## DETERMINANTS OF SOVEREIGN SPREADS IN EMERGING MARKETS: IMPLICATIONS FOR GABON (content unit 1gabea2024002)

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---

### A. Empirical strategy and data
- Objective: Estimate determinants of JP Morgan EMBIG spreads (log) for a panel of EMDEs and draw implications for Gabon.
- Model: Fixed effects panel regression:
  - S_i,t = α + β X_i,t + δ Z_t + γ ESG_i,t + η_i + ε_i,t
- Domestic regressors (X_i,t): debt-to-GDP, real GDP growth, primary fiscal balance-to-GDP, total arrears-to-GDP, trade openness.
- Global regressor (Z_t): VIX (Chicago Board Options Exchange’s CBOE Volatility Index).
- ESG indicators (ESG_i,t): HDI, WGI regulatory quality, WGI government effectiveness, ND-GAIN adaptive capacity.
- Sample: Panel of 50 EMDEs covering 2010–21 (reported regressions show number of countries 54 and 52; observations 534 and 482).

### B. Main regression findings (selected coefficients and interpretations)
- Debt-to-GDP:
  - Coefficients: 0.00824*** (column 1) and 0.00758*** (column 2).
  - Interpretation: A one percentage point increase in debt-to-GDP increases spreads by 0.76–0.83 percent (about 6–7 basis points if spreads are at 800).
- Real GDP growth:
  - Coefficients: -0.0112** (column 1) and -0.0157** (column 2).
- Primary balance to GDP:
  - Coefficients: -0.0118* (column 1) and -0.0125** (column 2).
  - Interpretation: A one percentage point improvement in the primary balance-to-GDP narrows sovereign spreads by about 1.2 percent.
- Total arrears to GDP:
  - Coefficients: 0.00614** (column 1) and 0.00625** (column 2).
  - Interpretation: A one percentage point increase in arrears-to-GDP widens spreads by about 0.61–0.63 percent.
- Global volatility (VIX):
  - Coefficients: 0.129** (column 1) and 0.122** (column 2).
  - Interpretation: A one percent increase in the VIX widens sovereign spreads by 0.1 percent.
- Trade openness:
  - Coefficients: -0.515* (column 1) and -0.363 (column 2); point estimate suggests increased trade activity reduces sovereign premium by 30–40 percent, but not robustly significant across specifications.
- Governance and development (ESG indicators):
  - WGI – Government Effectiveness: -0.324** (column 1), -0.275** (column 2).
    - One standard deviation increase reduces sovereign premium by 24–28 percent (i.e., 192–224 basis points for spreads of 800).
  - WGI – Regulatory Quality: -0.696*** (column 1), -0.701*** (column 2).
    - One standard deviation improvement narrows spreads by 50 percent in both models.
  - HDI: -2.243** (column 1), -2.080** (column 2).
    - A 1 percent improvement in HDI reduces sovereign spreads by 2 percent; Gabon’s HDI is 0.71 versus upper-middle income average 0.74.
  - ND-GAIN – Adaptive Capacity: 0.798 (column 2; not statistically significant).
    - Higher exposure to environmental risks increases spreads in sign, but adaptive-capacity coefficient is not statistically significant in this sample.
- Model fit and sample:
  - R-squared: 0.453 (column 1), 0.476 (column 2).
  - Observations: 534 (column 1), 482 (column 2).
  - Number of countries: 54 (column 1), 52 (column 2).

### C. Attribution and scenarios for Gabon
- Attribution of Gabon’s spread increase (2010–14 vs 2015–21):
  - Higher debt stock explains ~50 percent of the increase.
  - Deterioration in governance-related indicators explains about one-third of the increase.
- Investment-grade scenario:
  - Investment grade spreads ≈ 200 basis points, about 400 basis points below Gabon’s February 2024 level.
  - Example multi-pronged pathway:
    - Improve regulatory quality and government effectiveness to the median of Fitch-rated BBB sovereigns — could achieve ¾ of needed reduction in spreads.
    - Reduce debt from 70 percent of GDP to 55 percent (median for BBB sovereigns).
    - Eliminate arrears.
  - Combined measures considered achievable in the medium term and within authorities’ control.

