nigeria agenda 2050: draft final report on …

8/21/2020

NIGERIA AGENDA 2050: DRAFT FINAL REPORT ON DEVELOPMENT OF A MACROECONOMIC FRAMEWORK USING A SYSTEM DYNAMICS MODEL INSPIRED BY THE iSDG MODEL

REPORT OF iSDG TEAM OF THE MODELLING GROUP

NSF DEVELOPMENTS LTD DEVELOPMENT PLANNING, MANAGEMENT AND TRAINING CONSULTANTS

21 August 2020

Contributors: 1. Barth T. Feese – Team Lead/Lead Consultant 2. Prof. Jean-Paul Cleron – Chief Modeller/Analyst 3. Dr. Charles Nche – Modeller/Analyst

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EXECUTIVE SUMMARY

Nigeria is leading the way in Africa’s return to the era of development planning. This is evident

in both previous efforts since 2000 and present strides towards having successor plans for the

Economic Recovery and Growth Plan (ERGP) 2017-2020, and the Nigeria Vison 20:2020,

both of which come to an end in 2020. To this end the country has decided to use the Input-

Output model and the econometric model in developing a macroeconomic framework to guide

the preparation of the Medium Term National Development Plan (MTNDP), 2021-2025; while

the Computable General Equilibrium model and the System Dynamics based model inspired

by the integrated Sustainable Development Goals (iSDG) model are being used for a

perspective plan – the Agenda 2050, Nigeria’s 30-year Long Term National Development Pan

(LTNDP). This report highlights the background, approach, methodology and tools used in

developing the macroeconomic framework for the Agenda 2050. It examines the modelling

steps undertaken, the model structures that determine the long-term behaviour of the complex

system, which is Nigeria, and the interactions of different parts within the system. Finally, the

report presents an analysis of the preliminary results of simulations for two scenarios – i)

continuation of the present situation (base scenario) and ii) projections of a better future for

Nigeria (best scenario) over the next 30 years; and the assumptions underlying the simulations.

It must be emphasized that the purpose of long-term models cannot be to generate accurate

predictions. The uncertainties are far too many and the range of possibilities much too wide.

Rather, long-term models are useful to indicate trends or directions of change, shapes being

more important than the actual data which constitute them. To invent a better future for Nigeria,

eight assumptions were changed from the base case, one at a time, to simulate the best-case

scenario. These include: i) propensity to save increases over time, ii) government consumption

(the cost of governance) as a proportion of revenue falls over time, iii) government investment

(capital expenditure) as a proportion of revenue increases over time, iv) a higher initial, then

growing share of public domestic debt, v) interest rate on domestic debt falls, vi) subsidies on

petroleum products and electricity are completely removed by 2026, vii), productive capital is

better managed and better maintained, viii) net oil price and exports improve. Below is a

summary of the eight assumptions underlying the base case and best-case scenarios:

Assumption 2021 2026 2031 2036 2041 2046 2051

Propensity to save Base 14.0% 14.0% 14.0% 14.0% 14.0% 14.0% 14.0%

Dmnl 1st intermediate

simulation.

Propensity to save assumed to

increase over time Best

14.0% 14.5% 15.0% 16.0% 18.0% 21.0% 25.0%

1.Government

propensity to consume

Base 70.0% 68.0% 65.0% 60.0% 55.0% 49.0% 40.0%

Dmnl 2nd intermediate

simulation.

Government consumption falls

overtime Best

70.0% 68.0% 63.0% 56.0% 44.0% 33.0% 25.0%

2.Government

propensity to invest

Base 30.0% 30.0% 30.0% 30.0% 30.0% 30.0% 30.0%

Dmnl 3rd intermediate

simulation.

Government investment

increases over time

Best 30.0% 31.0% 34.0% 38.0% 44.0% 53.0% 63.0%

3.Share of domestic debt

Base 50.0% 50.0% 50.0% 50.0% 50.0% 50.0% 50.0%

Dmnl 4th intermediate

simulation. Higher share of domestic

debt Best 65.0% 66.0% 68.0% 71.0% 74.0% 80.0% 85.0%

4.Interest rate on domestic debt Base

7.8% 7.8% 7.8% 7.8% 7.8% 7.8% 7.8% 1/year 5th intermediate

simulation. Lower

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Best 7.8% 7.5% 7.2% 6.8% 6.4% 5.2% 3.0%

interest rate on domestic debt

5.Average US$

subsidy per litre

Base 0.0526 0.0480 0.0440 0.0380 0.0290 0.0170 0.0000

US$/l

6th intermediate simulation. No more subsidies

after 2025

Best 0.0526 0.000 0.000 0.000 0.000 0.000 0.000

Average US$ subsidy per kWh

Base 0.0395 0.0360 0.0335 0.0290 0.0240 0.0140 0.0000

US$/kWh

Best 0.0395 0.000 0.000 0.000 0.000 0.000 0.000

6.Average capital lifetime Base

25 Year 7th intermediate

simulation. Capital better managed,

last longer Best 30

7.Net oil price Base 15 20 25 25 22 18 15

US$/bbl 8th and last

simulation: best case. Changing

hydrocarbon market conditions

Best 5 35 35 35 30 25 20

8.Net oil export Base 400 700 700 700 650 550 450 Mbbl/year Best 400 700 700 600 500 450 450

One of the most important findings from the results of the simulations indicate that Nigeria

will be placed on the path of sustained economic growth, if a consistent and deliberate long-

term (30-year) implementation of policy intervention packages is done as outlined in the best-

case scenario shown above. From the graph below, economic growth approaches 7% by 2050.

ECONOMIC GROWTH (%)

Fractional change in productive capital

.07

.0525

.035

.0175

0

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

1/Y

ear

Fractional change in productive capital : AGENDA 2050 BASE

Fractional change in productive capital : AGENDA 2050 BEST

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The point of departure (2020) is a rate of economic growth of 1.78% and 2.31% respectively

for the base and best-case scenarios. And while it rises to just below 7% by 2050 in the best

case, economic growth remains flat at 1.78% by the plan end date in the base case as shown in

the Figure above. The Figure also shows that in the first 10 years of the simulation period,

between 2020 and 2030, the base case scenario only records marginal economic growth

improvements. Then economic growth falls. At the end of the period, growth is lower than it

was at the start. This is the result of an insufficient investment program over the period

considered. It also indicates that economic growth is the result of a long cumulative process

which rests upon recurrent streams of investments and the resulting build-up of productive

capital over a substantial period of time. The table below shows these two scenario results.

Economic Growth

Base Case Scenario Best Case Scenario

2025 1.92% 2025 3.04%

2030 1.97% 2030 3.23%

2035 1.94% 2035 3.55%

2040 1.85% 2040 4.21%

2045 1.77% 2045 5.31%

2050 1.74% 2050 6.75%

This process cannot be successful without persistence and the determination to build on what

already exists rather than starting afresh at each change of government. The report notes that

Nigeria requires the strict coordination of several medium-term plans and several legislatures

to achieve economic success.

Areas of further model development were suggested. Significant model improvement would

result if the following developments were implemented: production disaggregation using

dynamic input-output modelling; modelling of education, energy, the environment and the

informal economy; endogenous determination of the Interest rate. In addition, there always

remains the possibility of modelling in more depth some selected areas as may be required.

Furthermore, some of the lessons learnt in previous planning efforts identified by the Policy

Analysis Group (PAG) and some key binding constraints to growth as pointed out by the

Growth Diagnostics Group (GDG), can be implemented in the model. These include: i) perhaps

the most important one, which is integrating the informal sector into the economy, mentioned

earlier – if implemented well, this will facilitate direly needed revenue-driven fiscal

consolidation; and ii) weak implementation costing/funding of national plans - integrating the

excel-based costing tools into the SD model will ensure rigorous costing of projects and

programmes as well as preparation of sectoral investment plans. A requirement that only well

prepared/costed projects should be admitted into the annual budget will help bridge the budget-

plan gap; iii) Poor sub-national coordination – sub-national disaggregation of the SD model

will enhance coordination at the sub-national level and enable sub-national plans to be aligned

to national strategic plans and priorities. Finally, it must be noted, however, that a two-sector

Input-Output (I/O) model was presented in this report as an example of the SD tools’ prowess,

with prospects for further expansion to n-sectors of the I/O model.

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Table of Contents

EXECUTIVE SUMMARY ...................................................................................................... 1

CHAPTER 1: INTRODUCTION & BACKGROUND ................................................................... 6

a. Draft Final Report ..................................................................................................... 6

CHAPTER 2: REVIEW OF MACROECONOMIC DEVELOPMENTS IN NIGERIA........................... 7

a. Brief Overview of previous planning efforts ................................................................................................. 7

ii. Lessons learned from planning efforts of the last 20 years: ................................................................... 9

iii. Government Priorities, Global Megatrends and Growth Diagnostics .......................................................... 10

iv. Policy Implications: ....................................................................................................................................... 10

v. Policy recommendations on the basis of the GD analysis include the following: ........................................ 11

vi. Integration of key concepts and inputs from the Policy Analysis and the Growth Diagnostic Groups into the SD-based Model for Agenda 2050 Macro Framework: ................................................................................... 11

b. Macroeconomic developments in the last 20 years ................................................................................... 12

CHAPTER 3: APPROACH AND METHODOLOGY ................................................................. 14

a. Overview of approach, methods and tools: ................................................................................................ 14

b. Steps of System Dynamics Modelling. ........................................................................................................ 15

CHAPTER 4: SYSTEM DYNAMICS MODEL .......................................................................... 18

a. Key Concepts and Model Structures............................................................................................................ 18

b. The key feedback loops of the Nigerian socio-economy ............................................ 18

c. Model sketch, constants and parameters ................................................................. 25

d. Assumptions, Scenarios and Simulations .................................................................. 33

CHAPER 5: ANALYSIS OF PRELIMINARY RESULTS .............................................................. 34

Figure 25. Scenario comparison. Debt to GDP ratio.......................................................... 35

Figure 26. Population and national income ..................................................................... 36

Figure 27. Unemployment ............................................................................................... 37

Figure 28. National income per head ............................................................................... 38

Figure 29. Productive capital ........................................................................................... 39

Figure 30. Economic growth ............................................................................................ 40

Figure 32. Best scenario: economic growth...................................................................... 41

Figure 33. Government revenues & expenditures ............................................................ 41

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Figure 34. Government surplus / deficit ........................................................................... 42

Figure 35. Government debts .......................................................................................... 43

Figure 36. Debt servicing................................................................................................. 44

Figure 37. International trade ......................................................................................... 45

Figure 38. Forex reserves ................................................................................................ 46

Figure 39. The naira exchange rate ................................................................................. 47

Figure 40. Extract from the data entry worksheet. Relationship forex stock – exchange rate ...................................................................................................................................... 48

Figure 41. The exchange rate multiplier .......................................................................... 49

CHAPTER 6: FURTHER MODEL DEVELOPMENT - DYNAMIC INPUT-OUTPUT MODEL .......... 49

Figure 42. System dynamics sketch of the orders – inventory causal connection ............... 50

Figure 43. Stock and production adjustment ................................................................... 50

Figure 44. Labour force dynamics .................................................................................... 51

Figure 45. Material input procurement ........................................................................... 51

Figure 46. Complete causal structure of a single sector .................................................... 52

APPENDIX 1: MODEL EQUATIONS ................................................................................... 52

APPENDIX 2: SOME BIBLIOGRAPHICAL REFERENCES ........................................................ 61

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CHAPTER 1: INTRODUCTION & BACKGROUND a. Draft Final Report: This Draft Final Report is submitted by NSF Developments Ltd,

a development management, planning and training consultancy, based in Abuja, in respect

to the consultancy assignment by the Federal Ministry of Finance, Budget and National

Planning (FMFBNP) - to prepare a macroeconomic framework for Nigeria Agenda 2050

using the Computable General Equilibrium (CGE) model and the System Dynamics-based

Model referenced to the integrated Sustainable Development Goals (iSDG) model.

b. Background: Nigeria is in the process of developing successor plans to the Economic

Recovery and Growth Plan (ERGP, 2017-2020) and the Nigeria Vision 20: 2020, both of

which are ending by December 2020. Consequently, the Government of Nigeria has taken

steps to ensure the preparation of a Medium-Term National Development Plan (2021-

2025), or MTNDP to replace the ERGP (2017-2020) and a Long-Term National

Development Plan (LTNDP), the Nigeria Agenda 2050 Perspective Plan to take the place

of the Nigeria Vision 20:2020, using globally acceptable economic development and

planning models.

c. Planning Models: In order to accomplish this task, a number of models have been

identified for use by the supervising authority, the FMFBNP, for use in developing the

macroeconomic framework for the preparation of the two plans. Thus, for the MTNDP the

macro econometric model is to be used, together with the input-output model; while for the

LTNDP the Computable General Equilibrium (CGE) model is to be used in conjunction

with the system dynamics-based model derived with reference to the integrated Sustainable

Development Goals (iSDG) model. Modelling consultants were therefore engaged to

design, implement and train users of the four models in the Ministry, according to the Terms

of Reference.

d. Terms of Reference: The overall objective of the consultancy services is to develop a

dynamic CGE model and a system dynamics-based model of the Nigerian economy for use

by the FMFBNP in policy impact analysis. The output of the models would be used for the

preparation of the Macroeconomic Framework for the Perspective Plan called “Nigeria

Agenda 2050”. The two models are expected to be complementary in terms of operation

and consistency in the use of economic variables; while the output of one model may be

used as an input for the other model, the results of one may also be used to validate the

result of the other. Specific terms of reference include:

i. Review the existing DCGE/CGE models and iSDG model, with a view to presenting

options and solutions to problems in the Nigerian economy;

ii. Develop a theoretical and methodological framework for the DCGE and iSDG models

in Nigeria;

iii. Prepare a possible set of indicators for the models and determine their frequency,

accessibility and sources; and gather data on relevant indicators in excel format;

iv. Update a DCGE Model/SAM for Nigeria and iSDG Model that can be calibrated to

analyse the impact of changes in policy variables and/or economic shocks using

appropriate statistical software;

v. Provide in excel format the output of the model including draft forecasts and

assessment model simulation results

vi. Generate user manuals that contains the theoretical framework of the DCGE and iSDG

models, containing the equations, variables used to include their sources, and the

procedure for conducting simulations or sensitivity analysis, updating the parameter,

and error diagnostics, etc. and;

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vii. Conduct consultative workshop among the technical staff of FMFBNP, CBN, DMO,

BOF, SEC, NNPC, DPR, NCS, OAGF, FIRS, NBS, NISER, NASS, PEAC and key

sectors to solicit comments suggestions to enhance the initial DCGE and iSDG models;

viii. Enhance capacity of FMFBNP technical staff in updating the DCGE and iSDG Models

for Nigeria and conducting policy analysis using the model through hands-on trainings

and exercises and ensure technological transfer in updating, re-estimating and

calibrating the model.

