources.  GDP BY SECTOR AT CURRENT FACTOR COST TABLE I.1 ::s In U Sh Millions H 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 Agriculture 5,599 10,655 24,113 68,961 212,264 486,739 735,988 905,511 1,329,292 1,881,102 2,020,304 Cash Crops 1,688 2,547 2,662 3,278 8,347 20,363 30,190 51,393 90,994 106,306 143,893 Food Crops 2,947 5,934 16,388 48,948 150,736 344,226 530,407 621,652 896,227 1,351,514 1,388,814 Livestock 642 1,626 3,841 12,532 37,294 86,501 119,794 154,728 228,439 279,288 319,512 Forestry 135 259 656 1,927 6,439 15,293 24,001 32,452 44,795 59,819 69,752 Fishing 187 289 566 2,276 9,448 20,356 31,596 45,286 68,837 84,175 98,333 H Industry 866 1,704 4,322 12,823 40,062 96,291 150,440 224,773 367,731 505,290 591,151 Mining & Quarrying 13 23 50 143 341 682 2,047 4,732 8,585 12,171 12,844 Manufacturing 521 970 2,625 7,165 21,928 51,663 74,629 103,139 170,641 229,633 279,713 Coffee, Cotton, Sugar 90 226 745 745 1,858 5,960 9,005 12,254 22,877 25,800 32,287 Food Products 76 123 285 925 3,591 9,416 10,723 13,923 21,448 28,096 33,094 Miscelleneous 355 621 1,595 5,495 16,479 36,287 54,901 76,962 126,316 175,737 214,332 Public Utilities 73 159 400 1,325 3,928 10,139 16,180 24,360 34,523 49,560 63,417 Construction 259 552 1,247 4,190 13,865 33,807 57,584 92,542 153,982 213,926 235,177 Services 2,590 6,107 13,260 39,950 124,408 278,707 420,947 598,303 928,803 1,316,748 1,508,144 Trade 994 2,101 5,616 19,200 57,061 117,066 170,740 201,812 304,977 418,229 438,804 Hotels & Restaurants 82 147 366 1,288 3,888 9,761 15,862 22,016 34.789 48,540 57,793 Transport&Comnmunication 189 405 1,042 3,318 10,740 26,661 47,131 67,657 102,027 137,011 153,884 Road 159 324 853 2,523 7,993 20,090 35,116 50,320 76,931 105,809 117,534 Rail 15 48 74 222 942 2,103 3,152 4,422 5,193 5,984 7,698 Air 11 27 97 428 1,117 2,563 4,428 5,762 10,090 12,948 14,096 Communication 4 6 18 145 688 1,905 4,435 7,153 9,813 12,270 14,556 General Government 395 1,380 1,493 1,912 11,457 22,655 26,527 52,292 106,539 157,333 198,989 Education 280 727 1,395 3,287 10,194 25,948 40,227 64,484 90,213 152,866 195,693 Health 84 187 427 1,228 3,406 8,100 12,805 23,933 39,136 56,397 59,247 Rents 147 291 725 2,443 7,170 18,563 30,535 52,298 80,352 113,070 133,134 Owner-Occupied Dwellings 207 432 1,096 3,563 9,811 23,268 34,817 54,423 76,512 100,879 112,579 Miscellaneous 212 437 1,100 3,711 10,681 26,685 42,303 59,388 94,258 132,423 158,021 GDP at Factor Cost 9,055 18,466 41,695 121,734 376,734 861,737 1,307,375 1,728,587 2,625,826 3,703,140 4,119,599 o/w Non-Monetary 2,667 5,540 14,906 45,035 136,922 314,097 478,015 575,817 831,228 1,144,191 1,174,297 Indirect Taxes 774 1,479 2,637 4,385 16,781 37,980 80,098 119,495 156,691 244,450 329,211 GDP at Market Prices 9,829 19,945 44,332 126,119 393,515 899,717 1,387,473 1,848,082 2,782,517 3,947,590 4,448,810 Source: Statistics Department, MFEP.  GDP BY SECTOR AT CONSTANT 1991 PRICES TABLE H.2 In U Sh Millions 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 Agriculture 880,041 853,943 865,105 880,866 928,443 986,602 1,040,109 1,069,049 1,056,897 1,157,211 1,177,284 Cash Crops 64,126 69,585 58,146 55,935 55,443 59,274 66,328 68,437 72,028 74,319 80,480 Food Crops 584,848 555,124 584,614 599,999 635,283 678,883 715,074 729,161 705,707 792,566 801,112 Livestock 160,742 155,991 150,498 150,906 159,954 168,892 175,141 182,016 186,067 192,900 198,595 Forestry 29,899 29,713 29,499 30,704 33,020 34,341 35,205 36,593 38,170 40,347 42,016 Fishing 40,426 43,530 42,348 43,322 44,743 45,212 48,361 52,842 54,925 57,079 55,081 Industry 174,104 166,546 158,921 180,086 213,942 222,689 237,382 261,354 290,549 312,416 352,718 Mining & Quarrying 2,818 2,344 2,058 1,858 1,654 1,434 3,269 5,954 6,690 7,459 7,917 Manufacturing 84,824 80,190 76,301 78,155 91,424 99,943 107,389 117,271 139,467 148,679 170,573 Coffee, Cotton, Sugar 8,817 8,440 8,386 8,747 8,728 11,288 11,271 12,837 19,834 17,228 20,591 Food Products 10,212 9,298 8,776 9,857 13,716 14,456 13,098 15,639 17,051 18,225 19,452 Miscelleneous 65,795 62,452 59,139 59,551 68,980 74,199 83,020 88,795 102,582 113,226 130,530 Public Utilities 12,334 13,220 13,969 14,587 15,507 16,216 16,564 17,611 19,351 20,378 21,471 Construction 74,128 70,792 66,593 85,486 105,357 105,096 110,160 120,518 125,041 135,900 152,757 Services 517,423 512,607 515,242 534,784 573,217 610,930 652,130 703,218 758,934 817,459 873,773 Trade 171,370 164,886 160,563 164,744 184,488 197,887 210,969 227,244 247,690 270,811 295,039 Hotels & Restaurants 17,129 14,982 15,057 16,751 18,860 20,540 22,951 25,571 28,497 31,554 34,068 Transport & Communication 55,385 57,312 60,247 64,491 69,019 73,450 78,525 84,329 88,109 94,569 100,568 Road 38,311 41,948 44,842 47,625 51,112 55,278 59,303 63,363 66,596 71,446 75,512 Rail 4,914 4,285 4,002 4,285 4,258 4,183 4,604 5,554 5,034 5,206 5,624 Air 4,867 4,224 4,759 5,758 6,490 6,501 6,784 7,086 7,506 8,125 8,610 Communication 7,293 6,855 6,644 6,823 7,159 7,488 7,834 8,326 8,973 9,792 10,822 General Government 56,673 57,239 58,179 59,804 61,579 63,982 65,705 70,666 78,985 84,016 88,298 Education 59,496 60,710 61,096 61,226 61,881 65,501 70,543 74,629 75,726 76,208 77,184 Health 23,455 23,847 24,394 25,275 26,142 27,156 28,089 29,049 30,807 32,067 33,270 Rents 37,116 35,851 36,005 38,337 41,987 47,154 53,331 60,114 67,593 74,834 81,460 Owner-Occupied Dwellings 52,328 53,203 54,423 55,914 57,449 59,105 60,810 62,556 64,362 66,765 68,883 Miscellaneous 44,471 44,577 45,278 48,242 51,812 56,155 61,207 69,060 77,165 86,635 95,003 GDP at Faaor Cost 1,571,568 1,533,096 1,539,268 1,595,736 1,715,602 1,820,221 1,929,621 2,033,621 2,106,380 2,287,086 2,403,775 o/w Non-Monetary 543,504 526,806 550,316 563,196 592,014 624,733 647,827 653,697 633,295 685,158 681,329 Indirect Taxes 115,347 102,842 92,196 97,547 123,313 134,347 143,595 137,200 133,362 143,422 157,765 GDP at Market Prices 1,686,915 1,635,938 1,631,464 1,693,283 1,838,915 1,954,568 2,073,216 2,170,821 2,239,742 2,430,508 2,561,540 Source: Statistics Departnent, MFEP. :bE  GDP BY SECTOR AT CURRENT FACTOR COST TABLE 11.3 Percentage Share of GDP at Factor Cost 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 Agriculture 61.8 57.7 57.8 56.6 56.3 56.5 56.3 52.4 50.6 50.8 49.0 Cash Crops 18.6 13.8 6.4 2.7 2.2 2.4 2.3 3.0 3.5 2.9 3.5 Food Crops 32.5 32.1 39.3 40.2 40.0 39.9 40.6 36.0 34.1 36.5 33.7 Livestock 7.1 8.8 9.2 10.3 9.9 10.0 9.2 9.0 8.7 7.5 7.8 Forestry 1.5 1.4 1.6 1.6 1.7 1.8 1.8 1.9 1.7 1.6 1.7 Fishing 2.1 1.6 1.4 1.9 2.5 2.4 2.4 2.6 2.6 2.3 2.4 Industry 9.6 9.2 10.4 10.5 10.6 11.2 11.5 13.0 14.0 13.6 14.3 Mining & Quarrying 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.3 0.3 0.3 0.3 Manufacturing 5.8 5.3 6.3 5.9 5.8 6.0 5.7 6.0 6.5 6.2 6.8 Coffee, Cotton, Sugar 1.0 1.2 1.8 0.6 0.5 0.7 0.7 0.7 0.9 0.7 Food Products 0.8 0.7 0.7 0.8 1.0 1.1 0.8 0.8 0.8 0.8 Miscelleneous 3.9 3.4 3.8 4.5 4.4 4.2 4.2 4.5 4.8 4.7 Public Utilities 0.8 0.9 1.0 1.1 1.0 1.2 1.2 1.4 1.3 1.3 1.5 Construction 2.9 3.0 3.0 3.4 3.7 3.9 4.4 5.4 5.9 5.8 5.7 Services 28.6 33.1 31.8 32.8 33.0 32.3 32.2 34.6 35.4 35.6 36.6 Trade 11.0 11.4 13.5 15.8 15.1 13.6 13.1 11.7 11.6 11.3 10.7 Hotels & Restaurants 0.9 0.8 0.9 1.1 1.0 1.1 1.2 1.3 1.3 1.3 1.4 Transport&Communication 2.1 2.2 2.5 2.7 2.9 3.1 3.6 3.9 3.9 3.7 3.7 Road 1.8 1.8 2.0 2.1 2.1 2.3 2.7 2.9 2.9 2.9 2.9 Rail 0.2 0.3 0.2 0.2 0.3 0.2 0.2 0.3 0.2 0.2 0.2 Air 0.1 0.1 0.2 0.4 0.3 0.3 0.3 0.3 0.4 0.3 0.3 Communication 0.0 0.0 0.0 0.1 0.2 0.2 0.3 0.4 0.4 0.3 0.4 General Government 4.4 7.5 3.6 1.6 3.0 2.6 2.0 3.0 4.1 4.2 4.8 Education 3.1 3.9 3.3 2.7 2.7 3.0 3.1 3.7 3.4 4.1 4.8 Health 0.9 1.0 1.0 1.0 0.9 0.9 1.0 1.4 1.5 1.5 1.4 Rents 1.6 1.6 1.7 2.0 1.9 2.2 2.3 3.0 3.1 3.1 3.2 Owner-Occupied Dwellings 2.3 2.3 2.6 2.9 2.6 2.7 2.7 3.1 2.9 2.7 2.7 Miscellaneous 2.3 2.4 2.6 3.0 2.8 3.1 3.2 3.4 3.6 3.6 3.8 GDP at Factor Cost 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 o/w Non-Monetary 29.5 30.0 35.8 37.0 36.3 36.4 36.6 33.3 31.7 30.9 28.5 Indirect Taxes 8.5 8.0 6.3 3.6 4.5 4.4 6.1 6.9 6.0 6.6 8.0 GDP at Market Prices 108.5 108.0 106.3 103.6 104.5 104.4 106.1 106.9 106.0 106.6 108.0 Source: Statistics Department, MFEP.  GDP BY SECTOR AT CONSTANT 1991 PRICES TABLE 11.4 o Annual Growth Rates 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 Agricufrurc -3.0 1.3 1.8 5.4 6.3 5.4 2.8 -1.1 9.5 1.7 Cash Crops 8.5 -16.4 -3.8 -0.9 6.9 11.9 3.2 5.2 3.2 8.3 Food Crops -5.1 5.3 2.6 5.9 6.9 5.3 2.0 -3.2 12.3 1.1 Livestock -3.0 -3.5 0.3 6.0 5.6 3.7 3.9 2.2 3.7 3.0 Forestry -0.6 -0.7 4.1 7.5 4.0 2.5 3.9 4.3 5.7 4.1 Fishibg 7.7 -2.7 2.3 3.3 1.0 7.0 9.3 3.9 3.9 -3.5 Industry -4.3 -4.6 13.3 18.8 4.1 6.6 10.1 11.2 75 12.9 Mining & Quanrying -16.8 -12.2 -9.7 -11.0 -13.3 128.0 82.1 12.4 11.5 6.1 Manufacturing -5.5 -4.8 2.4 17.0 9.3 7.5 9.2 18.9 6.6 14.7 Coffee, Cotton, Sugar -4.3 -0.6 4.3 -0.2 29.3 -0.2 13.9 54.5 -13.1 Food Products -9.0 -5.6 12.3 39.1 5.4 -9.4 19.4 9.0 6.9 Miscelleneous -5.1 -5.3 0.7 15.8 7.6 11.9 7.0 15.5 10.4 Public Utilities 7.2 5.7 4.4 6.3 4.6 2.1 6.3 9.9 5.3 5.4 Construction -4.5 -5.9 28.4 23.2 -0.2 4.8 9.4 3.8 8.7 12.4 Services -0.9 0.5 3.8 72 6.6 6.7 7.8 Z9 7.7 6.9 Trade -3.8 -2.6 2.6 12.0 7.3 6.6 7.7 9.0 9.3 8.9 Hotels & Restaurants -12.5 0.5 11.3 12.6 8.9 11.7 11.4 11.4 10.7 8.0 Transport& Communication 3.5 5.1 7.0 7.0 6.4 6.9 7.4 4.5 7.3 6.3 Road 9.5 6.9 6.2 7.3 8.2 7.3 6.8 5.1 7.3 5.7 Rail -12.8 -6.6 7.1 -0.6 -1.8 10.1 20.6 -9.4 3.4 8.0 Air -13.2 12.7 21.0 12.7 0.2 4.4 4.5 5.9 8.2 6.0 Communication -6.0 -3.1 2.7 4.9 4.6 4.6 6.3 7.8 9.1 10.5 General Govermnent 1.0 1.6 2.8 3.0 3.9 2.7 7.6 11.8 6.4 5.1 Education 2.0 0.6 0.2 1.1 5.8 7.7 5.8 1.5 0.6 1.3 Health 1.7 2.3 3.6 3.4 3.9 3.4 3.4 6.1 4.1 3.8 Rents -3.4 0.4 6.5 9.5 12.3 13.1 12.7 12.4 10.7 8.9 Owner-Occupied Dwellings 1.7 2.3 2.7 2.7 2.9 2.9 2.9 2.9 3.7 3.2 Miscellaneous 0.2 1.6 6.5 7.4 8.4 9.0 12.8 11.7 12.3 9.7 GDP at Factor Cost -2.4 0.4 3.7 75 6.1 6.0 5.4 3.6 8.6 5.1 o/w Non-Monetary -3.1 4.5 2.3 5.1 5.5 3.7 0.9 -3.1 8.2 -0.6 Wndirect Taxes -10.8 -10.4 5.8 26.4 8.9 6.9 -4.5 -2.8 7.5 10.0 GDP at Market Prices -3.0 -0.3 3.8 8.6 6.3 6.1 4.7 3.2 8.5 5.4 Source: Statistics Department, MFEP.  GDP BY SECTOR AT CONSTANT 1991 PRICES TABLE Il.5 Percentage Share of GDP at Factor Cost 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 Agriculture 56.0 55.7 56.2 55.2 54.1 54.2 53.9 52.6 50.2 50.6 49.0 Cash Crops 4.1 4.5 3.8 3.5 3.2 3.3 3.4 3.4 3.4 3.2 3.3 Food Crops 37.2 36.2 38.0 37.6 37.0 37.3 37.1 35.9 33.5 34.7 33.3 Livestock 10.2 10.2 9.8 9.5 9.3 9.3 9.1 9.0 8.8 8.4 8.3 Forestry 1.9 1.9 1.9 1.9 1.9 1.9 1.8 1.8 1.8 1.8 1.7 Fishing 2.6 2.8 2.8 2.7 2.6 2.5 2.5 2.6 2.6 2.5 2.3 Industry 11.1 10.9 10.3 11.3 12.5 12.2 12.3 12.9 13.8 13.7 14.7 Mining & Quarrying 0.2 0.2 0.1 0.1 0.1 0.1 0.2 0.3 0.3 0.3 0.3 Manufacturing 5.4 5.2 5.0 4.9 5.3 5.5 5.6 5.8 6.6 6.5 7.1 Coffee, Cotton, Sugar 0.6 0.6 0.5 0.5 0.5 0.6 0.6 0.6 0.9 0.8 Food Products 0.6 0.6 0.6 0.6 0.8 0.8 0.7 0.8 0.8 0.8 Miscelleneous 4.2 4.1 3.8 3.7 4.0 4.1 4.3 4.4 4.9 5.0 Public Utilities 0.8 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 Construction 4.7 4.6 4.3 5.4 6.1 5.8 5.7 5.9 5.9 5.9 6.4 Services 32.9 33.4 33.5 33.5 33.4 33.6 33.8 34.6 36.0 35.7 36.4 Trade 10.9 10.8 10.4 10.3 10.8 10.9 10.9 11.2 11.8 11.8 12.3 Hotels & Restaurants 1.1 1.0 1.0 1.0 1.1 1.1 1.2 1.3 1.4 1.4 1.4 Transport&Comnmunication 3.5 3.7 3.9 4.0 4.0 4.0 4.1 4.1 4.2 4.1 4.2 Road 2.4 2.7 2.9 3.0 3.0 3.0 3.1 3.1 3.2 3.1 3.1 Rail 0.3 0.3 0.3 0.3 0.2 0.2 0.2 0.3 0.2 0.2 0.2 Air 0.3 0.3 0.3 0.4 0.4 0.4 0.4 0.3 0.4 0.4 0.4 Communrication 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.5 General Governrment 3.6 3.7 3.8 3.7 3.6 3.5 3.4 3.5 3.7 3.7 3.7 Education 3.8 4.0 4.0 3.8 3.6 3.6 3.7 3.7 3.6 3.3 3.2 Health 1.5 1.6 1.6 1.6 1.5 1.5 1.5 1.4 1.5 1.4 1.4 Rents 2.4 2.3 2.3 2.4 2.4 2.6 2.8 3.0 3.2 3.3 3.4 Owner-Occupied Dwellings 3.3 3.5 3.5 3.5 3.3 3.2 3.2 3.1 3.1 2.9 2.9 Miscellaneous 2.8 2.9 2.9 3.0 3.0 3.1 3.2 3.4 3.7 3.8 4.0 GDP at Factor Cost 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 o/w Non-Monetary 34.6 34.4 35.8 35.3 34.5 34.3 33.6 32.1 30.1 30.0 28.3 Indirect Taxes 7.3 6.7 6.0 6.1 7.2 7.4 7.4 6.7 6.3 6.3 6.6 GDP at Market Prices 107.3 106.7 106.0 106.1 107.2 107.4 1074 106.7 106.3 106.3 106.6 Source: Statistics Department, MFEP.  SECTORAL DEFLATORS TABLE 11.6 1991 = 100 oo 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 Agriculture 0.6 1.2 2.8 7.8 22.9 49.3 70.8 84.7 125.8 162.6 171.6 CashCrops 2.6 3.7 4.6 5.9 15.1 34.4 45.5 75.1 126.3 143.0 178.8 Food Crops 0.5 1.1 2.8 8.2 23.7 50.7 74.2 85.3 127.0 170.5 173.4 Livestock 0.4 1.0 2.6 8.3 23.3 51.2 68.4 85.0 122.8 144.8 160.9 Forestry 0.5 0.9 2.2 6.3 19.5 44.5 68.2 88.7 117.4 148.3 166.0 Fishing 0.5 0.7 1.3 5.3 21.1 45.0 65.3 85.7 125.3 147.5 178.5 Industry 0.5 1.0 2.7 7.1 18.7 43.2 63.4 86.0 126.6 161.7 167.6 Mining & Quarrying 0.5 1.0 2.4 7.7 20.6 47.6 62.6 79.5 128.3 163.2 162.2 Manufacturing 0.6 1.2 3.4 9.2 24.0 51.7 69.5 87.9 122.4 154.4 164.0 Coffee, Cotton, Sugar 1.0 2.7 8.9 8.5 21.3 52.8 79.9 95.5 115.3 149.8 Food Products 0.7 1.3 3.2 9.4 26.2 65.1 81.9 89.0 125.8 154.2 Miscelleneous 0.5 1.0 2.7 9.2 23.9 48.9 66.1 86.7 123.1 155.2 Public Utilities 0.6 1.2 2.9 9.1 25.3 62.5 97.7 138.3 178.4 243.2 295.4 Construction 0.3 0.8 1.9 4.9 13.2 32.2 52.3 76.8 123.1 157.4 154.0 Services 0.5 1.2 2.6 7.5 21.7 45.6 64.5 85.1 122.4 161.1 172.6 Trade 0.6 1.3 3.5 11.7 30.9 59.2 80.9 88.8 123.1 154.4 148.7 Hotels & Restaurants 0.5 1.0 2.4 7.7 20.6 47.5 69.1 86.1 122.1 153.8 169.6 Transport & Communication 0.3 0.7 1.7 5.1 15.6 36.3 60.0 80.2 115.8 144.9 153.0 Road 0.4 0.8 1.9 5.3 15.6 36.3 59.2 79.4 115.5 148.1 155.6 Rail 0.3 1.1 1.8 5.2 22.1 50.3 68.5 79.6 103.2 114.9 136.9 Air 0.2 0.6 2.0 7.4 17.2 39.4 65.3 81.3 134.4 159.4 163.7 Communication 0.1 0.1 0.3 2.1 9.6 25.4 56.6 85.9 109.4 125.3 134.5 General Governrment 0.7 2.4 2.6 3.2 18.6 35.4 40.4 74.0 134.9 187.3 225.4 Education 0.5 1.2 2.3 5.4 16.5 39.6 57.0 86.4 119.1 200.6 253.5 Health 0.4 0.8 1.8 4.9 13.0 29.8 45.6 82.4 127.0 175.9 178.1 Rents 0.4 0.8 2.0 6.4 17.1 39.4 57.3 87.0 118.9 151.1 163.4 Owner-Occupied Dwellings 0.4 0.8 2.0 6.4 17.1 39.4 57.3 87.0 118.9 151.1 163.4 Miscellaneous 0.5 1.0 2.4 7.7 20.6 47.5 69.1 86.0 122.2 152.9 166.3 GDP at Factor Cost 0.6 1.2 2.7 Z6 22.0 473 67.8 85.0 124.7 161.9 171.4 o/w Non-Monetary 0.5 1.1 2.7 8.0 23.1 50.3 73.8 88.1 131.3 167.0 172.4 IndirectTaxes 0.7 1.4 2.9 4.5 13.6 28.3 55.8 87.1 117.5 170.4 208.7 GDP at Market Prices 0.6 1.2 2.7 7.4 21.4 46.0 66.9 85.1 124.2 162.4 173.7 Source: Statistics Department, MFEP.  