## _wp1525 ## Source details **Canonical URL:** [_wp1525](https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2015/_wp1525.pdf) ## Other formats - [Markdown version](/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2015/_wp1525.pdf.md) - [Structured JSON version](/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2015/_wp1525.pdf.json) --- ### I. Introduction — context and high-level policy messages - Fragile countries emerging from conflict face urgent needs to improve living conditions and provide employment for low skilled, idle youth to consolidate macroeconomic stability and social cohesion. - Eleven out of 19 sub-Saharan African countries in the World Bank’s FY2015 Fragile Countries’ list are resource-endowed (Table 1 excerpt). - Confluence of latent resource wealth, renewed peace/political stability, and fiscal space from HIPC/MDRI debt relief creates opportunity to close infrastructure gaps and improve social outcomes. - Paper uses a variant of the Debt, Investment, Growth and Natural Resources model (DIGNAR) to: - Assess macro-fiscal implications of alternative fiscal rules for public investment over the medium term. - Explicitly account for redistribution through direct cash transfers. - Apply the model to the four Mano River Union Countries (MRU): Côte d’Ivoire, Guinea, Liberia, Sierra Leone. - Four high-level policy messages: - For countries where resource revenue is relatively small, fiscal space for scaling up public investment must also come from expanding the non-revenue tax base, expenditure control, and improving investment efficiency. - A cautious investment scaling up strategy is recommended given limited access to international capital markets and political difficulty of fiscal adjustment. - Sound fiscal regimes combining a royalty, corporate income tax and resource rent tax, plus effective and transparent resource administration, are essential to maximize government revenue over project life. - A simple fiscal rule based on a sustainable non-resource deficit (NRB) is appropriate when natural resource revenue is relatively small as a share of total revenue; it can deliver gradual scaling up financed by resource revenue and sustainable borrowing and is fairly robust to resource revenue uncertainty. - Additional findings: - Fiscal rule based on permanent income hypothesis (PIH) leads to a very conservative investment path. - Using a portion of resource revenue to fund social transfers raises private consumption and welfare in general equilibrium; a small fraction could sustainably expand safety nets and reduce poverty. ### II. Country characteristics and selected statistics (from Table 1 excerpts) - Selected country indicators (values preserved exactly as in source): - Central African Republic: Real GDP per Capita (constant 2005 US$), 282.65; Public Debt to GDP ratio (2013), 0.98; Natural resource revenue (share of total, 2013), 8.46; Poverty headcount* 62.89; Infant mortality rate (0-1 year) per 1,000 live births**, 90.73. - Chad: Real GDP per Capita 741.63; Public Debt to GDP ratio (2013) 1.06; Natural resource revenue (share of total, 2013) 3.26; Poverty headcount* 1.98; Infant mortality rate**, 94.1. - Cote d’Ivoire: Real GDP per Capita 1014.43; Public Debt to GDP ratio (2013) 9.94; Natural resource revenue (share of total, 2013) 4.82; Poverty headcount* 38.87; Infant mortality rate**, 62.8. - Democratic Rep. of Congo: Real GDP per Capita 288.22; Public Debt to GDP ratio (2013) 0.02; Natural resource revenue (share of total, 2013) 8.58; Poverty headcount* 77.8; Infant mortality rate**, 99.92. - Guinea: Real GDP per Capita 308.03; Public Debt to GDP ratio (2013) 9.51; Natural resource revenue (share of total, 2013) 8.74; Poverty headcount* 33.36; Infant mortality rate**, 52.10. - Liberia: Real GDP per Capita 299.42; Public Debt to GDP ratio (2013) 9.81; Natural resource revenue (share of total, 2013) 6.98; Poverty headcount* 38.85; Infant mortality rate**, 56.06. - Madagascar: Real GDP per Capita 265.23; Public Debt to GDP ratio (2013) 4.2...; Natural resource revenue (share of total, 2013) 8.1; Poverty headcount* 34.09; Infant mortality rate**, 40.91. - Mali: Real GDP per Capita 476.23; Public Debt to GDP ratio (2013) 2.11; Natural resource revenue (share of total, 2013) 7.05; Poverty headcount* 4.79; Infant mortality rate**, 61.9. - Sierra Leone: Real GDP per Capita 513.23; Public Debt to GDP ratio (2013) 0.514; Natural resource revenue (share of total, 2013) 2.45; Poverty headcount* 17.11; Infant mortality rate**, 117.48. - South Sudan: Real GDP per Capita 984.01; Public Debt to GDP ratio (2013) 4.69; Natural resource revenue (share of total, 2013) 94.6...; Poverty headcount* 66.7... - Togo: Real GDP per Capita 424.44; Public Debt to GDP ratio (2013) 44.6...; Natural resource revenue (share of total, 2013) 28.26; Poverty headcount* 2.02; Infant mortality rate**, 1. - Footnotes: - * Refers to different years, depending on data availability. - ** Refers to 2012. - Sources cited: UNDP, World Bank Development Indicators, IMF staff Calculations. ### III. Key development challenges in the MRU countries — findings and implications - Two decades of civil conflicts and political crisis severely impacted social and economic indicators in the MRU countries. - Country experiences: - Liberia and Sierra Leone: decade of civil wars. - Côte d’Ivoire and Guinea: protracted socio-political crises. - Liberia and Sierra Leone were more severely affected than Côte d’Ivoire and Guinea (Figure 1). - Common development challenges: - High poverty and inequality; more than half the population in MRU countries lives in poverty. - Acute unemployment and social cohesion challenges associated with a “youth bulge”. - Large infrastructure gaps; transportation and energy bottlenecks are more severe than in other fragile and LIC peers. - Human capital lagging peers; protracted conflicts disrupted health and education systems. - Labor force and jobs: - Labor force grows at about 3 percent per year. - Projected that by 2020 more than 7 million new jobs would have to be created in the four countries. - Most jobs will need to be in agriculture and services because mining and oil are capital intensive and manufacturing is very small (Fox et al., 2014). - Social safety nets: - Most MRU safety nets are embryonic, donor-funded and fragmented; focus on direct food distributions and temporary income support via public works (Appendix 1). - Poverty most severe in rural areas; female- and elderly-led households are typically most vulnerable; food insecurity pervasive in Guinea, Liberia and Sierra Leone. ### IV. Natural resource endowments, FARI projections, and revenue volatility (Box 1 summary) - Resource endowments by country (selected exact points): - Côte d’Ivoire: Proven oil reserves estimated at 100 million barrels. Oil production fell to 25,000 barrels a day in 2013 from a peak of 65,000 barrels a day in 2006. Natural gas proven reserves estimated at 1 trillion cubic feet. Natural gas production averaged 59,000 million of MMBTU over the last decade. - Guinea: About two thirds of global bauxite reserves; largest unexploited iron-ore deposit in Simandou range. - Liberia: Iron ore deposits estimated at more than 2 billion metric tons (bmt); resumed production end-2011. - Sierra Leone: Significant deposits of iron-ore, diamonds, rutile, bauxite, gold; iron-ore production recommenced in 2011. - FARI model inputs and revenue sources: - Inputs: concession agreements, cost structure, production schedules, projected commodity prices (IMF WEO April 2014) and other assumptions. - Revenue sources modeled: royalties, withholding income tax on sub-contractors, and corporate income tax; royalties typically 3–5 percent; corporate income tax materializes only in medium term due to loss-carry-forward provisions. - Scenarios and price assumptions: - Baseline: conservative, incorporates production from projects already under exploitation; prices from WEO 2014 for 2014–19, then constant in real terms. - Optimistic: includes new projects where concession agreements signed and investment ongoing; captures potential upside. - Adverse shock example for Liberia: iron ore prices in 2015–16 adjusted downward by 60 percent (i.e., twice the historical standard deviation), with gradual recovery reaching 90 percent of the latest WEO prices by year five. - Projected revenue magnitudes and volatility (preserve exact phrasing): - Baseline results: resource revenue as a share of GDP is small: resource revenue remains at around 2.5 percent of GDP over the projection period. Resource revenue represents about 16.8 percent of total revenues on average. Resource revenue under the baseline will not suffice to finance the transformative investments envisaged; external borrowing would be required. - Optimistic results: potentially much larger revenue if fiscal terms applied as projected; Guinea: if Simandou projects unfold as planned, iron ore revenue could reach almost 20 percent of GDP by 2026. Mining country revenue profiles under optimistic scenario are much more volatile and lumpy than Côte d’Ivoire’s oil profile. ### V. Fiscal frameworks and recommended rule (NRB) — design and calibration - Current practice and concerns: - Côte d’Ivoire, Liberia, Sierra Leone: extractive revenues including one-off payments are spent; no savings for future generations under current investment plans and baseline revenues. - Guinea: Special Investment Fund (SIF) created with US$250 million initial endowment from a US$700 million one-off receipt; SIF expected to be depleted by end-2014. - Institutional constraints (weak institutions, poor governance, low-quality data) and production-volume uncertainty limit fiscal rule choices. - Recommended focus: manage revenue volatility and avoid fiscal pro-cyclicality via a non-resource balance (NRB) target rule rather than a non-resource primary balance (NRPB). - Sustainable NRB target rule (formulation and example): - Total expenditure in real terms capped by a sustainable NRB deficit target; current spending fully financed by non-resource revenue (NRR); resource revenue allocated to infrastructure and possibly human capital; any surplus accumulated in a natural resource fund. - Example formulation: TE = NRR / (1 - NRB), where TE is total expenditure, NRR is non-resource revenue, and NRB is the non-resource deficit target (expenditure less non-resource revenue as a share of expenditure, in percent). - Calibration under baseline (selected country calibrations preserved exactly): - Liberia: - Sustainable NRB deficit target estimated to average 20 percent of the NRR during 2014–17, allowing scaling up capital spending to an annual average of 9.8 percent of GDP during that period. - NRB target set to decline by one percent per year thereafter, bringing annual average investment path to 7.1 percent of GDP in 2017–25 and around 5 percent of GDP thereafter. - Near 3.7 percent of GDP average investment during 2009–12 noted as comparison. - Côte d’Ivoire: - NRB target deficit estimated to average 25 percent of the NRR stream for 2014–17, or an annual investment level equal to 7.9 percent of GDP (up from an annual average of 2.2 percent of GDP). - NRB target to be reduced annually by 1 percent in line with debt limits implied by debt sustainability analysis. - Optimistic calibration examples: - Liberia: - NRB deficit target increased to 25 percent of projected NRR for 2014–17, equal to an annual capital spending of 12 percent of GDP. - NRB deficit target reduced by 1 percent thereafter, bringing capital spending to an annual average of 9.0 percent of GDP between 2018 and 2025 and to 6.6 percent of GDP thereafter. - Côte d’Ivoire: - Given limited additional revenue potential, rule calibration maintained as in the baseline. - Comparison to PIH and MPIH: - NRB allows frontloading of investment while smoothing spending; PIH emphasizes intergenerational smoothing and implies lower immediate investment paths when resource revenue is low. - Quantitative comparisons (selected preserved values): - Liberia, baseline: PIH-based rule implies investment path well below authorities’ envisaged path; PIH equals the rate of return on the PV of the projected natural resource wealth (about 1.8 percent of GDP), plus investment financed with the government’s own resources (about 2 percent of GDP). - Côte d’Ivoire, baseline: under PIH, public investment projected to equal on average the sum of the annual return on the PV of resource wealth (equal to 2.3 percent of GDP) and of grant-financed investment (1.3 percent of GDP). - Liberia, optimistic: pure PIH estimate is 4.3 percent of GDP, raising the investment path to an average of 10.3 percent of GDP during 2015-19. - Côte d’Ivoire, optimistic: under PIH the pure estimate of public investment ratio is only slightly higher than under the baseline at 3 percent of GDP. ### VI. Public investment efficiency, absorptive capacity, and macro simulations (Box 2 and DIGNAR results) - Public Investment Management Index (PIMI) and PFM: - Aside from Côte d’Ivoire, MRU countries perform poorly on PIMI compared to LIC and SSA peers; PEFA surveys indicate low scores for procurement systems and internal controls. - Any scaling up must be paired with improvements in public finance management systems to select high-growth projects and implement them timely. - Simulation approaches compared: - Approach 1: Public investment scaled up per NRB rule; transfers maintained at initial share of GDP. - Approach 2: Transfers increase to 1–2 percent of GDP while public investment reduced equally so combined spending unchanged. - Conservative approach: PIH-based public investment paths (much lower than NRB). - Liberia simulation highlights (exact figures preserved): - Baseline (NRB rule): front-loaded investment at 10–11 percent of GDP between 2014 and 2017; investment falls to about 6 percent of GDP starting 2022 to maintain public capital ~80 percent above trend; resource revenues low—below 3 percent of GDP for most years—requiring borrowing; total debt increases from 32 percent to almost 60 percent of GDP; consumption tax rate increases by two percentage points to stabilize debt. - PIH scenario: public investment below 4 percent of GDP in most years; resource fund reaches 32 percent of GDP by 2026; lower non-resource GDP growth and private consumption since revenue saved rather than invested. - Optimistic NRB: public investment reaches 13.4 percent of GDP in 2016; resource fund accumulates to 12.4 percent of GDP in 2026. - Transfers added: transfers gradually increase to 1.5 percent of GDP; public investment scales to 10 percent of GDP between 2014 and 2016 then stabilizes at 5 percent of GDP; private consumption increases as majority of households are hand-to-mouth. - Investment efficiency assumed 50 percent under baseline; falls to about 40 percent in first few years under optimistic scenario due to capacity constraints. - Adverse shock: resource revenues drop below 1 percent of GDP 2015–2017 and stay below 2 percent thereafter; debt increases more and consumption taxes must rise more; if fiscal adjustment constrained, public investment must be cut starting 2017. - Côte d’Ivoire, Guinea, Sierra Leone simulations (key preserved findings): - Côte d’Ivoire: oil revenues small; scaling-up requires substantial borrowing and higher consumption taxes; even with consumption tax raised by 3 percentage points, total debt climbs to almost 80 percent of GDP in 2026; without that tax increase public debt would climb to over 100 percent of GDP. PIH investment at 2–3 percent of GDP yields little growth in non-resource GDP and private consumption. - Guinea: baseline resource revenues 2–4 percent of GDP; optimistic scenario projects resource revenues jump to 17–19 percent of GDP starting 2022. If optimistic revenues do not materialize and consumption taxes cannot increase, public debt could approach 100 percent of GDP in 2026. - Sierra Leone: baseline resource revenues around 1 percent of GDP; keeping investment at almost 8 percent of GDP requires substantial borrowing; without consumption tax increases government debt would rise to almost 60 percent of GDP in 2026. Optimistic scenario projects resource revenue increasing to over 6 percent of GDP after 2022; with tax increases debt manageable, without them debt rises to 60 percent of GDP in 2026. - General lessons: - Trade-off between scaling up public investment and debt sustainability: frontloaded public capital boosts non-resource GDP and private investment but often requires borrowing given baseline revenues. - Fiscal adjustment costs: raising consumption taxes stabilizes debt but contracts private consumption, offsetting growth gains. - Absorptive capacity constraints: rapid scaling up can lower investment efficiency; “investing in investment” (improving PIMI/PFM) yields significant returns. - Price/downside risks: negative resource price shocks can have large consequences for debt dynamics; conservative scaling-up recommended where capacity to adjust is weak. ### VII. Allocating resource wealth to social protection and recent SSN experience (Box 3 summary) - Definitions and regional patterns: - Social protection includes social assistance (cash/in-kind transfers), social insurance, passive and active labor market programs. - In SSA, safety nets are most prevalent; spending on social safety nets in Africa averages about 1.7 percent of GDP and 4.4 percent of government spending, with donors main financiers. - Empirical evidence: - Conditional cash transfers effective in Latin America; require detailed household information and administrative capacity. - Pilot conditional cash transfer in Liberia suggests improvements in school enrollment, food security, child and adult health and local economy but faced targeting, misuse, and monitoring challenges. - Policy recommendations for MRU: - Develop a few key safety net programs based on careful country analysis while building administrative capacity. - Initial priorities: select a few cash transfer programs proven effective at targeting most vulnerable and expand them. - Program design aspects: (i) effective targeting using poverty maps and household surveys; (ii) improved coverage and coordination among providers; (iii) stronger institutional/administrative arrangements for beneficiary selection, registration, payment systems; (iv) efficient monitoring mechanisms. - Specific options: seasonal public works, voucher programs, non-conditional cash transfers targeting elderly, school-age children, food insecure. - Consider allocating portion of cash transfers to non-contributory pension schemes for vulnerable elderly and disabled war victims. - Social transfers and fiscal space: - DIGNAR simulations: direct transfers immediately raise private consumption due to high share of hand-to-mouth households; earmarking part of resource revenue to cash transfers can expand safety nets sustainably and enhance transparency. - Current social safety nets spending: Sierra Leone ~3½ percent of GDP; Liberia ~1½ percent of GDP (excluding recent turmoil in Guinea and Côte d’Ivoire). - Key conclusions: - Tapping resource potential can create fiscal space for infrastructure and inclusive growth, but uncertainty in resource projection warrants caution. - Simple fiscal rules based on sustainable NRB can be robust to resource revenue uncertainty. - Fragile countries with weak capacity should adopt more conservative scaling-up plans and start saving even small amounts of resource revenue early to build buffers. ### VIII. Fiscal regimes and resource revenue scenarios by country (selected calibrated assumptions) - Côte d’Ivoire (Baseline and Optimistic): - Baseline: Crude oil production assumed to reach 193,000 barrels per day by 2026 from 25,000 barrels per day in 2013; oil revenue increase from 1 percent of GDP (5.4 percent of total revenue) in 2013 to about 2.8 percent of GDP (9.9 percent of total revenue) by 2026, before declining to 1.9 percent of GDP (6.2 percent of total revenue). - Optimistic: crude oil production about 200 000 barrels per day by 2020 and 250 000 barrels per day by 2028; petroleum revenue expected to reach about 3.9 percent of GDP (16.8 percent of total revenue) by 2020; average 3.5 percent of GDP (12.8 percent of total revenue) over rest of period. - Guinea: - Baseline: mining revenue increase from 2.8 percent of GDP in 2014 to 3.9 percent of GDP in 2020; mining revenue roughly 24 percent of total government revenue in 2020. - Optimistic: Simandou-led production (investment around US$20 billion) could represent roughly 50 percent of total exports, reaching almost 80 percent from 2020 onwards. - Liberia: - Baseline: government revenue take expected to increase slightly from about 2 percent of GDP in FY2013 to a 2.3 percent annual average over the medium to long-term; combined production at full capacity expected to reach 20 million metric tons annually starting in 2021. - Optimistic: additional projects could increase production by 27 million metric tons per year; government revenues from iron-ore could reach 5.2 percent of GDP by 2021 (up from around 2.2 percent of GDP in baseline). - Sierra Leone: - Baseline: only Phase I iron-ore projects implemented; fiscal revenue from royalties primarily. - Optimistic: peak iron-ore production around 2022 at ~60 million tons p.a., sustained through early 2030s; tax revenues could initially be 50–60 percent higher than baseline before 2020, thereafter increase 3 fold through 2025 and briefly increase tenfold in 2025–28 from corporate income tax. ### IX. Model specification, solution method, calibration, and key structural parameters (Appendix 3 summary) - Model overview: - Real dynamic general equilibrium small open economy with households (optimizing and hand-to-mouth), firms (nontraded, traded non-resource, natural resource), and government with fiscal instruments and resource fund. - Public investment is an input to production; public investment paths are exogenous and implied by fiscal rules. - Resource fund accumulates inflows and can be drawn down; external commercial borrowing used if resource fund insufficient. - Investment efficiency less than unity; efficiency drops when scaling up beyond absorptive capacity. - Households: - Two types: optimizing fraction ω and hand-to-mouth fraction 1−ω. - Consumption aggregation is CES with parameter χ; labor supply has CES with parameter ρ. - Firms and resources: - Resource production treated as exogenous process; revenue through royalties r_o p_O O. - Traded sector TFP has learning-by-doing externalities to capture Dutch disease effects. - Government and fiscal rules: - Government budget constraint includes grants, transfers, user fees, public investment, and three debt instruments: external concessional (D_c), external commercial (D_x), domestic (D_d). Concessional loans exogenous. - Risk premium on external commercial debt depends on deviations of external public debt-to-GDP from initial steady state. - Fiscal adjustment instruments focused on consumption and labor income taxes with policy rules and bounds. - Public investment efficiency and absorptive constraints: - Efficiency function e(I^G/Y) with threshold; law of motion G_{t+1} = (1 − δ_G) G_t + e(I^G_t) I^G_t. - Steady-state investment efficiency set to 0.5; efficiency for additional investment exceeding threshold drops to 0.35. - Solution and calibration: - Perfect foresight solution computed using dynare’s nonlinear solver at yearly frequency for a 1000-period horizon. - Initial steady state calibrated to recent country conditions. - Key calibrated