CHAPTER 2: REVIEW OF MACROECONOMIC DEVELOPMENTS IN NIGERIA a. Brief Overview of previous planning efforts

i. Historical Evolution

The historical evolution of previous planning efforts in Nigeria in the post-colonial era can

be categorized into three phases as described below:

a) The development planning phase (1962-1985). There were four National Development

Plans launched between 1962 and 1985. These were the plans for 1962-1968, 1970-1974,

1975-1980 and 1981-1985. Government intervention was dominant, coordination among

regions was lacking, with modest growth and macroeconomic imbalances.

b) The Structural Adjustment Programme (SAP) and policy-oriented planning era (1985-

1999). This phase was characterized by SAP (1985-1989) and 3-year Rolling Plans, 1990-

1992, 1993-1995, 1996-1999. With an International Financial Institutions led development

agenda, promoting private sector participation through deregulation, liberalization and

privatization, and macroeconomic stabilization leading to macro-economic imbalances and

mixed outcomes;

c) The high growth and development phase (2000-present): The return to development

planning witnessed ambitious home-grown initiatives, with high economic growth rates

but no job or social development gains.

Below is a schematic diagram of the historical evolution of previous planning efforts in

Nigeria.

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Figure 2: Historical evolution of development planning-policy framework, institutional

configuration and outcomes – in Nigeria:

Source: Adapted from UN ECA (2016)

1.Development Planning 2.Government led interventions 3.Poor policy coordination

Development Outcomes

Macroeconomic and

Development Policy

Framework

Institutional Configuration

1.Modest economic growth rates 2. Structural change -some sectoral shifts 3. Macro imbalances developed over time

1.Little coalition between government and private agents 2.Government-dominant in command but week in capacity 3. Private agents-weak

1.Policy-oriented Planning 2.Liberalisation-deraegulation-privatisation 3. Macroeconomic stability

1.Lower or negative per capital growth 2. Productivity-reducing structural change 3. Macro imbalances developed over time

1.Aid donors dominated 2. Little coalition between government and private agents 3.Government-weak and dwindling resources 3.Private agents-disfranchised and fragmented

1.Home grown development

initiatives 2.Return to development planning 3.Ambitious goals

1.High economic growth rates 2.Growth didn’t trigger structural transformation despite stronger planning 3.Social development gains were achieved but not at a scale

1.Renewed faith in development planning, better policy formulation/implementation and better fiscal/monetary management

Development Planning phase,

1962-1985

Structural Adjustment

Programme, Policy oriented planning

1985-1999

High Growth & Development Phase,

2000-Present

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ii. Lessons learned from planning efforts of the last 20 years: A few of the Plans reviewed by the Policy Analysis Group (PAG) over the last 20 years include:

• The National Economic Empowerment and Development Strategy (NEEDS), which built

on the Interim Poverty Reduction Strategy Paper (IPRSP) between 2001 and 2003, and

incorporated the State Economic Empowerment and Development Strategies (SEEDS) and

Local Economic Empowerment and Development Strategies (LEEDS)

• Nigeria Vision 20:2020 (NV 20:2020) and the 1st medium-term national implementation

plans (NIPs)

• The Transformation Agenda (2011 – 2015)

• The Economic Recovery and Growth Plan (ERGP, 2017-2020)

Upon analyzing these various strategic documents that have guided Nigeria’s national

development policy over the past 20 years and even before, the group has deducted and

recommended that the country should avoid potential pitfalls both in the planning phase and

the implementation stage that have characterized national planning in the past. Table 1 below

exhibits some of the lessons learned from implementation of previous National Development

Plans in Nigeria.

Table 1: Lessons learned from previous National Development Plans

Weak link between

the plan and annual

budget

Key components of development plans are skipped or provided with less fund during

the preparation of the government annual budget.

Less emphasis on

inter-sectors

collaboration

There is little focus on building inter sectoral synergies for economic development.

Heavy reliance on

foreign funding

Relying on foreign funding is a major throwback for the implementation of several

plans. Most plans were also silent on implementation cost/funding.

Absence of

coordinating

institution(s) for

plan

implementation

This resulted in limited implementation capacities as well as issues of continuity and

coordination of programmes.

Less on addressing

key domestic

growth constraints

Several of the development plans skipped addressing key domestic growth and

productivity constraints. As a result, these issues became huge impediments to the

attainment of set targets.

Impact of oil prices Fluctuations in oil prices can have negative impact on Nigeria’s foreign exchange and

government revenue earnings culminating in severe macroeconomic shocks and

instability

Effect of political

changes

Plan implementation often affected by political and policy changes

Public vs private

investment

Public investment was promoted at the expense of private investment

Internal and

external pressures

Government often failed to keep scheduling and targets because of internal and external

pressures

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iii. Government Priorities, Global Megatrends and Growth Diagnostics The simulations of the SD model are informed by findings of other sub-groups that

analyzed and reviewed previous plans, government priorities, megatrends in the global

economy and growth diagnostics. Presidential Priorities consist of the following objectives:

Stabilization of the economy

Achieving Agricultural and Food Security

Ensuring Energy Sufficiency in Power and Petroleum Products

Improving Transportation and Other Infrastructures

Driving Industrialization

Improving Health, Education, and Productivity of Nigerians

Enhancing Social Security and Reducing Poverty

Fighting Corruption and Improving Governance, and

Improving Security for all Citizens.

A few of the mega trends that will be expected to affect the planning process in Nigeria

include:

Economic Globalization: e.g., gradual shift in the global economic power relations

from the current industrialized countries to the rising and emerging markets;

increasingly connected global economy and economic integration…

Technology and the Digital Revolution: e.g., Artificial intelligence; 4th Industrial

Revolution (Industry 4.0); Internet of Things…

Demographics and Mobility: e.g., Hyper-urbanization; Rise of the middle class in

Asia and Africa; Demographic dividend…

Energy and Environment: e.g., Resource Constraints, Climate Change; Changing

Energy Mix…

Innovation Acceleration: e.g., Knowledge and Information Society…

Health and Wellness: Involving consumption; Demand for better health care

Global Security Risks: e.g., Pandemics; Natural Catastrophe; Cyber Attacks;

Terrorism…

iv. Policy Implications: The policy recommendations of the Policy analysis Group and Growth Diagnostics Group

are as follow:

• In budgetary provisions, the proportion of capital expenditure should be increased,

and implementation of capital budgets should be scaled up.

• The cost of governance should be reduced by at least 30%.

• Emphasizing movement away from dependence on crude oil

• Closing the fiscal gap to about 3% of GDP

• Stimulating the economy and business development

• Increasing post COVID-19 investment to 9% of GDP

• Diversifying the product space – whether agricultural or non-agricultural products,

particularly products that could earn foreign exchange for the country other than the

oil sector

• Adopt transformative trade policies

• Prioritize self-reliance and home-grown solutions, including import-substitution

• Reduce post-harvest losses in agriculture to stabilize prices

• Measures to diversify revenue and increase tax to GDP ratio by improving tax

administration, including the informal sector and widening the tax base.

• Enhance non-oil forex earnings by attracting FDI, improving diaspora remittances

and promoting non-oil exports.

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• Prioritization and implementation of critical and strategic infrastructure projects

that will directly boost production and productivity in the SME, agriculture,

manufacturing and service sectors, in line with rapid growth, revenue and forex

diversification objectives.

v. Policy recommendations on the basis of the GD analysis include the following: Minimize macroeconomic volatility by strengthening domestic financial

institutions

Improve access to finance and credit to the private sector by removing existing

regulatory impediments

Strengthen legal and judicial reforms commensurate with economic reforms so as

to establish a stable policy environment in order to boost private investments

Ensure sufficient energy provision, particularly electricity, to enhance private

production

Focus policy on microfinance banking activities, which remain too minimal in

Nigeria and at times even financed by foreign firms, including improving access to

funding and intermediation.

vi. Integration of key concepts and inputs from the Policy Analysis and the Growth Diagnostic Groups into the SD-based Model for Agenda 2050 Macro Framework:

The SD-based Model for Agenda 2050 has the capability to incorporate many of the

lessons learnt from previous planning efforts and the recommendations of the other

Groups – PAG and GDG, a few examples of which include the following, some of which

have already been implemented in the model:

• Relaxing some of the growth constraints identified by the GDG – Feedback loops

in the SD model identify the leverage points where policy action can bring about

the desired development outcomes and impacts.

• Addressing the weak budget-plan link and poor implementation costing/funding of

projects and programmes – the SD model can incorporate the excel-based costing

tools to enable policy analysts in the MFBNP and line Ministries prepare investment

plans and detailed costing of interventions that can be used in programming

expenditures in the budget.

• To address diversification of revenue sources, increase the tax/GDP ratio, integrate

the informal sector and widen the tax base using the SD-based modelling approach.

• Strengthening the Sub-national coordination function of the MFBNP – By carrying

out the sub-national disaggregation of the analysis at the national level using the SD

Model the MFBNP will have a strong tool to deploy in the coordination of planning

at the sub-national level.

• The recommendation that government consumption (recurrent costs in the budget)

should be reduced by 30% while government investment (capital expenditure in the

budget) be increased has already been implemented in the SD Model for Agenda

2050.

• To facilitate the seamless integration of some of the many planning models/tools

and ensure complementarity for medium- and long-term planning, we have done an

SD version of a simple input/output model for demonstration to the Ministry. This

basic SD version of the I/O Model can be developed further if required.

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b. Macroeconomic developments in the last 20 years In May 1999, after nearly two decades of military dictatorship, Nigeria ushered in a new

administration. The new government’s target was to accelerate economic growth to alleviate

Nigeria’s widespread poverty. In year 2000, the proportion of Nigerians living below the

poverty line of one dollar a day was 56 per cent. This proportion had increased dramatically

during the preceding two decades.

But growing poverty is not the only challenge Nigeria has been facing in the last 20 years. A

fast-growing population, mounting unemployment, particularly youth unemployment,

persistent corruption, a continued heavy reliance on hydrocarbons and the heavy cost of

governance are serious additional difficulties.

Viewed as a global socio-economy, Nigeria was not making significant progress. In 2000,

both per capita income and per capita private consumption were lower than in the early 1970s.

The first decade of the 21st century confirmed the strong influence of oil price variations on

Nigeria’s growth performance. Between 2000 and 2014, Nigeria’s GDP grew at an average

rate of 7% per year. An annual rate of 7.3% was even reached in 2011/12. But growth did

not translate into a strong diversified economy. Oil, gas, and agricultural output continued to

dominate wealth generation, contributing around 70% of total output. Oil alone accounted

for more than a third of GDP. Oil had risen from 58% of exports in 1970 to more than 90%

in the 2000s. It is during this period that Nigeria discovered a new economic evil: non-

inclusive growth.

In 2010, extreme poverty, the share of population living on less than $1.25 a day, not only

persisted but significantly increased to about 68% of the population in 2010. More recently,

the instability in the North and the resulting displacement of people have contributed to the

high incidence of poverty in the North East.

Following the oil price collapse in 2014-2016, combined with negative production shocks,

Nigeria’s GDP growth dropped to 2.7% in 2015. In 2016 during its first recession in 25 years,

the economy contracted by 1.6%. Domestic demand remained constrained by stagnating

private consumption in the context of high inflation: 11% in the first half of 2019. On the

production side, growth in 2019 was primarily driven by services, particularly telecoms.

Agricultural growth remained below potential due to continued insurgency in the Northeast

and ongoing farmer-herdsmen conflicts. Industrial performance was mixed. Oil GDP growth

was stable, while manufacturing production slowed down in 2019 due to a weaker power

sector performance. Food and beverages output increased in response to import restrictions.

Construction continued to perform positively, supported by ongoing megaprojects, higher

public investment and import restrictions.

The Nigerian economy does not grow fast enough, and the Nigerian population grows too

fast to lift the bottom half of the population out of poverty. Prospects for the rural poor are

grim due to the weakness of the agriculture sector, and the livelihoods of the urban poor are

adversely affected by high food prices.

Employment is another major concern. Formal employment is low while Nigeria’s informal

sector accounts for between 65% and 70% of total employment. Rising unemployment has

become a permanent feature of the Nigerian economy: 4% in 1986, 13% in 2007 and 23-25%

in 2018 with another 20% of the labour force underemployed. Youth unemployment is an

even bigger challenge estimated at 38-40% in the last years of the 2010s. Nigeria’s

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employment problem is a simple arithmetic operation: employment creation remains

insufficient to absorb a much faster growing labour force.

Today, Nigeria’s external reserves stand at US$37 billion. External reserves rose from $4

billion in 1999 to $46 billion in 2010 after paying $12 billion in 2005 to liquidate the external

debt. The highest level of foreign reserves was observed in 2007/8 with a stock reaching

US$52/54 billion. Worth noting, it is also in the period 2006/8 that the naira exchange rate

appreciated. An empirical observation which gives some validity to our model structure. The

naira exchange rate passed the 100 mark for the first time in 2000 with ₦102 per US$. It then

increased to ₦306 per US$ in 2018. Today, the official rate is ₦380 for an American dollar

but the parallel market trades US dollar at ₦470.

Nigeria’s overall global competitiveness remains weak. This is due to the quantity and quality

of health, primary education and infrastructure.

One of Nigeria’s core strategies is a public-private partnership in investments, especially in

such core infrastructure projects as power, railways, roads and ports to generate employment

opportunities. But the private sector in general remains relatively weak. A large part of it is

the oil economy which has been unable to create linkages to the rest of the economy to

significantly contribute to structural change and transformation.

Nigeria is faced with problems both in implementation and in choice. It is not the right

approach to try and fix all problems simultaneously. It spreads thin resources too thin and

does not achieve much. One of the first lessons that economics students learn is that an

economy is a highly connected dynamic system. As a result of economic linkages, fixing one

important problem may result in fixing a number of others. It may also result in creating new

challenges.

Even with significant structural policy reforms, and considering climate change, the likely

fate of the international oil market and the likely appearance of Covid-type new challenges,

it will take a long time for Nigeria’s economic growth to go back to the performance of ten

years ago. For some time, the economy might even grow more slowly than the population,

leading to worsening living standards. Among the many factors that constrain economic

growth, rising public debt, inflation, multiple exchange rate windows and subsidies play a

role. But perhaps the most important is the lack of revenue-driven fiscal consolidation.

Nigeria is faced with the huge task of institutionalizing a large informal economy which

operates on a day to day basis outside of any formal financial and economic structures.

Another major challenge is to support the sustained growth of the non-oil economy. Reforms

in this direction would help raise living standards of low-income groups, reduce the size of

the informal economy and create job opportunities. It is indeed the lack of job opportunities

which is at the core of the high poverty levels, of regional inequality, and of social and

political unrest in the country.