CHANGE IN SECTORAL DEFLATORS TABLE 11.7 1991 = 100, In Percent 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 Agriculture 96.1 123.4 180.9 192.0 115.8 43.4 19.7 48.5 29.2 5.6 Cash Crops 39.1 25.1 28.0 156.9 128.2 32.5 65.0 68.2 13.2 25.0 Food Crops 112.1 162.2 191.0 190.8 113.7 46.3 14.9 49.0 34.3 1.7 Livestock 161.0 144.8 225.4 180.8 119.7 33.5 24.3 44.4 17.9 11.1 Forestry 93.1 155.1 182.2 210.7 128.4 53.1 30.1 32.3 26.3 12.0 Fishing 43.5 101.3 293.1 301.9 113.2 45.1 31.2 46.2 17.7 21.1 Industry 105.7 165.8 161.8 163.0 130.9 46.6 35.7 47.2 27.8 3.6 Mining & Quarrying 112.7 147.6 216.8 167.9 130.7 31.7 26.9 61.5 27.2 -0.6 Manufacturing 96.9 184.4 166.5 161.6 115.5 34.4 26.6 39.1 26.2 6.2 Coffee, Cotton, Sugar 162.3 231.8 -4.1 149.9 148.0 51.3 19.5 20.8 29.8 Food Products 77.8 145.5 189.0 179.0 148.8 25.7 8.7 41.3 22.6 Miscelleneous 84.3 171.2 242.1 158.9 104.7 35.2 31.1 42.1 26.0 Public Utilities 103.2 138.1 217.2 178.9 146.8 56.2 41.6 29.0 36.3 21.4 Construction 123.2 140.2 161.7 168.5 144.4 62.5 46.9 60.4 27.8 -2.2 Services 138.0 116.0 190.3 190.5 110.2 41.5 31.8 43.8 31.6 7.2 Trade 119.7 174.5 233.2 165.4 91.3 36.8 9.7 38.6 25.4 -3.7 Hotels & Restaurants 105.0 147.7 216.3 168.1 130.5 45.4 24.6 41.8 26.0 10.3 Transport& Communication 107.1 144.8 197.5 202.5 133.3 65.4 33.7 44.3 25.1 5.6 Road 86.1 146.3 178.5 195.2 132.4 62.9 34.1 45.5 28.2 5.1 Rail 267.0 65.1 180.2 327.0 127.3 36.2 16.3 29.6 11.4 19.1 Air 182.8 218.9 264.7 131.5 129.1 65.6 24.6 65.3 18.5 2.7 Conununication 59.6 209.5 684.4 352.2 164.7 122.5 51.8 27.3 14.6 7.3 General Government 245.9 6.4 24.6 481.9 90.3 14.0 83.3 82.3 38.8 20.3 Education 154.5 90.7 135.1 206.8 140.5 43.9 51.5 37.9 68.4 26.4 Health 119.0 123.2 177.6 168.2 128.9 52.8 80.7 54.2 38.4 1.3 Rents 104.9 148.1 216.5 168.0 130.5 45.4 51.9 36.6 27.1 8.2 Owner-Occupied Dwellings 105.3 148.0 216.4 168.0 130.5 45.4 51.9 36.6 27.1 8.2 Miscellaneous 105.6 147.8 216.6 168.0 130.5 45.4 24.4 42.0 25.1 8.8 GDP at Factor Cost 109.0 124.9 181.6 1879 115.6 43.1 25.5 46.7 29.9 5.8 o/w Non-Monetary 114.3 157.6 195.2 189.2 117.4 46.8 19.4 49.0 27.2 3.2 Indirect Taxes 114.3 98.9 57.2 202.7 107.7 97.3 56.1 34.9 45.1 22.4 GDP at Market Prices 109.2 122.9 174.1 18Z3 115.1 45.4 27.2 45.9 30.7 6.9 Source: Statistics Department. MFEP. 0  GDP BY EXPENDITURE IN CURRENT PRICES TABLE IL.8 In Millions of Ugandan Shillings 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 Consumption 7,971 17,200 42,528 128,459 396,264 937,975 1,454,647 1,897.177 2,896,806 4,013,877 4,602,803 Private 7,025 14,589 37,714 119,074 363,532 865,040 1,313,317 1,703,138 2,502,683 3,518,868 4,044,364 Public 946 2,611 4,814 9,385 32,732 72,935 141,330 194,039 394,123 495,009 558,439 Gross Domestic Investment 651 1,524 3,434 11,748 40,345 92,631 165,237 273,376 423,837 557,882 573,163 Fixed Capital Formation 659 1,488 3,433 11,540 40,230 94,829 166,111 267,077 425,985 548,766 570,362 Private 233 746 2,529 8,434 25,530 71,303 108,637 162,013 230,002 252,299 250,008 Public 426 742 905 3,107 14,700 23,526 57,474 105,064 195,984 296,468 320,354 Net Changes in Stocks -8 36 1 208 115 -2,198 -874 6,299 -2,148 9,116 2,801 Gross Domestic Expenditure 8,622 18,724 45,962 140,207 436,609 1,030,606 1,619,884 2,170,553 3,320,643 4,571,759 5,175,966 Resource Balance -95 -184 -1,003 -12,724 -40,221 -82,124 -151,302 -278,095 -438,314 -605,652 -522,781 Exports GNFS 998 2,317 5,014 8,369 23,776 60,493 83,120 112,600 199,212 216,017 271,702 Imports GNFS 1,093 2,501 6,017 21,093 63,997 142,617 234,422 390,695 637,526 821,669 794,483 Statistical Discrepancy 1,302 1,405 -627 -1,364 -2,873 -48,765 -81,109 -44,376 -99,812 -18,517 -204,375 GDP-Market Prices 9,829 19,945 44,332 126,119 393,515 899,717 1,387,473 1,848,082 2,782,517 3,947,590 4,448,810 GNP 9,719 19,676 43,855 125,188 390,095 888,471 1,362,863 1,816,020 2,698,927 3,888,822 4,382,222 Net Factor Service Income -110 -269 -477 -931 -3,420 -11,246 -24,610 -32,062 -83,590 -58,768 -66,588 Net Current Transfers 61 203 1,096 1,984 7,200 19,426 24,930 44,347 130,573 289,634 332,940 Gross Domestic Savings 556 1,340 2,431 -976 124 10,507 13,935 -4,719 -14,477 -47,770 50,382 Private 155 1,028 2,538 -387 -24 17,723 9,148 -29,600 32,452 -75,132 13,390 Public 401 312 -108 -589 148 -7,216 4,786 24,881 -46,929 27,362 36,992 Gross National Savings 507 1,274 3,049 77 3,904 18,686 14,254 7,566 32,506 183,095 316,734 Private 272 1,220 3,721 1,166 6,056 31,702 18,025 1,341 169,528 225,119 343,420 Public 235 54 -672 -1,089 -2,152 -13,016 -3,771 6,225 -137,022 -42,024 -26,686 Memorandun Items: Population (Millions) 13.9 14.2 14.5 14.9 15.3 15.7 16.2 16.7 17.1 17.8 18.3 Exchange Rate (U Sh/US$) 2 5 11 19.80 60 170 320 551 961 1202 1097 GDP in Current US$ m 4,200 3,926 4,086 6,370 6,559 5,280 4,341 3,355 2,896 3,285 4,055 Source: Statistics Department, MFEP, and staff estimates.  GDP BY EXPENDlTURE IN CONSTANT 1991 PRICES TABLE 11.9 In Millions of Ugandan Sillings 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 Consumption 1,709,642 1,677,076 1,711,407 1,761,240 1,874,144 1,991,133 2,108,219 2,176,952 2,276,676 2,387,857 2,460,688 Private 1,527,772 1,500,309 1,533,725 1,576,949 1,684,364 1,796,277 1,887,920 1,963,007 2,011,444 2,151,839 2,212,815 Public 181,870 176,767 177,682 184,291 189,780 194,856 220,299 213,945 265,232 236,018 247,873 Gross Domestic Investment 206,447 200,567 204,078 284,875 344,486 315,204 325,757 352,230 327,838 340,982 367,624 Fixed Capital Formation 204,061 199,055 204,010 279,667 342,548 324,796 329,236 342,473 329,728 331,866 364,612 Private 96,426 100,736 147,098 182,916 191,563 239,975 213,960 208,051 178,508 151,949 155,701 Public 107,635 98,319 56,912 96,751 150,985 84,821 115,276 134,422 151,220 179,917 208,911 Net Changes in Stocks 2,386 1,512 68 5,208 1,938 -9,592 -3,479 9,757 -1,890 9,116 3,012 Gross Domestic Expenditure 1,916,089 1,877,643 1,915,485 2,046,115 2,218,630 2,306,337 2,433,976 2,529,182 2,604,514 2,728,839 2,828,312 Resource Balance -245,845 -245,725 -256,550 -342,251 -385,454 -369,542 -346,012 -362,514 -325,031 -381,733 -320,598 Exports GNFS 137,264 133,542 134,781 130,001 133,485 142,562 150,708 138,538 162,249 149,782 219,043 Imports GNFS 383,109 379,267 391,331 472,252 518,939 512,104 496,720 501,052 487,280 531,515 539,641 Statistical Discrepancy 16,671 4,020 -27,471 -10,581 5,739 17,773 -14,748 4,153 -39,741 83,402 53,826 GDP-Market Prices 1,686,915 1,635,938 1,631,464 1,693,283 1,838,915 1,954,568 2,073,216 2,170,821 2,239,742 2,430,508 2,561,540 Terms of Trade Adjustment 212,611 217,806 191,301 57,369 59,311 74,654 25,416 5,867 -9,985 -10,047 -34,494 Import Capacity 349,875 351,348 326,082 187,370 192,796 217,216 176,124 144,405 152,264 139,735 184,550 Net Factor Service Income -38,537 -40,824 -31,048 -20,835 -27,732 -40,383 -52,146 41,119 -63,890 -38,015 45,229 Net Current Transfers 21,318 30,811 71,268 44,422 58,384 69,753 52,824 56,874 99,801 187,356 226,144 GNP 1,648,378 1,595,114 1,600,416 1,672,448 1,811,183 1,914,185 2,021,070 2,129,702 2,175,852 2,392,493 2,516,311 Gross Domestic Savings 173,213 172,648 138,829 -7 18,343 20,316 5,161 4,417 -7,178 -50,798 12,532 Gross National Savings 155,994 162,635 179,050 23,580 48,994 49,685 5,838 11,338 28,732 98,543 193,448 Gross Domestic Income 1,899,526 1,853,744 1,822,765 1,750,652 1,898,226 2,029,222 2,098,632 2,176,688 2,229,757 2,420,461 2,527,046 Gross National Income 1,860,989 1,812,920 1,791,718 1,729,817 1,870,493 1,988,839 2,046,485 2,135,569 2,165,867 2,382,446 2,481,818 Memorandwn Items: WPI (1991=100) 0.3 0.7 1.5 4.5 12.3 27.8 47.2 78.0 130.8 154.6 147.2 XPI (1991=100) 0.7 1.7 3.7 6.4 17.8 42.4 55.2 81.3 122.8 144.2 124.0 TOT (1991=100) 9.0 263.1 241.9 144.1 144.4 152.4 116.9 104.2 93.8 93.3 84.3 Source: Statistics Department, MFEP, and staff estimates.  GDP BY EXPENDITURE IN CURRENT PRICES TABLE 11.10 As a Percentage of GDP at Market Prices 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 Consutmption 81.1 86.2 95.9 101.9 100.7 104.3 104.8 102.7 104.1 101.7 103.5 Private 71.5 73.1 85.1 94.4 92.4 96.1 94.7 92.2 89.9 89.1 90.9 Public 9.6 13.1 10.9 7.4 8.3 8.1 10.2 10.5 14.2 12.5 12.6 Gross Domestic Investment 6.6 7.6 7.7 9.3 10.3 10.3 11.9 14.8 15.2 14.1 12.9 Fixed Capital Formation 6.7 7.5 7.7 9.2 10.2 10.5 12.0 14.5 15.3 13.9 12.8 Private 2.4 3.7 5.7 6.7 6.5 7.9 7.8 8.8 8.3 6.4 5.6 Public 4.3 3.7 2.0 2.5 3.7 2.6 4.1 5.7 7.0 7.5 7.2 NetChanges in Stocks -0.1 0.2 0.0 0.2 0.0 -0.2 -0.1 0.3 -0.1 0.2 0.1 Gross Domestic Expenditure 87.7 93.9 103.7 111.2 111.0 114.5 116.8 117.4 119.3 115.8 116.3 Resource Balance -1.0 -0.9 -2.3 -10.1 -10.2 -9.1 -10.9 -15.0 -15.8 -15.3 -11.8 Exports GNFS 10.2 11.6 11.3 6.6 6.0 6.7 6.0 6.1 7.2 5.5 6.1 Imports GNFS 11.1 12.5 13.6 16.7 16.3 15.9 16.9 21.1 22.9 20.8 17.9 Statistical Discrepancy 13.2 7.0 -1.4 -1.1 -0.7 -5.4 -5.8 -2.4 -3.6 -0.5 -4.6 GDP-Market Prices 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 GNP 98.9 98.7 98.9 99.3 99.1 98.8 98.2 98.3 970 98.5 98.5 Net Factor Service Income -1.1 -1.3 -1.1 -0.7 -0.9 -1.2 -1.8 -1.7 -3.0 -1.5 -1.5 Net Current Transfers 0.6 1.0 2.5 1.6 1.8 2.2 1.8 2.4 4.7 7.3 7.5 Gross Domestic Savings 5.7 6.7 5.5 -0.8 0.0 1.2 1.0 -0.3 -0.5 -1.2 1.1 Private 1.6 5.2 5.7 -0.3 0.0 2.0 0.7 -1.6 1.2 -1.9 0.3 Public 4.1 1.6 -0.2 -0.5 0.0 -0.8 0.3 1.3 -1.7 0.7 0.8 Gross National Savings 5.2 6.4 6.9 0.1 1.0 2.1 1.0 0.4 1.2 4.6 7.1 Private 2.8 6.1 8.4 0.9 1.5 3.5 1.3 0.1 6.1 5.7 7.7 Public 2.4 0.3 -1.5 -0.9 -0.5 -1.4 -0.3 0.3 -4.9 -1.1 -0.6 :s Source: Statistics Department, MFEP, and staff estimates. ::.  GDP BY EXPENDITURE IN CONSTANT 1991 PRICES TABLE II.11 Annual Percentage Growth Rates 1984/85 L985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 l993/94 Consumption -1.9 2.0 2.9 6.4 6.2 5.9 3.3 4.6 4.9 3.1 Private -1.8 2.2 2.8 6.8 6.6 5.1 4.0 2.5 7.0 2.8 Public -2.8 0.5 3.7 3.0 2.7 13.1 -2.9 24.0 -11.0 5.0 Gross Domestic Investment -2.8 1.8 39.6 20.9 -8.5 3.3 8.1 -6.9 4.0 7.8 Fixed Capital Formation -2.5 2.5 37.1 22.5 -5.2 1.4 4.0 -3.7 0.6 9.9 Private 4.5 46.0 24.3 4.7 25.3 -10.8 -2.8 -14.2 -14.9 2.5 Public -8.7 -42.1 70.0 56.1 -43.8 35.9 16.6 12.5 19.0 16.1 Gross Domestic Expenditure -2.0 2.0 6.8 8.4 4.0 5.5 3.9 3.0 4.8 3.6 Resource Balance 0.0 4.4 33.4 12.6 -4.1 -6.4 4.8 -10.3 17.4 -16.0 Exports GNFS -2.7 0.9 -3.5 2.7 6.8 5.7 -8.1 17.1 -7.7 46.2 Imports GNFS -1.0 3.2 20.7 9.9 -1.3 -3.0 0.9 -2.7 9.1 1.5 GDP-Market Prices -3.0 -0.3 3.8 8.6 6.3 6.1 4.7 3.2 8.5 5.4 Terms of Trade Adjustment 2.4 -12.2 -70.0 3.4 25.9 -66.0 -76.9 -270.2 0.6 243.3 Import Capacity 0.4 -7.2 -42.5 2.9 12.7 -18.9 -18.0 5.4 -8.2 32.1 NetFactorServiceIncome 5.9 -23.9 -32.9 33.1 45.6 29.1 -21.1 55.4 -40.5 19.0 Net Current Tansfers 44.5 131.3 -37.7 31.4 19.5 -24.3 7.7 75.5 87.7 20.7 GNP -3.2 0.3 4.5 8.3 5.7 5.6 5.4 2.2 10.0 5.2 Gross Domestic Income -2.4 -1.7 -4.0 8.4 6.9 3.4 3.7 2.4 8.6 4.4 Gross National Income -2.6 -1.2 -3.5 8.1 6.3 2.9 4.4 1.4 10.0 4.2 Current Account Balance -2.8 -15.4 47.3 11.3 -4.1 1.5 0.4 -16.6 -19.6 -39.9 Source: Statistics Department, MFEP, and staff estimates.  GDP BY EXPENDlTURE IN CONSTANT 1991 PRICES TABLE 11.12 As a Percentage of GDP at Market Prices 4 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 l992/93 I993194 Consumption 101.3 102.5 104.9 104.0 101.9 101.9 101.7 100.3 101.6 98.2 96.1 Private 90.6 91.7 94.0 93.1 91.6 91.9 91.1 90.4 89.8 88.5 86.4 Public 10.8 10.8 10.9 10.9 10.3 10.0 10.6 9.9 11.8 9.7 9.7 Gross Domestic Investment 12.2 12.3 12.5 16.8 18.7 16.1 15.7 16.2 14.6 14.0 14.4 Fixed Capital Formation 12.1 12.2 12.5 16.5 18.6 16.6 15.9 15.8 14.7 13.7 14.2 Private 5.7 6.2 9.0 10.8 10.4 12.3 10.3 9.6 8.0 6.3 6.1 Public 6.4 6.0 3.5 5.7 8.2 4.3 5.6 6.2 6.8 7.4 8.2 NetChangesinStocks 0.1 0.1 0.0 0.3 0.1 -0.5 -0.2 0.4 -0.1 0.4 0.1 GrossDomesticExpenditure 113.6 114.8 117.4 120.8 120.6 118.0 117.4 116.5 116.3 112.3 110.4 Resource Balance -14.6 -15.0 -15.7 -20.2 -21.0 -18.9 -16.7 -16.7 -14.5 -15.7 -12.5 Exports GNFS 8.1 8.2 8.3 7.7 7.3 7.3 7.3 6.4 7.2 6.2 8.6 Imports GNFS 22.7 23.2 24.0 27.9 28.2 26.2 24.0 23.1 21.8 21.9 21.1 Statistical Discrepancy 1.0 0.2 -1.7 -0.6 0.3 0.9 -0.7 0.2 -1.8 3.4 2.1 GDP-Market Prices 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Terms of Trade Adjustment 12.6 13.3 11.7 3.4 3.2 3.8 1.2 0.3 -0.4 -0.4 -1.3 Import Capacity 20.7 21.5 20.0 11.1 10.5 11.1 8.5 6.7 6.8 5.7 7.2 Net Factor Service Income -2.3 -2.5 -1.9 -1.2 -1.5 -2.1 -2.5 -1.9 -2.9 -1.6 -1.8 Net Current Transfers 1.3 1.9 4.4 2.6 3.2 3.6 2.5 2.6 4.5 7.7 8.8 GNP 97.7 975 98.1 98.8 98.5 97.9 975 98.1 97.1 98.4 98.2 Gross Domestic Savings 10.3 10.6 8.5 0.0 1.0 1.0 0.2 -0.2 -0.3 -2.1 0.5 Gross National Savings 9.2 9.9 11.0 1.4 2.7 2.5 0.3 0.5 1.3 4.1 7.6 GrossDomesticIncome 112.6 113.3 111.7 103.4 103.2 103.8 101.2 100.3 99.6 99.6 98.7 Gross National Income 110.3 110.8 109.8 102.2 101.7 101.8 98.7 98.4 96.7 98.0 96.9 Source: Statistics Department, MFEP, and staff estimates.  