Appendix I. Education

1. The SDG costing estimate for education is expressed as the additional spending needed to perform well in the education SDG, that is, the difference between the spending needed in 2030 and the spending level today. Both today’s education expenditures (as a percent of GDP), E2018, and the levels needed by 2030, E2030, are expressed as an identity:

E=wSTReSAP100Eoth

where w refers to teachers’ annual wages as a ratio to GDP per capita, STR is the student teacher ratio, e signifies the enrollment rate, i.e. the number of students as a percentage of the student-age population, SAP indicates the student-age population as a percent of total population, and Eoth, pertains to all education spending besides the teacher wage bill as a percent of total expenditures in education.

2. The spending needed in 2030 to perform well in the education SDG is the level of expenditures Nigeria would incur by 2030 due to projected demographics (student-age population) and if it matched, by 2030, today’s levels of the education cost-drivers of the high performers among Nigeria’s peers. These cost drivers include teachers’ wages, the student-teacher ratio, the enrollment rate, and education spending other than the teacher wage bill. The approach of matching Nigeria’s 2030 cost drivers to today’s level of the high performers is seen in the corresponding columns of Table 2. Table AI.1 gives the data sources and computation of demographic factors and cost drivers (latest estimates available are for 2017–18).

Table AI.1.

Computation and Data Sources for Variables Used in the Education SDG Costing Estimation

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Appendix II. Health Care

1. The SDG costing estimate for health is expressed, analogous to that for education, as the additional spending needed to perform well in the health SDG, that is, the difference between the spending needed in 2030 and the spending level today.

2. Both today’s health expenditures (as a percent of GDP), E2018, and the levels needed by 2030, E2030, are expressed as an identity:

E=10wD+0.5M100Eoth

where w refers to doctors’ annual wages as a ratio to GDP per capita, D and M are the numbers of doctors and other medical personnel, respectively, per 1,000 population, and Eoth pertains to all spending besides the health workers’ wage bill as a percent of total expenditures in education.

3. The spending needed in 2030 to perform well in the health SDG are the level of expenditures Nigeria would incur by 2030 in light of projected demographics (the projected population share of infants and the elderly, who have greater medical needs) and if it matched, by 2030, today’s levels of the health cost-drivers of the high performers among Nigeria’s peers. These cost drivers include doctors’ wages, the number of doctors relative to the population size, the number of other medical personnel relative to the population size, and health spending besides the health workers’ wage bill. The approach of matching Nigeria’s 2030 cost drivers to today’s level of the high performers is seen in the corresponding columns of Table 2. Table AII.1 gives the data sources and computation of demographic factors and cost drivers for Nigeria in today (latest estimates available are from 2016–17).

Table AII.1.

Computation and Data Sources for Variables Used in Health SDG Costing Estimation

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Appendix III. Electricity

1. We obtained power mix from the Nigeria’s Federal Ministry of Power and the National Council on Power (NACOP).1 The cost per kW of installed generation comes from international benchmarks. The average investment cost per kW of capacity is calculated as the weighted average of unit costs and share of installed capacity in the power mix.

2. The unit cost per kW is estimated at US$ 1,092. Table AIII.1 breaks down the calculations.

Table AIII.1.

Unit Cost of Investment in On-Grid Electric Power Generation

(per kW)

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Source: IMF staff calculations based on data from “Sustainable Energy for All Action Agenda (SE4ALL-AA)”, approved by the National Council on Power.

3. Based on interviews with experts the costs in transmission and distribution costs are assumed to add 50 percent each to investment costs in capacity. We also assumed that investment costs in power storage will be offset by lower transmission and distribution costs. Therefore, the total costs of investment in electric power generation, transmission, and distribution were estimated at US$ 2,184 per kW.

Appendix IV. Roads

Unit Cost per Kilometer of Road

1. We estimated the share of future highways—national and state—local (district, urban, and project), and rural roads from Nigeria’s Infrastructure Concession Regulatory Commission.2 The cost per type of road is taken from World Bank and African Development Bank projects as well as engineering estimates (Table AIV.1).

Table AIV.1.

Cost per km of Road

(in US$)

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Source: IMF staff calculations based on World Bank and African Development Bank projects, and engineering estimates.

2. We assumed that future roads are going to follow the same proportion. As a result, the average cost of road construction was estimated at US$550 thousand per kilometer.