### D. Policy takeaways (quantified impacts)
- Strengthen fiscal stance:
  - Target: reduce debt to around 55 percent of GDP and clear domestic arrears.
  - Potential impact: reduce spreads by some 80 basis points from arrears clearance and fiscal consolidation; save 0.1 percent of GDP in interest costs directly; plus more than 1 percentage point of GDP decline in interest bill due to lower debt level.
  - Requires: significant near-term fiscal adjustment via revenue mobilization, expenditure cuts, and improved public financial management.
- Bolster governance and transparency:
  - Potential impact: reduce spreads by approximately 450 basis points and save 0.5 percent of GDP in interest costs.
  - Mechanisms: lower perceived investment/default risk, improve business environment, support higher growth.
- Enhance growth drivers and economic diversification:
  - Support long-term growth, build external reserves, and contribute to currency union viability.
- Address social vulnerabilities:
  - Active policies to improve livelihoods, education, health, and human capital to support vulnerable populations, improve growth prospects, and reduce country risk.

---

### Box 1 — Literature review: condensed evidence relevant to the model
- Cross-study findings:
  - External vulnerability indicators (international reserves, current account, external debt) associated with lower borrowing costs.
  - Political risk and governance measures (WGI) significantly influence sovereign spreads.
  - Credit rating upgrades to investment grade lower spreads substantially (evidence: 36 percent reduction above fundamentals).
  - Long-term country-specific determinants (fiscal and external measures) vs short-term global factors (VIX) distinction is important.
  - Repayment history and arrears matter for spreads.
- ESG and climate:
  - Governance and social indicators often significant; environmental/physical climate risk linked with higher spreads in some studies.
  - Mixed evidence on environmental factors for EMDEs; ND-GAIN adaptive capacity not robustly significant in this chapter’s regression.
- Correlations (selected):
  - Spread with Debt to GDP: 0.366
  - Spread with Real GDP Growth: -0.284
  - Spread with Primary Balance to GDP: -0.193
  - Spread with VIX: 0.159
  - Spread with WGI – Effectiveness: -0.440
  - Spread with WGI – Regulatory Quality: -0.469
  - Spread with HDI: -0.257
  - Spread with Total Arrears to GDP: 0.223
  - Spread with ND-GAIN, Adaptive Capacity: 0.162

### Key empirical takeaways (from Box 1 and regressions)
- Debt-to-GDP is robustly positively associated with higher sovereign spreads across specifications.
- Better macroeconomic performance (higher real GDP growth, stronger primary balances) associated with lower spreads.
- Global risk sentiment (VIX) raises spreads in several specifications.
- Governance indicators and HDI are strongly negatively associated with spreads.
- Total arrears-to-GDP is positively associated with spreads where included.
- ND-GAIN adaptive capacity does not show a statistically significant association in the reported specification.

---

### PIH limitations and proposed fiscal framework for Gabon
- Limitations of the Permanent Income Hypothesis (PIH):
  - PIH becoming less relevant as the oil wealth horizon shortens; little time to increase savings sufficiently.
  - PIH does not consider returns on higher investment and has other practical limitations.
- Proposed new fiscal framework — three elements:
  - (i) a long-term anchor for the debt to be inherited by post-oil generations;
  - (ii) interim debt anchors while oil production continues, if needed;
  - (iii) operational rules to achieve these anchors.
- Long-term post-oil target (staff recommendation):
  - Target a debt ratio of at most 50 percent of GDP (lower levels may be preferred).
  - Supporting calibrations:
    - Comelli et al. (2023) approach: operational target range between 41 and 50 percent of GDP with a 20 percent of GDP buffer.
    - Eyraud et al. (2018) stochastic simulations: operational target about 45 percent of GDP (to keep debt below 70 percent CEMAC ceiling with 90 percent probability).
  - Post-oil: the 50 percent ratio refers to both GDP and nonoil GDP.
- Interim debt anchors — two options:
  - Option D1 (Debt-to-GDP): near-term anchor 70 percent, then 60 percent over 5–10 years after consolidation, and 50 percent thereafter.
  - Option D2 (Debt-to-nonoil-GDP): start from terminal post-oil target of 50 percent of nonoil GDP and reduce anchor gradually by 5–10 percentage points each decade; illustrative path: 115 → 90 percent of nonoil GDP by 2030, then 80, 70, 60, finally 50 percent.
  - Trade-offs: Option D2 less volatile with oil prices and better accountability.
- Stock and flow corrections; triggers:
  - Stock correction: trigger when debt ratio is 5–10 percentage points above target; reduce deficit to return debt to anchor within five years.
  - Flow correction: trigger when cumulative deviations from the primary balance target exceed 3 percentage points of nonoil GDP; corrections over no more than three years.
  - Escape clauses: specified conditions for temporary suspension in response to large exogenous shocks.
- Operational deficit targets and rules:
  - Near-term objective: bring nonoil primary deficit from 14–15 percent of nonoil GDP to around 2 percent of nonoil GDP by 2027–28.
  - Maintain 2 percent nonoil primary deficit until debt anchor reached; possible operationalization via expenditure growth rule (example: primary spending grows in line with potential GDP, e.g., 5 percent nominal or 3 percent real).
  - Alternative: adopt CEMAC structural balance rule after consolidation; probabilistic outcomes under CEMAC rule:
    - Debt-to-nonoil GDP below 70 percent (60 percent) by 2040 (2050) with 93 (97) percent probability.
- Design criteria for final rule:
  - Fully objective; clearly defined phase transitions; works across states of the world; government policy changes must be deficit-neutral.
- Implementation needs:
  - More transparent, accurate and timely fiscal reporting.
  - Credible budgeting and expenditure execution frameworks.
  - Final decision closer to legislation adoption with targeted technical assistance.