BALANCE OF PAYMENTS TABLE 111.1 In Millions of US Dollars 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 Exports (g+nfs) 402.0 408.0 389.0 406.0 323.9 304.0 245.7 198.9 195.1 206.2 333.1 Merchandise (fob) 378.0 383.0 379.0 384.0 297.9 282.0 210.0 175.5 172.1 157.1 253.9 o/w Coffee 342.0 353.0 360.0 365.0 285.9 276.0 159.0 127.0 116.9 99.1 172.3 Non-Factor Services 24.0 25.0 10.0 22.0 26.0 22.0 35.7 23.4 23.0 49.1 79.2 Imports (g+nfs) 450.0 484.0 446.0 600.0 682.0 712.0 675.8 670.5 581.6 753.4 893.4 Merchandise (fob) 368.0 404.0 380.0 514.0 545.0 562.0 584.0 545.0 450.6 573.2 717.7 o/w Petrol 91.0 76.0 61.0 63.0 69.0 76.0 78.0 87.0 57.0 53.2 64.4 Non-Factor Services 82.0 80.0 66.0 86.0 137.0 150.0 91.8 125.5 131.0 180.2 175.7 Resource Balance -48.0 -76.0 -57.0 -194.0 -358.1 -408.0 -430.1 -471.6 -386.5 -547.3 -560.2 Net Factor Income -47.0 -53.0 -44.0 -47.0 -57.0 -66.0 -77.0 -58.2 -87.0 -48.9 -60.7 o/w Net Interest -47.0 -53.0 -44.0 -47.0 -57.0 -66.0 -77.0 -58.2 -87.0 -48.9 -42.9 Current Private Transfers 26.0 40.0 101.0 100.2 120.0 114.0 78.0 80.5 135.9 241.0 303.5 CIA Balance (excl Grants) -69.0 -89.0 0.0 -140.8 -295.1 -360.0 -429.1 -449.3 -3376 -355.2 -317.4 CIA Balance (incl Grants) 2.0 -25.0 31.0 -100.7 -202.7 -229.0 -276.4 -187.4 -131.5 -96.3 -67.0 Official Transfers 71.0 64.0 31.0 40.1 92.4 131.0 152.7 261.9 206.1 258.9 250.4 o/w Import Support 0.0 0.0 0.0 0.0 33.5 49.3 28.8 86.7 75.1 111.4 75.5 o/w Project Aid 71.0 64.0 31.0 40.1 58.9 81.7 123.9 175.2 131.0 147.5 175.0 Net M&LT Loans -5.0 43.0 12.0 45.0 101.0 125.0 215.3 121.9 38.0 127.4 178.8 Disbursements 81.0 120.0 88.0 135.0 186.0 211.0 292.3 214.1 163.4 231.5 294.2 Project Loans 81.0 115.0 88.0 135.0 141.0 143.0 125.3 115.4 94.2 147.5 176.0 lmport Support Loans 0.0 5.0 0.0 0.0 45.0 68.0 167.0 98.7 69.2 83.9 118.2 Repayments 86.0 77.0 76.0 90.0 85.0 86.0 77.0 92.2 125.4 104.1 115.4 Foreign Investment/Kenya Comp. 0.0 30.0 29.0 28.0 10.0 13.0 5.5 1.0 2.0 4.0 4.6 Short-Term, net 64.0 -15.0 1.0 -31.0 37.0 -17.4 11.5 -36.8 -31.0 -22.2 -54.7 Errors and omissions 12.0 12.0 -49.0 -20.0 -10.0 6.5 0.0 0.0 1.4 -21.1 47.8 Overall Balance 73.0 45.0 24.0 -78.7 -64.7 -101.9 -44.1 -101.3 -121.1 -8.2 109.5 Continued I-,  BALANCE OF PAYMENTS TABLE III. In Millions of US Dollars 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 Financing. -73.0 -45.0 -24.0 78.7 64.7 101.9 44.1 101.3 121.1 8.2 -109.5 Monetary Authorities -52.0 -39.0 -39.0 22.0 -14.0 18.0 10.0 37.0 -1.8 -28.7 -89.7 Gross Reserve Changes -81.0 32.0 -1.0 33.0 -4.0 11.5 11.0 -14.9 -23.8 -38.4 -107.4 IMF, net 39.0 -70.0 -35.0 -3.0 -17.0 6.5 -1.0 51.9 22.0 9.7 17.7 SAF/ESAF and Purchases 69.0 0.0 0.0 57.0 34.0 94.0 42.0 89.0 55.0 28.0 27.5 Other, net -10.0 -1.0 -3.0 -8.0 7.0 0.0 0.0 0.0 0.0 0.0 0.0 Short Term/Commercial 0.0 0.0 -4.5 10.0 -9.5 6.0 12.0 -2.0 -3.7 -3.5 0.0 Change in External Arrears -63.0 -59.0 19.4 -45.0 47.4 18.0 -19.0 65.0 98.2 -329.7 -58.8 Exceptional Financing 42.0 53.0 0.1 91.7 40.8 59.9 41.1 1.3 28.4 370.1 39.1 Rescheduling/Cancellation 42.0 53.0 0.1 91.7 40.8 60.9 41.1 1.3 28.4 370.1 39.1 Towards arrears reduction 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.3 28.4 331.5 22.7 Towards current maturities 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 38.6 16.5 Residual Finance Gap 0.0 0.0 0.0 0.0 0.0 -1.0 0.0 0.0 0.0 0.0 0.0 Memo Item: Gross Reserves (EOP) 117 85 86 53 57 46 35 50 73 112 219 In months of imports GNFS 3.1 2.1 2.3 1.1 1.0 0.8 0.6 0.9 1.5 1.8 2.9 Source: BOU and IMF. Note: Before 1992/93 imports were derived from ftnancing items; as of 1992/93 customs data were used in calculating imports.  AnnexIII StatisticalAnnex 117 INCONSISTENCIES IN EXPORT DATA TABLE 111.2 FROM ALTERNATIVE SOURCES In Millions of US Dollars Traditional Exports Coffee Tea Tobacco BOU MFEP BOU MIFEP BOU MFEP 1989 103.0 262.8 1.2 3.2 0.6 0.6 1990 139.6 140.4 2.9 3.6 2.9 2.8 1991 100.7 117.6 5.3 6.8 4.5 4.5 1992 93.0 95.1 5.7 7.7 4.2 4.4 Non-Traditional Exports Cereals Fish & Fish Products Cocoa BOU MFEP BOU MEP BOU MFEP 1989 0.2 0.0 0.7 0.1 0.0 0.7 1990 3.3 3.3 1.2 1.2 0.5 0.6 1991 3.9 4.4 5.0 5.5 0.4 0.5 1992 3.9 4.7 5.8 5.5 0.3 0.2 Sources: BOU = Bank of Uganda, Quarterly Economic Report, 1988-93. MFEP = Ministry of Finance and Economic Planning, Background to the Budget, 1994-95.  118 AnnexIII StatisticalAnnex EXTERNAL DEBT OUTSTANDING TABLE IV.1 In Millions of US Dollars 1991 1992 1993 1994 1994 June June June June Dec Multilateral Institutions 1,644 1,755 1,843 2.150 2,284 African Development Bank 91 59 50 28 28 African Development Fund 18 139 142 197 197 BADEA 18 18 18 15 14 European Investment Bank 16 19 17 21 25 IBRD 28 24 22 18 16 IDA 957 1,043 1,152 1,418 1,533 Islamic Development Bank 19 21 22 16 14 IFAD 30 33 38 44 46 IMF 282 330 344 361 383 Other 185 69 39 32 28 Bilateral Paris Club 285 273 282 332 343 Pre-cutoff date .. 161 171 176 181 Post-cutoff date 113 110 156 162 Bilateral Non-Paris Club 526 378 381 398 424 China 48 61 59 65 66 India 62 61 54 51 54 Libya 84 87 90 98 111 Tanzania 131 71 68 68 68 Korea, DPR of 38 34 34 34 35 Other 163 65 77 82 91 Commercial Banks 40 15 14 1 1 Commercial Non-Banks 96 225 61 38 39 Other 0 0 101 73 78 Total DOD including Arrears 2,592 2,647 2,682 2,993 3,170 Source: IMF staff estimates based on data provided by the Ugandan authorities. Note: Arrears include principal and interest in arrears. The above data may not necessarily correspond to the statistics reported by the World Bank's Debtor Reporting System. Owing to differences in the classification of certain creditors, this table may not correspond to other debt tables in this report.  AnnexIII StatisticalAnnex 119 ARREARS TABLE IV.2 In Millions of US Dollars 1991 1992 1993 1994 1994 June June June June Dec Multilateral Institutions 52.0 59.1 19.3 0.0 0.0 World Bank IMF .. African Development Bank .. Islamic Development Bank 0.4 8.9 European Investment Bank 2.2 1.5 1.2 East African Development B 45.3 48.1 15.3 Other 4.1 0.6 2.8 Bilateral Paris Club 65.2 107.9 5.6 0.0 0.0 France 31.8 47.4 Italy 12.3 17.7 United Kingdom 5.0 9.8 Germany .. 1.7 United States 2.1 0.6 Spain 1.0 1.5 Japan 0.5 5.1 5.6 Israel .. 24.0 Other 12.5 0.0 Bilateral Non-Paris Club 122.1 197.6 132.6 143.4 152.4 Abu Dhabi 1.4 2.3 3.1 3.8 4.0 China 11.9 28.7 3.3 3.3 4.4 India 50.0 52.2 Kuwait 0.9 0.4 Iraq 3.4 3.5 3.5 2.9 2.9 Cuba 0.3 1.3 0.2 Former USSR 33.4 .. Yugoslavia 9.0 13.8 22.6 29.0 31.1 Libya 3.2 8.7 14.5 25.3 30.8 Saudi Arabia 1.3 .. Pakistan 1.4 2.0 2.7 3.4 3.5 Burundi 5.4 4.9 3.6 3.4 3.4 Korea, DPR of 0.4 4.4 7.5 Tanzania 0.1 71.2 67.6 67.5 67.5 Nigeria .. .. 0.3 0.9 0.9 Egypt .. 4.2 3.8 3.8 3.8 Other .. .. 0.1 .. 0.1 Suppliers Credits and Banks 138.4 244.6 122.3 77.5 82.7 IFC 4.1 6.9 6.9 10.0 10.1 CDC 10.1 16.6 15.8 21.1 25.4 EADB .. .. 33.6 .. Other 124.2 221.1 66.0 46.4 47.3 Total - Principal and Interest 377.7 609.2 279.8 220.9 235.1 Source: IMF staff estimates based on data provided by the Ugandan authorities.  CENTRAL GOVERNMENT OPERATIONS TABLE V.1 In U Sh Millions 183/84 1984/85 1985/86 1986/87 1987188 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 Total Revenue 930 1,622 2,846 5,811 22,548 47,854 94,525 136,808 185,995 281,428 363,881 Tax Revenue 869 1,595 2,791 4,835 19,697 40,423 86,555 128,211 173,654 259,024 338,818 o/w Coffee 412 942 1,891 1,996 6,299 5,370 14,931 12,730 2,005 Non-Tax Revenue 61 27 55 976 2,851 7,431 7,970 8,597 12,340 22,404 25,063 Total Expenditures 1,153 2,397 4,723 11,042 44,300 91,596 174,928 269,168 581,495 718,342 816,772 Current Expenditure 695 1,568 3,517 6,900 24,700 60,870 98,296 130,583 323,017 323,452 390,567 Wages & Salaries 126 440 535 1,200 3,700 9,778 12,973 24,132 47,846 62,691 84,427 Interest Payments 166 258 564 500 2,300 5,800 8,557 18,656 90,093 69,386 63,678 External 5,200 7,601 17,464 81,249 56,555 54,932 Domestic .. 600 956 1,192 8,844 12,831 8,746 Other 404 870 2,418 5,200 18,700 45,292 76,766 87,795 185,078 191,375 242,462 Net LedxlinglInvestment 330 480 0 0 0 1,926 0 4,500 8,500 1,200 2,800 Capital Expenditure 128 349 1,206 4,142 19,600 28,800 76,632 134,085 249,978 393,690 423,405 External 97 262 496 2,307 11,800 18,037 42,804 82,015 213.272 357,926 383,600 Domestic Counterpart 31 87 710 1,835 2,500 4,105 5,816 9,855 13,981 35,764 39,805 Local Capital 5,300 6,658 28,012 42,215 22,725 OveraU Deficit (Commitment) -223 -775 -1,878 -5,231 -21,752 43,742 -80,403 -132,360 -395,500 436,914 452,891 Change in Arrears, net -84 63 0 -30 -1,248 -3,222 -9,441 -12,385 2,491 -72,868 -65,265 External -5,226 -38,170 -40,552 Domestic 7,717 -34,698 -24,713 Adjustment to Cash 19,038 100 Overall Deficit (Cash) -307 -712 -1,878 -5,261 -23,000 46,964 -89,844 -144,745 -393,009 -490,744 -518,056 Financing: 307 712 1,878 5,261 23,000 46,964 89,844 144,746 393,010 490,744 518,055 Budgetary Grants 45 78 504 562 6,500 14,160 20,296 70,185 194,644 313,754 287,542 External, net 30 96 432 400 8,700 19,404 91,815 65,152 142,339 200,816 257,475 Borrowing 179 492 1,136 1,700 11,200 22,204 75,641 96,623 131,605 252,077 339,763 Repayment 149 396 704 1,300 4,900 13,600 28,355 58,361 123,839 125,538 114,653 :b Debt Relief less Mon Int 0 0 0 0 2,400 10,800 44,529 26,890 134,573 74,277 32,365 Z Domestic 232 538 942 4,299 7,800 13,400 -22,267 9,409 56,027 -23,826 -26,962 Bank -29 555 573 4,699 7,800 12,300 -19,325 3,700 51,391 -17,291 -36,700 Non-Bank 261 -17 369 400 0 1,100 -2,942 5,709 4,636 -6,535 9,738 4 Sources: MFEP, Statistics Department and IMF.  CENTRAL GOVERNMENT OPERATIONS TABLE V.2 As a Percentage of GDP at MP 4 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 Total Revenue 9.5 8.1 6.4 4.6 5.7 5.3 6.8 7.4 6.7 7.1 8.2 Tax Revenue 8.8 8.0 6.3 3.8 5.0 4.5 6.2 6.9 6.2 6.6 7.6 - o/w Coffee 4.2 4.7 4.3 1.6 1.6 0.6 1.1 0.7 0.1 .. Non-Tax Revenue 0.6 0.1 0.1 0.8 0.7 0.8 0.6 0.5 0.4 0.6 0.6 Total Expenditures 11.7 12.0 10.7 8.8 11.3 10.2 12.6 14.6 20.9 18.2 18.4 Current Expenditure 7.1 7.9 7.9 5.5 6.3 6.8 7.1 7.1 11.6 8.2 8.8 Wages & Salaries 1.3 2.2 1.2 1.0 0.9 1.1 0.9 1.3 1.7 1.6 1.9 Interest Payments 1.7 1.3 1.3 0.4 0.6 0.6 0.6 1.0 3.2 1.8 1.4 External .. .. .. .. .. 0.6 0.5 0.9 2.9 1.4 1.2 Domestic .. .. .. .. .. 0.1 0.1 0.1 0.3 0.3 0.2 Other 4.1 4.4 5.5 4.1 4.8 5.0 5.5 4.8 6.7 4.8 5.5 Net Lending/Investment 3.4 2.4 0.0 0.0 0.0 0.2 0.0 0.2 0.3 0.0 0.1 Capital Expenditure 1.3 1.7 2.7 3.3 5.0 3.2 5.5 7.3 9.0 10.0 9.5 External 1.0 1.3 1.1 1.8 3.0 2.0 3.1 4.4 7.7 9.1 8.6 Domestic Counterpart 0.3 0.4 1.6 1.5 0.6 0.5 0.4 0.5 0.5 0.9 0.9 Local Capital .. .. .. .. 1.3 0.7 2.0 2.3 0.8 Overall Deficit (Commitment) -2.3 -3.9 -4.2 -4.1 -5.5 -4.9 -5.8 -7.2 -14.2 -11.1 -10.2 Change in Arrears, net -0.9 0.3 0.0 0.0 -0.3 -0.4 -0.7 -0.7 0.1 -1.8 -1.5 External .. .. .. .. .. .. .. .. -0.2 -1.0 -0.9 Domestic .. .. .. .. .. .. .. .. 0.3 -0.9 -0.6 Adjustment to Cash .. .. .. .. .. .. .. .. .. 0.5 0.0 Overall Deficit (Cash) -3.1 -3.6 -4.2 -4.2 -5.8 -5.2 -6.5 -7.8 -14.1 -12.4 -11.6 Financing: 3.1 3.6 4.2 4.2 5.8 5.2 6.5 7.8 14.1 12.4 11.6 Budgetary Grants 0.5 0.4 1.1 0.4 1.7 1.6 1.5 3.8 7.0 7.9 6.5 External, net 0.3 0.5 1.0 0.3 2.2 2.2 6.6 3.5 5.1 5.1 5.8 Borrowing 1.8 2.5 2.6 1.3 2.8 2.5 5.5 5.2 4.7 6.4 7.6 Repayment 1.5 2.0 1.6 1.0 1.2 1.5 2.0 3.2 4.5 3.2 2.6 Debt Relief less Mort Int 0.0 0.0 0.0 0.0 0.6 1.2 3.2 1.5 4.8 1.9 0.7 Domestic 2.4 2.7 2.1 3.4 2.0 1.5 -1.6 0.5 2.0 -0.6 -0.6 Bank -0.3 2.8 1.3 3.7 2.0 1.4 -1.4 0.2 1.8 -0.4 -0.8 Non-Bank 2.7 -0.1 0.8 -0.3 0.0 0.1 -0.2 0.3 0.2 -0.2 0.2 Sources: MFEP, Statistics Department and IMF.  MONETARY SURVEY TABLE Vl.1 In U Sh Billions 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 Foreign Assets, net -0.8 -1.3 -2.4 -13.6 -18.7 -63.9 -89.1 -151.6 -271.0 -207.2 -76.1 Bank of Uganda -0.9 -1.4 -2.7 -14.0 -19.7 -66.0 -93.4 -165.8 -313.1 -277.4 -148.5 Commercial Banks 0.1 0.1 0.3 0.4 1.0 2.1 4.3 14.3 42.1 70.2 72.4 Domestic Credit 0.9 2.0 3.4 8.2 24.2 68.5 79.7 120.7 190.4 208.7 200.5 Claims on Government, net 0.4 1.0 1.5 4.1 11.9 26.4 9.2 12.9 57.2 40.0 -12.5 o/w Bank of Uganda .. .. .. 4.0 12.2 11.5 10.9 14.3 Claims onPrivate Sector 0.4 1.0 1.9 4.1 12.3 42.1 70.5 107.8 133.2 168.7 213.0 Crop Financing 0.2 0.5 1.1 1.5 4.5 19.5 24.4 40.5 38.4 48.0 53.6 Other 0.2 0.5 0.8 2.6 7.8 22.6 46.1 67.3 94.8 120.7 159.4 Total Assets 0.0 0.6 1.0 -5.4 5.5 4.6 -9.4 -30.8 -80.6 1.5 124.4 Total Liabilities 0.1 0.6 1.0 -5.4 5.5 4.6 -9.4 -30.8 -80.5 1.5 124.3 Money incl FX Deposits, M3 .. .. .. .. .. .. .. .. 237.0 338.0 448.7 Broad Money, M2 0.8 1.8 4.5 8.6 26.8 60.2 94.4 138.6 212.7 301.9 402.5 Money Supply, Ml 0.6 1.6 3.9 7.6 24.2 54.3 81.4 116.1 166.5 221.9 292.5 Currency in Circulation .. .. .. 4.0 14.4 29.2 38.6 56.2 92.7 108.9 147.8 Demand Deposits .. .. .. 3.6 9.8 25.1 42.8 59.9 73.8 113.0 144.7 Quasi-Money 0.1 0.3 0.6 1.0 2.6 5.9 13.0 22.5 46.2 80.0 110.0 Odier Deposits .. .. .. .. .. .. .. .. 24.3 36.1 46.2 Other Items, net -0.7 -1.2 -3.5 -14.0 -21.3 -55.6 -103.9 -169.4 -317.4 -336.5 -324.4 o/w Currency Revaluation -0.6 -1.4 -3.4 -14.1 -14.1 -43.2 .. .. .. -369.7 -331.9 Memorandum Items: M3/GDP .. .. 8.5 8.6 10.1 M2/GDP 7.7 9.1 10.2 6.8 6.8 6.7 6.8 7.5 7.6 7.6 9.0 Velocity (M2) 12.9 11.0 9.8 14.7 14.7 15.0 14.7 13.3 13.1 13.1 11.1 Change in M2 .. 139.5 147.8 90.7 211.9 124.3 57.0 46.7 53.5 42.0 33.3 Change inMl .. 153.2 149.7 93.9 218.6 124.0 50.0 42.6 43.4 33.3 31.8 Source: Bank of Uganda, IMF and Staff Estimates.  CHANGE IN MONETARY SURVEY TABLE Vl.2 In Billions of U Sh 1984/85 1985186 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 0 Foreign Assets, net -0.51 -1.12 -11.17 -5.10 -45.20 -25.20 -62.45 -119.45 63.80 131.10 ! Bank of Uganda -0.51 -1.29 -11.32 -5.74 -46.30 -27.33 -72.46 -147.27 35.70 128.90 2 Commercial Banks 0.00 0.17 0.15 0.64 1.10 2.13 10.01 27.82 28.10 2.20 :s Domestic Credit 1.10 1.49 4.76 16.02 44.25 11.18 41.07 69.67 18.30 -8.20 Claims on Government, net 0.55 0.57 2.56 7.83 14.48 -17.20 3.71 44.29 -17.20 -52.50 o/w Bank of Uganda .. .. .. 