Migration-Adjusted Rural Access Index

3. The Rural Access Index (RAI) is calculated based on a GIS model of the distribution of rural population, and a geospatial model of rural roads (including their location and type). Demographic dynamics affect the RAI even without additional roads. i.e., ceteris paribus, the migration from rural to urban areas increases mechanically the RAI. We account for demographic migration from rural to urban in 2030 areas to calculate the migration-adjusted RAI in 2030 keeping roads constant. The following equation presents the calculation:

RAI2030migrationadjusted=1Rutal2019×(1RAI2019observed)currentruralpopulationnotconnected(Rural2019Rural2030)migrationfromrualtourbanRural2030migrationajustedruralpopulationwitoutaccesstoroads

where Rural is the share of rural population in 2019 and projected in 2030. Taking into account the projected migration from rural to urban areas (from 49.7 percent in 2018 to 40.8 percent in 2030 of the population living in rural areas), we adjusted the Rural Access Index from the observed 25.5 percent in 2019 to a ceteris paribus migration-adjusted Rural Access Index of 31 percent.

Road Length Needed

4. Using a sample of low-income and emerging economies, we estimate the length of all-weather roads regressing road density on GDP per capita, population density, agriculture and manufacturing sector shares in the economy, urbanization rate, and migration-adjusted Rural Access Index—i.e., the share of the population that has access to road within two kilometers. This approach assumes away contemporaneous reverse causality: i.e., road density affects income per capita and population density with a substantial lag.3 The regression specification is as follows:

lg_cia_density = lggdp_cap rai agg_gdp manu_gdp lgpop_density urban

where lg_cia_density is natural logarithm of road density, lggdp_cap is the natural logarithm of GDP per capita, agg_gdp is the aggregated GDP, manu_gdp is the ratio of manufacturing to GDP, lgpop_density is the natural logarithm of population density, and urban is the share of urban population in total population. The regression is restricted to low-income and developing economies, and emerging market economies with medium-range road density (i.e., it does not incorporate advanced economies, or countries with too low or too high road density).

5. We then use the point estimates from the regression to calculate the additional kilometers of road needed given Nigeria’s projected population and GDP per capita growth and the increase in the RAI from 31 (migration-adjusted) to at least 75 percent by 2030.

6. We estimate the total cost of the additional road network by multiplying the estimated additional kilometers by the unit cost of constructing one kilometer, which is set at US$ 550,308 per kilometer.4 To account for depreciation, we increase the total cost of the additional kilometers by 5 percent.

Appendix V. Water and Sanitation

Definitions and Standards of Service

1. The goal in water and sanitation is full coverage in each category: end open defecation, and then access to basic water, sanitation, and hygiene, and finally safely managed water and sanitation provision. These categories are incremental: i.e., the safely managed implies access to basic water and sanitation. In this paper, we rely in the UN definition and threshold for each category:

1. End of open defecation: access to services that remove the need for open defecation— improved or unimproved toilet facility (e.g., pit latrines without a slab/platform, hanging latrines, bucket latrines)

2. Basic water, sanitation, and hygiene

  • 2.1. Basic water services: access to an improved water source within 30 minutes roundtrip

  • 2.2. Basic sanitation services: access to improved sanitation facility such as flush toilets or latrine with a slab

  • 2.3. Basic hygiene services: handwashing station in the household with soap and water present

3. Safely managed water and sanitation

  • 3.1. Safely managed water services: access to improved water source on the individual’s premises

  • 3.2. Safely managed sanitation services: access to improved sanitation facility on household premises where excreta are safely disposed of in situ or treated off-site

Population Unserved

2. The percentage of served population in rural and urban areas, and the cost per capita of providing the service was obtained from different sources and revised data by government authorities during the mission. Table AV.1 reports the reviewed statistics of coverage by type of water and sanitation service.

Table AV.1.

Statistics of Coverage by Type of Water and Sanitation Service

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Source: IMF staff calculations.Note: Average costs were provided by the Federal Ministry of Water Resources in NGN and converted to US$ at the rate of 360 NGN = 1 USD. Rural and urban cost per capita are assumed to be similar for basic services, and urban cost per capita are assumed to be three times larger than in rural areas for safely-managed services.

3. The target population unserved in 2030 was extrapolated from the percentage of rural and urban population unserved in 2019 and the migration from rural to urban areas. This implies, ceteris paribus, an improvement in the coverage ratios by simple migration from unserved rural to served urban areas.

Total Number of Population Unserved and Cost of Water and Sanitation

4. The cost per type of service and population strata was computed as the product of the population underserved times the cost per capita of providing the service by type of service and population strata by times.

5. To avoid double counting and since the services are incremental (i.e., populations with safely managed sanitation have access to more basic services like water and latrines), we compute the total population unserved as the maximum of rural population unserved by type of service plus the maximum of urban population unserved by type of service. Following the WASH methodology developed by the World Bank,5 the total cost was calculated as the full cost of providing safely managed water and sanitation services plus half of the cost of providing the basic water and sanitation.