values (preserved exactly where given): - ω: 0.25 (implying 75% hand-to-mouth) - inverse intertemporal substitution elasticity — 2.94 - inverse Frisch labor elasticity — 10 - χ: 0.44 - output elasticity w.r.t public capital — .05–.14 (chosen to target annual net return to public capital of 20%) - investment adjustment cost — 25 - annual depreciation rate of public capital — 0.07 - annual depreciation rate of private capital — 0.10 - learning-by-doing parameter — 0.1 - steady-state efficiency of public investment — 0.5 - lower efficiency on additional investment when constrained — 0.35 - net real rate earned by resource fund — 2.7% - net real rate on external commercial debt — 6% ### X. Policy recommendations and strategic implications (synthesized from analysis) - Adopt a cautious, phased scaling-up of public investment anchored by a simple NRB fiscal rule where resource revenue is small relative to total revenue and institutions are weak. - Prioritize measures to raise non-resource revenue and improve expenditure control to reduce reliance on external commercial borrowing. - Invest in strengthening public investment management and PFM (improve PIMI/PEFA indicators) to raise investment efficiency before large frontloaded investment pushes. - Maintain precautionary buffers (resource fund savings) where feasible; even small early savings can provide insurance against shocks and build constituency for sound resource management. - Use a small, targeted portion of resource revenue to scale up cash transfers and social safety nets (1–2 percent of GDP scenarios), prioritizing programs that target the poorest and most vulnerable and that can be implemented with available administrative capacity. - Prepare for downside risks: design contingency plans for adverse commodity price or production shocks that include limits on non-concessional borrowing and trigger-based adjustments to spending/taxation. *Source: _wp1525; IMF staff analysis and model results as presented in the provided content unit.* ### References ............................................................................................................. ### _wp1525 - References ............................................................................................................. ### Boxes (listed) - Box 1: Natural Resources Endowments in the MRU Countries. - Box 2: Public Investment Efficiency in MRU Countries. - Box 3: The Recent Experience with Social Protection Systems. ### Table (listed) - Table 1: Resource-Rich Sub-Saharan African Fragile Countries. ### Figures (listed) - Figure 1: Income Per Capita Trends in MRU Countries. - Figure 2: Social and Infrastructure Indicators in MRU Countries. - Figure 3: Public Investment by Source of Financing, 2003–13. - Figure 4: Current Natural Resource Revenue in MRU Countries. - Figure 5: The IMF’s FARI Model. - Figure 6: Natural Resource Revenue Profiles Under Baseline and Optimistic Scenarios. - Figure 7: Public Investment Paths Under Alternative Fiscal Rules. - Figure 8: Public Investment Scaling Up. - Figure 9: Macroeconomic Impact of Social Transfers. - Figure 10: Investment Efficiency in the Baseline and Optimistic Scenarios. - Figure 11: Adverse Iron-Ore Price Shock. ### Appendixes (listed) - Appendix 1: Poverty Diagnostics and Safety Nets in the MRU Countries. - Appendix 2: Fiscal Regimes and Resource Revenue Scenarios. - Appendix 3: Model Specification, Solution Method, Calibration, and Simulation Results. ### I. INTRODUCTION — Key points and context - Fragile countries, many emerging from conflict, face the urgent challenge of improving living conditions and providing employment opportunities for low skilled, idle youth to consolidate macroeconomic stability and maintain social cohesion. - As indicated in Table 1, 11 out of 19 sub-Saharan African countries in the World Bank’s FY2015 Fragile Countries’ list are endowed with abundant natural resources, though this potential remains mostly untapped. - The confluence of latent resource wealth, renewed peace and political stability, and fiscal space from debt relief under HIPC/MDRI provides these countries with a unique opportunity to close infrastructure gaps and improve social outcomes. - Fragile states face significant constraints: larger physical, human capital, and poverty gaps, and lower administrative capacity. - This paper uses a variant of the Debt, Investment, Growth and Natural Resources model (DIGNAR, see Melina et al., 2014) to: - Assess macro-fiscal implications of alternative fiscal rules for public investment over the medium term. - Explicitly account for redistribution through direct cash transfers. - Apply the model to the four Mano River Union Countries (MRU): Côte d’Ivoire, Guinea, Liberia, and Sierra Leone. - Prior uses of DIGNAR include assessments in Chad, Mozambique, and Kazakhstan (IMF, 2014a; Melina and Xiong, 2013; Minasyan and Yang, 2013). - Four high-level policy messages from the country cases: - For countries where resource revenue is relatively small, fiscal space for scaling up public investment must also come from expanding the non-revenue tax base, expenditure control, and improving investment efficiency. - A cautious investment scaling up strategy is recommended given limited access to international capital markets and political difficulty of fiscal adjustment. - Sound fiscal regimes that combine a royalty, corporate income tax and resource rent tax, together with effective and transparent resource administration, are essential for maximizing government revenue over project life. - A simple fiscal rule based on a sustainable non-resource deficit is appropriate when natural resource revenue is relatively small as a share of total revenue; it can deliver gradual scaling up financed by resource revenue and sustainable borrowing and is fairly robust to resource revenue uncertainty. - A fiscal rule based on the permanent income hypothesis leads to a very conservative investment path. - Using a portion of resource revenue to fund social transfers raises private consumption and welfare in the general equilibrium model, implying that a small fraction could sustainably expand social safety nets and reduce poverty while helping maintain social cohesion. - The paper notes the MRU countries’ development strategies aim to reach middle-income country status during the next decade by scaling up public investment, particularly in infrastructure. ### Country characteristics and selected statistics (from Table 1 excerpts) - The paper identifies multiple resource-rich fragile countries and reports selected indicators for them (values shown exactly as in source table): - Central African Republic: Real GDP per Capita (constant 2005 US$), 282.65; Public Debt to GDP ratio (2013), 0.98; Natural resource revenue (share of total, 2013), 8.46; Poverty headcount* 62.89; Infant mortality rate (0-1 year) per 1,000 live births**, 90.73. - Chad: Real GDP per Capita 741.63; Public Debt to GDP ratio (2013) 1.06; Natural resource revenue (share of total, 2013) 3.26; Poverty headcount* 1.98; Infant mortality rate**, 94.1. - Cote d’Ivoire: Real GDP per Capita 1014.43; Public Debt to GDP ratio (2013) 9.94; Natural resource revenue (share of total, 2013) 4.82; Poverty headcount* 38.87; Infant mortality rate**, 62.8. - Democratic Rep. of Congo: Real GDP per Capita 288.22; Public Debt to GDP ratio (2013) 0.02; Natural resource revenue (share of total, 2013) 8.58; Poverty headcount* 77.8; Infant mortality rate**, 99.92. - Guinea: Real GDP per Capita 308.03; Public Debt to GDP ratio (2013) 9.51; Natural resource revenue (share of total, 2013) 8.74; Poverty headcount* 33.36; Infant mortality rate**, 52.10. - Liberia: Real GDP per Capita 299.42; Public Debt to GDP ratio (2013) 9.81; Natural resource revenue (share of total, 2013) 6.98; Poverty headcount* 38.85; Infant mortality rate**, 56.06. - Madagascar: Real GDP per Capita 265.23; Public Debt to GDP ratio (2013) 4.2...; Natural resource revenue (share of total, 2013) 8.1; Poverty headcount* 34.09; Infant mortality rate**, 40.91; (table shows ellipses indicating missing/partial entries). - Mali: Real GDP per Capita 476.23; Public Debt to GDP ratio (2013) 2.11; Natural resource revenue (share of total, 2013) 7.05; Poverty headcount* 4.79; Infant mortality rate**, 61.9. - Sierra Leone: Real GDP per Capita 513.23; Public Debt to GDP ratio (2013) 0.514; Natural resource revenue (share of total, 2013) 2.45; Poverty headcount* 17.11; Infant mortality rate**, 117.48. - South Sudan: Real GDP per Capita 984.01; Public Debt to GDP ratio (2013) 4.69; Natural resource revenue (share of total, 2013) 94.6...; Poverty headcount* 66.7...; (table shows ellipses indicating missing/partial entries). - Togo: Real GDP per Capita 424.44; Public Debt to GDP ratio (2013) 44.6...; Natural resource revenue (share of total, 2013) 28.26; Poverty headcount* 2.02; Infant mortality rate**, 1. - Sources cited for the table: UNDP, World Bank Development Indicators, IMF staff Calculations. - Footnotes: - * Refers to different years, depending on data availability. - ** Refers to 2012. ### II. KEY DEVELOPMENT CHALLENGES IN THE MRU COUNTRIES — Findings and implications - Two decades of civil conflicts and political crisis have severely impacted social and economic indicators in the MRU countries. - Liberia and Sierra Leone experienced a decade of civil wars; Côte d’Ivoire and Guinea faced protracted socio-political crises. - Liberia and Sierra Leone were more severely affected than Côte d’Ivoire and Guinea (Figure 1). - Common development challenges across MRU countries: - High poverty and inequality. - Acute unemployment and social cohesion challenges associated with a “youth bulge”. - Large infrastructure gaps. - Lack of inclusiveness and competition for natural resources, together with ethnic and political tensions, contributed to coups and civil conflicts. - More than half of the population in MRU countries lives in poverty; progress in reducing poverty has been mixed: - Improved stability enabled Liberia and Sierra Leone to reduce poverty headcounts and improve social indicators. - Guinea and Côte d’Ivoire saw poverty headcounts rise and only modest improvements in multi-dimensional indicators. - Poverty diagnostics: - Poverty most severe in rural areas. - Households led by women and elderly persons are typically most vulnerable. - Food insecurity is pervasive in Guinea, Liberia and Sierra Leone. - Social safety nets are embryonic, mostly donor-funded and fragmented, reaching only a fraction of poorest and most vulnerable groups. - Safety nets mostly focus on direct food distributions (mostly school feedings) or temporary income support during lean season via public works programs (Appendix 1). - Infrastructure and human capital deficits: - Transportation and energy bottlenecks are more severe than in other fragile and LIC peers, identified as binding constraints on growth and private sector investment. - Human capital lags behind peers; protracted conflicts severely disrupted health and education systems (Figure 2). - Labor force and job creation challenge: - Labor force grows at about 3 percent per year. - Projected that by 2020 more than 7 million new jobs would have to be created in the four countries. - Most jobs will need to be in agriculture and services because mining and oil are capital intensive and manufacturing is very small (Fox et al., 2014). - National strategies: - All four countries have multi-year strategies targeting middle income status within 10 to 25 years through scaling up public investment, particularly infrastructure, and promoting inclusive growth via social safety nets. - Domestically-financed investments have remained limited, chiefly in Sierra Leone and Côte d’Ivoire (Figure 3). ### III. NATURAL RESOURCE REVENUE PROJECTIONS — Key observations - Côte d’Ivoire, Guinea, Liberia, and Sierra Leone are clustered in a resource-abundant region with exhaustible resources including diamonds, gold, iron-ore, bauxite, and oil (Box 1). - Natural resources remain largely untapped, explaining relatively low shares of natural resources fiscal revenue to GDP, total government revenue, and exports compared to other resource-rich developing countries (Figure 4). - Mineral extraction is ongoing through concession agreements mostly with foreign companies. - Oil and gas are currently produced only by Côte d’Ivoire, with petroleum exploration projects underway in other MRU countries. - Comparative statistic from IMF (2012a): For resource-rich developing countries, natural resource exports represent on average 72 percent of total exports and 43 percent of total revenue (Appendix 1, Table 1). *Source: _wp1525 - References; https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2015/_wp1525.pdf* ### Box 1. Natural Resources Endowments in the MRU Countries ### Box 1. Natural Resources Endowments in the MRU Countries ### Natural resource endowments by country - Côte d’Ivoire - Produces mainly oil and natural gas, smaller quantities of gold, manganese ore and diamonds (as of 2013). - Unexploited mineral resources: iron ore, bauxite, cobalt, nickel. - Proven oil reserves estimated at 100 million barrels (U.S. Energy Information Administration). - Oil production fell to 25,000 barrels a day in 2013 from a peak of 65,000 barrels a day in 2006. - Natural gas proven reserves estimated at 1 trillion cubic feet. - Natural gas production averaged 59,000 million of MMBTU over the last decade. - Almost all crude oil is exported; natural gas sold to domestic electricity producers. - Since 2011, several production-sharing agreements signed; development and exploration projects underway. - Guinea - About two thirds of global bauxite reserves; current contribution to world market remains marginal. - More advanced production of gold and diamond. - Largest unexploited iron-ore deposit in the world in the Simandou range. - Consortium of three companies undertaking oil exploration. - Potential for substantial increase in revenue inflows if bauxite and iron-ore projects come on stream and concessions are granted transparently and in line with the revised mining code. - Liberia - Endowments include iron ore, gold, diamonds, and potentially petroleum. - Resumed production and exports of iron-ore at end-2011. - Iron ore deposits estimated at more than 2 billion metric tons (bmt); two more projects expected to come on stream in the medium-term. - Offshore oil exploration commenced; commercially-viable deposits yet to be identified. - Government granted several mining concessions in 2010. - Sierra Leone - Significant deposits of iron-ore, diamonds, rutile, bauxite, and gold. - Iron-ore production recommenced in 2011 with two large scale projects underway. - Oil exploration ongoing; commercially-viable reserves yet to be identified. - Iron-ore related revenue collection has increased slowly but is estimated to pick up mirroring projected increase in production. ### FARI model, revenue sources, and data constraints - Methodology - IMF’s Fiscal Analysis of Resource Industries model (FARI Model) applied to Guinea, Liberia, Sierra Leone; similar methodology for Côte d’Ivoire. - Model inputs: individual projects’ fiscal regimes (signed concession agreements), cost structure, production schedules, projected commodity prices adjusted by quality (IMF, World Economic Outlook, April 2014), and other economic assumptions. - Revenue sources modeled - Royalties, withholding income tax on sub-contractors, and corporate income tax. - Corporate income tax materializes only in the medium-term once projects become profitable and investment losses absorbed. - Fiscal regimes rely mainly on royalties (typically 3–5 percent) enabling immediate revenue collection when production starts. - Loss-carry-forward provisions constrain corporate income tax receipts in early project years. - Key data and implementation constraints - Need strict enforcement of fiscal regimes for projections to materialize. - In some cases, contract terms are unknown or differ due to ad-hoc negotiations. - Weak capacity of tax administrations to obtain accurate information from mining companies on production volumes, product quality, and operating costs. - Most MRU countries are amending extractive industries laws to align fiscal regimes with international best practices. ### Scenarios and price assumptions - Scenario definitions - Baseline scenario: projections underpinning IMF-supported program macroeconomic frameworks; conservative, incorporating production from projects already under exploitation. - Optimistic scenario: captures potential revenue from new projects where concession agreements are signed, investment is ongoing, and projects are highly likely to come on stream. - Price assumptions - Prices projected using commodity price projections for 2014–19 from the IMF’s World Economic Outlook (WEO, Spring 2014). - For iron-ore, prices adjusted for content quality and special pricing arrangements. - After the WEO projection period, prices assumed constant in real terms. - Adverse shock simulation - Example adverse scenario for Liberia: iron ore prices in 2015–16 adjusted downward by 60 percent (i.e., twice the historical standard deviation), with gradual recovery reaching 90 percent of the latest WEO prices by year five. ### Resource revenue projections and volatility - Baseline results - Under the baseline scenario, resource revenue as a share of GDP is small: resource revenue remains at around 2.5 percent of GDP over the projection period. - Resource revenue represents about 16.8 percent of total revenues on average. - Resource revenue under the baseline will not suffice to finance the transformative investments envisaged; external borrowing would be required. - Optimistic results and country-specific upside - Optimistic scenario shows potentially much larger revenue if fiscal terms applied as projected, but long project gestation means upside may not materialize within the next decade for all countries. - For Guinea, if Simandou projects unfold as planned, iron ore revenue could reach almost 20 percent of GDP by 2026. - Resource revenue projections for mining countries (Guinea, Liberia, Sierra Leone) under the optimistic scenario are much more volatile and lumpy than Côte d’Ivoire’s oil profile. - Delays or re-phasing of production have large impacts on revenue projections; iron ore price volatility adds further uncertainty. ### Fiscal frameworks and recommended rule (NRB) - Current practice - Côte d’Ivoire, Liberia, Sierra Leone: extractive revenues collected including one-off payments are spent; no savings for future generations under current investment plans and baseline revenues. - Guinea: Special Investment Fund (SIF) created with US$250 million initial endowment from a US$700 million one-off receipt; SIF expected to be depleted by end-2014. - Liberia and Sierra Leone: early stages of considering fiscal rules to manage resource wealth. - Policy considerations and rule choice - Institutional constraints (weak institutions, poor governance, low-quality data) and the predominance of minerals (production-volume uncertainty) limit choice of fiscal rules. - Price-based rule (PBR) is of limited use when uncertainty relates mainly to production volumes. - High poverty and capital gaps reduce emphasis on long-term fiscal sustainability in the short to medium run. - Recommended focus: manage revenue volatility and avoid fiscal pro-cyclicality in short to medium term via a non-resource balance target rule (NRB) as fiscal anchor rather than a non-resource primary balance (NRPB) focused on long-term sustainability. - Sustainable NRB target rule (formulation) - Total expenditure in real terms capped by a sustainable NRB deficit target, where current spending is fully financed by non-resource revenue (NRR), and resource revenue is allocated to infrastructure and possibly human capital, with any surplus accumulated in a natural resource fund. - Example formulation: TE = NRR / (1 - NRB), where TE is total expenditure, NRR is non-resource revenue, and NRB is the non-resource deficit target (expenditure less non-resource revenue as a share of expenditure, in percent). - Calibration under the baseline scenario (selected country calibrations) - Liberia - Sustainable NRB deficit target estimated to average 20 percent of the NRR during 2014–17, allowing scaling up capital spending to an annual average of 9.8 percent of GDP during that period. - NRB target set to decline by one percent per year thereafter, bringing annual average investment path to 7.1 percent of GDP in 2017–25 and around 5 percent of GDP thereafter. - Near 3.7 percent of GDP average investment during 2009–12 noted as comparison. - Côte d’Ivoire - NRB target deficit estimated to average 25 percent of the NRR stream for 2014–17, or an annual investment level equal to 7.9 percent of GDP (up from an annual average of 2.2 percent of GDP). - NRB target to be reduced annually by 1 percent in line with debt limits implied by debt sustainability analysis. - Optimistic calibration example - Liberia - NRB deficit target increased to 25 percent of projected NRR for 2014–17, equal to an annual capital spending of 12 percent of GDP. - NRB deficit target reduced by 1 percent thereafter, bringing capital spending to an annual average of 9.0 percent of GDP between 2018 and 2025 and to 6.6 percent of GDP thereafter. - Côte d’Ivoire - Given limited additional revenue potential, rule calibration maintained as in the baseline. ### Comparison of NRB rule to PIH and modified PIH - General findings - NRB rule allows frontloading of investment while smoothing spending over time, suited for MRU countries with uncertain resource horizons and high short-term needs. - PIH-based rules emphasize intergenerational smoothing and long-term sustainability; in baseline scenarios with relatively low resource revenue, PIH implies lower immediate investment paths than NRB. - Modified PIH (MPIH) can allow frontloading but requires substantial fiscal adjustments later to return to rule-consistent investment paths. - Quantitative comparisons (selected values preserved from source) - Liberia, baseline: PIH-based rule implies investment path well below authorities’ envisaged path; PIH equals the rate of return on the PV of the projected natural resource wealth (about 1.8 percent of GDP), plus investment financed with the government’s own resources (about 2 percent of GDP). - Côte d’Ivoire, baseline: under PIH, public investment projected to equal on average the sum of the annual return on the PV of resource wealth (equal to 2.3 percent of GDP) and of grant-financed investment (1.3 percent of GDP). - Liberia, optimistic: pure PIH estimate is 4.3 percent of GDP, raising the investment path to an average of 10.3 percent of GDP during 2015-19. - Côte d’Ivoire, optimistic: under PIH the pure estimate of public investment ratio is only slightly higher than under the baseline at 3 percent of GDP. - Overall: NRB allows larger frontloading of public investment compared with PIH/MPIH in many baseline cases, while PIH/MPIH can be more sensible in optimistic scenarios with larger resource revenue. ### Macroeconomic modeling: DIGNAR application (overview) - Model purpose - Modified DIGNAR model applied to Liberia, Côte d’Ivoire, Guinea, Sierra Leone to assess macroeconomic and fiscal implications of investment paths under various fiscal rules. - Combines the debt sustainability framework of Buffie et al. (2012) with the natural resource model in Berg et al. (2013). - Key model features - Real dynamic general equilibrium small open economy