8.21 -0.75 -0.60 3.43 Claims on Private Sector 0.55 0.92 2.20 8.19 29.78 28.39 37.36 25.38 35.50 44.30 Crop Financing 0.31 0.61 0.37 3.03 14.94 4.92 16.14 -2.13 9.60 5.60 Other 0.24 0.31 1.83 5.16 14.84 23.47 21.23 27.51 25.90 38.70 Total Assets 0.59 0.37 -6.41 10.92 -0.95 -14.02 -21.38 -49. 78 82.10 122.90 Total Liabilities 0.59 0.37 -6.41 10.92 -0.96 -14.00 -21.38 -49.63 81.95 122.80 Money incl FX Deposits, M3 .. .. .. .. .. .. .. .. 101.05 110.70 Broad Money, M2 1.06 2.69 4.09 18.23 33.34 34.27 44.13 74.09 89.25 100.60 Money Supply, MI 0.95 2.35 3.68 16.62 30.04 27.15 34.67 50.43 55.40 70.60 Currency in Circulation .. .. .. 10.41 14.76 9.44 17.62 36.48 16.20 38.90 Demand Deposits .. .. .. 6.21 15.28 17.71 17.05 13.95 39.20 31.70 Quasi-Money 0.11 0.34 0.41 1.61 3.30 7.12 9.45 23.67 33.85 30.00 Other Deposits .. .. .. .. .. .. .. .. 11.80 10.10 Other Items, net -0.47 -2.32 -10.50 -7.31 -34.30 -48.27 -65.50 -148.02 -19.10 12.10 o/w Currency Revaluation -0.72 -2.01 -10.73 0.04 -29.15 .. .. .. .. 37.80 Source: Bank of Uganda, IMF and Staff Estimates. I-  MONETARY SURVEY TABLE VI.3 As a percent of GDP at MP 1983184 1964/85 W15/86 1966/87 1987/88 M98/89 1989/90 1990/91 1991/92 1992/93 1993/94 Foreign Assets. net -8.14 -6.57 -5.48 -10.78 4.75 -7.10 -6.42 -8.20 -9.74 -5.25 -1.71 Bank of Uganda -8.95 -6.97 -6.05 -11.10 -5.02 -7.34 -6.73 -8.97 -11.25 -7.03 -3.34 Commercial Banks 0.81 0.40 0.56 0.32 0.26 0.24 0.31 0.77 1.51 1.78 1.63 Domestic Credit 8.65 9.78 7.76 6.50 6.15 7.61 5.74 6.53 6.84 5.29 4.51 Claims on Government, net 4.27 4.86 3.47 3.25 3.03 2.93 0.66 0.70 2.06 1.01 -0.28 o/w Bank of Uganda .. .. .. 3.17 3.10 1.27 0.78 0.77 Claims on Private Sector 4.37 4.91 4.29 3.25 3.12 4.68 5.08 5.83 4.79 4.27 4.79 Crop Financing 2.14 2.61 2.55 1.19 1.15 2.16 1.76 2.19 1.38 1.22 1.20 Other 2.24 2.31 1.74 2.06 1.97 2.51 3.32 3.64 3.41 3.06 3.58 Total Assets 0.51 3.21 2.28 -4.28 1.40 0.51 -0.68 -1.67 -2.90 0.04 2.80 Total Liabilities 0.51 3.21 2.28 -4.28 1.40 0.51 -0.68 -1.67 -2.89 0.04 2.79 Money incl FX Deposits, M3 .. .. .. .. .. .. .. .. 8.52 8.56 10.09 Broad Money, M2 7.73 9.13 10.17 6.82 6.82 6.69 6.81 7.50 7.64 7.65 9.05 Money Supply, Ml 6.31 7.87 8.84 6.03 6.15 6.03 5.87 6.28 5.98 5.62 6.57 Currency in Circulation .. .. .. 3.17 3.66 3.24 2.78 3.04 3.33 2.76 3.32 Demand Deposits .. .. .. 2.85 2.49 2.79 3.08 3.24 2.65 2.86 3.25 Quasi-Money 1.42 1.25 1.33 0.79 0.66 0.66 0.94 1.22 1.66 2.03 2.47 Other Deposits .. .. .. .. .. .. .. .. 0.87 0.91 1.04 Odter Items, net -7.22 -5.92 -7.89 -11.10 -5.42 -6.18 -7.49 -9.17 -11.41 -8.52 -7.29 o/w Currency Revaluation -6.51 -6.82 -7.60 -11.18 -3.57 -4.80 .. .. 9.37 -7.46 Source: Bank of Uganda, IMF and Staff Estimates.  AnnexIII StatisticalAnnex 125 FOREIGN EXCHANGE MARKETS TABLE VI.4 Average Bureau Average Official Premium Calendar Fiscal Cash (Interbank) Bureau/ Year Year Mid-Rate Mid-Rate Official U Sh/US$ U Sh/US$ Percent 1984 6 4 52.1 1984/85 10 5 91.9 1985 17 7 145.1 1985/86 30 11 165.6 1986 61 14 329.0 1986/87 110 22 406.7 1987 164 45 266.3 1987/88 285 60 375.7 1988 414 106 289.8 1988/89 471 170 177.5 1989 569 222 156.2 1989/90 662 320 106.9 1990 698 433 61.3 1990/91 780 558 39.8 1991 935 750 24.7 1991/92 1130 983 15.0 1992 1237 1145 8.0 1992/93 1241 1202 3.2 1993 1217 1195 1.9 1993/94 1130 1103 2.5 1994 1004 979 2.5 Source: Bank of Uganda. Notes: Forex bureaus were legalized in July 1990. The auction was introduced in January 1992, and abolished on November 1, 1993. Beginning November 1993, the interbank mid-rate replaced the official mid-rate.  COMMERCIAL BANK LOANS AND ADVANCES TO TIlE PRIVATE SECTOR BY TYPE TABLE VI.5 1990 1991 1992 1993 March June Sept Dec March June Sept Dec March June Sept Dec March June Sept Dec In U Sh Billions Agriculture 12.79 15.83 15.21 20.44 25.01 25.92 29.49 31.86 30.06 25.31 33.17 32.87 37.40 36.36 34.50 43.13 o/w Crop finance 7.92 8.99 9.02 12.12 17.42 16.14 21.80 23.81 24.02 22.76 27.43 27.01 32.53 35.82 27.54 36.22 Trade & Commerce 16.47 17.62 19.75 22.97 26.24 30.23 30.43 34.83 39.00 44.78 54.64 59.39 63.25 78.75 74.52 79.20 Manufacturing 4.77 5.12 6.55 7.11 8.29 8.99 7.95 12.30 15.44 17.79 17.76 18.69 23.38 19.57 30.52 31.81 Transportation 4.17 4.55 4.32 4.93 5.27 6.14 7.93 5.68 7.10 6.68 6.99 7.48 5.52 7.80 7.92 9.47 Building & Construction 3.33 4.36 4.24 4.28 5.45 5.65 6.76 7.75 10.17 10.13 11.08 10.94 11.55 11.55 12.21 11.50 Others 0.04 0.08 0.05 0.01 0.08 0.10 0.17 0.27 0.09 0.10 0.16 0.18 0.20 0.65 0.17 0.29 Total 41.57 47.56 50.12 59.74 70.34 77.03 82.73 92.69 101.86 104.79 123.80 129.55 141.30 154.68 159.84 175.40 Percentage Distribution Agriculture 30.8 33.3 30.3 34.2 35.6 33.6 35.6 34.4 29.5 24.2 26.8 25.4 26.5 23.5 21.6 24.6 o/w Crop finance 19.1 18.9 18.0 20.3 24.8 21.0 26.4 25.7 23.6 21.7 22.2 20.8 23.0 23.2 17.2 20.6 Trade & Commerce 39.6 37.0 39.4 38.4 37.3 39.2 36.8 37.6 38.3 42.7 44.1 45.8 44.8 50.9 46.6 45.2 Manufacturing 11.5 10.8 13.1 11.9 11.8 11.7 9.6 13.3 15.2 17.0 14.3 14.4 16.5 12.7 19.1 18.1 Transportation 10.0 9.6 8.6 8.3 7.5 8.0 9.6 6.1 7.0 6.4 5.6 5.8 3.9 5.0 5.0 5.4 Building & Construction 8.0 9.2 8.5 7.2 7.7 7.3 8.2 8.4 10.0 9.7 8.9 8.4 8.2 7.5 7.6 6.6 Others 0.1 0.2 0.1 0.0 0.1 0.1 0.2 0.3 0.1 0.1 0.1 0.1 0.1 0.4 0.1 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Source: Bank of Uganida ini Background to the Budget, 1994-95.  IMNEST RATES TABLE Vl.6 1990 1991 1992 1993 1994 Mar. June Sept. Dec. Mar. June Sept. Dec. Mar. June Sept. Dec. Mar. June Sept. Dec. Mar. Apr.. Bank of Ugtmda Waysandmeans 15.0 15.0 14.0 14.0 14.0 14.0 14.0 14.0 14.0 14.0 14.0 14.0 14.0 14.0 14.0 17.1 22.0 20.8 Rediscount rate 48.0 48.0 43.0 43.0 38.0 38.0 40.0 40.0 41.0 43.0 43.0 40.0 25.0 25.0 23.0 23.0 23.0 23.0 Bank rate to commercial bankes 55.0 55.0 50.0 50.0 44.0 44.0 46.0 46.0 47.0 49.0 49.0 41.0 26.0 26.0 24.0 24.0 24.0 24.0 Treasury bills 35 days 1/ 38.0 38.0 34.0 34.0 29.0 29.0 35.0 35.0 36.0 40.0 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 63 days 1/ 40.0 40.0 36.0 36.0 30.0 30.0 36.0 36.0 37.0 40.0 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 91 days 43.0 43.0 39.0 39.0 31.0 31.0 37.0 37.0 38.0 39.4 43.4 30.1 22.9 23.8 22.8 17.1 22.0 20.0 180 Days 29.8 31.1 26.6 21.2 24.0 23.0 273 Days 29.4 29.4 30.8 22.0 25.0 25.0 Govemnment stocks I year 5 years 45.0 45.0 40.0 40.0 40.0 40.0 40.0 40.0 40.0 42.0 42.0 n.a. n.a. n.a. n.a. n.a. n.a. n.a. 10 years 47.0 47.0 42.0 42.0 42.0 42.0 42.0 42.0 42.0 44.0 44.0 n.a. n.a. n.a. n.a. n.a. n.a. n.a. 15 years 50.0 50.0 45.0 45.0 45.0 45.0 45.0 45.0 45.0 47.0 47.0 n.a. n.a. n.a. n.a. n.a. n.a. n.a. Commercial banks Deposit rates Demafnd deposits 20.0 20.0 18.0 18.0 12.0 12.0 13.0 13.0 8.0 8.0 8.0 opt. opt. opt. opt. opt. opt. opt. Savings deposits 33.0 33.0 30.0 30.0 28.0 28.0 32.0 32.0 33.0 35.0 34.4 21.1 13.9 14.8 13.5 8.1 13.0 11.0 Time deposits 3-6 months 33.0 33.0 30.0 30.0 29.0 29.0 34.0 34.0 34.0 36.0 37.4 24.1 16.9 17.8 16.5 11.1 16.0 14.0 7-12 months 35.0 35.0 32.0 32.0 30.0 30.0 35.0 35.0 36.0 38.0 38.4 25.1 17.9 18.8 17.5 12.1 17.0 15.0 Minimum I year 37.0 37.0 33.0 33.0 31.0 31.0 36.0 36.0 37.0 39.0 neg. neg. neg. neg. neg. neg. neg. neg. Lending rates Agriculture 25-40 25-40 36.0 36.0 32.0 32.0 37.0 37.0 38.0 40.0 40.0 33.1 25.9 26.8 25.5 20.1 20.0 23.0 Export & manufacturing 2/ 42.0 44.0 neg. neg. neg. neg. neg. neg. 20.0 23.0 Commerce 50.0 50.0 45.0 45.0 39.0 39.0 41.0 41.0 42.0 44.0 neg. neg. neg. neg. neg. neg. 25.0 23.0 Unsecured 42.0 44.0 neg. neg. neg. neg. neg. neg. neg. neg. Source: Bank of Uganda. 1/ After Nov 10, 1992, the rates are a reference rate based on the previous 4 weighted treasury bill auction average. 21 Short-term commercial nature depending on maturities. n.a. Not Applicable, these bills have not been offered for sale. neg. Interest rate is negotiable. - opt. Interest rate is optional. a  128 AnnexIIf StatisticalAnnex PRODUCTION OF PRINCIPAL MANUFACTURED COMMODITIES TABLE VII.1 Soft Electri- Laundry Sugar Beer Drinks Cigarettes Textiles Cement city Soap Unit Tons '000 Lir '000 Ltr Million '000 Sq M Tons '000 Kwh Tons Anual 1982 3,289 9,787 1,795 745.0 18,557 18,471 559,800 n.a. 1983 3,133 14,206 3,953 645.0 16,607 30,780 515,500 n.a. 1984 2,943 14,817 5,784 965.8 11,475 24,921 614,400 n.a. 1985 808 8,184 5,002 1,416.4 10,418 11,749 626,500 n.a. 1986 0 6,603 5,049 1,420.1 9,733 16,376 637,200 2,902 1987 0 16,484 5,875 1,434.8 10,465 15,904 618,087 15,508 1988 7,535 21,139 13,431 1,637.7 11,067 14,960 565,909 17,929 1989 15,859 19.516 16,178 1,585.9 11,589 17,378 659,971 26,872 1990 28,915 19,420 24,275 1,289.7 8.172 26,920 736,500 30,816 1991 42,456 19,529 25,982 1,688.2 8,901 27,138 782,518 33,283 1992 53,539 18,718 21,769 1,574.9 9.650 37,881 986,278 38,660 1993 49,264 23,881 26,899 1,412.5 7,481 51,985 974,677 47,588 Monthly 1989 Jan 1,603 2,428 876 110.8 375 477 41,512 2,469 Feb 1,264 1,592 1,215 132.4 988 325 45,549 2,264 Mar 775 2,382 1,385 149.3 1,066 2,109 56,429 2,382 Apr 1,204 1,746 1,159 141.9 1,203 1,358 53,952 2,003 May 430 997 1,510 136.8 1,222 71 52,595 1,897 Jun 1,273 2,442 1,546 173.1 963 1,008 55,655 2,671 Jul 1,482 1,179 1,586 142.5 1,032 1,185 57,864 2,047 Aug 1,906 1,472 1,368 132.7 1,115 1,490 57,261 1,704 Sep 1,641 1,342 1,822 125.1 1,039 1,793 56,916 1,928 Oct 1,655 1,237 1,294 120.5 1,079 2,071 58,521 2,606 Nov 707 1,288 1,167 140.6 1,085 2,785 60,840 2,285 Dec 1,919 1,411 1,250 80.2 422 2,706 62,877 2,616 1990 Jan 2,701 1,667 1,617 102.7 572 3,412 62,089 2,601 Feb 3,093 1,275 1,409 125.9 997 1,210 52,675 2,283 Mar 2,095 1,531 1,655 105.1 1,186 3,705 54,587 3,033 Apr 2,275 1,576 1,943 57.0 777 503 65,978 2,484 May 2,911 1,804 2,336 101.5 901 2,405 64,174 3,200 Jun 2,949 1,811 2,217 103.1 655 5,104 63,794 1,966 Jul 3,797 1,857 2,014 96.2 677 1,054 62,666 2,420 Aug 2,595 1,897 2,008 125.3 824 783 62,641 2,343 Sep 1,453 1,147 2,066 133.1 597 2,661 66,154 3,508 Oct 1,388 1,843 2,441 109.1 503 2,142 67,119 2,050 Nov 1,484 1,497 2,161 120.9 343 3,011 57,442 2,439 Dec 2,174 1,515 2,408 109.8 140 930 57,181 2,489 1991 Jan 3,146 1,464 2,229 139.0 8 2,659 56,266 2,280 Feb 3,604 1,222 1,976 136.1 170 2,944 50,592 2,916 Mar 3,387 1,572 2,523 112.6 743 4,315 55,672 3,024 Apr 2,059 1,501 1,869 127.7 774 899 51,683 3,137 May 2,418 1,529 1,909 139.4 875 2,022 53,314 2,325 Jun 2,850 1,206 1,877 154.1 860 2,620 66,264 2,163 Continued  AnnexIll StatisticalAnnex 129 PRODUCTION OF PRINCIPAL MANUFACTURED COMMODlTIES TABLE VII.1 Soft Electri- Laundry Sugar Beer Drinks Cigarettes Textiles Cement city Soap Unit Tons '000 Ltr '000 lUr Million '000 Sq M Tons '000 Kwh Tons 1991 Jul 2,674 1,581 1,767 143.6 1,164 686 73,172 1,587 Aug 5,142 1,638 2.159 146.1 1,111 2,679 74,677 2,561 Sep 4,273 1,678 2,188 137.1 1,036 401 66,180 3,392 Oct 4,679 1,822 2,353 135.7 1,153 739 77,662 3,123 Nov 4,190 2,038 2,080 160.6 824 5,346 76,139 3,202 Dec 4,034 2,278 3,052 156.2 183 1,828 80,897 3,573 1992 Jan 4,295 1,846 2,136 121.2 324 3,142 82,575 3,814 Feb 2,716 1,380 1,682 142.6 855 3,125 75,923 3,165 Mar 4,745 1,890 2,322 138.2 1,123 2,453 82,761 3,680 Apr 4,371 1,752 2.063 129.0 991 3,391 85,448 2,645 May 5,105 1,569 1,561 155.7 1091 4,482 77,100 3,634 Jun 4,599 1,592 1,529 140.3 800 46 72,486 2,447 Jul 4,498 968 1,482 141.8 1,007 4,038 87,485 2,304 Aug 5,022 1,153 1,458 126.3 1,079 2,251 87,111 3,008 Sep 4,595 1,253 1,540 140.0 1,084 1,260 77,957 3,156 Oct 4,961 1,283 1,620 127.0 913 3,365 87,688 3,342 Nov 4,535 1,435 1,986 117.7 305 4,267 86,826 3,645 Dec 4,097 2,597 2,390 95.1 78 6,061 82,918 3,820 1993 Jan 4,953 2,487 2,024 138.8 96 3,697 82,477 4,847 Feb 4,284 2,149 2,044 145.0 287 5,899 77,344 4,255 Mar 4,574 2,198 2,414 131.0 1,051 4,726 81,730 3,880 Apr 3,272 2,565 2,611 132.5 909 4,613 77,369 4,035 May 0 2,106 1,764 141.3 965 3,130 82,102 3,969 Jun 76 2,208 2,077 122.3 901 4,622 75,995 4,001 Jul 2,473 1,775 2,063 86.5 980 5,731 83,922 3,870 Aug 3,905 1,576 2,067 80.3 978 786 81,238 3,620 Sep 4,518 1,684 2,035 88.4 874 6,072 79,837 3,532 Oct 7,885 1,594 2,139 117.2 436 3,315 83,241 4,399 Nov 7,125 1,273 2,135 117.4 4 5,416 82,118 3.506 Dec 6,199 2,266 3,526 111.8 0 3,978 87,304 3,674 1994 Jan 6,339 2,290 2,873 104.5 0 6,203 86,702 4,759 Feb 6,740 1,737 2,052 100.2 0 4,208 79,990 4,315 Mar 5,889 1,830 2,565 116.8 521 4,048 91,322 3,422 Apr 5,778 2,325 2,504 130.3 582 4,384 84,465 3,509 May 4,291 1,851 2,188 121.7 536 2,837 84,111 3,831 Jun 3,581 1,995 2,380 133.9 586 3,011 81,030 4,114 Jul 4,881 2,258 3,428 119.6 533 6,014 88,077 4,124 Aug 6,209 2,691 4,009 101.6 501 3,849 85,326 3,909 Sep 6.465 3,159 4,482 120.0 457 4,319 81,760 4,403 Source: Statistics Department, MFEP.  130 Annex III StatisticalAnnex INDEX OF INDUSTRIAL PRODUCTION TABLE VII.2 Annual Summary, 1987 = 100 No. of Estabs Weight 1987 1988 1989 1990 1991 1992 1993 1994 Food processing 54 20.70 100.0 128.0 153.7 174.9 227.4 245.6 245.8 314.9 Meat, fish and dairy 12 1.70 100.0 149.4 109.4 127.2 166.8 201.0 245.9 264.3 Grain milling 13 4.30 100.0 139.5 139.1 134.7 114.9 104.7 106.9 186.9 Bakeries 9 1.40 i00.0 131.7 153.4 206.6 284.1 325.2 322.8 306.7 Sugar and jaggery 4 1.80 100.0 277.5 514.7 789.3 1220.5 1501.3 1325.6 1814.6 Coffee roasting 3 0.20 100.0 73.1 48.2 74.2 74.3 107.5 46.0 30.1 Coffee processing - 8.62 100.0 95.6 106.0 81.0 92.8 70.2 90.2 111.8 Tea processing * 1 1.39 100.0 98.6 130.9 184.1 238.1 247.0 312.1 315.8 Other food processing 4 0.30 100.0 115.4 104.9 100.9 91.1 69.5 73.6 69.2 Animal feeds 8 0.99 100.0 101.9 121.0 116.7 161.2 142.2 130.6 142.3 Tobacco and beverages 13 26.10 100.0 139.6 143.7 155.2 176.1 155.2 170.9 179.6 Beer and spirits 5 6.61 100.0 127.1 124.2 