Fiscal Transfers in the Republic of the Sudan Introduction to fiscal transfers Fiscal transfers from the national level are intended to help subnational levels of government meet their expenses. Fiscal transfers are one piece of the larger picture of fiscal allocation, which includes the allocation of revenue-raising competencies between national and subnational levels of government. The purpose of this analysis is to examine different fiscal transfer scenarios in the context of the Republic of the Sudan. Typically, governments assign fiscal transfers using mathematical formulas that take into account indicators across subnational units. Some indicators, such as population size or teachers wages, measure units expenditure need, or the demands on its budget. Others measure a unit s fiscal capacity, or its ability to raise its own revenues, such as its tax base. Fiscal transfers in the Sudan In the Republic of the Sudan, the Fiscal and Financial Allocation and Monitoring Commission (FFAMC) has been responsible for fiscal transfers to the states since its establishment by presidential decree in 2005. Its main roles are to: (a) set criteria for sharing resources between the levels of government; (b) monitor the transfers from the National Revenue Fund to the states; and (c) ensure fairness and transparency in the allocation of funds to the states. The FFAMC set a formula in 2011 for the transfer (see Table 1), although it is unclear whether other factors influence the amounts of the transfers. Figure 1 compares the equitability of historical Sudanese fiscal transfers. The 1949 Marshall Report notes that, at that time, fiscal transfers favored rural areas and took distance, population, prices, income and local taxes into account. In 2007, the FFAMC proposed a simple formula with four criteria: population, spending needs, social development, and internally-generated funds. The Commission s 2011 proposal, shown below, adds more criteria. Comparative fiscal transfer formulae Table 1 presents the indicators used in three fiscal transfer formulae from around the world. Spain s formula is based entirely on expenditure need indicators, while the formulae used by Indonesia and Sudan s FFAMC (2011) use a combination of expenditure need and fiscal capacity. Apart from state population, each formula uses very different indicators to determine each state s percentage of the transfer. 1
Cumulative % Transfer 100.00% Figure 1: Sudan Fiscal Transfers - Historical Comparison 80.00% 60.00% 40.00% 20.00% 1984/85 (GINI=0.188) 2006 (GINI=.130) 2007 (GINI=0.061) 2011 proposal (GINI = 0.211) 0.00% 0.00% 20.00% 40.00% 60.00% 80.00% 100.00% Cumulative % Population Table 1: Indicators and Weights used to determine the amount of fiscal transfers Formulas from Sudan 2011, Indonesia, and Spain Weight of each indicator in the equation Indicator FFAMC 2011 proposed formula Indonesia Scenario 1 Spain Scenario 2 Population 25% 40% 30 % Health & Education 25% - - Agricultural Needs 15% - - Security 15% - - Fiscal Performance 10% - - Poverty - 10% - Population age 0-14 - - 20.5% Population age 60+ - - 8.5% Population on state health insurance - - 38% Distance to capital, port 8% - 1.8% Area (km 2 ) - 10% 1.8% Zakat Revenues 2% - - Consumer Price Index 3-40% - Sources: FFAMC (2010); Hofman et al, 10; Spanish Ministry of Finance and Public Administration. This section runs data from the Sudan s states 4 through formulae used in Indonesia and Spain and compares the results with the Sudan s allocations from 2011. 5 The scope of possible analysis was limited 1 Indonesia s full formula takes fiscal capacity into account as well; this analysis compares only the effect of Indonesia s measures of expenditure need against other possibilities. 2 Spain s original formula uses age ranges of 0-16 and 65+. In addition, two other variables were excluded, measures of spread and insularity that were not defined and both weighted at less than 1%. 3 Indonesia uses construction prices to determine the cost index; this analysis uses Sudan s more comprehensive price index measure. 4 This analysis uses data up to 2010, before the states of Eastern and Central Darfur were established. 5 Data for Spain and Indonesia calculations came from "Statistical Year Book for the Year 2009," Central Bureau of Statistics and Ministry of The Cabinet, The Republic of Sudan. See also: "Sudan National Baseline Household Survey 2
State Transfer (in SDG) to expenditure needs, since reliable measures of fiscal capacity were unavailable for the Sudan s states. Therefore, the results show the effect solely of the expenditure need variables used by Indonesia and Spain on simulated allocations to the Sudan s states. Data from the Sudan s states were used in the formulae from Indonesia and Spain to simulate the effect of these formulae on allocations in the Sudan. Figure 2 shows the results of these two scenarios and compares them to the proposed allocations in Sudan for 2011. The graph also takes into account the amount of national revenues that make up the transfer fund in each of the three contexts (see below for full explanation). Figure 2: Scenarios of transfers to northern states, based on budget of 1000 SDG. The chart answers the question: If the Sudan s budget were 1,000 SDG, how much would each state receive under each scenario? First, the percentage of the total budget that makes up the transfer fund for each context is determined (see bullets). Then, the Table 1 formulae are used to determine each state s share of the fund. Under the Sudan s 2011 budget proposal, the national government would keep 687 SDG and the states would share 313 SDG. Spain s autonomous communities (ACs) contribute 75% of their tax revenues into an equalization fund, and the national government adds about 13% of that. For this simulation, the formula is used as it would be in the Sudan for national government transfers to the states. (See below for details of Spain s method.) In this model, the national government would keep 720 SDG and the states would share 280 SDG. Figure 2: Scenarios of transfers to northern states, based on 1000 SDG budget 45 40 35 30 25 20 15 10 5 0 Spain formula (GoS share: 720 SDG) Sudan 2011 proposal (GoS share: 687 SDG) Indonesia formula (GoS share: 750 SDG) 2009: North Sudan Tabulation Report. Sudan Central Bureau of Statistics, CBS/NBHS 2009 Statistical Report No. 3/2010. 3