with households, firms, fiscal authority. - Two types of households: forward-looking optimizing households with access to financial and capital markets; hand-to-mouth households who consume all disposable income each period. - Three production sectors: nontraded goods, non-resource traded goods, and natural resources. - Natural resource firms assumed foreign-owned; production does not employ labor and capital; all resource output exported; resource output subject to a royalty tax. - Public capital is an input to production and increases productivity of private inputs. - Traded goods sector TFP subject to learning-by-doing externalities to capture potential Dutch disease from domestic spending of resource revenues. - Government collects taxes, receives grants/aid, issues domestic and external debt, funds consumption, public investment, transfers, and debt service; includes a resource fund holding international financial assets as stabilization buffer. - Fiscal authority’s public investment path is exogenous and implied by alternative fiscal rules; excess resource revenues accumulated in resource fund; resource fund drawn down under negative revenue shocks; external commercial borrowing used if resource fund insufficient. - Investment efficiency less than unity; absorptive capacity constraints cause scaling up investment too quickly to decrease investment efficiency further. - Simulation setup - Simulations conducted under baseline and optimistic resource revenue scenarios discussed earlier. - Initial transfers to GDP ratios below one percent for all four countries; in experiments transfers rise exogenously from one percent to two percent of GDP. - Government consumption follows trend growth path in all simulations. - External concessional debt path taken exogenously consistent with IMF Debt Sustainability Analysis projections. *Source: IMF staff calculations and analysis from Box 1. Natural Resources Endowments in the MRU Countries* ### Box 2. Public Investment Efficiency in MRU Countries ### Box 2. Public Investment Efficiency in MRU Countries ### Public investment efficiency and institutions - The Public Investment Management Index (PIMI) captures countries’ public investment efficiency through capacity to select, implement, and evaluate projects. PIMI is not available for Liberia. - Aside from Côte d’Ivoire, the MRU countries perform poorly on the PIMI compared to low income countries and other SSA countries. - The Public Expenditure and Financial Accountability assessment (PEFA) survey (unavailable for Guinea) shows low scores for procurement systems and internal controls for non-salary expenditures across MRU countries. - Any scaling up strategy needs to be paired with improvements in public finance management (PFM) systems to select projects with the highest growth dividend and implement them in a timely fashion. ### Simulation approaches analyzed - Two main approaches across the four countries: - Approach 1: Public investment scaled up as implied by the NRB rule; transfer spending as a share of GDP maintained at its initial level. - Approach 2: Transfers as a share of GDP increase gradually, stabilizing at 1 to 2 percent of GDP, with an equal reduction in public investment so combined spending on transfers and investment is the same as in Approach 1. - A conservative investing approach: simulate public investment paths implied by the PIH rule for Liberia and Côte d’Ivoire (much lower public investment relative to NRB-based paths). ### Liberia — detailed simulation results and scenarios - Baseline scenario (NRB rule, left column of figures): - Front-loaded investment: elevated spending at 10–11 percent of GDP between 2014 and 2017. - Investment then gradually decreases to about 6 percent of GDP starting in 2022 to maintain public capital at about 80 percent above the trend growth path. - Resource revenues are low—below 3 percent of GDP for most years—so the investment path requires additional borrowing; no savings in the resource fund until very late in the projection period. - Total debt increases from 32 percent to almost 60 percent of GDP. - Higher public debt triggers a two percentage point increase in the consumption tax rate to stabilize debt growth, damping private consumption. - Conservative PIH scenario: - Public investment kept below 4 percent of GDP in most years. - Resource fund rapidly accumulates, reaching 32 percent of GDP by 2026. - Lower non-resource GDP growth and private consumption as revenue is diverted to savings rather than investment or transfers. - Real exchange rate appreciates much less than in the baseline; Dutch disease is not present under PIH. - Optimistic resource revenue scenario (right column): - Under NRB rule, public investment reaches 13.4 percent of GDP in 2016. - Resource fund accumulates savings, reaching 12.4 percent of GDP in 2026. - Qualitative differences among fiscal approaches similar to baseline. - Social transfers added to the model: - Simulate transfers increasing while offsetting public investment by same amount. - Under baseline, transfers gradually increase to 1.5 percent of GDP; public investment scales up to 10 percent of GDP between 2014 and 2016 before stabilizing at 5 percent of GDP. - Immediate benefit: higher private consumption, driven largely by hand-to-mouth households (majority in the model). - Less public investment reduces public capital buildup and non-resource GDP growth; net private consumption effect is positive for small transfer increases. - Fiscal adjustment and debt sustainability: - Significant borrowing required for front-loaded scaling-up; debt sustainability is a concern if fiscal adjustments are difficult. - Scenario with no tax adjustment: private consumption and investment are higher initially, but debt accumulates to 70 percent of GDP by 2025 with no sign of stabilizing. - Investment efficiency and absorptive capacity: - Investment efficiency assumed 50 percent under baseline; falls to about 40 percent in first few years under optimistic scenario due to management capacity, supply bottlenecks, and institutional quality issues. - Adverse resource revenue scenario: - Resource revenues drop below 1 percent of GDP from 2015 to 2017 and stay below 2 percent of GDP afterward. - Under adverse shock, government debt increases more and consumption tax rates must rise more to stabilize debt; private consumption rises less than baseline. - If fiscal adjustment is constrained, public investment must be cut starting 2017 to maintain debt sustainability. ### Côte d’Ivoire, Guinea, Sierra Leone — key simulation highlights - Côte d’Ivoire: - Main resource is oil; revenue difference between baseline and optimistic scenarios is small. - Resource revenues are a small part of government income; scaling-up approaches (except PIH) require substantial borrowing and higher consumption tax revenues. - Even with a consumption tax rate raised by 3 percentage points, total debt climbs to almost 80 percent of GDP in 2026; without that tax increase, public debt would climb to over 100 percent of GDP. - PIH investment at 2–3 percent of GDP yields little growth in non-resource GDP and private consumption. - Guinea: - High uncertainty in resource revenue projections. - Baseline resource revenues: 2–4 percent of GDP. - Optimistic scenario: resource revenues jump to 17–19 percent of GDP starting 2022. - If optimistic revenues do not materialize and consumption taxes cannot increase, public debt could approach 100 percent of GDP in 2026. - Sierra Leone: - Baseline resource revenues around 1 percent of GDP require substantial additional borrowing to keep investment at almost 8 percent of GDP. - If consumption tax rates cannot increase, government debt would rise to almost 60 percent of GDP in 2026. - Optimistic scenario projects resource revenue increasing to over 6 percent of GDP after 2022; with tax increases debt remains manageable, but without them debt rises to 60 percent of GDP in 2026. ### General lessons and policy implications - Trade-off between scaling up public investment and debt sustainability: - Increasing productive public capital boosts non-resource GDP growth and private investment, but scaling up often requires borrowing given baseline resource revenue projections. - Risk of unsustainable debt accumulation exists, especially where fiscal adjustments are difficult to implement. - Fiscal adjustment costs: - Raising consumption taxes to stabilize debt contracts private consumption and can offset growth gains from public capital. - If fiscal adjustment is politically difficult, a less aggressive, more gradual scaling-up is preferable. - Absorptive capacity constraints: - Rapid scaling up can lower investment efficiency due to weak institutional capacity, supply bottlenecks, and weak project management; additional investment may yield negligible public capital increases if efficiency falls. - For MRU countries, investing in improving investment efficiency (“investing in investment”) would bring significant returns. - Price and downside risks: - Negative resource price shocks can have large consequences for debt sustainability; even limited scaling up can lead to unsustainable debt dynamics if revenues fall and fiscal adjustment is constrained. - Recommended strategy: - Current fiscal strategy—gradual scaling up of public investment—is broadly appropriate given limited fiscal space and absorptive capacity, but further increases in investment will be necessary to overcome infrastructure bottlenecks. - Achieving higher investment while preserving debt sustainability requires structural reforms to: - increase efficiency of public investment and absorptive capacity; - boost non-resource revenue collection; - improve the business climate to crowd in private sector. - The Ebola outbreak highlights the high cost of neglecting social spending (health and social protection). ### Allocating part of resource wealth to social protection - DIGNAR model simulations show direct transfers to households immediately raise private consumption, important given the large share of hand-to-mouth households. - Cash transfers can offset declines in private consumption from fiscal adjustments and make such adjustments politically palatable; they may also aid social cohesion and political stability in post-conflict fragile states. - Earmarking part of natural resource revenue to cash transfers can enhance transparency and accountability and help ensure sustainability; direct redistribution (citizens’ dividend) would likely be problematic where institutional capacity is weak. - Transfers that target the poorest and most vulnerable are more effective at reducing or eliminating the poverty gap. - Using a small portion of resource revenue could help gradually and sustainably expand social protection systems. - Current social safety nets (excluding recent turmoil in Guinea and Côte d’Ivoire) have improved some social indicators but remain embryonic and donor-financed: - Total spending on social safety nets amounts to 3½ percent of GDP in Sierra Leone and 1½ percent of GDP in Liberia. - Policy recommendation: - Design a medium-term national social protection strategy embedded in each country’s development plan, with clear institutional responsibilities and coordination mechanisms; integrate successful existing interventions and ensure coordination with donors. *Source: Box 2. Public Investment Efficiency in MRU Countries (from the provided IMF content unit).