125.0 129.3 124.5 155.6 162.5 Soft drinks 7 5.40 100.0 221.3 253.8 362.4 385.5 311.4 378.4 411.8 Cigarettes 1 14.09 100.0 114.1 110.5 89.9 117.7 109.8 98.4 98.6 Textiles and clothing 13 16.30 100.0 121.8 132.7 116.3 110.9 111.9 92.7 72.9 Textiles 4 12.00 100.0 106.4 110.4 79.8 88.2 88.7 67.1 38.2 Textile products 4 3.09 100.0 84.3 107.7 116.5 48.7 52.9 77.1 113.3 Garments 5 1.21 100.0 370.9 419.1 477.8 556.0 494.7 387.6 314.2 Leather andfootwear 8 2.30 100.0 62.0 62.9 75.3 60.1 79.5 68.4 61.8 rimber, paper and printing 24 9.00 100.0 135.1 169.4 183.6 198.2 220.5 251.1 293.2 Sawmilling and timber 4 3.20 100.0 96.0 61.5 58.0 58.1 80.3 102.2 105.8 Furniture & foam products 7 2.90 100.0 140.0 221.9 190.9 162.3 175.9 149.3 136.4 Paper and printing 13 2.90 100.0 173.7 236.1 315.2 389.0 420.0 517.4 657.2 Chemicals, paint and soap 24 12.30 100.0 111.2 162.9 183.5 192.9 252.0 339.5 343.1 Chemicals 2 0.31 100.0 88.1 88.1 79.9 110.9 137.7 189.7 223.8 Paint 5 0.51 100.0 98.3 167.5 62.0 168.2 438.6 614.2 678.9 Medicine 6 0.50 100.0 70.1 166.8 284.3 103.6 338.2 461.0 481.8 Soap 11 10.98 100.0 114.3 164.6 187.4 200.4 242.7 325.5 324.6 Bricks and cement 14 4.30 100.0 94.5 109.0 154.2 162.6 203.1 261.1 264.8 Bricks, tiles, etc. 12 2.23 100.0 98.8 105.2 149.0 167.8 195.3 236.2 258.4 Cement 2 2.07 100.0 89.7 113.2 159.8 157.1 211.6 288.0 271.7 Steel and steel products 19 5.30 100.0 87.2 98.9 107.7 149.3 190.7 259.0 389.1 Iron and steel 6 1.51 100.0 125.1 74.1 57.5 130.8 254.3 526.0 919.2 Structural steel 4 2.28 100.0 66.4 134.6 131.0 166.9 141.6 105.6 90.8 Steel products 9 1.51 100.0 80.9 69.9 122.6 141.2 201.3 224.5 311.3 Miscellaneous 23 3.70 100.0 134.0 204.2 181.3 251.2 272.3 381.0 466.0 Vehicle accessories 5 0.91 100.0 104.5 164.0 224.8 299.9 329.3 423.9 470.9 Plastic products 7 0.63 100.0 58.2 105.0 107.2 187.1 258.5 434.4 659.2 Electrical products 3 1.15 100.0 100.9 142.9 110.5 82.1 120.0 353.6 426.3 Miscellaneous products 8 1.01 100.0 245.4 372.0 269.0 440.1 402.9 340.3 386.6 Index - all items * 192 100.00 100.0 123.7 145.2 155.5 178.2 191.2 215.6 243.2 Annual percentage change 16.1 23.7 17.4 7.1 14.6 7.3 12.8 12.8  AnnexIII StatisticalAnnex 131 INDEX OF INDUSTRIAL PRODUCTION TABLE V11.3 Monthly Summary, 1987 = 100 Drinks Text. Leather Timber Chem. Bricks Food and and and Paper Paint and Steel All Proc. * Tobac. Cloth. Footwear ect. Soap Cement Prod. Misc. Items No. of Estabs 54.0 13.0 13.0 8.0 24.0 24.0 14.0 19.0 23.0 192.0 Weight 20.7 26.1 16.3 2.3 9.0 12.3 4.3 5.3 3.7 100.0 Annual 1982 106.7 48.6 196.7 77.9 68.2 64.6 163.7 81.6 87.6 97.3 1983 103.7 59.8 177.6 152.8 79.6 68.8 177.4 118.5 124.3 103.7 1984 99.8 79.4 136.9 175.5 88.7 61.2 156.5 110.7 139.5 101.0 1985 93.9 84.8 98.9 86.9 76.8 58.6 122.7 133.1 139.1 91.3 1986 85.3 82.2 92.9 90.0 72.0 58.8 120.6 105.9 141.0 86.1 1987 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1988 128.0 139.6 121.8 62.0 135.1 111.2 94.5 87.2 134.0 123.7 1989 153.7 143.7 132.7 62.9 169.4 162.9 109.0 98.9 204.2 145.2 1990 174.9 155.2 116.3 75.3 183.6 183.5 154.2 107.7 181.3 155.5 1991 227.4 176.1 110.9 60.1 198.2 192.9 162.6 149.3 251.3 178.2 1992 245.6 155.2 111.9 79.5 220.5 252.0 203.1 190.7 272.3 191.2 1993 245.8 170.9 9W.7 68.4 251.1 339.5 261.1 259.0 381.0 215.6 1994 ** 314.9 179.6 72.9 61.8 293.2 343.1 264.8 389.1 466.0 243.2 Monthly 1992 Jan 260.2 165.2 69.5 94.3 177.4 264.4 180.0 193.1 282.1 187.4 Feb 197.1 154.1 121.0 78.1 211.0 234.4 191.3 152.3 295.1 177.6 Mar 255.4 185.0 145.2 48.0 191.3 278.3 170.7 154.2 324.0 204.9 Apr 232.9 165.5 132.7 110.5 178.0 230.4 190.3 188.4 301.2 189.2 May 256.4 157.2 138.8 74.1 239.9 292.6 226.3 171.5 349.7 207.8 Jun 231.6 148.9 109.1 81.8 255.8 206.9 108.0 203.0 290.3 181.1 Jul 245.4 138.2 134.1 112.4 248.9 189.3 265.4 208.0 241.6 188.4 Aug 258.6 131.1 118.9 72.4 228.2 239.6 191.0 200.1 194.8 184.8 Sep 237.8 142.6 147.4 45.1 206.9 252.5 173.7 241.4 216.6 189.5 Oct 262.2 144.8 112.4 67.9 258.1 257.7 205.6 171.1 256.5 194.3 Nov 256.7 153.0 64.9 131.1 232.6 277.5 234.3 213.7 263.1 192.9 Dec 252.5 177.0 48.8 37.9 217.8 300.5 300.6 191.3 252.1 196.2 1993 Jan 302.1 179.7 41.1 47.9 180.7 378.5 191.3 202.8 231.1 207.6 Feb 284.8 178.4 53.8 70.7 221.6 351.4 286.8 193.6 242.3 210.6 Mar 276.2 188.9 119.6 100.8 261.8 323.7 257.1 298.7 281.8 229.0 Apr 233.5 200.8 123.1 126.3 237.9 327.0 256.8 264.9 329.3 222.6 May 128.4 166.7 127.4 66.0 239.9 334.5 210.6 258.4 360.9 191.2 Jun 110.2 172.0 118.2 39.6 235.1 342.8 286.3 255.3 460.0 194.1 Jul 178.5 143.0 138.0 62.9 295.9 332.9 355.3 275.7 436.9 211.8 Aug 231.9 141.0 122.7 52.3 274.3 295.4 171.5 287.4 447.9 206.2 Sep 223.5 143.5 110.1 80.3 250.0 320.3 344.5 271.1 530.4 214.2 Oct 316.7 157.9 86.3 77.3 261.0 389.2 234.8 285.5 473.2 236.7 Nov 328.8 157.5 40.5 47.3 336.4 325.8 303.6 314.6 452.9 233.7 Dec 335.2 221.4 31.6 49.1 218.1 352.4 234.7 200.2 325.2 229.2 1994 Jan 366.7 193.5 34.8 61.5 277.8 407.2 313.4 338.6 432.4 256.0 Feb 364.2 151.7 42.0 25.6 265.5 368.1 241.3 319.2 405.7 233.9 Mar 325.0 180.5 90.5 47.6 313.4 304.4 258.3 389.9 433.8 243.7 Apr 346.0 194.9 88.3 62.0 295.9 277.7 265.6 377.3 407.9 245.6 May 265.6 168.4 92.5 68.0 297.4 329.5 247.2 436.5 590.7 238.5 Jun 222.0 188.6 89.4 106.1 309.2 371.5 263.1 473.3 525.4 241.6 Source: Statistics Department. MFEP. * Includes production data as provided by the coffee and tea marketing boards. Average for six months, January to June 1994.  132 Annex III StatisticalAnnex PRODUCTION AND EXPORTS OF PRINCIPAL AGRICULTURAL PRODUCTS TABLE VII.4 COFFEE TEA COTFON TOBACCO Deliveries Exports Prod Exports Exports Prod Exports Tons Tons USS'00 Tons Tons US$ '000 Tons US$ '000 Tons Tons USS '000 Annal 1982 161,866 174,700 349,400 2.580 1,200 800 1,800 3,200 647 0 0 1983 148,224 144,300 346,300 3,054 1,300 1,200 7,000 11,200 1,650 700 900 1984 145,971 133,200 359,600 5,214 2,500 3,300 6,700 12,100 1,969 700 1,500 1985 143,995 151,500 348,500 5,758 1,200 1,000 9,553 13,979 1,613 300 400 1986 159,881 140,800 394,200 3,335 2,800 3,100 4,875 5,086 949 0 0 1987 167,067 148,153 307,535 3,511 2,100 1.900 3,443 4,097 1,214 0 0 1988 151,157 144,254 265,279 3,512 3,079 3,079 2,088 2,968 2,639 39 58 1989 169,042 176,453 262,811 4,658 3,195 3,195 2,321 4,020 3,456 490 569 1990 128,747 141,489 140,384 6,704 4,760 3,566 3,808 5,795 3,322 2,269 2,821 1991 147,368 124,819 117,641 8,877 7,018 6,780 7,819 11,731 5,140 2,467 4,540 1992 110,295 119,006 95,372 9.504 7,816 7,721 7,536 8,218 6,686 2,322 4,333 1993 141,085 114,168 106,775 12,102 10,175 11,141 7,961 5,505 5,183 4,109 7,011 Monthly 1992 Jan 14,807 14,606 14,393 637 761 740 360 470 90 359 764 Feb 12,500 11,118 10,240 488 675 543 472 518 193 270 537 Mar 8,596 14,783 11,871 318 380 370 720 770 122 87 180 Apr 4,520 9,579 8,046 586 462 448 1,122 1,147 118 127 206 May 4,271 9,241 7,196 1,139 659 657 1,006 1,071 0 0 0 Jun 4,225 6,142 4,581 666 583 634 694 772 0 0 0 Jul 12,164 6,463 4,872 875 758 700 1,167 1,356 6 113 232 Aug 12,374 5,740 3,979 758 845 735 285 304 856 59 74 Sep 9,206 14,121 9,659 702 657 738 574 583 1,652 247 287 Oct 8,038 11,216 7,917 1,274 741 748 553 645 1,585 326 591 Nov 9,188 9,697 7,511 1,034 815 868 236 212 1,153 416 788 Dec 10,406 6,300 5,107 1,027 480 540 347 370 911 318 674 1993 Jan 22,106 7,961 7,225 966 873 875 128 137 449 480 948 Feb 22,741 8,746 8,111 987 787 909 632 702 226 401 705 Mar 15,158 14,707 13,252 928 846 843 219 204 200 394 631 Apr 9,472 14,831 12,835 1,115 714 722 1,453 722 166 413 773 May 6,493 12,071 10,666 1,174 897 909 406 456 0 189 300 Jun 3,836 9,415 8,147 1,072 860 850 1,165 559 0 957 1,483 Jul 7,215 6,328 5,269 992 1,020 1,149 1,418 714 343 315 496 Aug 7,237 11,329 9,914 853 916 1,080 2,143 1,514 1,483 20 26 Sep 6,577 12,716 12,922 815 707 821 172 269 362 0 0 Oct 5,631 4,203 4,819 910 756 916 66 87 638 154 292 Nov 10,906 5,098 5,639 1,201 950 1,150 44 59 532 294 511 Dec 23,713 6,763 7,976 1,089 849 917 115 82 784 492 846 1994 Jan 23,190 12,587 14,910 1,072 881 1,260 n.a. n.a. 39 285 569 Feb 18,054 18,667 20,466 804 730 898 n.a. n.a. 215 536 1,079 Mar 16,316 21,713 24,693 773 657 828 n.a. n.a. 544 483 1,109 Apr 13,985 22,012 26,077 1,314 917 1,219 n.a. n.a. n.a. 12 24 May 10,231 19,199 24,083 1,268 964 1,349 n.a. n.a. n.a. 144 274 Jun 11,147 14,052 20,720 1,148 1,053 1,685 n.a. n.a. n.a. 48 91 Jul 17,881 20,691 43,717 1,117 1,050 1,732 n.a. n.a. n.a. 96 182 Aug 20,875 12,357 25,133 n.a. n.a. n.a. n.a. n.a. n.a. 86 164 Sep 20,672 18,207 38,177 n.a. n.a. n.a. n.a. n.a. n.a. 696 1,167 Source: Statistics Department, MFEP.  AnnexIIf StatisticalAnnex 133 NEW CONSUMER PRICE INDEX: KAMPALA TABLE VIII. Based on 1989-90 Household Budget Survey All Households, September 1989 = 100 Iten Food Beverages Clothing Rent, HH & Transport Other Weighted Annual % Monthly % & & Fuel & Personal & Goods & Average Change Change Tobacco Footwear Utilities Goods Comm. Services CPI Weights 48.6 10.2 6.1 12.5 10.4 4.6 7.6 100.0 1994 January 231.0 292.5 234.1 364.5 239.7 287.5 443.6 273.8 10.7 3.1 February 232.5 292.1 230.5 353.6 239.9 287.0 444.4 273.0 10.8 -0.3 March 239.4 292.2 229.8 349.3 239.6 285.5 438.4 275.2 12.7 0.8 April 249.0 288.5 229.1 362.3 238.9 292.9 441.7 281.6 14.3 2.3 May 256.1 284.6 230.9 357.0 239.6 313.6 451.7 285.9 15.8 1.5 June 252.7 289.4 230.6 364.6 236.6 315.1 453.0 285.5 15.1 -0.1 July 243.5 269.0 226.5 365.2 232.0 313.1 451.3 278.1 8.9 -2.6 August 230.0 267.3 216.2 367.1 230.1 314.1 451.3 270.8 7.3 -2.6 September 226.3 263.6 217.7 372.9 230.0 314.7 461.3 270.2 3.3 -0.2 October 234.0 277.3 214.6 371.2 231.3 314.1 468.2 275.6 5.4 2.0 November 242.0 277.7 217.2 387.9 231.3 313.0 467.6 281.7 6.9 2.2 December 247.5 280.8 210.3 384.0 232.9 320.4 468.1 284.3 7.0 0.9 1995 January 245.3 284.0 211.5 405.6 233.1 320.4 472.9 286.7 4.7 0.8 February 252.2 282.6 235.5 422.5 232.7 312.7 531.9 297.6 9.0 3.8 March 257.4 284.1 218.6 419.2 234.7 320.3 528.5 299.1 8.7 0.5 ANNUAL AVERAGE - CALENDAR YEAR: 1989 90.7 91.2 99.4 88.6 94.1 97.6 93.1 91.8 1990 108.1 124.7 135.7 149.7 120.9 139.3 146.0 122.3 33.2 1991 132.9 158.9 172.9 211.9 151.3 177.9 196.2 156.6 28.1 1992 214.5 245.3 226.4 289.6 222.8 266.5 316.7 238.8 52.4 1993 206.5 279.7 239.8 333.3 236.1 285.3 400.6 253.3 6.1 1994 240.3 281.3 224.0 366.6 235.2 305.9 453.4 278.0 9.7 ANNUAL AVERAGE - FISCAL YEAR: 989/90 104.4 113.2 115.4 119.2 109.5 117.3 119.2 110.1 990/91 119.4 140.4 153.0 175.1 132.0 157.3 166.2 137.1 24.6 991/92 170.2 191.8 200.5 252.2 190.8 217.9 249.1 194.8 42.1 992/93 214.9 262.2 240.6 315.2 228.6 286.9 366.5 250.1 28.4 993/94 226.1 298.6 231.4 351.7 240.4 291.7 430.9 269.6 7.8 % RATE OF CHANGE Change in EOP EOP END POINT - CALENDAR YEAR: Average CPI Dec-Dec Jan-Dec 1989 .. .. .. .. .. .. .. .. 56.7 52.3 1990 19.3 36.8 36.5 69.0 28.4 42.7 56.9 33.2 22.4 12.7 1991 22.9 27.4 27.4 41.6 25.2 27.7 34.4 28.1 32.2 24.3 1992 61.4 54.4 31.0 36.7 47.3 49.8 61.4 52.4 41.6 33.4 1993 -3.7 14.0 5.9 15.1 6.0 7.0 26.5 6.1 6.1 7.4 1994 16.4 0.6 -6.6 10.0 -0.4 7.2 13.2 9.7 7.0 3.8 Change in EOP EOP END POINT - FISCAL YEAR: Average CPI Jun-Jun Jul-Jun 989/90 .. .. .. .. .. .. .. .. 26.9 21.5 990/91 14.3 24.0 32.6 46.9 20.5 34.1 39.5 24.6 32.0 32.0 991/92 42.6 36.7 31.0 44.1 44.6 38.5 49.9 42.1 62.9 58.8 992/93 26.3 36.7 20.0 25.0 19.8 31.7 47.1 28.4 -0.5 -2.9 993/94 5.2 13.9 -3.8 11.6 5.2 1.7 17.6 7.8 15.1 11.8 Source: Statistics Department, MFEP.  134 AnnexIII StatisticalAnnex NEW CONSUMER PRICE INDEX: COMPOSITE TABLE VIII.2 Based on 1989-90 Household Budget Survey All Households, September 1989 = 100 Item Food Beverages Clothing Rent, HH & Transport Other Weighted Annual % Monthly % & & Fuel & Personal & Goods & Average Change Change Tobacco Footwear Utilities Goods Comm. Services CPI Weights 50.1 10.0 6.6 10.8 10.7 4.3 7.6 100.0 1994 January 237.8 296.5 230.9 360.4 238.7 290.4 414.3 272.2 7.7 1.7 February 240.4 297.8 228.9 358.0 238.4 290.3 415.6 273.3 10.1 0.4 March 245.3 298.7 229.1 353.5 237.9 287.6 412.8 275.0 12.2 0.6 April 259.5 297.7 228.6 371.6 237.9 291.9 414.7 284.3 14.8 3.4 May 267.3 296.4 230.0 366.0 239.1 312.4 431.6 289.8 16.3 2.0 June 263.6 298.3 229.2 372.9 236.9 315.2 431.9 288.8 16.1 -0.4 July 251.3 283.2 224.6 378.7 232.7 313.3 431.1 280.8 10.2 -2.7 August 240.0 276.7 216.5 383.5 231.2 313.1 431.5 274.4 9.1 -2.3 September 234.3 278.9 217.9 383.1 229.9 313.9 443.4 272.6 5.4 -0.7 October 240.5 287.7 215.9 383.4 231.2 312.9 448.6 277.0 6.0 1.6 November 249.9 287.6 217.7 391.7 230.5 313.6 448.4 282.6 7.2 2.0 December 257.2 289.2 212.2 392.5 232.0 317.5 448.4 286.5 7.0 1.4 1995 January 252.1 292.9 214.2 403.1 232.2 320.0 451.9 286.0 5.1 -0.2 February 256.8 290.6 227.2 412.6 231.8 316.8 488.6 292.6 7.0 2.3 March 260.0 292.6 217.7 410.7 233.8 319.2 486.6 293.7 6.8 0.4 ANNUAL A VERAGE - CALENDAR YEAR: 1990 109.3 126.8 135.9 150.6 120.6 143.2 141.0 122.3 1991 135.2 158.2 174.2 211.7 150.4 183.2 190.9 156.2 27.7 1992 223.6 248.4 226.2 294.7 221.1 272.5 300.1 241.6 54.7 1993 214.8 285.3 238.2 338.9 233.5 288.4 375.2 254.1 5.2 1994 248.9 290.7 223.5 374.6 234.7 306.0 431.0 279.8 10.1 ANNUAL AVERAGE - FISCAL YEAR: 1990/91 121.1 140.4 153.6 175.0 131.3 162.4 161.1 136.9 1991/92 174.1 191.7 201.2 253.3 189.3 224.0 239.5 194.9 42.4 1992/93 225.8 270.1 239.5 321.7 226.6 290.8 344.4 253.4 30.0 1993/94 234.2 303.3 230.1 356.8 238.8 293.9 404.7 270.1 6.6 % RATE OF CHANGE Change in EOP EOP END POIVT - CALENDAR YEAR: Average CPI Dec-Dec Jan-Dec 1991 23.7 24.8 28.2 40.5 24.7 28.0 35.4 27.7 32.9 25.3 1992 65.5 57.0 29.9 39.2 47.0 48.7 57.2 54.7 45.2 36.3 1993 -4.0 14.8 5.3 15.0 5.6 5.8 25.0 5.2 4.2 5.9 1994 15.9 1.9 -6.2 10.5 0.5 6.1 14.9 10.1 7.0 5.2 END POINT - FISCAL YEAR: Change in EOP EOP Average CPI Jun-Jun Jul-Jun 1990/91 .. .. .. .. .. .. .. .. 