### Appendix I — model assumptions and calibration highlights
- Key parameter values used in analysis (Appendix Table 1):
  - Nonoil GDP growth (휸휸): 4.3 percent
  - Nonoil revenue to nonoil GDP (풚풚풔풔풏풏): 16.1 percent
  - Oil revenue to oil GDP: 23.1 percent
  - Interest rate (풓풓): 4.4 percent
  - Habit parameter (휶휶): 0.7 (robustness: 0.5 and 0.9)
  - Time to oil depletion (푻푻): 30 years
  - Number of simulations (푵푵): 10,000
- Key assumptions on oil:
  - Proven crude oil reserves: 2,000 million barrels in 2022 (OPEC reported).
  - Production declines by 1 percent each year from 2026 onwards.
  - Oil production follows authorities’ projections between 2024 and 2025; with assumptions oil will run out in 30 years.
- Interest rate and habit assumptions:
  - Interest rate constant and estimated as average effective interest rate over 2019–23.
  - Habit formation parameter initially 0.7; robustness checks at 0.5 and 0.9.

---

### Diversification Readiness Index (DRI), constraints and policy priorities
- DRI composition:
  - Combines business environment, macroeconomic policies, trade policy and performance, data quality, and manufacturing performance via averaged z-scores.
  - DRI strongly correlated with Economic Complexity Index.
- Main obstacles to diversification (selected):
  - Weak business environment: regulatory quality, government effectiveness, rule of law, corruption control.
  - Access to finance: low domestic credit, high financing costs, banks reluctant to lend; banks’ deposits ≈ 22 percent of GDP; account ownership at financial institutions 66 percent (middle-income average 72 percent).
  - Infrastructure: uneven access to electricity and internet; electricity access 92 percent (SSA average 51 percent); urban access 99 percent; rural access ≈ 30 percent; internet use 72 percent (SSA average 36 percent); high costs for electricity and internet.
  - Human capital and labor costs: better than SSA average but weaker than middle-income peers; skilled labor scarce; initiatives in vocational training noted.
  - Trade barriers and limited partnerships: high import tariffs, nontariff barriers, bottom 10 percent on OECD Trade Facilitation Indicators in 2022; reduced eligibility for some preferential programs.
  - Data quality: poor statistical capacity hinders strategy assessment.
  - Industrial policy fiscal cost: tax expenditures estimated between 4 and 5 percent of GDP; wood sector 0.4 percent of fiscal revenues while producing 2.3 percent of nominal GDP in 2022.
- Business survey (37 companies): three main obstacles — weak business environment, poor infrastructure, access to finance and human capital constraints.
- Policy priorities to enhance diversification:
  - Governance and transparency reforms: improve fiscal transparency, public financial management, and anti-corruption.
  - Improve financing conditions: accelerate repayment of domestic arrears; fiscal consolidation; establish comprehensive credit bureau; strengthen debt recovery framework and judicial capacity; promote financial deepening.
  - Strengthen fiscal position: reduce public debt and clear external arrears; example: reducing public debt to 55 percent of GDP and clearing arrears could bring about 0.1 percent of GDP in interest savings.
  - Trade policy reforms: remove trade barriers, simplify tariff implementation, work regionally to reduce tariffs, reinforce trade diplomacy to regain AGOA and strengthen EU integration.
  - Strengthen statistical capacity and communication.
  - Reduce costs/distortions of industrial policy: favor institutional improvements, invest in transport and electricity around production sites.