14

CHAPTER 3: APPROACH AND METHODOLOGY a. Overview of approach, methods and tools: System dynamics is one of the

approaches selected to develop a macro framework for Nigeria Agenda 2050. System

Dynamics is the brainchild of late Professor Jay W. Forrester of the Massachusetts

Institute of Technology (MIT). System Dynamics is neither a theory nor a solution. It

is a method, that is, a vision of how the world works and it is a tool, that is, a means to

an end.

System dynamics rests on four foundations:

• The theory of information feedback systems;

• A knowledge of decision‐making processes;

• The experimental model approach to complex systems;

• The digital computer as a means to simulate realistic mathematical models.

The purpose of system dynamics practitioners is to build models capable of deriving

dynamic behaviours solely from variables and interactions belonging to and within the

system. The dynamics of systems does not depend upon any exogenous forces but is

endogenously generated by their structure.

System dynamics models are built on four pillars:

• Stocks & flows

• Feedback loops

• Non-linearity

• Time & delays

i. Stocks and flows are key system dynamics variables. Stocks are accumulators. Flows

feed and/or drain stocks. Examples of stocks and flows abound. Population is a stock

fed by births and drained by deaths; your bank account is a stock fed by your deposits

and drained by your withdrawals; a trader’s inventory is a stock fed by goods

produced and drained by goods shipped; your reputation is a stock fed by all the good

things you do and drained by all the bad things you accomplish; a price is a stock fed

by inflation and drained by deflation.

ii. Feedback loops are closed chains of multiple, causal interconnections linking stocks

and flows. They also often include time delays and non-linear interactions. It is the

interplay of these loops which determines system’s behaviour. Feedback loops are

major structural elements in system dynamics models. They are of two types:

reinforcing and balancing. Reinforcing loops generate exponential growth or

exponential decline. These are popularly known as virtuous and vicious circles. If

unchecked reinforcing loops explode or collapse leading to unmanageable situations.

In contrast, balancing loops counteract system growth or system decline. They thrive

to create equilibrium, that is, system stability. One of the favourite examples cited by

system dynamics textbooks is the dynamics of population. Population is a stock

driven by two major flows: births and deaths which both depend on population size.

But births and deaths also affect population size. There exists therefore a dynamic

system driven by two feedback loops of opposing polarity. The interactions between

births and population create a reinforcing loop which feeds upon itself. The

interactions between deaths and population create a balancing loop which counteracts

the effect of births and thrives to balance the system. For economists, the virtue is in

reinforcing loops because economic growth remains the gospel of the profession. For

physicists and natural scientists, however, the virtue is in balancing loops because

15

equilibrium means system stability. This fundamental difference of perspective

explains why it is so difficult to reach a compromise between economic growth and

the preservation of nature.

iii. Non-linearity is a characteristic of many natural and made-made systems. It is a

reaction to stimulus in a manner non-proportional to the action that caused the

response. System dynamics models do incorporate non-linear relationships either as

equations or as user-defined functional tables. Examples of functional tables include

a multiplier of importation which is assumed to be influenced by the exchange rate

or the effect of the income per head on the population’s fertility. These assumed

functional relationships may be modified but the direction of the effect (direct or

inverse) should be preserved. For example, fertility is supposed to decrease and not

increase when the economy creates more wealth.

iv. Time is the most important variable in a system dynamics model. It is time together

with the stocks included in the model which generate its dynamics. This is because

the future value of each stock partly depends upon its present value:

STOCKT+TIME STEP = STOCKT + TIME STEP * (FLOW INT – FLOW OUTT)

In the above equation, T is the index of current time and TIME STEP is the Δ time

also known as DT. TIME STEP is a parameter of the integration process driving its

accuracy. It is not a parameter of the model. System dynamics models most

frequently use Euler as their integration method. Flows are calculated from values of

stocks, other flows and/or from auxiliary variables. Auxiliary variables are

components of flows. They are made explicit to clarify how complex flows are

calculated.

v. Delays: very few relationships, if any, are instantaneous. System dynamics include a

number of delay functions to take account of this reality. Delays are fixed or

exponential, material or information, and of order 1, 3 or n.

It is our conviction that system dynamics is the right perspective to address the

dynamic complexity of such large adaptive systems as states, regions or whole

countries. System dynamics is a valuable approach for high level issues such as

corporate strategy and government policy. It is and has been widely used to look at a

variety of issues such as industry structure, urban dynamics, population, public health,

engineering prototyping, risk assessment and such global concerns as economic

development and environmental protection.

b. Steps of System Dynamics Modelling. Not every system dynamics model constructed

is substantial. But when it is there should be six steps in its construction. Interestingly

enough these six steps are in a feedback loop:

• Conceptualization – group model building

• Sketch

• Identification of feedback loops

• Equations & units

• Simulations & calibration

• Back to sketch or perhaps even to conceptualization for potential model

improvement

16

i. Conceptualization. The first step in system dynamics modelling is group model

building to get the concept right and accepted by all. Models built with system

dynamics address a large variety of issues. But system dynamics modelers cannot

be experts in all the fields they model especially when multidisciplinarity is a key

model requirement. The corollary of such an approach is that such models, which

call for multidisciplinarity, are never build by one person. If they were, they would

fail. The specific skill of system dynamics modelers is to capture experts’ expertise

– to extract experts’ mental model and to transform it into a formalized and explicit

computable structure which exploits this expertise to uncover interventions and

policy decisions favorable to the system under study. Much if not all of the

knowledge and information required to build a substantial system dynamics model

reside in the mental models of those that are part of the system under study.

Participating in model construction also enhances the learning process of those to

whom the model is destined. Modelling a problem always results in considerable

learning for those participating in the modelling process. Finally, model validity

and model implementation - the trust model recipients put on the model greatly

benefit from group model building. Even the most brilliantly built model includes

debatable structures and debatable assumptions. Multidisciplinarity is therefore not

the only requirement. It is also required to reconcile different visions of the same

problem to reach consensus on how to solve a problem or to reach a goal. This is

certainly the case for a model of the very long term such as the present macro

framework model. To some extent, the approach adopted by Government in the

preparation of Nigeria Agenda 2050 resembles group model building although

there is room for perfecting it.

ii. Sketch. System dynamics model are built graphically on a workbench called view.

As an example, the equation presented in 3a under non-linearity is represented by

the following sketch:

Figure 1. Stock & flow sketch in system dynamics

Stocks are balance sheet elements with no time dimension which accumulate money,

material, people or information. The double arrows represent the movement of stuff in

and out of the stock. Causality, which is not correlation, is represented by a single arrow

starting from the cause and pointing to the effect.

STOCKFlow in Flow out

Initial stock

17

Figure 2. Sketch representation of causality in system dynamics

System dynamics therefore represents causality as X Y while the traditional

mathematical notation is Y = f(X).

Complex models do require several views. Views are connected through shadow

variables. A shadow variable is a variable the cause of which is shown on a view while

its impact appears on another.

A model is computable only if all its variables are quantified. It is also required that the

polarity of each relationship the model includes is determined with certainty: whether

a directional change in the cause creates the same directional change in the effect (direct

connection) or an opposite change (inverse connection).

iii. Identification of feedback loops

Except for very large models for which the task might be too demanding, it is always

useful to identify a model’s key feedback loops and to determine their polarity. The

operation can give useful insights on why the model produces the results it produces.

Feedback loop identification starts with the identification of the polarity of each causal

connection in the loop. If the number of direct connections in the loop is odd, the loop

is balancing; if it is even the loop is reinforcing. Feedback loop identification is also a

graphical exercise, but it differs from sketching especially with large models built on

several views. The multiplication of views makes it difficult if not impossible to

identify feedback connections.

iv. Equations & units.

The completion of a model’s sketch reveals the entire causal structure of the system

being modelled. What remains to be done is to enter the model equations, that is, to

define the rules connecting the causal elements. An important aspect of this segment of

model construction is to define the units of each model parameters (variables and

constants) and to ensure their coherence. The unit on the left of the equal sign must be

the same as the unit on the right. Ensuring unit coherence is important. Even though

Vensim allows models with unit errors to simulate. Such unit errors may hide more

fundamental structural errors. It is therefore important that modellers take time to check

the units of their models.

v. Simulations & calibration

Models will only simulate if all equations are correctly written and all required

numerical data, including time parameters, entered. But that does not guarantee success.

Complex models simulating over a long period – a large number of time units might

diverge quickly and stop simulating well before the final time is reached. What is then

required is to calibrate the model: identify assumptions which are such that small

changes made to them have a large impact on model behavior. Calibration may take

time. Yet, it is an indispensable step for the success of a modelling project.

CAUSE

EFFECT

18

A set of numerical data that leads to a successful simulation is a scenario. System

dynamics models can produce a large number of scenarios in a very short time. It is

important to change one assumption at a time and to take time to understand why the

model produces the results it produces.

vi. Back to sketch

It may happen that simulation results produce inconsistencies or impossibilities or

reveal structural deficiencies or point to missing structures in the model or that any

combination of the above is observed. It is then necessary to rethink the concept and to

go back to the design of the model. Complex models are better built on a step by step

basis so that complexity is always under control. The building of system dynamics

models is therefore a feedback loop.

CHAPTER 4: SYSTEM DYNAMICS MODEL a. Key Concepts and Model Structures

In its present state, which we do not consider as the final state, the model depicts the

interactions of two major social structures: population and the global economy. The

economy is not disaggregated, and the environment is not modelled. Those are two

critical and required additions. It would not pose any major problem to disaggregate the

economy and build the environment in the model. It might even be useful to review the

existing model structure with the purpose of improving it. For this to be done, more time,

additional expertise and the implementation of group model building are required.

b. The key feedback loops of the Nigerian socio-economy are represented

in 11 diagrams. The diagram on Figure 3 shows the four reinforcing loops which drive

population growth through fertility rate and income per head. The sketch also shows a

potential connection between the economy and the population that would be created if a

policy existed to link investment volumes to the level of unemployment. This causal link,

however, has not been built in the model as it is not the purpose of models to substitute

for decision makers.

Figure 3. Population and the economy

VERY YOUNG(0-4)

Yearly births

SCHOOLAGE (5-14)

Growing toschool age

YOUNG ADULT(15-24)

ADULT(25-64)

Maturing toyoung adult Maturing to

adult

Laboursupply to

theeconomy

Unemployment

Labour requiredby the economy

PRODUCTIVECAPITAL

Fertilityrate

Indicated impact ofincome per head on

fertility rate

Income perhead index

Populationtotal

Income perhead

GDPfc

GDPmp

Nationalincome Investment

LINKAGES POPULATION - ECONOMY

Labouravailable

R

R

R

R

B

B

19

The two loops that would be created if the model had built in a formal policy to link investment

to unemployment are both balancing. This is because an increase (decrease) in the labour force

that population supplies to the economy creates more (less) investment and a higher (lower)

GDP which tends to reduce (increase) the fertility rate.

Evidently, this relationship is not instantaneous. The reaction of the population to the stimulus

generated by changes in the income per head is assumed to occur continuously and

progressively over a period of 5 years. This is indicated by a constant called delay impacting

on fertility.

Figure 4 displays the model’s major causal connections. Although this model is relatively

simple – with the exclusion of the population segment it has only five interconnected

differential equations, it is clear that this structure already constitutes a rather complex system

which only a computer can process. Understanding it requires further clarifying. This is the

purpose of the next nine diagrams.

Figure 4. Model major causal structures

The capital accumulation loop shown on Figure 5 represents the core of the economic growth

process. Each period, a proportion of the wealth created is reinvested in the stock of capital

which increases and produces more wealth. It is clearly a reinforcing process that feeds upon

itself.

Deficitfinancingdomestic

PUBLICDOMESTIC

DEBT

Interest paid ondomestic debt

Debtservicingdomestic

Debtservicing

total

Governmentexpenditures

Governmentsurplus/deficit

Governmentdomesticrevenues

Governmenttax revenue

Governmentnon-tax revenue

GDPfc index GDPfcPRODUCTIVE

CAPITAL

InvestmentGovernmentinvestment

Privateinvestment

Savings

Disposableincome

Nationalincome

GDPmp

Deficitfinancingforeign

PUBLICFOREIGN

DEBT

Interest paid onforeign debt

Debtservicingforeign

Productivecapital index

Capitalmultiplier of

non-oil export

Non-oilexport

Export

FOREIGNRESERVES

Desiredexchange

rateRATE OF

EXCHANGE

Forex in

Exchangerateindex

Forex out

Import

Exchangerate

multiplierof import

Exchange ratemultiplier of

non-oil export

20

Figure 5. The reinforcing capital accumulation loop

Two parameters are important here: the propensity to consume and the depreciation fraction of

the capital stock. The model also includes a third parameter called investment effectiveness. It

is a simple multiplier varying between 0 and 1. Lowering the value of investment effectiveness

is equivalent to assuming an imperfect flow of domestic saving to capital which may reflect

either capital flight or corruption or both. This parameter was not activated. It was kept neutral

(with the value 1) in the model simulations presented in this report.

By nature, a reinforcing loop is unstable and tends to make systems unmanageable except if

one or several balancing loops mitigate the exploding exponential growth or decay. One of

these loops is shown on Figure 6.

Figure 6. The first balancing tax loop

The income tax loop shows the stabilizing impact of taxation on the economy. More (less) tax

reduces (increases) disposable income, saving, investment and the stock of capital and

Deficit financingdomestic

PUBLICDOMESTIC DEBT


Debt servicingdomestic

Debt servicingtotal



Governmentdomestic revenues

Government taxrevenue



CAPITAL


Privateinvestment

Savings

Disposableincome

Nationalincome

GDPmp

Deficit financingforeign

PUBLICFOREIGN DEBT


Debt servicingforeign


Capital multiplier ofnon-oil export

Non-oilexport

Export

FOREIGNRESERVES

Desiredexchange rate

RATE OFEXCHANGE

Forex in

Exchange rateindex

Forex out

Import

Exchange ratemultiplier of import

Exchange ratemultiplier of non-oil

export

R


PUBLICDOMESTIC

DEBT



Debtservicing

total







CAPITAL


Privateinvestment

Savings

Disposableincome

Nationalincome

GDPmp


PUBLICFOREIGN

DEBT





non-oil export

Non-oilexport

Export

FOREIGNRESERVES

Desiredexchange

rateRATE OF

EXCHANGE

Forex in

Exchangerateindex

Forex out

Import

Exchangerate

multiplierof import


non-oil export

B

21

dynamically results in less (more) tax revenue. While a reinforcing loop is such that an increase

(or a decrease) in any of its variables results in more increase (or decrease) in that same

variable, a balancing loop is such that an increase (or a decrease) in any of its variables results

in a decrease (or an increase) in that same variable. Applying this reasoning to taxation

demonstrates that it may end up being a good policy to reduce taxes to ultimately increase tax

revenue.