32.2 32.6 1991/92 43.7 36.5 31.0 44.8 44.2 38.0 48.7 42.4 66.5 63.7 1992/93 29.7 40.9 19.0 27.0 19.7 29.8 43.8 30.0 -2.3 -3.9 1993/94 3.7 12.3 -3.9 10.9 5.4 1.0 17.5 6.6 16.1 13.3 Source: Statistics Department, MFEP.  AnnexlII StatisticalAnnex 135 MAJOR SOURCES OF INCOME BY REGION TABLE IX.1 Quartile Lower Upper Bottom Middle Middle Top CENTRAL RURAL 100.0 100.0 100.0 100.0 Earned income 74.0 86.9 86.0 91.7 Agriculture 58.6 69.6 61.5 52.8 Business 7.0 8.9 15.9 25.1 Employment 7.0 6.8 7.8 12.0 Government employment 1.4 2.4 2.9 6.1 Private employment 5.6 4.4 4.9 5.9 Residual earned income 1.5 1.6 0.8 1.8 Unearned income 26.0 13.1 14.1 8.3 Rent 5.7 2.1 1.6 1.3 Remittances 16.8 10.0 11.0 6.5 Transfers 0.0 0.1 0.0 0.2 Dowry 1.7 0.3 0.5 0.2 Inheritance 1.8 0.6 1.0 0.1 EASTERN RURAL 100.0 100.0 100.0 100.0 Earned income 77.2 84.6 89.3 92.2 Agriculture 60.4 62.5 65.7 57.7 Business 11.1 11.9 14.1 23.6 Employment 3.7 7.0 7.2 9.3 Government employment 1.4 5.0 4.5 6.3 Private employment 2.3 2.1 2.6 3.0 Residual earned income 2.0 3.2 2.4 1.7 Unearned income 22.8 15.4 10.7 7.8 Rent 1.7 1.0 0.6 0.3 Remittances 17.9 11.6 8.6 6.3 Transfers 1.2 0.0 0.0 0.0 Dowry 1.2 1.9 0.8 0.7 Inheritance 0.9 0.8 0.7 0.5 Continued  136 Annex III StatisticalAnnex MAJOR SOURCES OF INCOME BY REGION TABLE IX.1 Quartile Lower Upper Bottom Middle Middle Top WESTERN RURAL 100.0 100.0 100.0 100.0 Earned income 52.9 63.2 70.6 79.3 Agriculture 47.2 52.9 60.0 63.5 Business 1.6 4.2 5.6 8.7 Employment 3.4 5.5 4.5 6.3 Government employment 1.9 1.9 2.2 3.7 Private employment 1.5 3.6 2.3 2.6 Residual earned income 0.7 0.6 0.5 0.9 Unearned income 47.2 36.8 29.4 20.7 Rent 2.9 1.9 1.7 0.7 Remittances 29.4 27.6 22.4 14.8 Transfers 1.8 0.0 0.3 0.2 Dowry 10.2 4.5 3.1 2.9 Inheritance 2.9 2.8 2.0 2.1 NORTHERN RURAL 100.0 100.0 100.0 100.0 Earned income 70.8 80.2 80.3 85.7 Agriculture 60.4 66.5 64.1 61.8 Business 7.0 5.3 8.0 8.9 Employment 2.4 6.8 6.5 12.4 Government employment 1.3 4.3 4.1 6.8 Private employment 1.2 2.6 2.4 5.7 Residual earned income 1.0 1.5 1.7 2.7 Unearned income 29.2 19.8 19.7 14.3 Rent 1.1 0.2 0.4 0.1 Remittances 21.2 14.8 12.1 11.0 Transfers 0.2 0.2 0.9 0.0 Dowry 4.4 3.6 4.6 2.4 Inheritance 2.4 1.0 1.8 0.7 Source: Calculations from the 1992/93 Integrated Household Survey. Note: The quartiles are defined with reference to the national population: the cut-off points for each quartile are the same for all regions. Thus, the poorest quartile in the northern rural region will include more than 25 % of the northern population, and the poorest quartile in urban areas will include less than 25% of the urban population.  AnnexIII StatisticalAnnex 137 AGRICULTURAL REVENUE SOURCES IN UGANDA TABLE IX.2 Quartile Lower Upper Bottom Middle Middle Top URBAN 100.0 100.0 100.0 100.0 Crops 98.4 97.7 94.6 80.6 Grains 23.6 21.1 22.1 15.2 Maize 11.7 10.3 12.0 12.4 Rice 3.9 0.5 0.9 0.3 Millet 4.2 4.0 2.8 1.1 Sorghum 3.8 6.2 6.3 1.4 Other grains 0.1 0.1 0.1 0.1 Matooke and tubers 47.2 44.1 50.3 44.5 Matooke 3.6 11.3 10.7 11.4 Sweet potatoes 14.8 16.2 20.9 15.1 Cassava 22.5 15.3 17.3 16.6 Other tubers 6.3 1.3 1.4 1.4 Pulses, beans and nuts 20.2 27.0 15.9 15.6 Beans 10.3 14.6 10.0 10.8 Peas 0.6 0.5 0.1 0.3 Groundnuts 7.5 9.5 4.5 3.4 Cow peas 0.5 0.2 0.3 0.7 Simsim 1.1 1.3 0.8 0.3 Other pulses, beans and nuts 0.1 1.0 0.3 0.2 Fruit 1.7 1.0 1.2 1.0 Sugar cane 0.9 0.1 0.3 0.1 Other fruits 0.7 0.9 0.9 0.9 Vegetables 2.4 1.2 0.7 2.1 Onions 0.0 0.0 0.2 0.1 Other vegetables 2.4 1.2 0.5 2.1 Cash crops 3.1 3.1 4.1 2.0 Coffee 2.6 2.8 2.0 1.5 Cotton 0.5 0.1 1.4 0.1 Tea 0.0 0.0 0.1 0.0 Tobacco 0.0 0.2 0.2 0.2 Other cash crops 0.0 0.0 0.4 0.2 Other crops 0.1 0.2 0.2 0.1 Animal revenue 1.6 2.3 5.4 19.5 Continued  138 Annex III StatisticalAnnex AGRICULTURAL REVENUE SOURCES IN UGANDA TABLE IX.2 Quartile Lower Upper Bottom Middle Middle Top RURAL 100.0 100.0 100.0 100.0 Crops 94.9 94.9 95.3 93.1 Grains 26.4 21.3 19.3 16.0 Maize 8.5 7.7 7.3 6.8 Rice 1.0 1.2 1.3 1.1 Millet 8.5 7.2 6.2 5.0 Sorghum 7.5 5.0 3.9 3.0 Other grains 0.9 0.2 0.6 0.1 Matooke and tubers 41.2 45.2 49.4 52.8 Matooke 8.8 12.7 18.3 22.0 Sweet potatoes 15.2 15.5 13.6 15.0 Cassava 16.0 15.5 15.7 14.1 Other tubers 1.3 1.5 1.8 1.7 Pulses, beans and nuts 17.4 18.2 17.1 16.0 Beans 8.6 9.9 10.0 9.5 Peas 0.8 0.5 0.3 0.3 Groundnuts 4.7 4.3 4.2 4.1 Cow peas 0.2 0.4 0.2 0.2 Simsim 2.3 2.4 1.7 1.5 Other pulses, beans and nuts 0.9 0.7 0.7 0.4 Fruit 2.2 2.3 2.2 2.3 Sugar cane 0.2 0.2 0.1 0.2 Other fruits 2.0 2.1 2.1 2.1 Vegetables 1.4 1.4 1.2 1.3 Onions 0.1 0.2 0.2 0.3 Other vegetables 1.3 1.1 1.1 1.0 Cash crops 6.0 6.3 5.9 4.6 Coffee 3.7 3.8 3.4 3.1 Cotton 1.7 1.2 1.7 0.9 Tea 0.0 0.1 0.1 0.2 Tobacco 0.5 1.1 0.6 0.3 Other cash crops 0.1 0.1 0.1 0.1 Other crops 5.0 5.4 4.9 3.7 Animal revenue 5.1 5.2 4.8 6.9 Source: Calculations from the 1992/93 Integrated Household Survey. Note: This table reports average household shares. Agricultural revenue includes crops grown for own consumption valued at producer prices. Revenue is reported rather than income because costs were not disaggregated.  Annex III StatisticalAnnex 139 AGRICULTURAL REVENUE SOURCES IN UGANDA BY REGION TABLE IX.3 Quartile Lower Upper Bottom Middle Middle Top CENTRAL RURAL 100.0 100.0 100.0 100.0 Crops 96.2 95.2 94.0 88.2 Grains 7.0 7.8 7.8 7.6 Maize 4.7 5.8 6.4 5.9 Rice 0.0 0.0 0.0 0.0 Millet 1.8 1.5 1.2 1.0 Sorghum 0.5 0.4 0.2 0.6 Matooke and tubers 53.4 57.0 58.3 56.0 Matooke 14.1 14.9 18.6 19.3 Sweet potatoes 15.1 18.3 15.6 16.9 Cassava 23.4 21.7 21.7 17.9 Other tubers 0.7 2.1 2.4 1.8 Pulses, beans and nuts 17.2 14.5 14.9 13.3 Beans 14.3 12.1 12.4 10.5 Peas 0.0 0.1 0.0 0.0 Groundnuts 2.6 1.8 2.1 2.6 Cow peas 0.0 0.2 0.0 0.1 Simsim 0.0 0.1 0.3 0.1 Other pulses, beans and nuts 0.3 0.2 0.1 0.1 Fruit 2.6 3.5 3.6 3.2 Sugar cane 0.1 0.2 0.1 0.0 Other fruits 2.5 3.3 3.5 3.2 Vegetables 1.1 1.9 1.6 1.9 Onions 0.1 0.6 0.4 0.6 Other vegetables 1.1 1.3 1.2 1.3 Cash crops 14.6 10.3 7.8 6.0 Coffee 14.5 10.2 7.3 5.5 Cotton 0.0 0.0 0.0 0.1 Tea 0.0 0.0 0.0 0.3 Tobacco 0.0 0.0 0.1 0.0 Other cash crops 0.1 0.1 0.5 0.2 Other crops 0.3 0.2 -0.1 0.1 Animal revenue 3.9 4.8 6.0 11.8 Continued  140 AnnexIII StatisticalAnnex AGRICULTURAL REVENUE SOURCES IN UGANDA BY REGION TABLE IX.3 Quartile Lower Upper Bottom Middle Middle Top EASTERN RURAL 100.0 100.0 100.0 100.0 Crops 97.6 96.7 95.4 95.9 Grains 32.9 32.3 31.8 30.2 Maize 11.1 11.6 11.4 13.5 Rice 2.3 3.3 4.4 3.4 Millet 14.8 12.6 11.3 8.9 Sorghum 4.7 4.8 4.7 4.1 Other grains 0.1 0.0 0.1 0.2 Matooke and tubers 44.4 44.0 42.9 44.1 Matooke 7.1 9.5 13.5 14.8 Sweet potatoes 19.4 18.5 13.1 13.2 Cassava 17.4 15.7 15.9 15.3 Other tubers 0.6 0.3 0.4 0.8 Pulses, beans and nuts 10.1 11.3 11.3 12.3 Beans 4.1 5.0 6.0 6.6 Peas 0.2 0.1 0.1 0.1 Groundnuts 3.8 4.1 3.7 4.1 Cow peas 0.2 0.8 0.2 0.3 Simsim 0.2 0.4 0.3 0.7 Otherpulses, beans and nuts 1.6 0.9 0.9 0.5 Fruit 2.4 2.1 1.7 2.1 Sugar cane 0.4 0.0 0.2 0.4 Other fruits 2.0 2.0 1.5 1.7 Vegetables 1.5 1.4 1.2 1.4 Onions 0.0 0.1 0.1 0.2 Other vegetables 1.4 1.4 1.2 1.2 Cash crops 6.0 5.4 6.5 5.8 Coffee 2.1 2.8 3.2 3.3 Cotton 3.9 2.5 3.3 2.3 Tea 0.0 0.2 0.0 0.1 Tobacco 0.0 0.1 0.0 0.1 Other crops 0.3 0.1 0.1 0.1 Animal revenue 2.4 3.3 4.6 4.1 Continued  Annexll StatisticalAnnex 141 AGRICULTURAL REVENUE SOURCES IN UGANDA BY REGION TABLE IX.3 Quartile Lower Upper Bottom Middle Middle Top WESTERN RURAL 100.0 100.0 100.0 100.0 Crops 99.1 97.1 97.0 95.5 Grains 17.3 14.2 13.0 9.7 Maize 5.4 4.9 4.3 3.1 Rice 0.4 0.3 0.1 0.4 Millet 5.4 5.9 5.0 4.1 Sorghum 5.5 3.1 3.6 2.2 Other grains 0.6 0.0 0.0 0.0 Matooke and tubers 52.5 55.6 58.9 64.5 Matooke 20.3 26.8 31.6 37.0 Sweet potatoes 15.8 14.7 14.9 15.7 Cassava 11.5 10.4 8.7 8.9 Other tubers 4.9 3.7 3.7 2.9 Pulses, beans and nuts 20.4 19.8 18.7 15.1 Beans 15.2 15.4 13.1 10.5 Peas 1.0 0.4 0.4 0.3 Groundnuts 3.6 3.4 4.9 4.0 Cow peas 0.1 0.0 0.1 0.1 Simsim 0.5 0.4 0.1 0.0 Other pulses, beans and nuts 0.1 0.3 0.1 0.2 Fruit 2.7 2.6 2.2 2.1 Sugar cane 0.2 0.1 0.0 0.3 Other fruits 2.5 2.5 2.2 1.8 Vegetables 1.6 0.8 0.8 0.7 Onions 0.2 0.2 0.1 0.1 Other vegetables 1.4 0.6 0.7 0.6 Cash crops 4.6 3.8 3.4 3.3 Coffee 3.3 2.7 2.2 2.2 Cotton 0.4 0.5 0.2 0.2 Tea 0.0 0.0 0.3 0.4 Tobacco 0.8 0.6 0.7 0.5 Other cash crops 0.1 0.0 0.0 0.0 Animal revenue 0.9 2.9 3.0 4.5 Continued  142 Annex III StatisticalAnnex AGRICULTURAL REVENUE SOURCES IN UGANDA BY REGION TABLE IX.3 Quartile Lower Upper Bottom Middle Middle Top NORTHERN RURAL 100.0 100.0 100.0 100.0 Crops 89.0 90.3 93.6 91.7 Grains 35.1 27.9 26.8 23.2 Maize 9.8 7.5 6.8 6.4 Rice 0.6 0.7 0.0 0.7 Millet 7.3 7.3 7.3 8.0 Sorghum 15.1 11.7 9.2 8.0 Other grains 2.4 0.8 3.4 0.1 Matooke and tubers 24.9 24.8 29.0 32.1 Matooke 0.7 0.7 1.2 0.9 Sweet potatoes 10.4 9.6 8.7 12.7 Cassava 13.7 14.4 19.1 18.5 Other tubers 0.1 0.0 0.0 0.0 Pulses, beans and nuts 22.9 29.0 28.3 30.3 Beans 6.2 8.7 7.7 10.2 Peas 1.6 1.4 1.1 1.4 Groundnuts 7.4 7.9 7.1 7.7 Cow peas 0.4 0.4 0.7 0.5 Simsim 6.5 9.3 9.2 9.6 Other pulses, beans and nuts 0.9 1.3 2.5 0.9 Fruit 1.6 1.0 1.0 1.0 Sugar cane 0.2 0.4 0.0 0.0 Other fruits 1.5 0.6 1.0 1.0 Vegetables 1.4 1.3 1.5 1.4 Onions 0.1 0.1 0.0 0.0 Other vegetables 1.3 1.2 1.4 1.4 Cash crops 2.6 5.8 6.6 3.2 Coffee 0.1 0.2 0.2 0.1 Cotton 1.1 1.5 3.9 2.3 Tobacco 1.2 3.9 2.5 0.6 Other cash crops 0.2 0.2 0.0 0.3 Other crops 1.9 5.2 5.7 2.2 Animal revenue 11.0 9.7 6.4 8.4 Source: Calculations from the 1992/93 Integrated Household Survey. Note: This table reports average household shares. Agricultural revenue includes crops grown for own consumption valued at producer prices. Revenue is reported rather than income because costs were not disaggregated.  AnnexIII StatisticalAnnex 143 MEAN SHARE OF FOOD ITEMS IN HOUSEHOLD BUDGETS TABLE IX.4 Real Expenditure Quartiles Lower Upper Bottom Middle Middle Top Matooke, cash 0.6 1.3 1.6 2.6 Matooke, kind 3.8 5.5 7.3 7.4 Sweet potatoes, cash 0.7 0.7 0.8 0.9 Sweet potatoes, kind 6.4 7.2 6.0 4.8 Irish potatoes, cash 0.2 0.2 0.4 0.3 Irish potatoes, kind 0.7 0.8 0.9 0.8 Cassava, cash 3.7 2.6 2.5 2.0 Cassava, kind 5.9 5.7 5.2 3.5 Other tubers, kind 0.1 0.1 0.1 0.1 Rice, cash 0.2 0.3 0.3 1.0 Rice, kind 0.1 0.2 0.2 0.2 Maize, cash 3.4 2.9 2.7 2.7 Maize, kind 2.4 2.8 2.9 1.8 Bread, cash 0.0 0.1 0.2 0.6 Millet, cash 0.7 0.6 0.5 0.4 Millet, kind 2.9 2.7 2.4 1.5 Sorghum, cash 1.0 0.7 0.6 0.3 Sorghum, kind 2.7 1.7 1.5 0.9 Simsimn, cash 0.4 0.5 0.4 0.3 Simsim, kind 0.9 0.6 0.3 0.3 Other cereals, cash 0.1 0.0 0.0 0.0 Other cereals, kind 0.1 0.0 0.0 0.0 Meat, cash 2.7 3.6 3.8 4.5 Meat, kind 1.0 1.0 1.1 0.9 Fish, cash 2.8 3.1 2.9 2.7 Milk, cash 0.7 0.9 1.3 2.2 Milk, kind 1.5 1.8 2.1 3.1 Oil, cash 0.4 0.7 0.9 1.1 Oil, kind 0.1 0.1 0.1 0.1 Fruit/vegetables, cash 1.1 1.4 1.7 2.1 Fruit/vegetables, kind 6.0 3.9 3.1 1.9 Beans, cash 3.0 2.6 2.3 2.2 Beans, kind 5.7 6.1 5.7 4.4 Coffee/tea, cash 1.7 2.4 3.0 3.5 Coffee/tea, kind 0.1 0.1 0.2 0.2 Soft drinks, cash 0.0 0.0 0.1 0.3 Alcohol, cash 2.0 2.0 2.1 2.6 Alcohol, kind 0.7 0.6 0.5 0.5 Tobacco, cash 0.7 0.7 0.7 0.9 Tobacco, kind 0.2 0.1 0.1 0.1 Source: Estimates from the 1992/93 Integrated Household Survey. Notes: The above data indicate the mean of the share across housholds rather than the share of the total.  144 AnnexIII StatisticalAnnex SHARE OF RENT AND FUEL IN HOUSEHOLD BUDGETS TABLE IX.5 Expenditure Quartiles Lower Upper AD Urban Rural Bottom Middle Middle Top IMPLIED SHARE 11.8 13.9 9.4 12.6 11.9 11.1 11.9 Rent, cash 2.6 4.7 0.4 0.8 1.3 1.9 3.5 Rent, imputed 3.6 4.0 3.2 3.8 3.5 3.0 3.8 Electricity 0.6 1.0 0.1 0.1 0.2 0.3 0.8 Paraffm 1.3 1.1 1.5 1.8 1.7 1.5 1.1 Charcoal 1.1 2.0 0.2 0.4 0.8 1.1 1.3 Firewood 2.6 1.1 4.1 5.6 4.5 3.3 1.4 Other fuel 0.0 0.0 0.0 0.0 0.0 0.0 0.0 MEAN SHARE 12.0 13.9 11.0 13.5 12.7 11.6 11.1 Rent, cash 1.8 4.5 0.4 0.7 1.3 1.7 2.9 Rent, imputed 3.3 2.7 3.6 4.3 3.6 3.0 2.7 Electricity 0.2 0.6 0.0 0.1 0.1 0.2 0.5 Paraffin 1.6 1.6 1.7 1.8 1.8 1.7 1.4 Charcoal 0.9 2.4 0.2 0.3 0.7 1.0 1.4 Firewood 4.1 2.1 5.2 6.4 5.3 4.0 2.3 Other fuel 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Source: Estimates based on the 1992/93 Integrated Household Survey.  AnnexIII StatisticalAnnex 145 HOUSEHOLD DEMOGRAPHICS TABLE IX.6 Ratio to Total Population Dependency District Men Women Ratio Apac 21.9 24.0 54.1 Arua 25.4 26.1 48.5 Bundibugyo 25.5 26.5 48.0 Bushenyi 22.1 25.4 52.5 Gulu 21.5 26.1 52.4 Hoima 21.9 24.8 53.3 Iganga 23.1 24.8 52.1 Jinja 27.5 27.7 44.8 Kabale 24.3 24.6 51.1 Kabarole 23.0 25.4 51.6 Kalangala 26.5 21.4 52.1 Kampala 27.8 29.7 42.5 Kainuli 22.4 24.1 53.5 Kapchorwa 24.1 23.3 52.6 Kasese 22.9 25.2 51.9 Kibaale 21.6 23.7 54.7 Kiboga 21.9 22.1 56.0 Kisoro 20.2 24.5 55.3 Kitgum 21.8 27.5 50.7 Kotido 19.7 26.0 54.3 Kumi 19.4 56.5 24.1 Lira 24.3 22.4 53.3 Luwero 20.5 24.2 55.3 Masaka 21.5 23.0 55.5 Masindi 25.2 24.8 50.0 Mbale 24.1 25.4 50.5 Mbarara 25.0 27.4 47.6 Moroto 20.3 27.9 51.8 Moyo 25.1 23.8 51.1 Mpigi 23.2 24.8 52.0 Mubende 21.5 23.7 54.8 Mukono 21.3 24.8 53.9 Nebbi 21.1 25.8 53.1 Pallisa 22.1 24.8 53.1 Rakai 21.6 25.7 52.7 Rukungiri 24.0 26.0 50.0 Soroti 21.2 25.1 53.7 Tororo 23.7 27.4 48.9 Source: Estimates from the 1992/93 Integrated Household Survey. Note: The above data refer to men and women from 16 to 59 years of age.  146 Annex III StatisticalAnnex DISTRIBUTION OF THE DISTRICT POPULATION TABLE IX.7 BY EXPENDITURE QUARTILES In Percent Expenditure Quartile Lower Upper Bottom Middle Middle Top Total Apac 24.8 30.0 28.9 16.4 100.0 Arua 32.5 35.0 19.4 13.1 100.0 Bundibugyo 15.0 23.5 26.0 35.5 100.0 Bushenyi 15.3 21.4 29.1 34.3 100.0 Gulu 38.4 27.6 15.4 18.7 100.0 Hoima 25.0 17.2 25.8 31.9 100.0 Iganga 29.5 25.3 21.9 23.3 100.0 Jinja 15.5 20.0 36.7 27.9 100.0 Kabale 17.0 25.7 35.4 21.9 100.0 Kabarole 15.2 27.0 25.5 32.3 100.0 Kalangala 11.7 17.0 16.8 54.5 100.0 Kampala 3.4 11.5 22.4 62.7 100.0 Kamuli 42.6 27.5 20.3 9.6 100.0 Kapchorwa 12.6 21.4 31.4 34.6 100.0 Kasese 22.8 19.5 28.2 29.5 100.0 Kibaale 21.0 29.9 30.6 18.5 100.0 Kiboga 19.1 28.3 33.2 19.4 100.0 Kisoro 38.8 22.4 22.7 16.0 100.0 Kitgum 63.5 27.3 6.3 2.8 100.0 Kotido 67.6 18.5 10.5 3.5 100.0 Kumi 26.6 38.1 24.9 10.4 100.0 Lira 25.5 26.8 28.2 19.6 100.0 Luwero 27.0 31.4 21.8 19.9 100.0 Masaka 20.5 26.7 27.5 25.3 100.0 Masindi 32.8 29.7 22.0 15.5 100.0 Mbale 22.8 22.1 31.4 23.7 100.0 Mbarara 6.8 20.4 32.1 40.7 100.0 Moroto 46.7 23.7 7.3 22.3 100.0 Moyo 41.1 27.2 20.6 11.2 100.0 Mpigi 13.7 18.7 31.9 35.7 100.0 Mubende 19.6 29.3 28.0 23.1 100.0 Mukono 21.3 24.1 24.0 30.7 100.0 Nebbi 45.2 36.1 15.5 3.3 100.0 Pallisa 31.3 29.7 25.3 13.7 100.0 Rakai 24.7 21.5 27.5 26.3 100.0 Rukungiri 26.2 18.3 24.4 31.2 100.0 Soroti 37.3 32.4 20.2 10.2 100.0 Tororo 28.6 28.8 21.9 20.7 100.0 Source: 1992/93 Integrated Household Survey.  