* ### Box 3. The Recent Experience with Social Protection Systems ### Box 3. The Recent Experience with Social Protection Systems ### Definitions and scope of social protection - Social protection (SP) interventions typically include: - (a) social assistance programs, such as cash or in kind transfers to alleviate poverty, often termed social safety nets (SSN); - (b) social insurance programs, such as contributory programs, (i.e., pensions, unemployment benefits and health insurance); - (c) passive labor regulations and active labor market programs, such as education and training, credit, and employment services (Holzmann and Jorgensen, 2000). - Social protection systems vary greatly depending on countries’ institutional development and administrative capacity: - In fragile and post-conflict countries interventions consist mainly of donor-provided safety nets in the context of humanitarian interventions. - In OECD economies, social protection systems are primarily insurance-based, linked to formal labor markets, and financed domestically through tax bases (Gentilini and Omamo, 2009). ### Empirical evidence and regional patterns - Sub-Saharan Africa: - Social safety nets are the most prevalent form of social protection in sub-Saharan Africa (Monchuk, 2014, Garcia and Moore, 2012). - Most common forms: school feeding programs, public works programs, in-kind emergency and non emergency programs, transfer programs and general subsidies; very few cash transfer programs. - Spending on social safety nets in Africa averages about 1.7 percent of GDP and 4.4 percent of government spending, with donors being the main financiers (excluding general subsidies). - Evidence suggests social safety nets have a positive long-term impact on the poorest households, allowing them to invest more in health and education. - Conditional cash transfers (Latin America evidence): - Experience suggests effectiveness at reducing income inequality and poverty (Lustig et al., 2013). - These programs require detailed household information and fairly developed administrative systems to target, deliver benefits, and monitor programs. - Pilot experiences in fragile contexts: - Some pilot conditional cash transfers in sub-Saharan Africa show positive results. - A small pilot conditional cash transfer program in Liberia suggests increases in school enrollment, food security, improved child and adult health, and boosted the local economy, but faced challenges including misuse of transfers, difficulties in targeting, and monitoring impact due to lack of data. ### Policy recommendations and program design guidance - Develop a few key safety net programs based on careful analysis of country needs, while building institutional and administrative capacity. - Given institutional and administrative limitations in the MRU country, initial priorities could include selecting a few cash transfer programs that have proven effective targeting the most vulnerable households, and expanding them. - Aspects to consider in program design: - (i) effective targeting based on poverty maps and households surveys; - (ii) improved coverage and increased coordination among providers; - (iii) enhanced institutional and administrative arrangements, particularly for the selection and registration of beneficiaries and payment systems; - (iv) efficient monitoring mechanisms to ensure the highest impact. - Specific options could include: - seasonal public work programs to help with the building of rural roads or other infrastructure; - vouchers programs; - non-conditional cash transfers targeting the elderly, school-age children, food insecure populations. - Labor policies and insurance schemes: - Could be strengthened by allocating a portion of cash transfers to non-contributory pension schemes to targeted groups of vulnerable elderly, notably disabled war victims and jobless adults with disability. ### Key conclusions relevant to resource-rich fragile countries (MRU) - Tapping natural resource potential can help unlock fiscal space to address infrastructure gaps and promote inclusive growth, but limits on authorities’ ability to project resource revenue warrant caution. - For MRU countries: - Sound fiscal regimes and effective and transparent natural resource administration are essential for maximizing government revenue over project life (IMF, 2012b). - Simple fiscal rules based on a sustainable non-resource deficit can be robust to fairly high resource revenue uncertainty. - Model results highlight the merits of a sustainable public investment scaling up strategy, particularly when tax increases are politically unpalatable and access to commercial borrowing is limited. - Higher resource revenue can help MRU countries scale-up social protection programs and reduce extreme poverty. - Fragile countries with weaker capacity to assess and project natural resource revenue, implement complex fiscal rules, and mitigate external shocks should adopt more conservative investment scaling up plans to maintain precautionary buffers. - The Ebola epidemic demonstrates how elusive projections of natural resource revenue can be: - All indications point to significant reductions in current production (at least in Liberia and Sierra Leone) and delays in future mining investment in all three countries, pushing resource revenue further into the future. - Additional donor support can help cover additional spending needs for containing the outbreak in the short term, and rebuilding health systems and safety nets in the medium term, but will compress already paltry budget envelopes. - Starting to save even some nominal amount of natural resource revenue early could build a buffer against external shocks and create an early constituency for sound natural resource management. - The severe impact of the epidemic on poor and vulnerable groups highlights the importance of establishing nation-wide social safety nets that can be scaled up in case of emergencies. ### Appendix — Poverty diagnostics and safety nets in MRU countries (selected points) - Côte d’Ivoire: - Poverty indicators not updated since 2008; authorities estimate slightly more than half the population living below the poverty line in 2011, against 48 percent in 2008 and only 10 percent in 1985. - Real per capita income in 2011 was about 57 percent of its peak 1978 level. - High and broad-based average annual real GDP growth of about 9 percent in 2012–13 likely improved poverty indicators. - Government boosted pro-poor spending from 7.4 to 9.3 percent of GDP in 2011–13, with priority to health and education; a universal health insurance program will begin operating in 2015. - Social safety nets: government spending about 0.04 percent of GDP for targeted social spending and 0.23 percent of GDP if spending on former soldiers is included; small cash transfer, public-work programs, WFP-run school-feeding program; World Bank-supported comprehensive SSN strategy under preparation. - Guinea: - Poverty rates rose from 53 to 55.2 percent over 2007–12 per two small-scale ELEP surveys. - Rising food prices account for over 30 percent of child malnutrition rates; gender and education of household heads identified as main determinants of poverty. - The “Productive Social Safety Net Project” (World Bank) — total cost US$25 million, fully financed over 2013–18 — focuses on social safety nets (95 percent) and labor markets improvement (5 percent) with three components: - (i) labor intensive public works and life skills development in rural areas targeted at youth (US$16.50 million); - (ii) piloting a cash transfer project to improve human capital in rural areas (US$4.50 million); - (iii) strengthening institutional capacity to design and coordinate SSN interventions (US$4 million). - Liberia: - Poverty analysis informed by the 2008 Census and the CWIQ: poverty declined from 64 percent (2007) to 56 percent (2010). - About 80 percent of the labor force in vulnerable employment; 28 percent vulnerable to food insecurity. - Social assistance programs focus on food security (76 percent of total spending) and public works programs targeting the food insecure and unemployed or under-employed (about three quarters of the population). - SSN interventions reached about 830,000 beneficiaries in 2010, or about 24 percent of the population (coverage likely overestimated due to overlap). - Total average benefits cover only between 7 and 20 percent of the poverty line. - Social transfers are highly fragmented and mostly donor-financed (93.8 percent of the total). - Cash-for-work temporary employment projects created temporary employment for 17,000 vulnerable Liberians and transferred US$2 million to these households with an average reduction in the poverty gap of 27 percent, from 17.2 percent to 12.6 percent. - Sierra Leone: - An integrated household survey estimates national headcount poverty declined from 66.4 in 2003 to 52.9 percent in 2011. - Rural headcount poverty declined from 78.7 to 66.1 percent; urban poverty declined from 46.9 to 31.2 percent; but increased in Freetown from 13.6 to [text truncated]. *Source: Box 3. The Recent Experience with Social Protection Systems, _wp1525.* ### 20.7 percent, due to economic migrants. The intensity of poverty has declined, helping to ### _wp1525 - 20.7 percent, due to economic migrants. The intensity of poverty has declined, helping to ### Poverty incidence and trends - Poverty incidence: 20.7 percent, due to economic migrants. - Intensity of poverty: declined, reducing the national poverty gap from 27 to 16.1 percent. - Food poverty: decreased from 68.1 percent in 2003 to 47.7 percent in 2011, led by moderation in urban areas. - Survey findings on poverty incidence: - Highest among larger households (7+ persons). - Higher where the household head is elderly. - Higher where the household head is employed in agriculture. ### Social safety net (SSN) programs and delivery - SSN execution channels: - Line ministries and government agencies involved in social and welfare issues. - Local authorities. - Non Government Organizations (NGOs). - Civil society and faith-based organizations. - Main SSN programs in the last five years: - Free Health Care Initiative (for pregnant women, lactating mothers, and children under 5 years of age). - School feeding programs. - Cash transfers. - Cash-for-work. - Food Security Project. - Youth Employment Program and Youth Enterprise Development. - Programs for the elderly. ### Appendix 2.A — Fiscal regimes (MRU countries) - Côte d’Ivoire (mining and petroleum): - Oil fields: production-sharing agreements (PSAs) give government a share of total oil production; exploration and production rights determined by contracts among government, private companies, and Petroci (manages government’s share). - No royalties, special company profit taxes, or other fees or levies for oil fields (per text). - New mining code (2014) provisions: - Tax incentives for title holders including VAT and customs relief for a broader range of imported goods, income tax exemption for the five first years, property tax exemption on specific land, water tax exemptions. - Maintains royalty system comprising taxes based on surface rent and turnover; rates not specified in the new Code but to be included in the Application Decrees. - Provides for tax stability. - Mining permits subject to grant of 10 percent free carried interest in favor of the government in the share capital of the project company. - Government may acquire up to 15 percent of shares of the project company, additional share at market price. - Guinea (mining): - New mining code approved April 2013 to ensure larger share for government. - Royalties: 3 percent for iron-ore, 0.075 percent for bauxite. - Production tax: between 2 and 5 percent for gold and diamond. - Corporate income tax: 35 percent (some tax holidays often granted). - Export tax applies; exempted from VAT in return. - Committee established to review all 18 existing mining titles and conventions to align with new code. - Contracts published online; expected to reach EITI validation point by April 2014. - Liberia (mining and petroleum): - Current revenue