Figure 7 shows the two reinforcing government investment loops. Just like the private sector,

government uses part of its revenue to invest and contribute to the growth of the economy.

Both this structure and that shown on Figure 5 combine to produce the growth of the entire

economic system as they both aim at increasing the country’s stock of productive capital and

therefore GDP.

Figure 7. Two reinforcing government investment loops

The critical parameters in these feedback loops are the government propensity to consume and

invest. A high cost of governance may not necessarily reduce the contribution of government

to the country’s investment and growth but, if government does not run a budget surplus, it will

create more indebtedness and higher debt servicing obligations.

The model is constructed in such a way that no constraint is placed either on the size of deficit

financing, on public debts or on debt servicing both at home and abroad. Figure 8 displays the

reinforcing domestic debt loop and the deficit financing process as far as public domestic debt

is concerned.


PUBLICDOMESTIC

DEBT



Debtservicing

total







CAPITAL


Privateinvestment

Savings

Disposableincome

Nationalincome

GDPmp


PUBLICFOREIGN

DEBT





non-oil export

Non-oilexport

Export

FOREIGNRESERVES

Desiredexchange

rateRATE OF

EXCHANGE

Forex in

Exchangerateindex

Forex out

Import

Exchangerate

multiplierof import


non-oil export

R

R

22

Figure 8. The reinforcing domestic indebtedness loop

More (less) domestic debt means more (less) interest to pay which translates into more (less)

government expenditures, a larger (lower) deficit or a lower (larger) surplus, a larger (lower)

demand for deficit financing and further (less) debt deterioration.

As no indebtedness constraints are built in the model, the results the model generates entirely

depend upon the assumptions that model users make. The model might very well diverge or

produce unrealistic results as a result of the assumptions made. Calibration is then required. It

must occur for the assumptions leading to rejected results to be amended until acceptable

results are generated. This is one of the most difficult segments in system dynamics modelling

especially when working with complex models. It is also a very useful procedure as it allows

model users to understand the relative sensitivities of the parameters that drive the model and

the points of leverage. Where in the model a small variation of assumption generates a large

change in system behaviour.

Figure 9. The reinforcing foreign indebtedness loop


PUBLICDOMESTIC

DEBT



Debtservicing

total







CAPITAL


Privateinvestment

Savings

Disposableincome

Nationalincome

GDPmp


PUBLICFOREIGN

DEBT





non-oil export

Non-oilexport

Export

FOREIGNRESERVES

Desiredexchange

rateRATE OF

EXCHANGE

Forex in

Exchangerateindex

Forex out

Import

Exchangerate

multiplierof import


non-oil export

R


PUBLICDOMESTIC

DEBT



Debtservicing

total







CAPITAL


Privateinvestment

Savings

Disposableincome

Nationalincome

GDPmp


PUBLICFOREIGN

DEBT





non-oil export

Non-oilexport

Export

FOREIGNRESERVES

Desiredexchange

rateRATE OF

EXCHANGE

Forex in

Exchangerateindex

Forex out

Import

Exchangerate

multiplierof import


non-oil export

R

23

Exactly the same deficit financing process is at play when foreign domestic debts are

concerned. This is shown on Figure 9. It is, however, clear and obvious that such reinforcing

loops cannot continue forever if only because of the willingness of fund lenders to oblige.

Figure 10. The three balancing foreign reserves loops

The exchange rate is the naira price of a particular foreign currency: In Nigeria’s case and in

this model, the American dollar. Prices are stocks. When they are connected to a physical

inventory, they are determined by the size of this inventory compared to its desired size. In this

model, the inventory to which the exchange rate is connected is the reserve of foreign exchange,

basically the reserves of US dollars. The process that is taking place is a dynamic adjustment

of the price (the exchange rate) as a function of the fluctuations of the inventory. The model

assumes that the desired stock of foreign exchange is equal to the volume of US dollars required

to meet the country’s US dollar commitments plus a given precautionary margin. The model

also assumes that the ratio between desired and actual foreign reserves drives a price multiplier

of the actual exchange rate which both determine its desired level. The adjustment then takes

place over a given time delay indicated by constant time adjusting exchange rate.

The three balancing loops shown on Figure 10 depict this simple price adjustment mechanism

based on the dynamics of the stock of foreign reserves. This is precisely the reason why the

loops are balancing: the model generates inflows and outflows of US dollars which drive the

stock of foreign reserves and simultaneously searches for the equilibrium price (the exchange

rate) which corresponds to this inventory level.

The fluctuations in government revenue do not only affect domestic and foreign indebtedness,

they also affect disposable income in a reinforcing manner.

Domestic debt service adds purchasing power to the economy and therefore boosts

consumption and investment. The two additional balancing tax loops shown on Figure 11 add

to the first balancing tax loop shown on Figure 6. The causality described on Figure 11

illustrates the impact of a rising (falling).


PUBLICDOMESTIC

DEBT



Debtservicing

total







CAPITAL


Privateinvestment

Savings

Disposableincome

Nationalincome

GDPmp


PUBLICFOREIGN

DEBT





non-oil export

Non-oilexport

Export

FOREIGNRESERVES

Desiredexchange

rateRATE OF

EXCHANGE

Forex in

Exchangerateindex

Forex out

Import

Exchangerate

multiplierof import


non-oil export

BB

B

24

Domestic debt on national and disposable income through debt servicing. More (less)

disposable income generates more (less) GDP and more (less) tax and non-tax revenue which

themselves decrease (increase) government deficit and the need to borrow.

Figure 11. A second group of two balancing tax loops

Figure 12 displays the reinforcing impact of the foreign debt on the exchange rate. An increase

(decrease) in foreign debt servicing drains more (less) foreign reserves and leads to a further

depreciation (appreciation) of the exchange rate which, in turn, makes foreign debt servicing

more (less) expensive.

Figure 12. Interactions foreign indebtedness - exchange rate

Figure 13 displays the last component of the model structure which rests on a model assumption

that budget surpluses feed the stock of foreign reserves. If it is assumed that government budget

surpluses are kept in foreign currencies as foreign reserves, an additional reinforcing loop is


PUBLICDOMESTIC

DEBT



Debtservicing

total







CAPITAL


Privateinvestment

Savings

Disposableincome

Nationalincome

GDPmp


PUBLICFOREIGN

DEBT





non-oil export

Non-oilexport

Export

FOREIGNRESERVES

Desiredexchange

rateRATE OF

EXCHANGE

Forex in

Exchangerateindex

Forex out

Import

Exchangerate

multiplierof import


non-oil export

B

B


PUBLICDOMESTIC

DEBT



Debtservicing

total







CAPITAL


Privateinvestment

Savings

Disposableincome

Nationalincome

GDPmp


PUBLICFOREIGN

DEBT





non-oil export

Non-oilexport

Export

FOREIGNRESERVES

Desiredexchange

rateRATE OF

EXCHANGE

Forex in

Exchangerateindex

Forex out

Import

Exchangerate

multiplierof import


non-oil export

R

25

created, similar to the loop shown on Figure 12 but with opposite effect. The effect of an

increase (decrease) in foreign debt service is to increase (decrease) the drainage of foreign

exchange from the economy.

The effect of an increase (decrease) in government surplus is to add to (remove from) the stock

of foreign exchange. The controlling stock in the loop (foreign exchange reserves) is increased

rather than depleted.

Figure 13. Management of government surplus

c. Model sketch, constants and parameters. Whether a feedback loop is

reinforcing or balancing, its impact on the dynamic system under study depends upon the

value of the coefficients or parameters that drive it. A structure is driven by data which

can become structures when more complexity is built into the model. The structural

components discussed in section a. above do not explicitly display the parameters and

coefficients which drive feedback loops. This would make the causal diagrams shown

above too bulky and more difficult to read. Parameters and coefficients, however, are

clearly shown on the different views of the model sketch which, together with the

database, are the sole input to the model’s computation process. The model sketch is

made of in nine views connected by shadow variables. In order to make views easier to

read, the following colour conventions are used:

• Green: initial values. All stocks in a model must be initialized. These are the model’s

opening balance sheet values. Initial values may be either assumed or calculated.

• Pink: constants that are fixed once and for all. For example, conversion factors: there

are 1,000 million in a billion or it takes 4 years to be 4 years old

• Dark red: parameters the model reads from the Excel database

• Orange: lookup or functional tables

The first view of the model is the population view. There are five stocks representing the aging

process.


PUBLICDOMESTIC

DEBT



Debtservicing

total







CAPITAL


Privateinvestment

Savings

Disposableincome

Nationalincome

GDPmp


PUBLICFOREIGN

DEBT





non-oil export

Non-oilexport

Export

FOREIGNRESERVES

Desiredexchange

rateRATE OF

EXCHANGE

Forex in

Exchangerateindex

Forex out

Import

Exchangerate

multiplierof import


non-oil export

R

26

Figure 14. The population view

The model assumes that Nigeria’s total population at time start, which is January 1st 2021, is

196 million distributed as follows:

• Very young (0-4): 34.5 million

• School age (5-14): 40 million

• Young adults (15-24): 40 million

• Adults (25-64): 75 million

• Old (65 over): 6.5 million

It takes 4 years for a newborn to be 4 and enter the school age cohort. It takes 10 years for

school age children to become young adults, another 10 years for young adults to become adults

and 40 years for adults to become old. 4 + 10 + 10 + 40 = 64: people enter the old cohort when

they have lived 64 years, that is, when they enter their 65th years of life.

Each cohort is a stock driven by three flows except the last which is only driven by two: those

who move from the previous cohort and those who die.

Seven important parameters in the population sketch are the fertility rate, the fertile period and

the five life expectancies.

The model assumes the following values for initial life expectancies:

• At birth: 54 years

• At 5: 58 years

• At 15: 62 years

• At 25: 64 years

• At 65: 78 years

Those are initial values assumed to remain constant over the simulation period. But this is

unrealistic especially considering a 30-year period. One of the improvements to be made to the

model is to transform this data into a structure by linking life expectancies to both economic

performances and the development of health care.

VERY

YOUNG

(0-4)Yearly

births

Femaleratio

Growing to

school age

ADULT

(25-64)

Growingtime

OLD (65

over)

Aging

Aging time

Deaths

old

Deaths very

youngVery young

death fraction

Deaths

adult

Adultdeath

fraction

Initialold

Initialadult

Initial veryyoung

Fertileperiod

Birth

fraction

Net

population

growth Total deaths

Flat profile

SCHOOL

AGE (5-14)

School age

death fractionDeaths

school

age

Maturing to

young adult

1st Maturingtime

Initialschool age

Death fraction

Lifeexpectancy

at 65

Life

expectancy

at 25

Lifeexpectancy

at 5Life

expectancy

at birth

Total births

expected

YOUNG

ADULT

(15-24)

Deaths

young

adult

Initialyoungadult

Maturing

to adult

Young adult

death fraction

Life

expectancy

at 15

2ndmaturing

time

POPULATION

<Population

total>Initial life

expectancyat 65

Initial lifeexpectancy

at 25


at 15


at 5


at birth

<Fertility

rate>

27

The fertility rate is the number of children that, on average, a fertile woman will engender over

her fertile period. What makes the fertility rate important is its connection with the

performances of economies. There is a clear world level relationship between GDP per head

and fertility rate.

Fertility rates are very high at very low GDP level (below US$1,000) but a very large fall in

fertility occurs as soon as GDP per head rises to about US$3,000 to 4,000. This is shown on

Figure 15.

Figure 15. Correlation between fertility and GDP per head

This relationship may be one of the keys to Nigeria’s population problem. This is the reason

why it must be part of the model. The assumed relationship between fertility and income per

head included in the model is shown on Figure 16. It is a relatively mild assumption which has

been kept the same in both simulated scenarios.

Figure 16. Assumed effect of income per head on fertility

A second important connection between population and the economy is shown on the left-hand

side of Figure 17. The key coefficient in the relationship is the fraction participating, that is,

the proportion of the adult population able and willing to work.

0.00

0.20

0.40

0.60

0.80

1.00

1.20

0 2 4 6 8

EFFECT OF INCOME PER HEAD INDEX ON FERTILITY

28

Figure 17. The model’s second view: labour supply, fertility and growth

In both scenarios, the model keeps this coefficient constant, but it is likely that as economies

develop more people, especially more women, would seek employment.

Figure 18.The capital, production and income view

The view displayed on Figure 18 describes the model’s production process. It is assumed that

output is a fixed proportion of the stock of productive capital. The connection between capital

and output, the capital output ratio, is one of the few major model parameters. The capital

output ratio is a time parameter. It is the number of years it takes for capital to return its value.

The model assumes a value of 3 years. The second key parameter of the production process is

the average capital lifetime. It is also a key parameter because it directly affects the value of

the stock of productive capital through its draining rate. In the base and best scenario, the model

assumes a value of respectively 25 and 30 years for this parameter. Another important

assumption in the model is a structural assumption. It is the assumption that the capital stock

LABOUR SUPPLY,FERTILITY,GROWTH

Population

total

Fraction

dependent

<VERY YOUNG

(0-4)>

<OLD (65

over)>

<ADULT

(25-64)>

<SCHOOL AGE

(5-14)>

Labour supply to

the economy

Fractionparticipating

<YOUNG ADULT

(15-24)>

Initial fertilityrate

Fertility rate

Indicated impact of

income per head on

fertility rate

Lookup effect onfertility

Delay impactingon fertility

<Income per

head index>

Initial

population

Initial labour

supply

GDPfc index

<Initial

GDPfc><GDP at factor

costs>

<PRODUCTIVE

CAPITAL><Investment>

<Depreciation>

Net change in

productive capital

Fractional change in

productive capital

GDP growth

Averagetime

Initial growth

PRODUCTIVE

CAPITAL

Initial

productive

capital

Investment

Depreciation

Averagecapitallifetime

Capitaloutputratio

GDP at market

pricesNational

income

Disposable

income

Savings

Propensityto save

Labour

requirement

Initial labour

required per M$

capital

Labour

available

Private

investment

Investmenteffectiveness

unemployment

CAPITAL, PRODUCTION & INCOME

Productive

capital index

InitialGDPfc

Labouravailability

ratio

Initial labourdemand

<Initial

productive

capital>

GDP atfactor costs

<VAT> <Labour

supply to the

economy>

Labour

ratio

Labour requirement

multiplier

Lookuplabour

required

Labour

required per

M$ capital

B$ CAPITALM$perB$

B$ private

investment

B$

Investment

B$ Government

investment

B$

Depreciation

<M$

per

B$>

<M$ per B$>B$ GDPfc

B$ GDPmp

B$ NI

B$ DI

<Private

transfers>

<Government

investment>

<Debt

servicing

domestic>

<Government tax

revenue><M$ total

subsidies>

Net

investment

<Investment>

<Depreciation>

B$ net

investment

<M$ per B$>

Initial

unemployment

29

determines the economy’s labour requirement. There exists initially in the economy a given

demand for labour: the labour required to operate the capital stock.