Annex III StatisticalAnnex 147 CENSUS ESTIMATES OF CHELD MORTALITY BY DISTRICT TABLE X.1 Mortality Rates 0-11 Months 12-59 Months 0-59 Months Apac 114 86 191 Arua 137 108 230 Bundibugyo 150 122 254 Bushenyi 122 93 204 Gulu 172 143 290 Hoima 91 63 148 Iganga 125 96 209 Jinja 97 69 159 Kabale 114 86 190 Kabarole 136 107 228 Kalangala 98 70 161 Kampala 80 53 129 Kamuli 118 89 196 Kapchorwa 104 76 172 Kasese 103 75 171 Kibaale 122 94 205 Kiboga 138 109 231 Kitgum 165 136 279 Kosoro 105 76 173 Kotido 145 117 245 Kumi 122 93 204 Lira 127 99 214 Luwero 117 88 195 Masaka 107 79 178 Masindi 118 89 196 Mbale 129 100 216 Mbarara 145 117 245 Moroto 147 118 248 Moyo 143 114 241 Mpigi 94 66 154 Mubende 119 90 198 Mukono 102 74 169 Nebbi 139 110 237 Pallisa 124 95 207 Rakai 119 91 199 Rukungiri 122 97 205 Soroti 116 87 192 Tororo 138 109 231 Uganda 122 93 203 Source: 1991 Population and Housing Census, Statistics Department.  148 AnnexIII StatisticalAnnex WOMEN'S FERTILITY AND CHILD MORTALITY TABLE X.2 Women < 20 21-25 26-30 31-35 36-40 > 40 Mean Births Rural 0.41 2.33 4.00 5.56 6.50 6.83 Urban 0.33 1.86 3.04 4.60 6.14 6.31 Expenditure quartiles: Bottom 0.38 2.53 4.32 5.84 6.94 7.25 Lower middle 0.41 2.39 3.97 5.44 6.41 6.68 Upper middle 0.42 2.24 4.06 5.62 6.56 6.80 Top 0.37 1.98 3.25 4.73 5.86 6.37 Maternal education: None 0.60 2.42 4.07 5.46 6.35 6.73 Some primary 0.36 2.43 4.00 5.57 6.64 7.14 Some secondary 0.24 1.38 3.10 4.89 6.73 6.17 Some further 0.54 1.29 2.14 3.51 4.97 5.59 Ratio of Children Who Have Died Rural 0.12 0.15 0.18 0.20 0.20 0.31 Urban 0.09 0.11 0.13 0.15 0.17 0.27 Expenditure quartiles: Bottom 0.13 0.17 0.17 0.19 0.19 0.33 Lower middle 0.15 0.13 0.16 0.19 0.20 0.32 Upper middle 0.07 0.17 0.19 0.20 0.19 0.30 Top 0.11 0.13 0.16 0.19 0.20 0.30 Maternal education: None 0.10 0.17 0.20 0.21 0.22 0.34 Some primary 0.11 0.15 0.16 0.20 0.18 0.25 Some secondary 0.04 0.08 0.11 0.09 0.14 0.11 Some further 0.00 0.03 0.07 0.05 0.08 0.09 Source: Calculations from the 1992/93 Integrated Household Survey. Note: The above calculations use the proportion of children, who have since died, born to surviving mothers.  AnnexIII StatisticalAnnex 149 CHILD NUlTRITION: HEIGHT-FOR-AGE TABLE X.3 Z-Scores < -3 -3 to -2 -2 to -1 -1to+1 +1to+2 > +2 Male 23.0 20.7 24.2 24.7 4.5 2.8 Female 19.0 18.7 22.6 31.1 4.3 4.3 Urban 13.4 15.3 25.3 36.0 6.9 3.1 Rural 22.2 20.4 23.1 26.6 4.0 3.6 Expenditure quartiles: Bottom 23.0 21.2 21.5 26.0 4.8 3.5 Lower Middle 22.7 19.3 23.4 27.0 4.1 3.4 Upper Middle 20.1 20.2 24.8 28.2 3.5 3.2 Top 18.6 18.4 23.8 30.0 5.2 4.0 Age in years: Boys 0 13.4 22.1 26.7 31.4 4.0 2.3 1 29.4 24.8 20.7 18.0 4.3 2.8 2 23.9 18.9 22.0 24.8 4.8 5.5 3 23.1 18.9 24.5 26.2 4.4 2.7 4 23.3 19.6 27.6 24.0 5.0 0.5 Girls 0 11.0 12.7 27.5 39.6 4.9 4.2 1 20.5 20.4 25.9 26.6 2.5 3.9 2 19.6 19.9 19.1 31.2 4.7 5.5 3 19.0 20.7 22.9 28.9 4.3 4.1 4 23.0 17.8 20.9 29.1 5.2 3.9 Maternal education Illiterate 23.4 20.6 22.1 25.5 4.3 4.0 Literate, incomlete primary 21.0 20.2 24.7 27.5 3.6 3.1 Completed primary/some secondary 17.0 17.6 22.6 32.9 6.1 3.8 Completed further .. 7.9 12.9 79.2 Source: Calculations based on the 1992/93 Integrated Household Survey. Note: The z-scores represent the distance of the relevant indicator from the mean of an international reference (American) population, measured in standard deviations of the reference population. Formula for z-score: (x - U)/s where: x = relevant indicator A = mean of reference population s = standard deviations of reference population Poor performance on this indicator is known as 'stunting'.  150 AnnexIII StatisticalAnnex CHILD NUTRITION: WEIGHT-FOR-HEIGHT TABLE X.4 Z-Scores < -3 -3to-2 -2to-1 -lto+1 +lto+2 > +2 Male 2.0 3.9 13.5 61.3 13.2 6.0 Female 1.5 3.6 15.0 60.8 13.1 5.9 Urban 3.4 3.2 12.4 58.9 13.7 8.3 Rural 1.5 3.9 14.5 61.4 13.1 5.6 Expenditure quartiles: Bottom 1.9 5.4 17.2 60.9 10.4 4.2 Lower Middle 2.0 4.8 14.2 60.5 12.9 5.5 Upper Middle 1.6 3.0 13.3 64.2 13.6 7.2 Top 1.6 2.2 12.4 61.6 15.4 6.7 Age in years: Boys 0 3.1 3.4 8.9 48.3 20.6 15.6 1 1.7 7.1 20.9 49.8 14.7 5.6 2 2.0 2.9 10.9 70.1 11.5 2.5 3 2.3 2.3 13.1 67.5 11.7 3.1 4 1.0 4.1 13.2 65.2 10.4 6.9 Girls 0 2.4 2.7 8.3 46.6 23.0 17.1 I 1.1 8.2 17.4 52.0 13.2 8.0 2 2.5 2.1 17.3 66.4 9.4 2.2 3 1.6 2.8 13.4 68.5 10.6 3.1 4 0.5 2.7 15.8 64.0 13.3 3.5 Maternal education Illiterate 1.9 4.0 14.3 62.1 12.1 5.6 Literate, incomlete primary 1.5 3.7 14.3 60.4 13.7 6.4 Completed primary/some secondary 2.3 3.5 13.9 60.2 14.3 5.9 Completed further .. .. .. 76.1 10.9 12.9 Source: Calculations based on the 1992/93 Integrated Household Survey. Note: The z-scores represent the distance of the relevant indicator from the mean of an international reference (American) population, measured in standard deviations of the reference population. Formula for z-score: (x - /)/s where: x = relevant indicator u = mean of reference population s = standard deviations of reference population Poor performance on this indicator is known as 'wasting'.  AnnexllI StatisticalAnnex 151 CHILD NUTTION: HEIGHT-FOR-AGE BY DISTRICT TABLE X.5 Z-Scores Boys Girls < -3 -2 to -3 < -3 -2 to -3 Apac 27.2 15.5 15.8 24.5 Arua 33.2 16.4 26.5 15.9 Bundibugyo 35.6 24.6 30.0 18.3 Bushenyi 23.4 19.8 21.7 14.1 Gulu 14.1 15.2 18.5 14.0 Hoima 12.8 16.0 10.4 17.4 Iganga 27.6 19.1 18.5 22.3 Jinja 17.0 20.9 11.6 15.6 Kabale 24.0 30.0 17.3 21.1 Kabarole 22.6 32.6 18.2 19.8 Kalangala 17.5 24.5 7.6 16.0 Kampala 6.8 15.9 11.8 14.5 Kamuli 14.4 19.6 18.6 22.2 Kapchorwa 32.9 19.9 21.0 12.7 Kasese 33.4 24.5 38.0 17.6 Kibaale 18.4 17.8 12.3 13.1 Kiboga 31.2 12.7 8.5 17.6 Kisoro 13.3 6.8 20.2 22.1 Kitgum 27.9 23.3 23.0 29.0 Kotido 27.7 10.4 19.5 19.1 Kumi 29.4 37.6 22.1 30.9 Lira 18.0 21.6 13.0 17.6 Luwero 15.8 19.2 18.6 10.0 Masaka 22.4 20.8 16.6 25.5 Masindi 27.4 26.7 21.7 17.5 Mbale 21.6 21.8 24.0 22.8 Mbarara 29.4 18.5 23.9 15.7 Moroto 20.3 13.2 35.7 10.9 Moyo 26.7 9.8 33.6 12.2 Mpigi 28.2 20.5 19.2 19.9 Mubende 18.3 26.4 18.0 19.6 Mukono 23.0 23.3 7.2 16.0 Nebbi 30.0 16.8 21.5 22.7 Pallisa 20.9 18.4 33.0 21.3 Rakai 20.1 22.5 16.8 20.2 Rukungiri 31.8 15.5 15.9 18.9 Soroti 14.9 26.9 18.2 17.2 Tororo 26.5 23.3 18.3 16.7 Source: Calculations based on the 1992/93 Integrated Household Survey. Note: The z-scores represent the distance of the relevant indicator from the mean of an international reference (American) population, measured in standard deviations of the reference population. Formula for z-score: (x - f)/S where: x = relevant indicator u = mean of reference population s = standard deviations of reference population Poor performance on this indicator is known as 'stunting'.  152 AnnexIII StatisticalAnnex PRIMARY SCHOOL ENROLLMENT TABLE X.6 Gross Enrollment Populaon Enrollment Ratio Total 3,848,651 3,513,695 0.91 Male 1,970,685 1,948,699 0.99 Female 1,877,966 1,564,996 0.83 Urban 408,574 420,599 1.03 Rural 3,440,077 3,093,096 0.90 Expenditure quartiles: Bottom 1,095,919 842,207 0.77 Lower Middle 992,994 884,244 0.89 Upper Middle 962,828 931,419 0.97 Top 796,910 855,825 1.07 Source: Calculations based on the 1992/93 Integrated Household Survey. Notes: Gross enrollment figures include an unknown proportion of repeaters, hence the average attainment of children in primaxy education is nuch less than they suggest. Both the public arnl private sectors are included in these calculations.  AnnexIII StatisticalAnnex 153 PRIMARY SCHOOL ENROLLMENT BY DISTRICT TABLE X.7 Population Gross Enrollment Gross Enrollment Ratios Male Female Total Male Female Total Male Female Total Apac 53,994 57,849 111,843 54,567 33,027 87,594 1.01 0.57 0.78 Arua 94,746 86,988 181,734 126,588 68,177 194,765 1.34 0.78 1.07 Bundibugyo 10,880 12,000 22,880 8,983 8,894 17,877 0.83 0.74 0.78 Bushenyi 74,467 75,192 149,659 75,979 75,540 151,519 1.02 1.00 1.01 Gulu 57,997 74,556 132,553 71,228 61,593 132,821 1.23 0.83 1.00 Hoima 20,883 16,546 37,429 19,223 13,260 32,483 0.92 0.80 0.87 Iganga 106,600 91,411 198,011 97,341 80,622 177,963 0.91 0.88 0.90 Jinja 31,237 42,971 74,208 45,095 44,573 89,668 1.44 1.04 1.21 Kabale 57,808 38,383 96,191 55,151 30,291 85,442 0.95 0.79 0.89 Kabarole 84,030 69,554 153,584 75,703 59,969 135,672 0.90 0.86 0.88 Kalangala 1,791 1,971 3,762 2,226 2,068 4,294 1.24 1.05 1.14 Kampala 67,907 74,959 142,866 71,262 77,314 148,576 1.05 1.03 1.04 Kamuli 51,707 55,923 107,630 51,717 51,791 103,508 1.00 0.93 0.96 Kapchorwa 14,257 12,943 27,200 17,335 14,265 31,600 1.22 1.10 1.16 Kasese 43,086 34,538 77,624 38,556 24,879 63,435 0.89 0.72 0.82 Kibaale 23,861 18,104 41,965 20,043 11,685 31,728 0.84 0.65 0.76 Kiboga 22,865 12,816 35,681 19,626 13,200 32,826 0.86 1.03 0.92 Kisoro 20,534 19,571 40,105 16,849 12,282 29,131 0.82 0.63 0.73 Kitgum 32,746 32,527 65,273 41,488 22,998 64,486 1.27 0.71 0.99 Kotido 42,006 48,149 90,155 13,572 5,557 19,129 0.32 0.12 0.21 Kumi 29,388 26,953 56,341 33,032 23,478 56,510 1.12 0.87 1.00 Lira 77,535 55,834 133,369 73,435 40,099 113,534 0.95 0.72 0.85 Luwero 56,634 50,988 107,622 53,691 48,127 101,818 0.95 0.94 0.95 Masaka 103,178 96,987 200,165 98,495 94,406 192,901 0.95 0.97 0.96 Masindi 26,468 23,372 49,840 29,342 19,322 48,664 1.11 0.83 0.98 Mbale 94,833 101,011 195,844 99,421 87,777 187,198 1.05 0.87 0.96 Mbarara 86,160 85,548 171,708 85,226 80,275 165,501 0.99 0.94 0.96 Moroto 26,340 30,358 56,698 7,941 6,797 14,738 0.30 0.22 0.26 Moyo 25,168 24,267 49,435 23,839 17,155 40,994 0.95 0.71 0.83 Mpigi 125,405 118,444 243,849 135,543 115,125 250,668 1.08 0.97 1.03 Mubende 52,504 48,863 101,367 48,699 40,386 89,085 0.93 0.83 0.88 Mukono 64,045 73,897 137,942 55,435 62,238 117,673 0.87 0.84 0.85 Nebbi 43,183 35,203 78,386 26,612 19,281 45,893 0.62 0.55 0.59 Pallisa 45,074 32,285 77,359 42,520 26,078 68,598 0.94 0.81 0.89 Rakai 47,932 39,576 87,508 49,388 36,578 85,966 1.03 0.92 0.98 Rukungiri 45,012 45,939 90,951 48,075 40,872 88,947 1.07 0.89 0.98 Soroti 49,913 53,120 103,033 51,637 46,180 97,817 1.03 0.87 0.95 Tororo 58,511 58,370 116,881 63,836 48,837 112,673 1.09 0.84 0.96 Uganda 1,970,685 1,877,966 3,848,651 1,948,699 1,564,996 3,513,695 0.99 0.83 0.91 Source: Calculations based on the 1992/93 Integrated Household Survey. Note: The above figures include both public and private education. Gross enrollment figures include an unknown proportion of repeaters, hence the average attainment of children in primary education is much less than they suggest.  154 Annex I StatisticalAnnex SECONDARY SCHOOL ENROLLMENT TABLE X.8 Gross Enrollment Population Enrollment Ratio Total 2,302,584 303,099 0.13 Male 1,158,905 194,349 0.17 Female 1,143,679 108,750 0.10 Urban 293,786 87,946 0.30 Rural 2,008,798 215,153 0.11 Expenditure quartiles: Bottom 637,433 36,543 0.06 Lower Middle 548,832 56,222 0.10 Upper Middle 570,277 78,137 0.14 Top 546,042 132,197 0.24 Source: Calculations based on the 1992/93 Integrated Household Survey. Notes: Gross enrollment figures include an unknown proportion of repeaters, hence the average attainment of children in primnary education is much less than they suggest. Both the public and private sectors are included in these calculations.  AnnexII StatisticalAnnex 155 SECONDARY SCHOOL ENROLLMENT BY DISTRICT TABLE X.9 Population Gross Enrollment Gross Enrollment Ratios Male Female Total Male Female Total Male Female Total Apac 29,892 26,826 56,718 2,541 0 2,541 0.09 0.00 0.04 Arua 72,171 46,674 118,845 10,952 4,820 15,772 0.15 0.10 0.13 Bundibugyo 5,607 7,473 13,080 1,418 0 1,418 0.25 0.00 0.11 Bushenyi 48,570 47,085 95,655 3,346 4,789 8,135 0.07 0.10 0.09 Gulu 37,973 36,998 74,971 4,359 2,086 6,445 0.11 0.06 0.09 Hoima 7,682 9,137 16,819 2,694 1,176 3,870 0.35 0.13 0.23 Iganga 63,388 64,474 127,862 8,853 1,496 10,349 0.14 0.02 0.08 Jinja 31,868 28,498 60,366 8,355 3,159 11,514 0.26 0.11 0.19 Kabale 27,926 24,692 52,618 5,511 2,263 7,774 0.20 0.09 0.15 Kabarole 46,682 56,493 103,175 5,320 4,219 9,539 0.11 0.07 0.09 Kalangala 942 893 1,835 0 4 4 0.00 0.00 0.00 Kampala 46,330 71,166 117,496 18,015 22,005 40,020 0.39 0.31 0.34 K.amuli 29,861 32,306 62,167 6,778 552 7,330 0.23 0.02 0.12 Kapchorwa 6,470 8,198 14,668 1,687 1,616 3,303 0.26 0.20 0.23 Kasese 21,080 18,407 39,487 4,273 719 4,992 0.20 0.04 0.13 Kibaale 9,624 8,406 18,030 569 15 584 0.06 0.00 0.03 Kiboga 10,387 7,554 17,941 1,442 852 2,294 0.14 0.11 0.13 Kisoro 11,532 13,285 24,817 1,897 503 2,400 0.16 0.04 0.10 Kitgum 22,120 26,106 48,226 2,086 448 2,534 0.09 0.02 0.05 Kotido 16,181 16,134 32,315 92 26 118 0.01 0.00 0.00 Kumi 15,955 14,947 30,902 2,054 3,394 5,448 0.13 0.23 0.18 Lira 41,901 20,984 62,885 4,562 1,507 6,069 0.11 0.07 0.10 Luwero 25,160 24,153 49,313 2,113 2,372 4,485 0.08 0.10 0.09 Masaka 54,145 60,388 114,533 4,988 5,406 10,394 0.09 0.09 0.09 Masindi 21,961 15,332 37,293 1,730 1,159 2,889 0.08 0.08 0.08 Mbale 62,229 51,997 114,226 11,217 8,834 20,051 0.18 0.17 0.18 Mbarara 46,621 65,027 111,648 7,152 5,441 12,593 0.15 0.08 0.11 Moroto 14,969 16,121 31,090 0 588 588 0.00 0.04 0.02 Moyo 16,700 12,003 28,703 4,965 470 5,435 0.30 0.04 0.19 Mpigi 90,608 75,570 166,178 29,019 11,576 40,595 0.32 0.15 0.24 Mubende 27,669 29,260 56,929 4,120 3,026 7,146 0.15 0.10 0.13 Mukono 33,039 42,332 75,371 4,379 3,844 8,223 0.13 0.09 0.11 Nebbi 16,314 21,826 38,140 2,799 663 3,462 0.17 0.03 0.09 Pallisa 26,480 22,476 48,956 5,232 2,458 7,690 0.20 0.11 0.16 Rakai 28,540 30,550 59,090 1,421 3,486 4,907 0.05 0.11 0.08 Rukungiri 30,023 20,620 50,643 5,819 56 5,875 0.19 0.00 0.12 Soroti 23,716 32,219 55,935 3,723 626 4,349 0.16 0.02 0.08 Tororo 36,589 37,069 73,658 8,868 3,096 11,964 0.24 0.08 0.16 Uganda 1,158,905 1,143,679 2,302,584 194,349 108,750 303,099 0.17 0.10 0.13 Source: Calculations based on the 1992/93 Integrated Household Survey Note: The above figures include both public and private education. Gross enrollment figures include an unknown proportion of repeaters, hence the average attainment of children in primary education is much less than they suggest.  