code of November 2011 provides for taxing large-scale mining; governance deemed appropriate to collect a fair share of mining revenues transparently. - Mining fiscal regime projected to raise revenues similar to international benchmarks. - Liberia is a member of the EITI and has made public the signed concession agreements. - Existing concession agreements include ad-hoc fiscal terms negotiated prior to current revenue code which may limit potential fiscal receipts. - Mining fiscal regime comprises royalty, income tax, and surtax on income from high yield projects. - Petroleum regime combines royalty-income tax with contractual terms under production sharing contract (PSC); signed PSCs include ad hoc fiscal terms. - Government working on passing a new petroleum law to improve governance and update the petroleum fiscal regime to international standards. - Sierra Leone (mining): - Tax and royalty regime regulated by Mines and Minerals Act 2009 (MMA) and Income Tax Act 2000 (ITA) as amended up to 2010; MMA cross-refers to ITA. - Five classes of mineral license: reconnaissance, exploration, artisanal, small-scale, large-scale. - Extraction licenses in principle subject to same fiscal terms, but five cases overridden by special agreements ratified by Parliament, providing investor assurances and differing fiscal concessions. - Special agreements vary across investors and may include concessions on corporate income tax, dividend withholding tax, import duties, and reduced royalty rates; unilateral amendment risks litigation. ### Table 1 — Selected fiscal regime parameters (as presented) - Mining Regime (columns: Liberia | Guinea | Sierra Leone | Côte d’Ivoire) - Royalty: 3%-5% | 2%-10% | 3%-5% | 3% - Corporate Income Tax: 30% | 35% | 37.5% | 35% - State Participation: Varies | Varies | Varies | 10% - Additional Benefits Tax: NA | 50% | NA | Accelerated Depreciation - Depreciation: 2.5%-30% | 20%-33% | 20%-100% | NA - Loss Carry Forward: 5 yrs. | 3 yrs. | Indefinitely | NA - Withholding Taxes on Dividends: 15% | 15% | 10% | 12% - Withholding Taxes on Interest: On columns provided (see source for full matrix) - Withholding Taxes on interest to non residents: 30% | 20% | 0% | 18% - Withholding Taxes on royalties to non residents: 30% | 10% | 25% | 20% - Capital Gains Tax (where specified): 20% (column alignment per source table) - Petroleum Regime (selected entries) - Signature Bonus: Varies | - | - | $300,000 - Production Bonus: - | - | - | US$1 M–US$10 M - Royalty (Oil offshore): 12%-15% (Liberia) | 10% (Guinea) | 10%, 6.5%, 8% (Sierra Leone) | - - Gas royalty: 12%-15% (Liberia) | 10% (Guinea) | - | - - Cost Recovery Limit: 70% (Liberia) | 75% (Guinea) | NA | 40% - Production Sharing: 40%-60% (Liberia) | 20%-60% (Guinea) | NA | 60%-90% - Corporate Income Tax (petroleum): 35% (Liberia) | 35% (Guinea) | 30%, 37.5% (Sierra Leone) | - - State Participation (petroleum): 20% (Liberia) | 15% (Guinea) | NA | 10% ### Appendix 2.B — Resource revenue scenarios by country Côte d’Ivoire - Baseline assumptions: - Gradual increase in oil and natural gas production as technical problems fixed and new discoveries developed, especially near maritime border with Ghana. - Crude oil production: assumed to reach 193,000 barrels per day by 2026 from 25,000 barrels per day in 2013, and remain flat thereafter. - Natural gas production: from about 75,000 million BTU in 2013 to 110,000 million BTU by 2024, remaining flat thereafter. - Oil revenue projections: - Increase from 1 percent of GDP (5.4 percent of total revenue) in 2013 to about 2.8 percent of GDP (9.9 percent of total revenue) by 2026, before declining gradually to 1.9 percent of GDP (6.2 percent of total revenue). - Optimistic scenario (oil and natural gas only): - Crude oil production: about 200 000 barrels per day by 2020 and 250 000 barrels per day by 2028. - Natural gas production: reach 200,000 million BTU by 2025 and 340,000 million BTU by 2030. - Petroleum revenue: - Expected to reach about 3.9 percent of GDP (16.8 percent of total revenue) by 2020. - Average 3.5 percent of GDP (12.8 percent of total revenue) over the rest of the period. - Note: authorities’ projections are more ambitious, with oil production expected at 200,000 barrels per day within five years (per footnote). Guinea - Baseline scenario phases: - 2014–2016: mining activity from existing gold, bauxite and diamond extraction representing 50 percent, 33 percent and five percent of total exports respectively. - 2017 onwards: bulk of mining hinges on Rio Tinto-led Simandou iron-ore project (investment around US$20 billion, expected to start in 2017), projected to represent roughly 50 percent of total exports, reaching almost 80 percent from 2020 onwards. - Mining revenue projection: - Increase from 2.8 percent of GDP in 2014 to 3.9 percent of GDP in 2020. - Mining revenue to become roughly 24 percent of total government revenue in 2020, compared to around 15 percent in 2014. - Optimistic scenario key potential projects (may change outlook substantially): - Expansion of CBG capacity: initial increase of 9 million tons by 2017 and further increase of 5 million tons by 2022; investment US$1 billion. - China Power Investment (CPI) US$6 billion investment to extract bauxite and build an alumina refinery; initial production 4 million tons of alumina, to be doubled in second stage; construction expected to start in 2014. - United Arab Emirates agreement for a $5 billion investment project in bauxite sector. - Russian company COBAD S.A. potential US$4 billion investment expected to start in 2014 for estimated production of 9 million tons of bauxite a year (possible increase to 12 million tons). Liberia - Baseline scenario: - Reflects activity of two mining projects under operation (Arcelor-Mittal and China Union); other projects not included due to limited information. - Exports of iron-ore expected to exceed 50 percent of total exports by 2017. - Government revenue take expected to increase slightly from about 2 percent of GDP in FY2013 to a 2.3 percent annual average over the medium to long-term. - At full capacity, combined production and exports from the two companies expected to reach 20 million metric tons annually starting in 2021. - Estimated government revenues include royalties and withholding taxes on subcontractors. - Corporate income tax projected to begin flowing only after 2020 given loss-carry-forward provisions in the revenue code. - Emphasis: strong oversight on concessionaires critical to ensure government collects its share and reduces transfer pricing risks. - Optimistic scenario: - Includes two additional large iron-ore projects: Western Cluster (under construction, production expected by 2015) and Putu (may come on stream by 2018). - Combined additional production estimated annual average of 27 million metric tons per year. - Government revenues from iron-ore production could reach 5.2 percent of GDP by 2021 (up from around 2.2 percent of GDP in the baseline scenario). - Iron-ore related revenues as a share of total revenues could represent up to close to 22 percent compared to less than 11 percent in the baseline. Sierra Leone - Baseline scenario: - Assumes only implementation of Phase I of ongoing iron-ore projects. - Fiscal revenue comes only from royalty; realization of corporate income tax contingent on project profitability timelines and expansion. - Iron-ore exports expected to decrease gradually from 55 percent of total exports in 2014 to less than 50 percent over the medium-term. - Optimistic scenario: - Includes full expansion to maximum potential of existing mines (African Minerals Limited and London Mining) and start of mine with pending operating license (Cape Lambert Resources). - Peak iron-ore production around 2022 at around 60 million tons p.a., sustained through early 2030s — roughly 120 percent higher than the baseline scenario. - Tax revenue implications: - Initially around 50-60 percent higher than the baseline before 2020 due to royalties increasing with production. - Thereafter, revenues increase 3 fold through 2025 due to projected dividend withholding taxes. - Revenues briefly increase tenfold in 2025–28 from corporate income tax. - Assumption: additional future revenue would allow for higher public investment in the medium term (2015–19), increasing by an average 1.7 percent of projected GDP financed through external non-concessional borrowing. *Source: _wp1525 (excerpt).* ### Appendix 3. Model Specification, Solution Method, Calibration, and Simulation Results ### Appendix 3. Model Specification, Solution Method, Calibration, and Simulation Results ### A. Households - Two household types: - Optimizing (OPT): fraction ω have access to capital markets and can trade contingent securities and own firms. - Hand-to-mouth (HTM): fraction 1− ω are financially constrained and consume all disposable income each period. - Consumption aggregation: - Consumption basket is a CES aggregate of traded goods (T) and nontraded goods (N): C_i = [φ^(1/χ) C_Ni^((χ−1)/χ) + (1−φ)^(1/χ) C_Ti^((χ−1)/χ)]^(χ/(χ−1)), i = OPT, HTM (Equation (1)). - φ is degree of home bias; χ > 0 is intra-temporal elasticity of substitution. - Relative prices of nontraded and traded goods to the consumption basket denoted p_N and p_T; law of one price holds for traded goods; real exchange rate ε defined as price of one unit of foreign consumption basket in units of domestic basket. Unit price of consumption basket equals 1 = p_T^(1−φ) p_N^φ (Equation (2)). - Labor supply: - Each household supplies labor to traded and nontraded sectors. Total labor has CES specification: L_i = [δ^(1/ρ) L_Ni^((ρ−1)/ρ) + (1−δ)^(1/ρ) L_Ti^((ρ−1)/ρ)]^(ρ/(ρ−1)), i = OPT, HTM (Equation (3)). - δ is steady-state share of labor in nontraded sector; ρ > 0 is intra-temporal elasticity of substitution. - Real wage index defined as w_i = [δ w_Ni^(1−ρ) + (1−δ) w_Ti^(1−ρ)]^(1/(1−ρ)) (Equation (4)). - Optimizing households: - Maximize lifetime utility (intertemporal) subject to budget constraint (Equation (6)). - Discount factor β; σ and ψ are inverse inter-temporal elasticity of substitution of consumption and of labor supply; ν is disutility weight of labor. - Effective tax rates on consumption and labor income: τ_c and τ_l. - Domestic government bonds B^d pay q units of consumption basket at t+1; foreign liabilities L pay (1+r^*) units of foreign consumption basket at t+1. - Firms’ profits π_T and π_N enter income; tax rebate on firms’ return on capital included; remittances R and government transfers TR enter budget; μ is user fees of public capital; portfolio adjustment costs on foreign liabilities governed by η and initial steady-state value L̄. - Private sector pays a constant premium s over the interest rate the government pays on external commercial debt r_g^x such that r^x = r_g^x + s (Equation (7)). - Hand-to-mouth households: - Same utility function as optimizing households (Equation (8)); consumption determined by budget constraint (Equation (9)). - Static maximization yields labor supply function (Equation (10)). - Aggregation: - Aggregate consumption, labor, privately owned government bonds, and foreign liabilities computed as weighted sums across household types (Equations (11)–(13)). ### B. Firms - Three production sectors: - Nontraded sector (N), traded sector (T) excluding resource, natural resource sector (O). - Resource output assumed entirely exported. - B.1 Nontraded good sector: - Production: Y_N = A_N K_N^α_KN G^α_GN L_N^α_LN with specification in Equation (14); A_N is total factor productivity, K_N private capital, G public capital, α parameters: labor share and output elasticity w.r.t public capital. - Capital law of motion: K_{N,t+1} = (1 − δ_K) K_{N,t} + I_{N,t} − (ϕ/2)(I_{N,t}/Ī − 1)^2 Ī (Equation (15)), where I is investment, δ_K