This initial labour demand is calculated as the difference between the volume of labour

population supplies to the economy and the level of unemployment. In addition, the model

assumes that, as the stock of capital renews itself through the replacement of depreciated

equipment, a labour-saving effect takes place as a result of the technical progress embodied

into new acquired capital. This tends to reduce labour demand. The critical parameter in this

relationship is the labour required per US$ millions of capital. The critical functional

relationship is the relation between productive capital index and labour requirement multiplier.

This relationship, however, was not activated in simulations.

The model also includes a labour availability ratio. This is a parameter between 0 and 1 the

purpose of which is to simulate in a simple way the impact of any disruption in the flow of

labour to the production process.

Figure 19 displays the fourth view of the model. This is a simple and straightforward view

which calculates the national income per head. The model requires an index of national income

per head. This index is calculated from the initial values of population and national income.

Figure 19. Fourth model view: the national income per head

Figure 20 shows the calculation of government revenue. This fifth model view depicts

another straightforward arithmetic.

National incomeper head

<Nationalincome>

$ per $million

<Populationtotal>

Initial nationalincome

Population totalinitial Initial national

income per head

<Initialadult>

<Initialold>

<Initialschoolage>

<Initialvery

young><Initialyoungadult>

Income perhead index

INCOME PER HEAD

30

Figure 20. Government revenue

Government domestic revenue is made of tax revenue, non-tax revenue (mainly royalties) and

net hydrocarbon revenue. Tax revenue includes personal & corporate income tax, VAT and

other taxes. Both tax and non-tax revenue are assumed to be a function of GDP while net oil

and gas revenue are totally exogenous – the product of a net revenue per barrel and a

hydrocarbon export volume.

The model assumes that tax revenue represents 5.7% of GDP and non-tax revenue 2.5%.

Income tax is 61% of tax revenue while VAT is 15%. These assumptions have been kept

constant in all simulations.

Figure 21. Subsidies

Government

domestic revenues

Personal &

corporate

income tax

VAT

Net oil & gas

revenue

Oilexport

Net oilprice

Initial tax revenue asa fraction of GDP

Income taxfraction oftax revenue

VAT fraction oftax revenue

GOVERNMENTREVENUES

Barrels permillion barrels

B$income

tax

B$ VAT

<M$

per

B$>

B$ tax

revenue

B$ oil & gas

revenue

<M$ per B$>

B$ government

domestic revenue

Government

tax revenue

Government

non-tax revenue

<M$ per B$>

<Initial

GDPfc>

Initial tax

revenue

Initial non-taxrevenue as a

fraction of GDP

<M$ per B$>

B$ non-tax

revenue

<$ per

$million>

Other tax

B$ other tax

<Initial

GDPfc>

Initial non-tax

revenue

<GDPfc

index>

M$ totalsubsidies

Ml of refinedpetroleumimported

Average US$subsidy per kWh

Electricityproduction

<GDP at factorcosts>

MkWh perM$GDP

Ml per M$GDP

M$ Petroleumsubsidy

M$ Powersubsidy

Average US$subsidy per litrel per Ml

kWh perMkWh

B$ powersubsidy

B$ petroleumsubsidy

B$ totalsubsidy

<M$ per B$>

GOVERNMENT SUBSIDIES

<$ per$million>

31

The model includes both petrol and electricity subsidies. Both imported petroleum products

and electricity production are GDP related and the model assumes a decreasing subsidy per

kWh of electricity and per litre of refined petroleum consumed.

Figure 22 displays one of the model’s most important views: government expenditures and

indebtedness. Government expenditures include three components: consumption, investment

and debt servicing. The model assumes that government consumption and investment both

depend upon government domestic revenue and that the budget is in surplus or deficit whether

or not domestic revenue exceeds expenditures. Government propensity to consume and to

invest are two important parameters driving this structure.

Figure 22. Government expenditures and indebtedness

In the base case the model assumes that government propensity to consume falls slowly from

70% of revenue at the beginning of the simulation period to 40% at the end while propensity

to invest remains constant at 30% of revenue yearly. In contrast, in the best case, government

propensity to consume falls more rapidly to 25% at the end of the period while propensity to

invest more than double from 30% to 63%.

Budget deficits are financed by both the domestic public debt and the foreign public debt

according to an assumed share. In the base case, the sharing is on a 50/50 basis, in the best

case, the share of the domestic debt grows from 65% to 85%. Each debt pays interest which

add into total debt servicing and reimburses the principal borrowed. The model assumes a

constant foreign interest rate which is right as the foreign interest rate is truly an exogenous

parameter and a constant domestic interest rate which is wrong. One of the additional structures

required is one that would endogenously determine the domestic interest rate.

The penultimate view of the model is shown on Figure 23.

PUBLIC

DOMESTIC

DEBT

Initial publicdomestic debt

Domestic debtmaturity

Principal

repayment

domestic


Domesticdebt share

Interest paid on

domestic debt

Interest rate ondomestic debt

PUBLIC

FOREIGN

DEBT

Initial publicforeign debt

Deficit

financing

foreign

Principal

repayment

foreign

Maturityforeigndebt

Interest paid on

foreign debt

Interest rateon foreign debt

<Exchange

rate

index>Governmentexpenditures

Government

surplus/deficit

Debt

servicing

total

Government

consumption

expenditures Government

investment

Governmentpropensity to

consume

Governmentpropensity to

invest

GOVERNMENTEXPENDITURES

&INDEBTEDNESS

Debt servicing

domestic

Debt servicing

foreign

<M$ total

subsidies>

<Government

domestic

revenues>

B$ gov.

surplus/deficit

<M$ per B$>

B$ government

expenditures

<Government

expenditures>

B$ total

debt service

<M$ per B$>

B$ gov.

investment

B$ gov.

consumption

<M$ perB$>

B$ foreign

debt

B$ domestic

debt

<M$perB$>

<M$perB$>

B$ foreign

interest

<M$perB$>

B$domesticinterest

B$ total

debt

<B$ foreign

debt>

B$ interest

total

<B$ foreign

interest>

<B$ GDPfc>

Debt to GDP

Debt service per

unit of revenue

32

Figure 23. Import, export and the diaspora

This view calculates import, non-oil export and the Nigerian diaspora’s remittances. Both

import and non-oil export are assumed to be a function of GDP with an added multiplier effect

resulting from the fluctuations of the exchange rate. As the naira appreciates (depreciates)

import become cheaper (dearer) and tend to increase (fall). The same exchange rate effect but

inversed applies to export, but the other way around: a deteriorating exchange rate favours

export. But even with the best possible exchange rate conditions, exportable goods must first

be produced before they are shipped. This is why the model also includes a capital multiplier

of non-oil export.

The model also assumes that there are 15 million Nigerians in the diaspora and that they remit

an average of US$1,700 per year.

The ninth and last view of the model is shown on Figure 24. It depicts the dynamic adjustment

of the exchange rate as a function of the variations in the stock of foreign exchange as was

explained earlier in the text. The exchange rate is assumed to be worth 380 naira per US dollar

at the beginning of the simulation period.

INTERNATIONALTRADE &

REMITTANCES

<Productivecapital index>

Lookupcapitalexport

multiplier

Initialpropensityto export(non-oil)

Capitalmultiplierof non-oil

export

NIGERIANSIN

DIASPORA

Initialdiaspora

Net change indiaspora

Net changefraction diaspora

Averageunit

remittance

Privatetransfers

Exchangerate

multiplierof import

Lookupexchange

rate importmultiplier

<Exchangerate index>

Total imports

Initialpropensityto import


B$ imports

<M$ per B$>

B$ privatetransfers

Non-oilexports



non-oil export

Lookupexchange rate

exportmultiplier

B$ non-oilexports

<$ per$million>

33

Figure 24. The dynamic adjustment of the exchange rate

d. Assumptions, Scenarios and Simulations The model simulates from the first day of 2021 to the last day of 2050. Its time period is

the year and its financial data are measured in US dollars if stocks are concerned or in

US dollars per year if they are flows. A multitude of scenarios can be created and

simulated as the model requires 258 numerical data to simulate.

It takes less than a second to simulate the model, but significantly more time is required

to define a scenario and even more to analyze the results produced. It is important for

model users to learn how to define interesting or relevant scenarios and to be prepared to

spend the right amount of time to understand the results the model generates. The power

and speed of computers keep increasing while our own reasoning ability remains more

or less constant.

In order to facilitate the preparations of scenarios and data entry, the model is

accompanied by a data entry workbook called MODEL DATA PCDI.xlsx which initially

includes five worksheets: TITLE, DATA, DATA ENTRY, DATA CAPTURE and

DATA SHEET TEMPLATE.

Before simulating, the model reads worksheet DATA to capture the numerical

assumptions it requires to compute the model. The results of the simulation are saved in

a Vensim .vdf file named as specified by the model user in the data entry box under

‘Simulation results file name’.

Data are entered using worksheet DATA ENTRY. They are simultaneously saved on

worksheet DATA CAPTURE. Copy numerical values only from DATA CAPTURE and

paste special (data and formats) on a DATA SHEET TEMPLATE to save your scenario.

Rename worksheet ‘DATA SHEET TEMPLATE’: ‘DATA’ when ready to simulate.

FOREX

RESERVESForex in Forex out

Initialexchange

rateChange in

rate of

exchange

Timeadjustingexchange

rate

Desiredexchange

rate

Forex stockcoverage

Relative

forex stock

gap

Impact on

exchange rate

Lookup forexreserves

impact onexchange rate

Desired forex

reserves

FOREX RESERVES& THE EXCHANGE

RATE

Initialforeign

exchangereservesExports

RATE OF

EXCHANGE

<Net oil

& gas

revenue>

Total forex

demand

Forex available

<TIME STEP>

Exchange

rate index

<Private

transfers>

<Total

imports>

<Non-oil

exports>

<Debt servicing

foreign>

B$ forex

reserves

<FOREX

RESERVES>

<M$ per B$>

B$ desired

forex

<M$ per B$>

B$ forex inB$ forex out

<Forex out>

Government

surplus

<Government

surplus/deficit>

34

The results presented in the section below are the outcome of two scenarios: base and

best. A detailed list of all numerical data running each scenario is given in the data entry

workbook. A detailed description of each scenario together with their assumptions is

provided in the users’ guide.

CHAPER 5: ANALYSIS OF PRELIMINARY RESULTS The results of any simulation are presented in 13 views, 35 graphs and 6 tables. Results are

displayed on specific views of the Vensim model file. Simulation results are loaded invoking

Windows -> Control panel -> Dataset and selecting the dataset name(s) as earlier defined by

the user.

Another series of 13 views and 18 graphs are comparative results. They display on the same

graph the simulation results of any two (or more) loaded result files. Such graphs are very

useful to assess policy impacts provided scenarios have been properly defined changing only

one assumption at a time. What is discussed in this section is the comparison of scenarios base

and best.

It is important to keep in mind that the purpose of long-term models cannot be to generate

accurate predictions. The uncertainties are far too many and the range of possibilities much too

wide. Rather, long-term models are useful to indicate trends or directions of change, shapes

being more important than the actual data which constitute them.

The first graph displayed on Figure 25 can be interpreted as a quality indicator for the scenario.

What is compared is the ratio of debt to GDP in both scenarios. Debt to GDP is the ratio of a

stock to a rate. Its unit is therefore a time period, here the year.

35

Figure 25. Scenario comparison. Debt to GDP ratio

The comparison leads to a straightforward conclusion. Although the base scenario gives rise to

an indebtedness situation equivalent to less than half a year of GDP, which is manageable, the

trend is worrying. In contrast, the best scenario achieves a reversal in relative indebtedness

with a debt GDP ratio lower at the end of the period than at the beginning.

Debt to GDP

.6

.45

.3

.15

0

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

Yea

r

Debt to GDP : AGENDA 2050 BASE

Debt to GDP : AGENDA 2050 BEST

DEBT TO GDP RATIO (year)

36

Figure 26. Population and national income

The left-hand side of Figure 26 shows the simulated evolution of population while the right-

hand side of the figure displays the behaviour over time of Nigeria’s national income (in US$

billion per year).

Because the model assumption that connects fertility to income per head is rather moderate, by

the end of the simulation period the model does not generate a large population difference

between the two scenarios. The base scenario gives 427 million compared to 416 million for

the best scenario. The difference is 11 million. A population reduction of 11 million is relatively

marginal for Nigeria. Yet it is a little more than the present population of Switzerland.

A much larger improvement is observed as far as the national income is concerned. From an

initial value of US$423 billion at the beginning of the simulation period, the base scenario

reaches US$763 billion at the end while the best scenario attains US$1360 billion. The

difference in favour of the best scenario is considerable: US$597 billion or 1.8 times what the

base scenario is capable of achieving.

POPULATION (people) & NATIONALINCOME (US$ billion)

Population total

500 M

375 M

250 M

125 M

0

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

peo

ple

Population total : AGENDA 2050 BASE

Population total : AGENDA 2050 BEST

B$ NI

2000

1500

1000

500

0

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

B$

/Yea

r

B$ NI : AGENDA 2050 BASE

B$ NI : AGENDA 2050 BEST

37

Figure 27. Unemployment

When unemployment is considered, a massive difference between both scenarios is observed.

From a starting level of 26 million unemployed or under-employed people at the beginning of

the simulation period, the model produces at the end of the period a very large difference of 61

million people between both scenarios. In the base scenario, in spite of a fall in unemployment

to about 18 million over the first ten years of the period, 44 million people are unemployed at

the end of the period. In sharp contrast, the best scenario shows a negative unemployment of

17 million. That means that Nigeria is projected to need an additional 17 million people in the

labour force to be able to run the economy. Several factors, however, which the scenarios have

not (but may have) considered come to mitigate this result. First it is likely that the Nigerian

population will produce a larger than simulated number of candidates for employment

especially from the female gender. Second the labour-saving impact of capital accumulation

has not been considered. All in all, while the best scenario undeniably offers a much better

perspective than its counterpart, the situation may not be as rosy as indicated by the simulation.

UNEMPLOYMENT (people)

unemployment

50 M

25 M

0

-25 M

-50 M

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

peo

ple

unemployment : AGENDA 2050 BASE

unemployment : AGENDA 2050 BEST

38

Figure 28. National income per head

The gap in national income per head (US$ per person per year) between base and best scenario

is also significant although, in absolute value, both scenarios may be considered as generating

results below expectations. From US$2,200 per person per year at the beginning of the period,

at the end of the period, national income per head falls to US$1,790 per person per year in the

base scenario and raises to US$3,270 in the best scenario. The weight of the large and growing

Nigerian population is difficult to carry especially with an economy which is yet to reach

maturity.