156 Annex IfI StatisticalAnnex PRIMARY SCHOOL ENROLLMENT BY AGE TABLE X.10 Age of Population in Years 6 7 8 9 10 11 12 Total 753,506 545,017 577,591 536,764 488,753 377,753 569,267 Male 373,487 285,884 305,646 275,372 251,700 190,305 288,291 Female 380,019 259,133 271,945 261,392 237,053 187,448 280,976 Urban 79,899 60,533 60,812 56,369 52,314 50,178 48,469 Rural 673,607 484,484 516,779 480,395 436,439 327,575 520,798 Expenditure quartiles: Bottom 209,530 149,800 169,349 146,526 146,393 100,556 173,765 Lower Middle 212,000 145,217 140,210 140,184 128,484 85,469 141,430 Upper Middle 184,627 140,799 147,218 133,921 122,436 98,215 135,612 Top 147,349 109,201 120,814 116,133 91,440 93,513 118,460 Gross Enrollment by Grade Level P1 P2 P3 P4 P5 P6 P7 Total 781,647 710,315 633,847 454,260 386,226 290,183 257,217 Male 416,597 390,715 349,166 260,537 211,744 160,580 159,360 Female 365,050 319,600 284,681 193,723 174,482 129,603 97,857 781,647 710,315 633,847 454,260 386,226 290,183 257,217 Urban 82,499 85,345 64,975 56,106 57,261 38,623 35,790 Rural 699,148 624,970 568,872 398,154 328,965 251,560 221,427 Expenditure quartiles: 781,647 710,315 633,847 454,260 386,226 290,183 257,217 Bottom 184,803 165,630 155,828 122,213 91,909 72,119 49,705 Lower Middle 210,220 173,012 163,724 108,615 100,169 63,565 64,939 Upper Middle 201,606 203,185 165,739 109,287 101,821 80,289 69,492 Top 185,018 168,488 148,556 114,145 92,327 74,210 73,081 Gross Enrollment Ratios by Grade Level P1 P2 P3 P4 P5 P6 P7 Total 1.04 1.30 1.10 0.85 0.79 0.77 0.45 Male 1.12 1.37 1.14 0.95 0.84 0.84 0.55 Female 0.96 1.23 1.05 0.74 0.74 0.69 0.35 Urban 1.03 1.41 1.07 1.00 1.09 0.77 0.74 Rural 1.04 1.29 1.10 0.83 0.75 0.77 0.43 Expenditure quartiles: Bottom 0.88 1.11 0.92 0.83 0.63 0.72 0.29 Lower Middle 0.99 1.19 1.17 0.77 0.78 0.74 0.46 Upper Middle 1.09 1.44 1.13 0.82 0.83 0.82 0.51 Top 1.26 1.54 1.23 0.98 1.01 0.79 0.62 Source: Calculations from the 1992/93 Integrated Household Survey.  AnnexIII StatisticalAnnex 157 SECONDARY SCHOOL ENROLLMENT BY AGE TABLE X.11 Age of Population in Years 13 14 15 16 17 18 Total 414,999 403,399 371,713 371,653 297,205 443,615 Male 215,337 199,789 205,528 190,479 154,335 193,437 Female 199,662 203,610 166,185 181,174 142,870 250,178 Urban 52,550 41,499 47,122 46,124 48,912 57,579 Rural 362,449 361,900 324,591 325,529 248,293 386,036 Expenditure quartiles: Bottom 121,348 115,683 100,762 110,729 78,203 110,708 Lower. Middle 99,071 103,236 90,874 85,306 72,086 98,259 Upper Middle 101,448 103,441 96,157 89,456 64,615 115,160 Top 93,132 81,039 83,920 86,162 82,301 119,488 Gross Enrollment by Grade Level Si S2 S3 S4 Ss S6 Total 81,722 75,072 58,002 50,710 18,507 19,086 Male 45,573 48,543 36,774 35,547 12,630 15,282 Female 36,149 26,529 21,228 15,163 5,877 3,804 Urban 14,906 16,704 18,764 12,832 11,794 12,946 Rural 66,816 58,368 39,238 37,878 6,713 6,140 Expenditure quartiles: Bottom 13,918 7,556 7,518 5,174 559 1,818 Lower Middle 13,070 19,439 10,555 10,550 959 1,649 Upper Middle 25,486 19,509 12,385 13,226 3,578 3,953 Top 29,248 28,568 27,544 21,760 13,411 11,666 Gross Enrollment Ratios by Grade Level S1 S2 S3 S4 S5 S6 Total 0.20 0.19 0.16 0.14 0.06 0.04 Male 0.21 0.24 0.18 0.19 0.08 0.08 Female 0.18 0.13 0.13 0.08 0.04 0.02 Urban 0.28 0.40 0.40 0.28 0.24 0.22 Rural 0.18 0.16 0.12 0.12 0.03 0.02 Expenditure quartiles: Bottom 0.11 0.07 0.07 0.05 0.01 0.02 Lower Middle 0.13 0.19 0.12 0.12 0.01 0.02 Upper Middle 0.25 0.19 0.13 0.15 0.06 0.03 Top 0.31 0.35 0.33 0.25 0.16 0.10 Source: Calculations from the 1992/93 Integrated Household Survey.  158 AnnexIII StatisticalAnnex EDUCATIONAL ATTANDMENT BY DISTRICT TABLE X.12 Percentage of Population over 16 Years of Age No Level Proportion Completed P1 to P4 P5 to P7 S1 to S4 S5 to S7 Further Literate Kalangala 7.7 26.0 40.9 15.4 0.0 10.0 90.5 Kampala 5.6 12.1 31.2 30.7 6.7 13.8 91.8 Kiboga 24.2 33.4 31.2 9.2 0.6 1.5 68.7 Luwero 30.5 28.2 30.5 9.7 0.4 0.7 63.8 Masaka 28.4 30.8 29.0 9.6 0.6 1.6 68.8 Mpigi 16.7 20.1 35.0 19.0 2.8 6.4 80.1 Mubende 25.0 31.5 30.8 8.6 0.0 4.0 72.5 Mukono 31.3 25.1 28.8 11.8 0.7 2.3 60.5 Rakai 33.4 30.5 26.4 8.0 0.3 1.3 60.8 Iganga 38.1 19.5 30.3 9.5 0.4 2.3 54.6 Jinja 17.9 22.4 31.4 20.7 1.7 5.9 76.8 Kamuli 37.7 24.2 25.2 10.4 0.1 2.3 56.0 Kapchorwa 29.9 11.7 39.3 14.1 1.7 3.1 60.7 Kumi 38.3 21.1 26.5 9.8 0.1 4.1 55.1 Mbale 31.2 22.4 31.7 12.1 0.7 2.0 59.0 Pallisa 36.8 26.0 24.7 10.0 0.4 2.0 56.1 Soroti 38.6 23.8 25.8 6.8 0.4 4.5 50.8 Tororo 32.5 21.1 30.4 12.2 0.1 3.6 58.6 Bundibugyo 38.9 25.7 25.4 7.8 0.2 1.9 54.9 Bushenyi 41.4 26.2 22.6 7.3 0.6 2.0 56.6 Hoima 30.2 27.1 30.0 11.2 0.1 1.3 65.5 Kabale 36.0 21.1 28.5 8.9 1.4 4.0 65.8 Kabarole 39.0 26.8 25.1 6.8 0.3 2.0 55.7 Kasese 35.5 21.6 28.3 10.8 0.4 3.4 58.9 Kibaale 47.5 26.3 22.9 2.9 0.3 0.0 50.2 Kisoro 50.1 19.0 20.5 6.4 0.0 4.0 51.8 Masindi 39.0 26.3 25.4 8.1 0.3 0.8 57.3 Mbarara 39.3 23.3 27.1 7.6 0.3 2.4 58.8 Rukungiri 35.3 26.8 28.6 6.5 0.7 2.0 62.8 Apac 29.1 20.4 39.0 9.2 0.4 1.9 66.2 Arua 41.0 22.5 23.9 9.7 0.8 2.1 49.5 Gulu 33.7 24.0 30.5 8.7 0.3 2.7 61.3 Kitgum 41.7 22.2 29.3 5.1 0.6 0.9 52.2 Kotido 73.4 14.7 10.2 1.1 0.0 0.6 22.5 Lira 36.0 19.3 29.2 11.1 1.1 3.2 56.9 Moroto 75.7 9.1 7.1 4.5 0.0 3.5 20.8 Moyo 36.9 19.8 25.7 16.0 0.3 1.2 55.6 Nebbi 37.9 28.9 25.7 6.4 0.0 1.1 52.2 Source: Calculations from the 1992/93 Integrated Household Survey. Note: Literacy means reading and writing.  Annex III StatisticalAnnex 159 MDEDICAL TREATMENT DURING THE LAST 30 DAYS TABLE X.13 In Percent Expenditure Quartile Lower Upper Bottom Middle Middle Top None 83.9 79.8 78.1 77.8 Home treatment 7.2 8.3 8.5 6.7 Outpatient government hospital/clinic 3.6 4.4 4.3 3.6 Outpatient private hospital/clinic 3.7 5.2 7.0 9.2 Private doctor 0.3 0.7 0.6 1.1 Pharmacy 0.3 0.4 0.4 0.5 Traditional doctor 0.5 0.6 0.5 0.3 Inpatient government hospital/clinic 0.2 0.3 0.2 0.3 Inpatient private hospital/clinic 0.2 0.2 0.3 0.5 Other 0.0 0.1 0.1 0.1 Source: 1992/93 Integrated Household Survey.  160 Annex III StatisticalAnnex DISTRIBUTION OF TYPES OF SCHOOLS AlTENDED TABLE X.14 WITH1N EACH EXPENDITURE QUARTILE PI to P4 PS to P7 Sl to S4 S5 to S6 Further Bottom quartile 100.0 100.0 100.0 100.0 100.0 None 85.9 95.3 99.3 100.0 100.0 Govt managed. costs shared 10.1 3.9 0.5 0.0 0.0 Govt financed and managed 1.0 0.2 0.1 0.0 0.0 Govt finance, non-profit managed 0.9 0.2 0.0 0.0 0.0 Non-profit financed and managed 1.3 0.2 0.0 0.0 0.0 Private commercial 0.8 0.2 0.1 0.0 0.0 Lower middle quartile 100.0 100.0 100.0 100.0 100.0 None 85.3 94.9 98.8 100.0 99.9 Govt managed. costs shared 10.8 4.2 1.0 0.0 0.1 Govt financed and managed 0.6 0.2 0.1 0.0 0.0 Govt finance, non-profit managed 0.5 0.3 0.0 0.0 0.0 Non-profit financed and managed 2.0 0.3 0.1 0.0 0.0 Private commercial 0.8 0.1 0.0 0.0 0.0 Upper middle quartile 100.0 100.0 100.0 100.0 100.0 None 84.7 94.3 98.5 99.9 100.0 Govt managed, costs shared 10.2 4.3 1.1 0.1 0.0 Govt financed and managed 0.9 0.4 0.1 0.0 0.0 Govt fuance, non-profit managed 0.7 0.2 0.1 0.0 0.0 Non-profit financed and managed 2.3 0.4 0.1 0.0 0.0 Private commercial 1.2 0.4 0.1 0.0 0.0 Top quartile 100.0 100.0 100.0 100.0 100.0 None 86.2 94.6 97.5 99.5 99.5 Govt managed, costs shared 9.0 4.1 1.6 0.4 0.1 Govt financed and managed 0.9 0.5 0.2 0.0 0.1 Govt finance, non-profit managed 0.6 0.2 0.1 0.0 0.0 Non-profit financed and managed 1.8 0.2 0.3 0.0 0.1 Private commercial 1.5 0.4 0.3 0.1 0.2 Source: Calculations from the 1992/93 Integrated Household Survey. Notes: The code for 'government managed and costs shared' seems also to have been used for missing observations, so that the public sector may be overstated. To avoid double-counting, children away for over 6 months are not included in the household, so that boarding schools, which are mainly in the private sector. may be underestimated.  AnnexIII StatisticalAnnex 161 DISTRBUTION OF EXPENDITURE QUARTlLES TABLE X.1S WITN EACH SCHOOL TYPE PI to P4 PS to P7 Sl to S4 All schools 100.0 100.0 100.0 Bottom quartile 24.4 22.9 12.9 Lower middle quartile 25.4 24.5 20.2 Upper middle quartile 26.3 26.9 26.6 Top quartile 23.9 25.7 40.3 Government managed, costs shared 100.0 100.0 100.0 Bottom quartile 25.2 23.8 12.8 Lower middle quartile 26.9 25.7 22.7 Upper middle quartile 25.4 25.9 26.9 Top quartile 22.6 24.6 37.6 Governmentfinanced and managed 100.0 100.0 100.0 Bottom quartile 28.9 17.9 16.8 Lower middle quartile 18.7 18.0 18.5 Uppermiddlequardle 27.1 29.6 31.1 Top quartile 25.3 34.5 33.6 Governmentfinanced, non-profit managed 100.0 100.0 100.0 Bottom quartile 34.2 28.6 11.8 Lower middle quartile 16.4 29.0 9.3 Upper middle quartile 26.1 17.7 43.2 Top quartile 23.2 24.7 35.7 Non-profitfinanced and managed 100.0 100.0 100.0 Bottom quartile 17.3 14.7 2.7 Lower middle quartile 27.7 26.3 18.5 Upper middle quartile 30.7 38.5 16.1 Top quartile 24.3 20.4 62.7 Private commercial 100.0 100.0 100.0 Bottom quartile 18.0 17.7 16.6 Lower middle quartile 19.1 8.9 7.9 Upper middle quartile 27.7 35.9 23.7 Top quartile 35.2 37.5 51.7 Source: Calculatons from te 1992193 Intcgrated Household Survey. Notes: The sample size is too small above dte lower scondary level for the dar to make much sense, hence only P1 to P4. P5 w P6 and Si to S4 are shown. The code for governcnt manqaed and cost shared seems also to have been used for missing observadons, so chat the public sector may be overstted. To avoid double-counting. children away for over 6 months are not included in the household, so that boarding schools, which are mainly in the private sector, may be underestimated.  162 AnnexIII StatisticalAnnex PRIMARY SCHOOL ENROLLMENT BY DISTRICT AND BY SEX TABLE X.16 Headcount as of May 17, 1994 Female Male Total Eastern Region 287,238 338,527 625,765 46% 54% 100% Kamuli 26,764 29,598 56,362 Iganga 55.473 61,900 117,373 Tororo 33,604 42,102 75,706 Mbale 58,627 63,669 122,296 Kapchorwa 10,173 11,988 22,161 Korido 9,463 12,052 21,515 Kumi 17,458 22,929 40,387 Jinja 19,850 20,580 40,430 Moroto 3,863 4,819 8,682 Soroti 33,576 46,723 80,299 Pallisa 18,387 22,167 40,554 Northern Region 160,967 273,663 434,630 37% 63% 100% Apac 29,348 46.862 76,210 Lira 28,761 49,763 78,524 Gulu 24,880 37,916 62,796 Kitgum 21,127 41.475 62,602 Nebbi 13,901 23,965 37,866 Moyo 6,426 10,579 17,005 Arua 36,524 63,103 99,627 Western Region 300,275 341,485 641,760 47% 53% 100% Masindi 15,808 18,485 34,293 Bushenyi 41,821 44,395 86,216 Rukungiri 33,621 35,473 69,094 Bundibiugyo 6,154 9,008 15,162 Kabale 31,290 35,683 66,973 Mbarara 54,330 58,759 113,089 Kabarole 36,957 42,600 79,557 Kasese 22,179 27,079 49,258 Hoima 16,716 18,037 34,753 Kibale 17,467 20,505 37,972 Kisoro 8,105 12,837 20,942 Ntungamo 15,827 18,624 34,451 Central Region 310,824 311,204 622,028 50% 50% 100% Mpigi 65,310 64,905 130,215 Mubende 32,633 34.041 66,674 Masaka 45,956 44,955 90,911 Rakai 32,718 33,256 65,974 Luwero 31,952 33,151 65,103 Mukono 56,714 57,141 113,855 Kampala 36,651 34,247 70,898 Kalangala 844 837 1,681 Kiboga 8.046 8,671 16,717 Uganda 1,059,304 1,264,879 2,324,183 46% 54% 100% Source: Ministry of Education and Sports.  Annex.III StatisticalAnnex 163 STUDENT ENROLLMENT IN EDUCATIONAL INSTITUTIONS TABLE X.17 1993/94 PRIMARY 2,389,227 SECONDARY 260,000 TERTIARY 45,901 64 Primary Teachers Colleges (PTCs) 18,349 10 National Teachs Colleges (NTCs) 7,000 4 Uganda Technical Colleges (UTCs) 1,588 5 Uganda Colleges of Commece (UCCs) 2,264 30 Technical Institutes (TIs) 8,000 25 Technical Schools (TSs) 6,500 1 Uganda Polytechnic Kyambogo (ITEK) 700 1 National College of Business Studies, Nakawa 1,500 UNIVERSITIES 8,310 Makerere 7,000 Mbarara 260 Institute of Teacher Education, Kyambogo 1,050 TOTAL 2,703,438 Source: Ministry of Education and Sport. Note: The primary enrollment data are available by region from different sources.   BIBLIOGRAPHY   BIBLIOGRAPHY Ahmed, R. and M. Hossain, 1990, Developmental Impact of Rural Infrastructure in Bangladesh, International Food Policy Research Institute, Research Report No. 83 Ainsworth, M. and M. Over, 1994, AIDS and African Development, The World Bank Research Observer, Vol. 9, No. 2, July Armington, P., 1994, The Medium-Term Evolution of the Tax System in Uganda: Principles and Plans, Background paper for the Uganda Country Economic Memorandum, World Bank Public Information Center, Washington, D.C. Appleton, S., 1994, Problems of Measuring Poverty Over Time. The Case of Uganda, 1989-1992, Working paper, Centre for the Study of African Economies, University of Oxford Appleton, S., 1995, Women-Headed Households and Poverty: An Empirical Deconstruction for Uganda, Working paper, Centre for the Study of African Economies, University of Oxford Appleton, S. and J. 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