Appendix VI. Annualized Cost of Investment6

1. Let K2030* be the additional stock of infrastructure required by 2030 to meet the desired goals. We can write the capital stock at any point in time as:

Kt=Kt1(1d)+It

where d is the annual depreciation rate and It is the gross investment in year t. Therefore, the additional stock built between 2018 and 2030 will be equal to:

K20182030=Σt=2018T=2030It(1d)Tt

which equals the additional stock required by 2030 to meet the desired goals. Standardizing time relative to 2018, we can write this as:

K2030*=Σt=0T=12It(1d)Tt

2. If we want spending on roads to be a constant fraction of GDP between 2018 and 2030 then spending must grow at the rate as GDP. Thus, we can write spending in each year as:

It=I0(1+g)t

where I0 is the initial (in 2018) annual spending and g is the annual constant growth rate of GDP between 2018 and 2030. Thus, we can write the additional stock of roads required by 2030 as:

K2030*=Σt=0T=12I0(1g)t(1d)Tt=I0Σt=0T=12(1+g)t(1d)T(1d)tK2030*=I0(1d)TΣt=0T=12(1+g1d)t

3. The summation term is a geometric series, so the whole expression becomes:

K2030*=I0(1d)T1aT+11a

where a = (1 + g)/(l – d). From this we can solve for the initial spending, as all other terms are known:

I0=K2030*(1d)121a131a

4. Finally, we scale I0 to GDP in 2018 to get the spending in terms of percent of GDP. This ratio remains constant between 2018 and 2030 and generates the additional stock required by 2030 to meet the desired goals.

1

This technical mission was financed by the European Union under the EU-IMF Public Financial Management Partnership Program (PFM-PP).

2

Nigeria has defined a path for implementing the 2030 Agenda (2015), made progress in developing baseline and tracking statistics (2016), and implemented a national review of SDG implementation progress. A recent scenario analysis which illustrated the challenge of the SDGs. For example, even under an optimistic scenario, the SDG indices that set 100 percent for SDG achievement would remain under 60 percent for health and education.

3

The costing is done following the methodology developed by Gaspar and others. 2019. Fiscal Policy and Development: Human, Social, and Physical Investment for the SDGs. IMF Staff Discussion Note.

4

See Nigeria’s “Education for Change: A Ministerial Strategic Plan 2018–2022”, Federal Ministry of Education

5

Hasan, Rifat Afifa and others, 2019, “Nigeria’s Demographic Dividend?” 2017–2020. World Bank.

6

Filmer, D., Langthaler, M., Stehrer, R., & Vogel, T. ,2018, Learning to Realize Education’s Promise, World Development Report, World Bank.

7

African Development Bank, 2020, African Economic Outlook 2020.

8

Nigeria Human Capital Index Country Brief, World Bank.

9

Bold, T., and others, ,2019, The Lost Human Capital: Teacher Knowledge and Student Achievement in Africa; Bold, Tessa, and others, 2017, What do teachers know and do? Does it matter? World Bank, 2017.

10

We assume full enrollment in 2030 for at least two years of preprimary and tertiary education and 12 years of primary and secondary education. I.e., the target enrollment rates are 50 percent for preprimary and tertiary, and 100 percent for primary and secondary. Overall, the targeted enrollment rate is 80 percent (16 years/20 years).

11

UNICEF, 2007, “A human rights-based approach to education for all: A framework for the realization of children’s right to education and rights within education”.

12

Favara, M., Appasamy, I., and Garcia, M., 2015, Nigeria: Skills for Competitiveness and Employability. World Bank.

13

Klasen, S. (2002). Low schooling for girls, slower growth for all? Cross-country evidence on the effect of gender inequality in education on economic development. The World Bank Economic Review, 16(3), pp. 345–73

14

UNICEF Education Program in Nigeria.

15

Onwuameze, N. C. (2013). Educational opportunity and inequality in Nigeria: assessing social background, gender and regional effects

16

Adebayo, F. A. (2009). Parents’ preference for private secondary schools in Nigeria. International Journal of Educational Sciences, 1(1), pp. 1–6.

17

World Bank Group, 2015, “Nigeria Partnership for Education Project”. World Bank.

18

Tandon, A., Murray, C. J., Lauer, J. A., & Evans, D. B., 2000, “Measuring overall health system performance for 191 countries.” World Health Organization.

19

The SDG3 index comprises 14 variables: maternal, neonatal, and under-5 mortality rates; incidence of tuberculosis; new HIV infections; death rates from: selected noncommunicable diseases, air pollution, and traffic accidents; life expectancy; adolescent fertility rate; professionally attended births; vaccination rates; and the Tracer index; and a subjective wellbeing measure. See Sachs, J., Schmidt-Traub, G., Kroll, C., Lafortune, G., Fuller, G. (2019). Sustainable Development Report 2019.

20

Since 2005, 18,949 doctors (43 percent of the doctors in 2018) have applied for a verification of standing letter (i.e., a proxy of migration).