NATIONAL INCOME PER HEAD (US$per people per year)

National income per head

4000

3250

2500

1750

1000

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

$/(

Year*

peo

ple

)

National income per head : AGENDA 2050 BASE

National income per head : AGENDA 2050 BEST

39

Figure 29. Productive capital

The higher growth in productive capital in the best scenario depicted by Figure 29 is the

reflection of previous comments. The productive capital index increases from 1 respectively to

1.75 in the base scenario and to 3.25 in the best scenario. Yet the investment effort is not strong

enough to let the economy take off at an earlier stage.

PRODUCTIVE CAPITAL (US$ billion)

B$ CAPITAL

4000

3000

2000

1000

0

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

B$

B$ CAPITAL : AGENDA 2050 BASE

B$ CAPITAL : AGENDA 2050 BEST

40

Figure 30. Economic growth

This is perhaps the most important graph of both simulations. And what the graph conveys is

perhaps the most important message of the entire report.

The point of departure (2020) is a rate of economic growth of 1.78% and 2.31% respectively

for the base and best scenarios.

Figure 31 shows that in the first 10 years of the simulation period, between 2020 and 2030, the

base scenario only records marginal economic growth improvements. Then economic growth

falls. At the end of the period, growth is lower than it was at the start. This is the result of an

insufficient investment program over the period considered.

2025 1.92%

2030 1.97%

2035 1.94%

2040 1.85%

2045 1.77%

ECONOMIC GROWTH (%)

Fractional change in productive capital

.07

.0525

.035

.0175

0

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

1/Y

ear

Fractional change in productive capital : AGENDA 2050 BASE

Fractional change in productive capital : AGENDA 2050 BEST

41

2050 1.74%

Figure 31. Base scenario: economic growth

Figure 32 clearly shows that the best scenario does much better.

2025 3.04%

2030 3.23%

2035 3.55%

2040 4.21%

2045 5.31%

2050 6.75%

Figure 32. Best scenario: economic growth

It also indicates that economic growth is the result of a long cumulative process which rests

upon recurrent streams of investments and the resulting build-up of productive capital over a

substantial period of time. This process cannot be successful without persistence and the

determination to build on what already exists rather than starting afresh at each change of

government. Nigeria requires the strict coordination of several medium-term plans and several

legislatures to achieve economic success.

Figure 33 is concerned with government revenues and expenditures.

Figure 33. Government revenues & expenditures

GOVERNMENT REVENUES & EXPENDITURES (US$ billion per year)

B$ government domestic revenue

200

150

100

50

0

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

B$

/Year

B$ government domestic revenue : AGENDA 2050 BASE

B$ government domestic revenue : AGENDA 2050 BEST

B$ government expenditures

200

150

100

50

0

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

B$

/Year

B$ government expenditures : AGENDA 2050 BASE

B$ government expenditures : AGENDA 2050 BEST

42

Unsurprisingly in both areas – revenues and expenditures, the best scenario shows higher

performances than the base. The effect on budget surplus/deficit is analysed in the next graph.

Figure 34. Government surplus / deficit

In the base scenario, government is incapable of keeping its budget under control and the

budget deficit grows exponentially to reach over US$47 billion at the end of the simulation

period. In sharp contrast, in the best scenario, government keeps public indebtedness under

control and, while still in deficit, toward the end of the period, a reduction in deficit is observed.

In the best scenario, the 2050 deficit is about US$8 billion, almost six times less than in the

base scenario.

B$ gov. surplus/deficit

0

-12.5

-25

-37.5

-50

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

B$

/Year

"B$ gov. surplus/deficit" : AGENDA 2050 BASE

"B$ gov. surplus/deficit" : AGENDA 2050 BEST

GOVERNMENT SURPLUS / DEFICIT (US$ billion per year)

43

Figure 35. Government debts

When a country’s currency is weak, it is much better for government to put emphasis on

domestic rather than on foreign indebtedness. This is what Figure 35 illustrates. On domestic

debt, the divergence between both scenarios is only noticeable in the last five years of the

simulation as both debts grow in parallel for most of the period. Domestic debt is US$56.4

billion in 2020 and raises to reach respectively US$163 billion and US$165 billion in the base

and best scenario. Yet, at the end of the period, public domestic debt in the base scenario has

reached US$228 billion while in the best scenario the growth is slower, and the debt stock

stands at US$194 billion.

A vastly different situation is observed as far as the public foreign debt is concerned. While in

the base scenario, the foreign debt grows unabated from US$28 billion to over US$171 billion

at the end of the period, in the best scenario foreign debt grows moderately to US$69 billion in

2040 then starts declining to US$49 billion at the end of the period.

B$ domestic debt

300

225

150

75

0

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

B$

B$ domestic debt : AGENDA 2050 BASE

B$ domestic debt : AGENDA 2050 BEST

B$ foreign debt

200

150

100

50

0

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

B$

B$ foreign debt : AGENDA 2050 BASE

B$ foreign debt : AGENDA 2050 BEST

GOVERNMENT DEBTS (US$ billion)

44

Figure 36. Debt servicing

Debt servicing is a direct consequence of the debt situation. This is shown on Figure 36. As

both graphs clearly show, the burden of the debt is much easier to carry in the best scenario

than it is in the base scenario. The graph on the left-hand side shows how vastly the debt service

profiles of both scenarios differ from each other. This is another way to measure the effects of

good public management. In the base scenario total debt service grows exponentially from

US$7.5 billion at the beginning of the period to over US$66 billion at the end of the period

while in the best scenario debt servicing reaches a peak of only US$25 billion in 2047 then

declines to US$22.3 billion at the end of the period.

The graph on the right-hand side displays the share of government revenue that is allocated to

service the debt. In the base scenario this ratio grows from 19% at the beginning of the period

to over 100% at the end. This is a clearly untenable situation in which a country would have to

borrow to service its debt. In sharp contrast, in the best scenario, the ratio remains within a

range of 18/26% to finally fall back to 19% at the end of the period.

B$ total debt service

70

52.5

35

17.5

0

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

B$

/Year

B$ total debt service : AGENDA 2050 BASE

B$ total debt service : AGENDA 2050 BEST

GOVERNMENT DEBT SERVICE (US$ billion per year)

Debt service per unit of revenue

2

1.5

1

.5

0

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

Dm

nl

Debt service per unit of revenue : AGENDA 2050 BASE

Debt service per unit of revenue : AGENDA 2050 BEST

45

Figure 37. International trade

In the model, imports and non-oil exports depend upon GDP and the exchange rate. Non-oil

exports, however, also depend upon a third variable, the accumulation of productive capital.

An appreciation of the exchange rate makes the naira more expensive in terms of foreign

currency, discourages exports and boosts imports. Conversely a depreciation of the exchange

rate makes the naira cheaper in terms of foreign currency, boosts exports and discourages

imports. The left-hand side of Figure 37 reflects the fluctuations of the exchange rate, the

difference in position on the graph indicating the fact that economic growth is substantially

stronger in the best scenario. Also reflective of the difference in economic growth is the

evolution of non-oil exports. Starting at US$4 billion in both scenarios, non-oil exports reach

US$20 and US$50 billion respectively in the base and best scenarios. A better managed

economy results in multiplying export by a factor of 2.5.

B$ imports

80

60

40

20

0

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

B$/Y

ear

B$ imports : AGENDA 2050 BASE

B$ imports : AGENDA 2050 BEST

B$ non-oil exports

50

37.5

25

12.5

0

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

B$

/Year

"B$ non-oil exports" : AGENDA 2050 BASE

"B$ non-oil exports" : AGENDA 2050 BEST

IMPORT & NON-OIL EXPORT (US$ billion per year)

46

Figure 38. Forex reserves

The stock of foreign exchange is an important variable in the model as it drives the exchange

rate and, therefore, international trade. The dynamics of this stock is controlled, on the side of

feeding flows, by exports, private transfers, potential government surpluses and the exchange

rate and, on the side of draining flows, by imports and foreign debt servicing. The fluctuations

recorded by the graph on Figure 38 reflect the relative importance of the flows in and out of

the stock. Fluctuations are very significant. The lowest level recorded is US$13 billion while

the highest is over US$100 billion. These, of course, partly depend upon the strength of the

adjustment mechanism assumed and built in the model.

FOREIGN EXCHANGE RESERVES (US$ billion)

B$ forex reserves

200

150

100

50

0

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

B$

B$ forex reserves : AGENDA 2050 BASE

B$ forex reserves : AGENDA 2050 BEST

47

Figure 39. The naira exchange rate

There is some convergence between Figure 38 and Figure 39 but the result generated by the

model is surprising and certainly counter-intuitive. One important lesson to learn from this

model’s result is that the exchange rate should certainly not be an exogenous variable in

economic models. Modelling the exchange rate in connection with the stock of foreign

exchange seems to be the right approach as past developments in the Nigerian economy seem

to support it.

First the results. The behavior over time is clearly cyclical. From 2021 to 2039/2040 the model

shows exchange rate stability in both scenarios. The starting point is ₦380 per US$. In the base

scenario, the exchange rate grows to ₦400/US$ in 2026 then falls to ₦344/US$ 10 years later

in 2036. It then rises again exponentially until the end of the period. In 2050 the exchange rate

stands at ₦1,562/US$, over 4 times its initial value.

RATE OF EXCHANGE

2000

1500

1000

500

0

2021 2025 2029 2033 2037 2041 2045 2049

Time (Year)

nair

a/$

RATE OF EXCHANGE : AGENDA 2050 BASE

RATE OF EXCHANGE : AGENDA 2050 BEST

THE EXCHANGE RATE naira per (US$)

48

In the best scenario the exchange rate rises faster to ₦426/US$ in 2025 then falls to ₦299/US$

10 years later in 2035 then climbs again to ₦2,516/US$ in 2049 but begins a turnaround in the

last year of the simulation to ₦1,494/US$. It is therefore a quite different behavior.

To be able to judge the validity of these results and the importance of the assumptions that

drive them, it is necessary to delve into the structure of the model.

The driver of the exchange rate’s dynamics is the ratio between forex reserves and desired

forex reserves. To put it bluntly the ratio between what we have and what we want. This is a

very common approach in system dynamics. If the ratio is greater than one it means that we

have more forex stock than what we want. It is therefore time to lower its price to clear the

excess. Lowering the price means to make the US dollar cheaper in terms of naira which means

for the naira exchange rate to appreciate. The table on the left-hand side of Figure 40 which is

extracted from the data entry worksheet, shows that when X grows above 1, Y, the exchange

rate multiplier falls below 1.

45. TABLE 23

X Y

RELATIVE EXCHANGE

RATE

FOREX

STOCK IMPACT

GAP [Line 46] [Line 47]

0.1 1.5

1.0 1

2.0 0.8

4.0 0.6

8.0 0.5

12 0.4

15 0.4

Figure 40. Extract from the data entry worksheet. Relationship forex stock – exchange rate

Conversely, if the ratio is lower than 1 it means that we have less forex stock than what we

want. It is therefore time to increase its price so as to reduce or stop stock drainage. Increasing

the price means to make the US dollar dearer in terms of naira which means for the naira

exchange rate to depreciate.

Figure 41 shows, for each scenario, the coefficient by which the exchange rate is multiplied.

When it is higher than 1 the exchange rate depreciates, when it is lower, it appreciates. The

superiority of the best scenario then becomes very clear.

0

0.5

1

1.5

2

0.0 5.0 10.0 15.0 20.0

IMPACT OF RELATIVE FOREX STOCK GAP ON EXCHANGE

RATE

49

Figure 41. The exchange rate multiplier

CHAPTER 6: FURTHER MODEL DEVELOPMENT - DYNAMIC INPUT-OUTPUT MODEL Significant model improvement would result if the following developments were implemented:

production disaggregation using dynamic input-output modelling; modelling of education,

energy, the environment and the informal economy; endogenous determination of the Interest

rate. In addition, there always remains the possibility of modelling in more depth some selected

areas as may be required.

As a preview of what can be done to improve the existing model, the following description of

how dynamic input-output modelling can be done using system dynamics illustrates the

powerful capability of this modelling and simulation tool to build complex computable

structures. The steps of this dynamic process inspired by supply chain management are detailed

below.

Any sector of a global economy purchases inputs to produce. It also sells its own products to

various clients. Clients are either the sector itself, which needs to consume some of its own

output to produce, other sectors of the economy which are procuring inputs, or final consumers.

Industries do not immediately respond to orders as they come, neither do they directly sell what

they produce. Rather, industries accumulate orders in a stock of unfilled orders which they

manage in line with their inventory (the stock of what they produce).

Impact on exchange rate

2

1.4

.8

2021 2029 2037 2045

Time (Year)

Dm

nl

Impact on exchange rate : AGENDA 2050 - BASE

Impact on exchange rate : AGENDA 2050 BEST

50

Figure 42. System dynamics sketch of the orders – inventory causal connection

Similarly, they stock what they produce in an inventory which they manage in line with the

orders they receive. Figure 42 is the system dynamics sketch of this process. P stands for

product and S for sector. The digit 1 represents a product/sector index.

The stock of unfilled orders indicates what must be in stock to meet demand. Comparing what

must be in stock to meet demand to what is actually in stock indicate how much must be

produced (Figure 43).

Figure 43. Stock and production adjustment

Once desired production is known, the labour force required to produce is also known.

INVENTOR

Y OF P1 IN

S1Production of

P1 in S1

Shipments of

P1

UNFILLEDORDERSFOR P1

Total orders

for P1

P1 inventory

coverage

Normal

shipment P1

INVENTOR

Y OF P1 IN

S1Production of

P1 in S1

Shipments of

P1


Total orders

for P1

Initial unfilled

orders for P1

Desired inventory

of P1 in S1

Desired production

of P1 in S1

P1 inventory

coverage

Normal

shipment P1

Normal shipment

fractionP1 Production

adjustment time

Inventory

coverage P1

Smoothing

time

51

Figure 44. Labour force dynamics The volume of labour to hire is obtained by comparing desired labour force to existing labour

force (Figure 44).

Labour is one of the components that sectors require to produce. The others are the material

inputs to the production process. These inputs are supplied by the other sectors of the economy

then stocked as shown on Figure 45.

Figure 45. Material input procurement

This structure is replicated as many times as there are sectors in the economy.