*Source: "DETERMINANTS OF SOVEREIGN SPREADS IN EMERGING MARKETS: IMPLICATIONS FOR GABON" (Selected Issues Paper).*

### References ____________________________________________________________________________ 16

### DETERMINANTS OF SOVEREIGN SPREADS IN EMERGING MARKETS: IMPLICATIONS FOR GABON

### A. Introduction
- Context: Since the onset of the pandemic, heightened volatility, weak market sentiment, and tighter financial conditions raised borrowing costs for EMDEs; Gabon’s EMBIG spreads have hovered around distressed and stressed territories since mid-2022 despite relatively high oil prices.
- Focus: Investigate determinants of sovereign spreads across a panel of 50 EMDEs (2010–21) using a fixed effects panel model and leverage results to draw implications and policy options for Gabon.
- Added features: Inclusion of arrears and Environmental, Social, and Governance (ESG) performance in the model given Gabon’s repayment track record and investor interest in sustainable finance.

### B. Gabon’s Credit Risk Profile: Key vulnerabilities
- Sovereign ratings and market position:
  - Rated Caa1 by Moody’s and B- by Fitch (non-investment grade).
  - An enhancement of one notch in sovereign rating could potentially reduce spreads by 100 basis points.
- Economic structure and performance:
  - Oil represents about 40 percent of GDP and accounts for two thirds of total exports.
  - Oil production projected to deteriorate in the medium to longer term due to aging fields and energy transition risks.
- Fiscal and external buffers:
  - Public debt estimated at 70 percent of GDP at end-2023.
  - External reserves cover less than 5 months of imports targeted for the CEMAC region.
  - Fiscal revenues relatively low due to weak nonoil revenue mobilization and a decline in oil revenues.
- Institutional and social fragilities:
  - Weak rule of law, poor regulatory quality, elevated corruption, lack of government effectiveness per World Bank WGI.
  - High unemployment rate estimated at 36 percent.
- Repayment record:
  - Recurring arrears to bilateral and multilateral creditors; external arrears about one percent of GDP at end-December 2023.

### C. Methodology
- Model specification: Fixed effects panel regression for JP Morgan EMBIG spreads (log) for countries i over time t:
  - S_i,t = α + β X_i,t + δ Z_t + γ ESG_i,t + η_i + ε_i,t (Equation 1)
- Domestic factors (X_i,t): debt-to-GDP ratio, real GDP growth, primary fiscal balance-to-GDP ratio, share of total arrears to GDP, trade openness.
- Global factor (Z_t): Chicago Board Options Exchange’s VIX.
- ESG indicators (ESG_i,t): Human Development Index (HDI), World Bank WGI regulatory quality and government effectiveness, ND-GAIN Adaptation capacity (adaptive capacity sub-index).
- Data: Panel of 50 EMDEs covering 2010–21 (number of countries in reported regressions: 54 and 52; observations: 534 and 482).