21

National Population Commission and ICF. 2019. Nigeria Demographic and Health Survey 2018.

22

Pan American Health Organization and World Health Organization. 2017. Health Financing in the Americas.

23

World Bank and World Health Organization, 2019. Global Monitoring Report on Financial Protection in Health.

24

World Health Organization. (2018). A vision for primary health care in the 21st century: towards universal health coverage and the Sustainable Development Goals (No. WHO/HIS/SDS/2018.15). World Health Organization.

25

In the Second National Strategic Health Development Plan (NSHDP II), one of the pillars is setting up actions to expand coverage and reduce financial barriers through social health insurance and improving government funding to the health sector.

26

World Bank, 2018, Nigeria Health Financing System Assessment; World Bank, 2020, Advancing Social Protection in a Dynamic Nigeria.

27

Hafez, R. (2018). Nigeria Health Financing System Assessment. World Bank.

28

Data provided by the Nigeria’s Federal Ministry of Power.

29

Sustainable Development Goal No. 7 (SDG7)-Electricity Progress and Priorities in Nigeria, presented by Engr. Faruk Yusuf Yabo, Ag. Director – Renewable Energy & Rural Power Access (RRD), on 31st January 2020 at the meeting with IMF team.

30

See “The Rural Electrification Agency’s Impact Report,” available at https://rea.gov.ng/rural-electrification-agencys-impact-report/.

31

Data provided by the Nigeria’s Transmission Services Department: “Outcomes and Performance Metrics for the year 2019.”

32

Individuals consider off-grid electricity provision as inadequate and seem to favor on-grid provision (Leo, Ben, Jared Kalow, and Todd Moss, 2018, “What Can We Learn about Energy Access and Demand from Mobile-Phone Surveys? Nine Findings from Twelve African Countries,” Centre for Global Development).

33

The electricity consumption per capita in 2019 of 348kWh was estimated as follows: actual 151.9kWh on-grid consumption + 10 percent unmet demand divided by 48 percent on-grid capacity (i.e., 151.9kWh x 1.1 / 0.48 = 348kWh). This reflects what on-grid demand would have been should the systems have properly worked.

34

See Appendix III for the details on the calculation of investment costs in generation, transmission, and distribution of electric power per kW.

39

GSM Association. (2011). Community Power from Mobile-Charging Services. GSM Association. Accessible at: https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2012/07/charging_services.pdf.

40

Melorose, J., Perroy, R., and Careas, S. (2015). An Infrastructure Action Plan for Nigeria: Closing the Infrastructure Gap and Accelerating Economic Transformation. African Development Bank Group.

42

World Bank (2019). “Nigeria Transport Issue Paper #5: Federal Roads.”

43

World Bank (2019). “Nigeria Transport Issue Paper #3: Rural Access.”

44

World Bank. 2017. A Wake-Up Call: Nigeria Water Supply, Sanitation, and Hygiene Poverty Diagnostic. WASH Poverty Diagnostic. World Bank, Washington, DC.

45

Joseph-Raji, Gloria and others, 2019. Nigeria Biannual Economic Update: Water Supply, Sanitation and Hygiene – A Wake-up Call. World Bank.

46

See “Making Nigeria Open-Defecation Free by 2025—A National Road Map” (2016). Federal Ministry of Water Resources, in collaboration with the European Union, Kuai, and UNICEF.

48

Hutton and Varughese, 2016, The costs of meeting the 2030 sustainable development goal targets on drinking water sanitation, and hygiene. Water and Sanitation Program technical paper.

49

See also Hutton, G., & Varughese, M. (2016). The Costs of Meeting the 2030 Sustainable Development Goal Targets on Drinking Water. Sanitation, and Hygiene. World Bank.

50

Water and Sanitation Program, 2012. Economic Impacts of Poor Sanitation in Africa.

51

Akpabio, E. M., 2012, Water supply and sanitation services sector in Nigeria: the policy trend and practice constraints (No. 96). ZEF Working Paper Series.

1

See “Sustainable Energy for All Action Agenda (SE4ALL-AA)” (2016). National Council on Power, Federal Ministry of Power, Abuja, Nigeria.

3

Fay, M., and Yepes, T. (2003). Investing in Infrastructure: What is Needed from 2000 to 2010? The World Bank.

4

See Iommi, A., Ahmed, F., Anderson, E. C., Diehl, A. S., Maiyo, L., Peralta-Quirós, T., and Rao, K. S. (2016). New rural access index: main determinants and correlation to poverty. The World Bank.

5

Hutton, G., and Varughese, M., 2016, “The Costs of Meeting the 2030 Sustainable Development Goal Targets on Drinking Water, Sanitation, and Hygiene.” Water and Sanitation Program Technical Paper, World Bank.

6

Formula developed by Fernanda Brollo from the IMF’s Fiscal Affairs Department.