Analysis of Gini indixes Table 2: Gini indexes of different transfer scenarios GINI Measure Spain scenario Indonesia scenario Sudan 2011 proposal 1) GINI (population) 0.031 0.172 0.211 2) GINI (pop in poverty) 0.115 0.175 0.219 This section assesses the equitability of the three scenarios above. Table 2 presents two Gini indexes for each scenario. Each Gini index is based on one of two criteria: 1) state share of the Sudan s total population; or 2) state share of the total Sudanese population living in poverty. A Gini index measures equitability of distribution in a system, with an index of 0 representing statistically exact proportional distribution and 1 representing the maximum level of inequality in the distribution. 6 A Gini (population) equal to 0 would mean that state s allocation exactly matches the state s share of population. For example, if Khartoum state has 16 percent of the Sudan s population, it would receive 16 percent of the total transfer funds, and so for all the states. However, a low Gini index is not necessarily the best outcome, as illustrated below. It is instructive to compare the two Gini indexes for each scenario. The Spain scenario, for example, shows the allocation to be more equitable compared to population than compared to poverty. This suggests that a large, rich state may receive a disproportionately large transfer compared with a small, poor state. For example, Khartoum has a relatively low poverty rate but under Spain s formula would receive a far higher transfer than any other state due to its high population. Red Sea state has high poverty, but would receive one of the lowest transfers under Spain s formula because of its low population. On the other hand, the two Gini indexes for the Sudan s 2011 proposal are very close, suggesting that the proposed formula is equally sensitive to states population and poverty levels. Under this formula, as well as in the Indonesia scenario, neither larger states nor poorer states would have a special advantage in securing funds. Measuring poverty and development Every formula for fiscal transfers requires measuring indicators. Indicators such as population or revenues are numerical, but it is inherently more difficult to find indicators that accurately measure the level of development. The FFAMC in 2010 used common indicators of education and health, such as ratio of students to teachers, ratio of population to doctors, and number of health centers. This section compares different measures of development. The Human Development Index (HDI) is perhaps the most well-known measure of development. It considers three dimensions of human development: Long and healthy life, measured by life expectancy at birth 6 The Gini index is a calculation of the area on a graph between a y=x diagonal line and the curve representing the cumulative percentage of whatever is being measured. 4
Knowledge, measured by adult literacy and school enrollment Standard of living, measured by GDP per capita The HDI attempts the difficult task of measuring outcomes instead of simply demographics and infrastructure. Life expectancy and adult literacy can be seen as end results of development, while enrolment and GDP per capita are means to an end. See Figure 3 for HDI calculated for the Sudan s states. 7 The HDI can also be calculated separately for men and women to look at development through a gender perspective. The 2009 Arab Human Development Report applies a human security perspective to development in the Arab States. The report underlines seven elements of Arab human security (though does not attempt to measure every one): 1) land, water, and ecology; 2) guarantees of rights to resolve identity conflict; 3) better conditions for women, children, and refugees; 4) political will for domestic development; 5) food security and nutrition; 6) health as a human right; and 7) sovereignty. 8 Finally, some countries are beginning to use a Multi-dimensional Poverty Index (MPI) to improve how they define who is poor. An MPI looks at both breadth and depth of deprivation. 9 For breadth, an MPI defines several important dimensions of poverty in a particular context. Each dimension has a cutoff level, under which a person is considered deprived in that dimension. For depth, it answers the question: in how many dimensions must a person be deprived to be considered poor? An MPI is context-specific, so each country must choose locally-relevant dimensions and cutoffs. 7 University of Gezira and UNDP-Sudan, Geography of Peace: Putting human development at the centre of peace in Sudan, Sudan National Human Development Report, 2011. 8 Arab Human Development Report 2009, Challenges to Human Security in the Arab Countries, UNDP Regional Bureau for Arab States, 2009. 9 Sabina Alkire and James Foster, Counting and Multidimentional Poverty Measurement, Oxford Poverty and Human Development Initiative Working Paper no. 32, 2009. 5