### D. Empirical Results — Main determinants and magnitudes
- Debt-to-GDP:
  - Coefficient: 0.00824*** (column 1) and 0.00758*** (column 2).
  - Interpretation: A one percentage point increase in debt-to-GDP is expected to increase spreads by 0.76-0.83 percent depending on the model (i.e., about 6–7 basis points if spreads are at 800).
- Real GDP growth:
  - Coefficient: -0.0112** (column 1) and -0.0157** (column 2).
- Primary balance to GDP:
  - Coefficient: -0.0118* (column 1) and -0.0125** (column 2).
  - Interpretation: A one percentage point improvement in the primary balance to GDP narrows sovereign spreads by about 1.2 percent.
- Total arrears to GDP:
  - Coefficient: 0.00614** (column 1) and 0.00625** (column 2).
  - Interpretation: A one percentage point increase in arrears-to-GDP widens spreads by about 0.61–0.63 percent.
- ESG / governance indicators:
  - WGI – Government Effectiveness: -0.324** (column 1), -0.275** (column 2).
    - A one standard deviation increase in government effectiveness reduces the sovereign premium by 24 to 28 percent (i.e., 192 to 224 basis points for an economy with spreads of 800).
  - WGI – Regulatory Quality: -0.696*** (column 1), -0.701*** (column 2).
    - A one standard deviation improvement in regulatory quality narrows spreads by 50 percent in both models.
  - HDI: -2.243** (column 1), -2.080** (column 2).
    - A 1 percent improvement in HDI reduces sovereign spreads by 2 percent; Gabon’s HDI is 0.71 vs. upper-middle income average of 0.74.
  - ND-GAIN – Adaptation capacity: 0.798 (column 2, not statistically significant).
    - Higher exposure to environmental risks increases spreads, but the adaptive-capacity coefficient is not statistically significant in this sample.
- Global factor (VIX):
  - Coefficient: 0.129** (column 1) and 0.122** (column 2).
  - Interpretation: A one percent increase in the VIX widens sovereign spreads by 0.1 percent.
- Trade openness:
  - Coefficient: -0.515* (column 1) and -0.363 (column 2); not robustly statistically significant.
  - Point estimate suggests increased trade activity reduces sovereign premium by 30 to 40 percent.

- Model fit and sample:
  - R-squared: 0.453 (column 1), 0.476 (column 2).
  - Observations: 534 (column 1), 482 (column 2).
  - Number of countries: 54 (column 1), 52 (column 2).

- Attribution of Gabon’s spread increase (2010–14 vs 2015–21):
  - Increase largely explained by higher debt stock (explains ~50% of increase) and deterioration in governance-related indicators (about one-third of the increase).

- Scenarios for reaching investment grade:
  - Investment grade spreads ≈ 200 basis points, about 400 basis points below Gabon’s February 2024 level.
  - Example multi-pronged pathway:
    - Improve regulatory quality and government effectiveness to the median of Fitch-rated BBB sovereigns — could achieve ¾ of needed reduction in spreads.
    - Reduce debt from 70 percent of GDP to 55 percent (median for BBB sovereigns).
    - Eliminate arrears.
  - Combined measures considered achievable in the medium term and within authorities’ control.

### E. Policy Takeaways and quantified policy impacts
- Strengthen fiscal stance:
  - Reduce debt to around 55 percent of GDP and clear domestic arrears.
  - Potential impact: reduce spreads by some 80 basis points from arrears clearance and fiscal consolidation; save 0.1 percent of GDP in interest costs directly; plus more than 1 percentage point of GDP decline in interest bill due to lower debt level.
  - Requires significant near-term fiscal adjustment via revenue mobilization and expenditure cuts and improved public financial management.
- Bolster governance and transparency:
  - Potential impact: reduce spreads by approximately 450 basis points and save 0.5 percent of GDP in interest costs.
  - Mechanisms: lower perceived investment/default risk, improve business environment, and support higher growth.
- Enhance growth drivers and economic diversification:
  - Support long-term growth, build external reserves, and contribute to currency union viability (see companion SIP “Gabon’s Diversification Journey: What is Missing?”).
- Address social vulnerabilities:
  - Active policies to improve livelihoods, education, health, and human capital will support vulnerable populations, improve growth prospects, and help reduce country risk.

*Source: "DETERMINANTS OF SOVEREIGN SPREADS IN EMERGING MARKETS: IMPLICATIONS FOR GABON" (Selected Issues Paper).*

### Box 1. Literature Review on Determinants of Spreads

### Box 1. Literature Review on Determinants of Spreads

### Empirical findings from prior literature
- Strong economic fundamentals—especially external vulnerability indicators (international reserves, the current account, external debt)—are associated with lower borrowing costs (Comelli (2012)).
- Political risk and governance measures (World Bank Worldwide Governance Indicators) significantly influence sovereign spreads (Gupta, Mati, and Baldacci (2008); Baldacci, Gupta, and Mati (2011); Comelli (2012)).
- Credit rating changes matter: a sovereign rating upgrade to “investment grade” lowers spreads by 36 percent “above and beyond what is implied by macroeconomic fundamentals” (Jaramillo and Tejada (2011)).
- Distinction between long-term country-specific determinants and short-term global factors:
  - Fiscal and external measures important for long-term spreads (Bellas, Papaioannou and Petrova (2010); Csonto and Ivaschencko (2013)).
  - Global financial stress indicators explain more short-term variation (same studies).
- Push vs pull factors for SSA Eurobonds (Senga, Cassimon and Essers (2018)):
  - Push factors: commodity prices, VIX, US Treasury yields.
  - Pull factors: debt, GDP growth, inflation.
- Repayment history matters for spreads (Eichler (2014)), relevant for Gabon given repeated arrears.