The above analysis is conducted in volume. What is measured are quantities or volumes. The

value analysis is done from the calculation of accounting costs for inputs and the determination

of selling prices for outputs. Accounting costs are calculated dividing a stock value by a stock

volume. They are needed to determine the costs of material usages. Figure 46 includes input

stocks and inventory valuations and shows the overall causal structure of a single sector. The

four highlighted feedback loops are balancing as the growth of the system results from inter-

INVENTOR

Y OF P1 IN

S1

Initial P1

inventory in S1

Production of

P1 in S1Desired production

of P1 in S1

Desired labour

in S1

LABOUR

EMPLOYED

IN S1

Initial labour

employed in S1

Net hiring in

S1

P1 Production

from S1 labour

Labour

productivity in S1 Time adjusting

labour

INVENTOR

Y OF P1 IN

S1Production of

P1 in S1

Shipments of

P1


Total orders

for P1

Desired inventory

of P1 in S1

P2 STOCK

IN S1

P2 Deliveries

from S2

Desired stock of

P2 in S1

I/O ratio P2 per

unit of P1

S1 Orders for

P2

P1 Production

from P2 stock

P1 inventory

coverage

<S2 Orders for

P1>

52

industry orders which constitute reinforcing loops as they trigger more demand and more

production in each sector. Replicating this structure as many times as there are products and

sectors in the economy using the indexing capability of Vensim DSS and feeding the structure

with the required data produces what constitutes in our opinion the best representation of

dynamic inter-industry linkages.

Figure 46. Complete causal structure of a single sector

APPENDIX 1: MODEL EQUATIONS The 255 equations of the model are listed below.

1. Initial growth = 0.0175 1/Year

2. Net change in productive capital = Investment-Depreciation M$/Year

3. Fractional change in productive capital = Net change in productive capital /

PRODUCTIVE CAPITAL 1/Year

4. GDP growth = TREND (GDP at factor costs, Average time, Initial growth) 1/Year

5. Average time = 1 Year

6. Forex in = Exports + Private transfers + (Government surplus * Exchange rate index)

M$/Year

7. Government surplus = IF THEN ELSE ("Government surplus/deficit" > 0,

"Government surplus/deficit", 0) M$/Year

8. Debt to GDP = B$ total debt / B$ GDPfc Year

9. B$ desired forex = Desired forex reserves / M$ per B$ B$

10, "Government non-tax revenue" = "Initial non-tax revenue" * GDPfc index

M$/Year

11. B$ forex out = Forex out / M$ per B$ B$/Year

12. Government tax revenue = Initial tax revenue * GDPfc index M$/Year

13. B$ forex in = Forex in / M$ per B$ B$/Year

14. GDPfc index = GDP at factor costs / Initial GDPfc Dmnl

15. "Initial non-tax revenue" = Initial GDPfc * "Initial non-tax revenue as a fraction of

GDP" M$/Year

INVENTORYOF P1 IN S1

Initial P1inventory

in S1

Production ofP1 in S1

Shipments ofP1


Totalordersfor P1

Initial unfilledorders for P1

Desired inventoryof P1 in S1

Desiredproduction of

P1 in S1

Desiredlabour in S1

LABOUREMPLOYED

IN S1

Initial labouremployed in S1

Net hiringin S1

P1 Productionfrom S1 labour

Labourproductivity

in S1

P2 STOCKIN S1

Initial stockof P2 in S1

Usage ofP2 in S1

P2 Deliveriesfrom S2

Desired stock ofP2 in S1

I/O ratio P2 perunit of P1

S1 Ordersfor P2

P1 Productionfrom P2 stock

Finaldemandfor P1

P1 inventorycoverage

Normalshipment P1

Normalshipmentfraction

<I/O ratio P2per unit of P1> P1 Production

adjustment time

Inventorycoverage P1

Smoothingtime

P2 Stockadjustment

time

<S2 Ordersfor P1>

P2 STOCKVALUE IN S1P2 Material

purchase

P2usagecost

Initial P2 stockvalue in S1

P2Accounting

cost

P1INVENTORY

VALUE

Initial P1inventory value

P1 productionvalue

P1 salesvalue P1 selling

price

SECTOR 1

PRODUCT 1<TIMESTEP>

Timeadjustinglabour

<P2 sellingprice>

B

B

B

B

53

16. B$ interest total = B$ domestic interest + B$ foreign interest B$/Year

17. B$ domestic interest = Interest paid on domestic debt / M$ per B$ B$/Year

18. B$ foreign debt = PUBLIC FOREIGN DEBT / M$ per B$ B$

19. B$ foreign interest = Interest paid on foreign debt / M$ per B$ B$/Year

20. Initial population = INITIAL (Population total) people

21. "B$ gov. investment" = Government investment / M$ per B$ B$/Year

22. B$ total debt = B$ domestic debt + B$ foreign debt B$

23. "B$ gov. consumption" = Government consumption expenditures / M$ per B$

B$/Year

24. B$ total debt service = Debt servicing total / M$ per B$ B$/Year

25. Initial labour supply = INITIAL (Labour supply to the economy) people

26. "Non-oil exports" = GDP at factor costs * "Initial propensity to export (non-oil)" *

"Exchange rate multiplier of non-oil export" * "Capital multiplier of non-oil export"

M$/Year

27. B$ domestic debt = PUBLIC DOMESTIC DEBT / M$ per B$ B$

28. Initial unemployment = INITIAL (unemployment) people

29. B$ government expenditures = Government expenditures / M$ per B$ B$/Year

30. B$ forex reserves = FOREX RESERVES / M$ per B$ B$

31. "B$ gov. surplus/deficit" = "Government surplus/deficit" / M$ per B$ B$/Year

32. Other tax = Government tax revenue - "Personal & corporate income tax" – VAT

M$/Year

33. B$ other tax = Other tax / M$ per B$ B$/Year

34. Net investment = Investment – Depreciation M$/Year

35. B$ net investment = Net investment / M$ per B$ B$/Year

36. Initial installed distribution capacity = 2000 MW

37. Initial installed production capacity = 4000 MW

38. M$ Power subsidy = Electricity production * Average US$ subsidy per kWh * kWh

per MkWh / "$ per $million" M$/Year

39. INSTALLED DISTRIBUTION CAPACITY = INTEG (Distribution capacity

added - Distribution capacity depreciated, Initial installed distribution capacity) MW

40. CULTIVATED LAND= INTEG (Land addition - Land erosion, Initial cultivated

land) ha

41. Distribution capacity added = 0 MW/Year

42. Distribution capacity depreciated = INSTALLED DISTRIBUTION CAPACITY *

Depreciation fraction distribution MW/Year

43. Initial cultivated land = 0 ha

44. Production capacity added = 0 MW/Year

45. Production capacity depreciated = INSTALLED PRODUCTION CAPACITY *

Depreciation fraction production MW/Year

46. Land addition = 0 ha/Year

47. INSTALLED PRODUCTION CAPACITY = INTEG (Production capacity added -

Production capacity depreciated, Initial installed production capacity) MW

48. Erosion fraction = 0 1/Year

49. Land erosion = CULTIVATED LAND * Erosion fraction ha/Year

50. Depreciation fraction production = 0 1/Year

51. Depreciation fraction distribution = 0 1/Year

52. Indicated impact of income per head on fertility rate = Lookup effect on fertility

(Income per head index) Dmnl

53. Government consumption expenditures = Government domestic revenues *

Government propensity to consume M$/Year

54

54. Disposable income = National income - Government tax revenue M$/Year

55. Change in rate of exchange = (Desired exchange rate - RATE OF EXCHANGE) /

Time adjusting exchange rate naira/$/Year

56. "Net oil & gas revenue" = (Oil export * Net oil price * Barrels per million barrels)

/ "$ per $million" M$/Year

57. Private transfers = NIGERIANS IN DIASPORA * Average unit remittance / "$ per

$million" M$/Year

58. GDP at market prices = GDP at factor costs + VAT - M$ total subsidies M$/Year

59. Initial tax revenue = Initial GDPfc * Initial tax revenue as a fraction of GDP

M$/Year

60. Government investment = Government domestic revenues * (Government

propensity to invest) M$/Year

61. "Government surplus/deficit" = Government domestic revenues - Government

expenditures M$/Year

62. Government expenditures = Government consumption expenditures + Government

investment + Debt servicing total + M$ total subsidies M$/Year

63. M$ Petroleum subsidy = Ml of refined petroleum imported * Average US$ subsidy

per litre * l per Ml / "$ per $million" M$/Year

64. "$ per $million" = 1e+06 $/M$

65. M$ total subsidies = M$ Petroleum subsidy + M$ Power subsidy M$/Year

66. kWh per MkWh = 1e+06 kWh/MkWh

67. l per Ml = 1e+06 l/Ml

68. B$ tax revenue = Government tax revenue / M$ per B$ B$/Year

69. Ml of refined petroleum imported = GDP at factor costs * Ml per M$ GDP

Ml/Year

70. Initial national income = INITIAL (National income) M$/Year

71. Initial national income per head = (Initial national income * "$ per $million") /

Population total initial $ / (Year*people)

72. "Initial non-tax revenue as a fraction of GDP" = GET XLS CONSTANTS

('MODEL DATA PCDI.xlsx', 'DATA', 'B29') Dmnl

73. Average US$ subsidy per kWh = GET XLS DATA ('MODEL DATA

PCDI.xlsx', 'DATA', '1', 'B45') $/kWh

74. Average US$ subsidy per litre = GET XLS DATA ('MODEL DATA PCDI.xlsx',

'DATA', '1', 'B44') $/l

B$ power subsidy = M$ Power subsidy / M$ per B$ B$/Year

75. Income per head index = National income per head / Initial national income per

head Dmnl

76. B$ government domestic revenue = Government domestic revenues / M$ per B$

B$/Year

77. B$ VAT = VAT / M$ per B$ B$/Year

78. "Personal & corporate income tax" = Government tax revenue * Income tax fraction