depreciation, ϕ investment adjustment cost parameter. - Firms choose L_N, K_N, I_N to maximize discounted lifetime profits weighted by marginal utility of consumption; return to capital R_K defined. - B.2 Traded good sector: - Production analogous to nontraded sector (Equation (17)). - Total factor productivity A_T subject to learning-by-doing externalities: A_T = Ā_T (1 + κ (I_T/Y)^{γ}) with formulation in Equation (18), where κ, γ control severity of Dutch disease. - Private capital law of motion analogous (Equation (19)). - Firms choose L_T, K_T, I_T to maximize discounted profits. - B.3 Natural resource sector: - Resource production exogenous AR(1): O_t = ρ_O O_{t−1} + ε^O_t (Equation (21)), with ρ_O autoregressive coefficient, ε^O resource production shock. - International commodity price p_O_t taken as given and evolves AR(1): p_O_t = ρ_P p_O_{t−1} + ε^P_t (Equation (22)), with ρ_P autoregressive coefficient, ε^P price shock. - Resource GDP in domestic consumption basket units: Y_O = p_O O (Equation (23)). - Royalty rate on production r_o; resource revenue each period: Rev_O = r_o p_O O (Equation (24)). ### C. Government - Government flow budget constraint (Equation (25)): - Components include grants, transfers, user fees, government consumption, public investment, and three debt instruments: external concessional debt (D_c), external commercial debt (D_x), and domestic debt (D_d). - Concessional loans taken as exogenous. - Gross real interest rates on concessional and commercial debt are r_c and r_x. r_x includes a risk premium dependent on deviations of total external public debt-to-GDP from initial steady state: r_x = r^* + φ_1 ( (D_ext/Y) − (D̄_ext/Ȳ) ) (Equation (26)) with r^* the risk-free world interest rate and φ_1, φ_2 structural parameters. - Fiscal instruments and assumptions: - Public investment paths (as share of GDP) are exogenous across fiscal approaches analyzed in Section V. - Except for approach that increases transfers, all other approaches assume constant transfers as share of GDP. - Government consumption kept constant as level in a trend-growth path. - C.1 Government purchases: - Government expenditure G_t is CES aggregate of domestic traded and nontraded goods: G_t = [γ^(1/χ) G_Nt^((χ−1)/χ) + (1−γ)^(1/χ) G_Tt^((χ−1)/χ)]^(χ/(χ−1)) (Equation (27)), where γ is weight on nontraded goods; same χ as private consumption. - Government consumption price index p_G defined in Equation (28); note p_G is time-varying and weight for additional government spending, γ̃, can differ from steady-state γ̄. - C.2 Public investment efficiency, absorptive capacity constraints, and public capital depreciation: - Investment efficiency for additional investment above a threshold drops from steady-state efficiency value ē to lower value e_low. - Let I^G/Y be public investment-to-output ratio; efficiency function e(I^G/Y) specified in Equation (29) with threshold Ī^G/Y set where efficiency costs trigger. - Law of motion of public capital: G_{t+1} = (1 − δ_G) G_t + e(I^G_t) I^G_t (Equation (30)), where δ_G depreciation of public capital. - C.3 Resource fund and fiscal gap: - Resource fund foreign asset value F_t evolves as F_{t+1} = (1 + r_F) F_t + Inflows_t − Outflows_t, with constant gross real interest rate r_F (Equation (31)). Resource fund cannot accumulate liabilities: when F_t < 0 it is set to zero. - Given paths of public investment, concessional borrowing, foreign aids and grants, the government budget constraint can be rewritten to isolate a fiscal gap term (Equations (32)–(35)). - Covering the fiscal gap entails domestic and/or external commercial borrowing or adjustments in fiscal instruments. In analysis, when government must borrow we assume only external commercial debt can be accessed (D_d = 0). - Fiscal adjustment instruments focused on: consumption and labor income tax rates. Debt-stabilizing (target) values of the two tax rates computed using Equations (36) and (37). - Tax rates follow policy rules with speed parameters ζ and upper bounds τ_c^max and τ_l^max (Equations (38)–(41)). ζ’s control speed of fiscal adjustments; (D^d + D^x)/Y is sum of domestic and external commercial debt as share of GDP entering adjustment rule. ### D. Identities and Market Clearing Conditions - Nontraded goods market clearing condition specified in Equation (42). - Balance of payments condition specified in Equation (43), where dividend from resource production is assumed to be received by foreigners and set to zero net for domestic receipts; current account deficit c is defined in Equation (44). - Total real GDP Y is given by Y = Y_N + Y_T + Y_O (Equation (45)). ### E. Model Equilibrium, Solution, and Calibration - Equilibrium system comprises first-order conditions of households and firms, market clearing conditions, balance of payments, and exogenous paths of resource variables (production quantities, prices, revenues as share of GDP), public investment and transfers, and concessional debt. - Solution method: - Perfect foresight solution computed using dynare’s nonlinear solver. - Resource fund process: to guarantee non-explosiveness a small autoregressive coefficient ρ_small ∈ (0,1) is attached to F and is activated after first 100 years of simulations. The model is typically solved at a yearly frequency for a 1000-period horizon. - Calibration: - Initial steady state calibrated to recent country conditions using national accounts and fiscal data. - For countries with multiple resource commodities, production and price shocks calibrated to the major commodity; resource revenue paths used in simulations include all resource commodities and resource tax rates are endogenously determined to target a particular path. - Many structural parameters taken from Melina et al. (2014) when country-specific estimates unavailable. - Key calibrated choices and deviations: - Output elasticity with respect to public capital, α_G, chosen such that each country has an annual net rate of return to public capital at 20 percent. - Public investment efficiency set to 0.5 (steady state). Investment efficiency for additional investment exceeding threshold drops to 0.35. Threshold set at 60 percent of initial investment as share of GDP. - Share of forward-looking households ω set to 0.25, implying 75 percent of households are hand-to-mouth, consistent with Financial Access data (Ardic et al., 2013). - Table 1 in the source lists calibrated values of key structural parameters. *Source: Appendix 3. Model Specification, Solution Method, Calibration, and Simulation Results* ### Appendix 3. Table 1. Calibration of Key Structural Parameters Across the Four Countries ### Appendix 3. Table 1. Calibration of Key Structural Parameters Across the Four Countries ### Calibration: Household and Labor Parameters - ω: share of optimizing households — 0.25 (implying 75% of households are hand-to-mouth) - inverse of intertemporal substitution elasticity — 2.94 (Ogaki et al. (1996)) - inverse of Frisch labor elasticity — 10 (minimizing income effect in labor) ### Calibration: Trade and Production Elasticities - χ: substitution elasticity, traded & nontraded goods — 0.44 (Stockman and Tesar (1995)) - substitution elasticity between [goods unspecified in excerpt] — 1 (Horvath (2000)) - labor income share in nontraded good sector — 0.45 (Buffie et al. (2012)) - labor income share in traded good sector — 0.6 (Buffie et al. (2012)) ### Calibration: Public Capital and Investment Parameters - output elasticity with respect to public capital — .05–.14 (Chosen to target the annual net return to public capital is 20%) - investment adjustment cost — 25 (Beg et al. (2010)) - annual depreciation rate of public capital — 0.07 (Melina et al. (2014)) - annual depreciation rate of private capital — 0.10 (Melina et al. (2014)) ### Calibration: Externalities and Efficiency - learning-by-doing parameter ( , ) — 0.1 (Berg et al. (2010), mild externality) - steady-state efficiency of public investment ( ) — 0.5 (Pritchett (2000) for SSA countries) - lower efficiency on additional investment when absorptive capacity is constrained ( ) — 0.35 (Arestoff and Hurlin (2006)) ### Calibration: Rates on Funds and Debt - net real rate earned by resource fund — 2.7% (Gros and Mayer (2010)) - net real rate on external commercial debt ( ) — 6% (Buffie et al. (2012)) --- ### Appendix 3. Figure 1. Simulation Results: Côte d’Ivoire, Baseline and Optimistic Scenarios Note: The units of y-axis are in percent deviation from a trend growth path, unless specified in parentheses. ### Key series and scales shown (per figure panels) - resource revenue (% of GDP): scale examples shown 0, 1, 2, 3, 4 - public investment (% of GDP): scale examples shown 5, 10 - transfers (% of GDP): scale examples shown 0, 1, 2 - resource fund (% of GDP): scale examples shown 0, 5, 10, 15 - public capital: scale examples shown 0, 50, 100, 150 - non-resource GDP: scale examples shown 0, 5, 10 - private consumption: scale examples shown -5, 0, 5 - private investment: scale examples shown 0, 5, 10 - real exchange rate: scale examples shown -6, -4, -2, 0 - total debt (% of GDP): scale examples shown 50, 100 - investment efficiency (level): scale examples shown 0.4, 0.6 - consumption tax rate (level): scale examples shown 0.08, 0.1, 0.12 ### Scenarios illustrated - baseline scenario - optimistic scenario - investment scaling-up - investment scaling-up with higher transfer - PIH (Perpetual Income Hypothesis) no tax rate increase --- ### Appendix 3. Figure 2. Simulation Results: Guinea, Baseline and Optimistic Scenarios Note: The units of y-axis are in percent deviation from a trend growth path, unless specified in parentheses. ### Key series and scales shown (per figure panels) - resource revenue (% of GDP): scale examples shown 0, 10, 20 - public investment (% of GDP): scale examples shown 5, 10, 15 - transfers (% of GDP): scale examples shown 0, 1, 2 - resource fund (% of GDP): scale examples shown 0, 20, 40 - public capital: scale examples shown 0, 50, 100 - non-resource GDP: scale examples shown 0, 5, 10 - private consumption: scale examples shown -2, 0, 2, 4 - private investment: scale examples shown 0, 5, 10 - real exchange rate: scale examples shown -6, -4, -2, 0, 2 - total debt (% of GDP): scale examples shown 50, 100 - investment efficiency (level): scale examples shown 0.4, 0.6 - consumption tax rate (level): scale examples shown 0.06, 0.08, 0.1 ### Scenarios illustrated - baseline scenario - optimistic scenario - investment scaling-up - investment scaling-up with higher transfer - no tax rate increase --- ### Appendix 3. Figure 3. Simulation Results: Sierra Leone, Baseline and Optimistic Scenarios Note: The units of y-axis are in percent deviation from a trend growth path, unless specified in parentheses. ### Key series and scales shown (per figure panels) - resource revenue (% of GDP): scale examples shown 0, 5 - public investment (% of GDP): scale examples shown 6, 8, 10 - transfers (% of GDP): scale examples shown 0, 1, 2 - resource fund (% of GDP): scale examples shown 0, 5, 10, 15 - public capital: scale examples shown 0, 20, 40, 60 - non-resource GDP: scale examples shown 0, 5 - private consumption: scale examples shown 0, 2, 4 - private investment: scale examples shown 0, 5 - real exchange rate: scale examples shown -2, 0, 2 - total debt (% of GDP): scale examples shown 40, 50, 60 - investment efficiency (level): scale examples shown 0.4, 0.5, 0.6 - consumption tax rate (level): scale examples shown 0.05, 0.06, 0.07 ### Scenarios illustrated - baseline scenario - optimistic scenario - investment scaling-up - investment scaling-up with higher transfer - no tax rate increase *Source: Appendix 3, Table 1 and Figures 1–3 from the provided content unit.* --- _Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2015/_wp1525.pdf_