Figure 3: Human Development Index by state (Sudan) Khartoum El-Gezira Northern Nile White Nile Sennar N. Kordofan Kassala Red Sea Al-Gadarif N. Darfur S. Kordofan S. Darfur Blue Nile W. Darfur 0.714 0.698 0.620 0.619 0.607 0.601 0.585 0.572 0.569 0.559 0.553 0.537 0.536 0.535 0.526 High Human Development ---------------------------------- Low Human Development Source: UNDP Sudan and University of Gezira Transfer fund The total amount allocated to each state will depend on the amount in the transfer fund. The formulas above do not impact the amount of the transfer fund, only its distribution among the states. In addition, FFAMC reports from 2007 and 2010 do not address this issue. Figure 4 shows the changing percentage of the Government of National Unity budget that was transferred to the northern states between 2007 and 2011, using data from the World Bank and from the Sudan s Central Bureau of Statistics. 6
Figure 4: Historicalf GoNU Budget for North Sudan 100% 80% 60% 75.2% 69.6% 65.9% 71.0% 68.7% 40% 20% 24.8% 30.4% 34.1% 29.0% 31.3% 0% 2007 2008 2009 2010 2011 Transfers to Northern States Other Expenditures Comparative examples show various methods determining the amount of funds in the transfer pool. In Indonesia, the total transfer fund is made up of 25 percent of all national government revenues (not including shared taxes). 10 In Spain, the largest transfer fund is called the Guarantee Fund (GF). Autonomous communities (ACs) give 75 percent of their own revenues to the GF, and the national government contributes about 13 percent of the states contribution. 11 The fund is then redistributed among ACs according to need. The total fund amounts to approximately 28 percent of total governmental revenues in Spain. Another important issue in many countries is how to account for natural resource revenues in transfers to subnational governments. The Sudan s constitution stipulates that no less than 2 percent of oil and gas revenues are to be allocated to oil-producing states. 12 In Indonesia, regions receive 15 percent of oil and 35 percent of gas revenues, except for Papua and Aceh, which receive 70 percent of locallygenerated oil and gas revenues under their special autonomy status. Elsewhere, Canada calculates its fiscal transfer formula using only the provinces revenue-raising abilities but takes only 50 percent of oil revenues into account. States dependence on national funds 10 The World Bank, Decentralizing Indonesia: A Regional Public Expenditure Review, Report No. 26191-IND, 2003, 26. 11 CDI calculations with data from: Andoni Zabalza and Julio Lopez-Laborda, "The New Spanish system of intergovernmental transfers," Andres Young School of Policy Studies at Georgia State University, Working Paper 11-03, 2011, 18. ACs receive 33 percent of total government revenues and contribute 75 percent of this revenue to the Guarantee Fund. The government contributes 13 percent of the total contributions of the ACs. 12 Interim National Constitution of the Republic of the Sudan, as amended 2011, Article 147. 7
In 2005, the average state budget in Sudan was 70 percent funded by national government transfers. 13 This high level of dependence limits states freedom to make internal decisions, especially because some transfers are conditional. The graph below compares average dependence on national government transfers from different countries and years. 14 100% Average of state budget dependence on fiscal transfers 90% 80% 70% 60% 50% 40% Sudan 05 (World Bank '07) Sudan Darfur States 08 (UN 2011) Ethiopia 93-01 Indonesia 01-04 Spain Conclusion This document has explored several aspects of fiscal transfers from the national government of the Sudan to the states. The data and analysis presented above suggest the following considerations for a fiscal transfer system. Diversity of indicators: Within the categories of expenditure need and fiscal capacity, a wide range of indicators can be used in a formula. The comparative formulae above show hypothetical effects of different indicators on the Sudan s fiscal transfers. The discussion of measuring poverty and human development also shows the diversity of possible indicators. Ultimately, it is up to the Sudanese, led by the FFAMC, to decide which indicators fit the context. Comparison across multiple criteria: The discussion of Gini indexes shows that comparing against a single criterion may miss factors that are more important to some states than others. The multiple dimensions of states needs favor multiple bases for comparison of a transfer system. 13 The World Bank, Sudan Public Expenditure Review: Synthesis Report, Report No. 41840-SD, 2007, 59. 14 Figure 4 contains data drawn from The World Bank, Sudan Public Expenditure Review: Synthesis Report ; Sudan: UN and Partners Work Plan 2011, 35; Abu Girma Moges, "An Economic Analysis of Fiscal Federalism in Ethiopia," Northeast African Studies 10, no. 2 (2003); The World Bank, Decentralizing Indonesia: A Regional Public Expenditure Review ; Bert Hofman, Kadjatmiko Kai Kaiser, and Bambang Suharnoko Sjahrir, Evaluating Fiscal Equalization in Indonesia, World Bank policy research working paper 3911, 2006; Julio Lopez-Laborda, Jorge Martinez-Vazquez, and Carlos Monasterio, Kingdom of Spain, in The Practice of Fiscal Federalism: Comparative Perspectives, ed. Anwar Shah, (Montreal: McGill-Queen s University Press, 2007). 8
Transparency: Central to the FFAMC s mandate is ensuring the transparency and fairness of the allocation of funds. 15 Openness can increase buy-in into the process of creating a formula and determining the amount of the transfer fund. Fiscal transfers are only part of the picture: The distribution of revenue and fiscal competencies among levels of government is an important part of political accommodation within a country. Ensuring fair fiscal transfers is one step toward building a fair system of fiscal decentralization. 15 Republican Decree No. (35) 2006 on the establishment of a Fiscal and Financial Allocation and Monitoring Commission. 9