of tax revenue M$/Year

79. VAT= Government tax revenue * VAT fraction of tax revenue M$/Year

80. Population total initial = Initial very young + Initial school age + Initial young adult

+ Initial adult + Initial old people

81. "B$ non-tax revenue" = "Government non-tax revenue" / M$ per B$ B$/Year

82. B$ petroleum subsidy = M$ Petroleum subsidy / M$ per B$ B$/Year

83. National income per head = (National income * "$ per $million") / Population total

$ / people/Year

55

84. Government domestic revenues = "Net oil & gas revenue" + Government tax

revenue + "Government non-tax revenue" M$/Year

85. B$ total subsidy = B$ petroleum subsidy + B$ power subsidy B$/Year

86. MkWh per M$GDP = GET XLS DATA ('MODEL DATA PCDI.xlsx', 'DATA', '1',

'B43') MkWh/M$

87. Electricity production = GDP at factor costs * MkWh per M$GDP MkWh/Year

88. Ml per M$ GDP = GET XLS DATA ('MODEL DATA PCDI.xlsx', 'DATA', '1',

'B42') Ml/M$

89. National income = GDP at market prices + Debt servicing domestic + Private

transfers M$/Year

90. "Exchange rate multiplier of non-oil export" = Lookup exchange rate export

multiplier (Exchange rate index) Dmnl

91. Exports = "Non-oil exports" + "Net oil & gas revenue" M$/Year

92. B$ private transfers = Private transfers / M$ per B$ B$/Year

93. Forex out = MIN (MAX (Forex available, 0), Total forex demand) M$/Year

94. Interest paid on domestic debt = PUBLIC DOMESTIC DEBT * Interest rate on

domestic debt $/Year

95. Interest paid on foreign debt = PUBLIC FOREIGN DEBT * Interest rate on foreign

debt*Exchange rate index M$/Year

96. B$ imports = Total imports / M$ per B$ B$/Year

97. Debt servicing total = Debt servicing domestic + Debt servicing foreign M$/Year

98. "B$ non-oil exports" = "Non-oil exports" / M$ per B$ B$/Year

99. Total forex demand = Total imports + Debt servicing foreign M$/Year

100. Debt servicing domestic = Principal repayment domestic + Interest paid on

domestic debt M$/Year

101. Lookup exchange rate export multiplier = GET XLS LOOKUPS ('MODEL DATA

PCDI.xlsx', 'DATA', '54', 'B55') Dmnl

102. Total imports = GDP at factor costs * Initial propensity to import * Exchange rate

multiplier of import M$/Year

103. Deficit financing domestic = IF THEN ELSE ("Government surplus/deficit" < 0,

(-"Government surplus/deficit" * Domestic debt share), 0) M$/Year

104. Deficit financing foreign = IF THEN ELSE ("Government surplus/deficit" < 0, -

"Government surplus/deficit" * (1-Domestic debt share), 0) M$/Year

105. Principal repayment foreign = (PUBLIC FOREIGN DEBT / Maturity foreign

debt) * Exchange rate index M$/Year

106. Debt servicing foreign = Principal repayment foreign + Interest paid on foreign

debt M$/Year

107. Initial propensity to import = GET XLS CONSTANTS ('MODEL DATA

PCDI.xlsx', 'DATA', 'B30') Dmnl

108. Investment = (Private investment + Government investment) * Investment

effectiveness M$/Year

109. Government propensity to consume = GET XLS DATA ('MODEL DATA


110. NIGERIANS IN DIASPORA = INTEG (Net change in diaspora, Initial diaspora)

people

Government propensity to invest = GET XLS DATA ('MODEL DATA PCDI.xlsx',

'DATA', '1', 'B38') Dmnl

111. "Initial propensity to export (non-oil)" = GET XLS CONSTANTS ('MODEL

DATA PCDI.xlsx', 'DATA', 'B39') Dmnl

56

112. "Capital multiplier of non-oil export" = Lookup capital export multiplier

(Productive capital index) Dmnl

113. Lookup exchange rate import multiplier = GET XLS LOOKUPS ('MODEL

DATA PCDI.xlsx', 'DATA', '54', 'B31') Dmnl

114. Exchange rate multiplier of import = Lookup exchange rate import multiplier

(Exchange rate index) Dmnl

115. Average unit remittance = GET XLS DATA ('MODEL DATA PCDI.xlsx',

'DATA', '1', 'B53') $/people/Year

116. Lookup capital export multiplier = GET XLS LOOKUPS ('MODEL DATA


117. Initial diaspora = GET XLS CONSTANTS ('MODEL DATA PCDI.xlsx', 'DATA',

'B57') people

118. Net change fraction diaspora = GET XLS DATA ('MODEL DATA PCDI.xlsx',

'DATA', '1', 'B56') 1/Year

119. Net change in diaspora = NIGERIANS IN DIASPORA * Net change fraction

diaspora people/Year

120. B$ GDPmp = GDP at market prices / M$ per B$ B$/Year

121. B$ DI = Disposable income / M$ per B$ B$/Year

122. B$ GDPfc = GDP at factor costs / M$ per B$ B$/Year

123. B$ NI = National income / M$ per B$ B$/Year

124. "B$ oil & gas revenue" = "Net oil & gas revenue" / M$ per B$ B$/Year

125. B$ income tax = "Personal & corporate income tax" / M$ per B$ B$/Year

126. Labour requirement multiplier = Lookup labour required (Productive capital

index) Dmnl

127. B$ private investment = Private investment / M$ per B$ B$/Year

128. B$ Government investment = B$ Investment - B$ private investment B$/Year

129. B$ CAPITAL = PRODUCTIVE CAPITAL / M$ per B$ B$

130. B$ Depreciation = Depreciation / M$ per B$ B$/Year

131. M$ per B$ = 1000 M$/B$

132. B$ Investment = Investment / M$ per B$ B$/Year

133. Interest rate on domestic debt = GET XLS DATA ('MODEL DATA PCDI.xlsx',

'DATA', '1', 'B33') 1/Year

134. Interest rate on foreign debt = GET XLS DATA ('MODEL DATA PCDI.xlsx',

'DATA', '1', 'B36') 1/Year

135. Initial public foreign debt = GET XLS CONSTANTS ('MODEL DATA

PCDI.xlsx', 'DATA', 'B34') M$

136. Principal repayment domestic = PUBLIC DOMESTIC DEBT / Domestic debt

maturity M$/Year

137. Domestic debt maturity = GET XLS DATA ('MODEL DATA PCDI.xlsx',

'DATA', '1', 'B41') Year

138. Domestic debt share = GET XLS DATA ('MODEL DATA PCDI.xlsx', 'DATA',

'1', 'B32') Dmnl

139. PUBLIC FOREIGN DEBT = INTEG (Deficit financing foreign - Principal

repayment foreign, Initial public foreign debt) M$

140. PUBLIC DOMESTIC DEBT = INTEG (Deficit financing domestic - Principal

repayment domestic, Initial public domestic debt) M$

141. Maturity foreign debt = GET XLS DATA ('MODEL DATA PCDI.xlsx', 'DATA',

'1', 'B35') Year

142. Initial public domestic debt = GET XLS CONSTANTS ('MODEL DATA


57

143. Exchange rate index = RATE OF EXCHANGE / Initial exchange rate Dmnl

144. Labour required per M$ capital = Initial labour required per M$ capital * Labour

requirement multiplier people/M$

145. Labour requirement = PRODUCTIVE CAPITAL * Labour required per M$

capital people

146. Lookup effect on fertility = GET XLS LOOKUPS ('MODEL DATA PCDI.xlsx',

'DATA', '66', 'B67') Dmnl

147. Delay impacting on fertility = GET XLS CONSTANTS ('MODEL DATA

PCDI.xlsx', 'DATA', 'B65') Year

148. Lookup labour required = GET XLS LOOKUPS ('MODEL DATA PCDI.xlsx',

'DATA', '68', 'B69') Dmnl

149. Initial fertility rate = GET XLS CONSTANTS ('MODEL DATA PCDI.xlsx',

'DATA', 'B9') Dmnl

150. Total births expected = ("YOUNG ADULT (15-24)" + "ADULT (25-64)") *

Female ratio * Fertility rate people

151. Fertility rate = Initial fertility rate * DELAY1 (Indicated impact of income per

head on fertility rate, Delay impacting on fertility) Dmnl

152. GDP at factor costs = PRODUCTIVE CAPITAL / Capital output ratio * Labour

ratio M$/Year

153. Forex available = FOREX RESERVES / TIME STEP M$/Year

154. Labour ratio = Labour available / Labour requirement Dmnl

155. Actual effect of environmental degradation on life expectancy at birth = DELAY1

(Indicated effect of environmental degradation on life expectancy at birth, Delay

impacting on life expectancy) Dmnl

156. Initial labour required per M$ capital = Initial labour demand / Initial productive

capital people/M$

157. Indicated effect of environmental degradation on life expectancy at birth = Lookup

effect on life expectancy (Index of environmental degradation) Dmnl

158. Lookup effect on life expectancy (GET XLS LOOKUPS ('MODEL DATA

PCDI.xlsx', 'DATA', '63', 'B64')) Dmnl

159. Degradation unit per M$ GDP = GET XLS DATA ('MODEL DATA

PCDI.xlsx', 'DATA', '1', 'B59') unit/M$

160. Delay impacting on life expectancy = GET XLS CONSTANTS ('MODEL DATA


161. Environmental restoration budget = GET XLS DATA ('MODEL DATA

PCDI.xlsx', 'DATA', '1', 'B61') M$/Year

162. Unit restoration cost = GET XLS DATA ('MODEL DATA PCDI.xlsx', 'DATA',

'1', 'B58') M$/unit

163. Restoration rate = Environmental restoration budget / Unit restoration cost

unit/Year

164. Foreign debt maturity = GET XLS DATA ('MODEL DATA PCDI.xlsx', 'DATA',

'1', 'B35') Year

165. VAT fraction of tax revenue = GET XLS DATA ('MODEL DATA PCDI.xlsx',

'DATA', '1', 'B28') Dmnl

166. Income tax fraction of tax revenue = GET XLS DATA ('MODEL DATA


167. Initial foreign exchange reserves = GET XLS CONSTANTS ('MODEL DATA


168. Initial environmental degradation units = GET XLS CONSTANTS ('MODEL

DATA PCDI.xlsx', 'DATA', 'B60') unit

58

169. Share of domestic debt = GET XLS DATA ('MODEL DATA PCDI.xlsx', 'DATA',

'1', 'B32') Dmnl

170. Net oil price = GET XLS DATA ('MODEL DATA PCDI.xlsx', 'DATA', '1', 'B24')

$/bbl

171. Barrels per million barrels = 1e+06 bbl/Mbbl

172. Oil export = GET XLS DATA ('MODEL DATA PCDI.xlsx', 'DATA', '1', 'B25')

Mbbl/Year

173. Initial tax revenue as a fraction of GDP = GET XLS CONSTANTS ('MODEL

DATA PCDI.xlsx', 'DATA', 'B26') Dmnl

174. Degradation rate = GDP at factor costs * Degradation unit per M$ GDP unit/Year

175. ENVIRONMENTAL DEGRADATION UNITS = INTEG (Degradation rate -

Restoration rate, Initial environmental degradation units) unit

176. Index of environmental degradation = ENVIRONMENTAL DEGRADATION

UNITS / Initial environmental degradation units Dmnl

177. Initial life expectancy at birth = GET XLS CONSTANTS ('MODEL DATA


178. Life expectancy at birth = Initial life expectancy at birth Year

179. Life expectancy at 15 = Initial life expectancy at 15 Year


181. Deaths young adult = "YOUNG ADULT (15-24)" / Life expectancy at 15

people/Year


183. Initial life expectancy at 65 = GET XLS CONSTANTS ('MODEL DATA









188. Birth fraction = Yearly births / Population total 1/Year

189. Death fraction = Total deaths / Population total 1/Year

190. Population total = "VERY YOUNG (0-4)" + "SCHOOL AGE (5-14)" + "YOUNG

ADULT (15-24)" + "ADULT (25-64)" + "OLD (65 over)" people

191. Average capital lifetime = GET XLS CONSTANTS ('MODEL DATA PCDI.xlsx',

'DATA', 'B20') Year

192. Investment effectiveness = GET XLS DATA ('MODEL DATA PCDI.xlsx',

'DATA', '1', 'B22') Dmnl

193. Fraction dependent = ("VERY YOUNG (0-4)" + "SCHOOL AGE (5-14)" + "OLD

(65 over)") / Population total Dmnl

194. Unemployment = Labour supply to the economy - Labour requirement people

195. Labour supply to the economy = ("YOUNG ADULT (15-24)" + "ADULT (25-

64)") * Fraction participating people

196. Fraction participating = GET XLS DATA ('MODEL DATA PCDI.xlsx', 'DATA',

'1', 'B16') Dmnl

197. Desired exchange rate = RATE OF EXCHANGE * Impact on exchange rate

naira/$

198. RATE OF EXCHANGE = INTEG (Change in rate of exchange, Initial exchange

rate) naira/$

59

199. Desired forex reserves = Forex out * Forex stock coverage M$

200. Initial labour demand = GET XLS CONSTANTS ('MODEL DATA PCDI.xlsx',

'DATA', 'B18') people

201. Forex stock coverage = GET XLS CONSTANTS ('MODEL DATA PCDI.xlsx',

'DATA', 'B49') Year

202. Initial exchange rate = GET XLS CONSTANTS ('MODEL DATA PCDI.xlsx',

'DATA', 'B50') naira/$

203. Relative forex stock gap = FOREX RESERVES / Desired forex reserves Dmnl

204 Lookup forex reserves impact on exchange rate (GET XLS LOOKUPS ('MODEL

DATA PCDI.xlsx', 'DATA', '46', 'B47')) Dmnl

205. Impact on exchange rate = Lookup forex reserves impact on exchange rate

(Relative forex stock gap) Dmnl

206. Time adjusting exchange rate = GET XLS CONSTANTS ('MODEL DATA


207. FOREX RESERVES = INTEG (Forex in - Forex out, Initial foreign exchange

reserves) M$

208. Labour availability ratio = GET XLS DATA ('MODEL DATA PCDI.xlsx',

'DATA', '1', 'B19') Dmnl

209. Labour available = Labour requirement * Labour availability ratio people

210. Initial GDPfc = GET XLS CONSTANTS ('MODEL DATA PCDI.xlsx', 'DATA',

'B17') M$/Year

211. Propensity to save = GET XLS DATA ('MODEL DATA PCDI.xlsx', 'DATA', '1',

'B23') Dmnl

212. Depreciation = PRODUCTIVE CAPITAL / Average capital lifetime M$/Year

213. Savings = Disposable income * Propensity to save M$/Year

214. Capital output ratio = GET XLS DATA ('MODEL DATA PCDI.xlsx', 'DATA',

'1', 'B21') Year

215. PRODUCTIVE CAPITAL = INTEG (Investment - Depreciation, Initial

productive capital) M$

216. Private investment = Savings M$/Year

217. Productive capital index = PRODUCTIVE CAPITAL / Initial productive capital

Dmnl

218. Initial productive capital = Initial GDPfc * Capital output ratio M$

219. "ADULT (25-64)" = INTEG (Maturing to adult - Aging-Deaths adult, Initial adult)

people

220. Maturing to adult = DELAY CONVEYOR (Maturing to young adult, "2nd

maturing time", Young adult death fraction, Flat profile , "YOUNG ADULT (15-

24)","2nd maturing time") people/Year

221. "2nd maturing time" = 10 Year

222. Initial young adult = GET XLS CONSTANTS ('MODEL DATA PCDI.xlsx',

'DATA', 'B4') people

223. Aging = DELAY CONVEYOR (Maturing to adult, Aging time, Adult death

fraction, Flat profile, "ADULT (25-64)", Aging time) people/Year

224. Total deaths = Deaths very young + Deaths school age + Deaths young adult +

Deaths adult + Deaths old people/Year

225. Maturing to young adult = DELAY CONVEYOR (Growing to school age, "1st

Maturing time", School age death fraction, Flat profile , "SCHOOL AGE (5-14)", "1st

Maturing time" ) people/Year

226. "YOUNG ADULT (15-24)" = INTEG (Maturing to young adult - Deaths young

adult-Maturing to adult, Initial young adult) people

60

227. Young adult death fraction = Deaths young adult / "YOUNG ADULT (15-24)"

1/Year

228. Participation fraction = GET XLS CONSTANTS ('MODEL DATA PCDI.xlsx',

'DATA', 'B21') 1/Year

229. Initial school age = GET XLS CONSTANTS ('MODEL DATA

PCDI.xlsx','DATA','B3') people

230. Yearly births = Total births expected / Fertile period people/Year

231. Aging time = 40 Year

232. Deaths adult = "ADULT (25-64)" / Life expectancy at 25 people/Year

233. Deaths old = "OLD (65 over)" / Life expectancy at 65 people/Year

234. Deaths school age = "SCHOOL AGE (5-14)" / Life expectancy at 5 people/Year

235. Deaths very young = "VERY YOUNG (0-4)" / Life expectancy at birth

people/Year

236. Female ratio = GET XLS DATA ('MODEL DATA PCDI.xlsx', 'DATA', '1', 'B8')

Dmnl

237. Flat profile ([(0, 0) - (1, 5)], (0, 1), (1, 1)) Dmnl

238. Adult death fraction = Deaths adult / "ADULT (25-64)" 1/Year

239. School age death fraction = Deaths school age / "SCHOOL AGE (5-14)" 1/Year

240. Very young death fraction = Deaths very young / "VERY YOUNG (0-4)" 1/Year

241. Growing time = 4 Year

242. Growing to school age = DELAY CONVEYOR (Yearly births, Growing time,

Very young death fraction, Flat profile, "VERY YOUNG (0-4)", Growing time)

people/Year

243. Initial adult = GET XLS CONSTANTS ('MODEL DATA


244. Initial old = GET XLS CONSTANTS ('MODEL DATA PCDI.xlsx','DATA','B6')

people

245. Initial very young = GET XLS CONSTANTS ('MODEL DATA


246. "1st Maturing time" = 10 Year

247. Net population growth = Birth fraction-Death fraction 1/Year

248. "OLD (65 over)" = INTEG (Aging-Deaths old, Initial old) people

249. Fertile period = GET XLS CONSTANTS ('MODEL DATA

PCDI.xlsx','DATA','B10') Year

250. "SCHOOL AGE (5-14)"= INTEG (Growing to school age - Deaths school age -

Maturing to young adult, Initial school age) people

251. "VERY YOUNG (0-4)" = INTEG (Yearly births - Deaths very young - Growing

to school age, Initial very young) people

252. FINAL TIME = 2051 Year

253. INITIAL TIME = 2021 Year

254. SAVEPER = 1 Year

255. TIME STEP = 0.25 Year

61

APPENDIX 2: SOME BIBLIOGRAPHICAL REFERENCES There are thousands of interesting references in system dynamics. The very few that are listed

below are among the best and meant to provide a general understanding of the tool and of what

it can accomplish.

The reference book worldwide in system dynamics is John Sterman’s Business dynamics,

systems thinking and modelling for a complex world. Professor John Sterman is the head of the

system dynamics group at MIT where system dynamics was born and first applied to

deciphering actual world systems.

An excellent text written by a seasoned system dynamicist to learn system dynamics and its

applications to the environment is Andrew Ford’s Modeling the Environment: an introduction

to system dynamics models of environmental systems published by Island Press.

George P. Richardson, another seasoned system dynamicist, has produced two videos worth

watching: An introduction to system dynamics and Models that matter - system dynamics

applications with impact.

The late Donella Meadows was in 1972 the lead author of The Limits to Growth, a best-selling

and widely translated book. The cautions she and her fellow authors issued then are recognized

today as the most accurate warnings of how unsustainable patterns could, if unchecked, wreak

havoc across the globe. That

book made headlines around the world for its observations that continual growth in population

and consumption could severely damage the ecosystems and social systems that support life

on earth, and that a drive for limitless economic growth could eventually disrupt many local,

regional, and global systems. The findings in that book and its updates are, once again, making

front-page news as we face the realities of climate change, and watch a world of over 7 billion

people deal with the devastating consequences of physical growth.

Donella Meadows has published a number of other books since. Among them Thinking in

Systems, A Primer is a must read.

nigeria agenda 2050: draft final report on …

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