### ESG, climate, and sovereign spreads
- Governance: Jeanneret (2018) finds sovereign CDS spreads decrease with lower government effectiveness, especially in countries with high default risk, indebtedness, and weak macroeconomic performance.
- Environmental/physical climate risk: evidence that higher exposure to physical climate risk increases sovereign spreads (Cevik and Jalles (2020); Boehm (2022); Boitan and Marchewka-Bartkowiak (2022)).
- Broader ESG: mixed evidence on environmental factors; social and governance measures often significant (Margaretic and Pouget (2018); Crifo, Diaye and Oueghlissi (2017); Capelle-Blancard et al. (2019)).
- ESG and ratings: Pineau, Le and Estran (2022) show ESG factors impact sovereign ratings for advanced economies, but less so for EMDEs since the global financial crisis.

### Contribution of the current work
- Builds on existing literature by assessing effects of arrears and ESG performance on sovereign costs of borrowing for Gabon and a sample of EMDEs.
- Explicitly considers arrears as a country-specific determinant and ND-GAIN adaptive capacity as a climate adaptation indicator.

### Key data and variable definitions (selected)
- Spread: J.P. Morgan Markets, EMBI Spread.
- Gross Debt: Gross general government debt as a share of GDP (IMF World Economic Outlook).
- Real GDP Growth: Annual percentage change in real GDP (IMF WEO).
- Primary Balance to GDP: Difference between general government revenues and expenditures, excluding interest payments, as a share of GDP (IMF WEO).
- VIX: Chicago Board Options Exchange's CBOE Volatility Index via Haver Analytics.
- WGI – Government Effectiveness and WGI – Regulatory Quality: World Bank Worldwide Governance Indicators.
- HDI: United Nations Development Programme Human Development Index.
- Total Arrears to GDP: Principal and interest payments due but not yet paid on long-term debt as a share of GDP (World Bank International Debt Statistics).
- ND-GAIN Index – Adaptive Capacity: Notre Dame Global Adaptation Initiative.

### Correlation highlights (from Appendix I. Table 3)
- Correlation of Spreads with:
  - Debt to GDP: 0.366
  - Real GDP Growth: -0.284
  - Primary Balance to GDP: -0.193
  - VIX: 0.159
  - WGI – Effectiveness: -0.440
  - WGI – Regulatory Quality: -0.469
  - HDI: -0.257
  - Total Arrears to GDP: 0.223
  - ND-GAIN, Adaptive Capacity: 0.162

### Regression evidence on determinants of sovereign spreads (Appendix I. Table 4) — selected coefficients and statistics
- Debt to GDP:
  - Column (1): 0.0100*** (0.00128)
  - Column (2): 0.00728*** (0.00160)
  - Column (3): 0.00719*** (0.00158)
  - Column (4): 0.00720*** (0.00159)
  - Column (5): 0.00678*** (0.00160)
  - Column (6): 0.00691*** (0.00139)
  - Column (7): 0.00624*** (0.00147)
  - Column (8): 0.00933*** (0.00158)
  - Column (9): 0.00824*** (0.00151)
  - Column (10): 0.00758*** (0.00160)
- Real GDP Growth:
  - Column (1): -0.0195*** (0.00505)
  - Column (2): -0.0161*** (0.00525)
  - Column (3): -0.0147*** (0.00537)
  - Column (4): -0.0122** (0.00542)
  - Column (5): -0.0131** (0.00529)
  - Column (6): -0.0130** (0.00512)
  - Column (7): -0.0153*** (0.00505)
  - Column (8): -0.0112** (0.00530)
  - Column (9): -0.0157** (0.00713)
- Primary Balance to GDP:
  - Column (2): -0.0137** (0.00629)
  - Column (3): -0.0116* (0.00614)
  - Column (6): -0.00880 (0.00629)
  - Column (7): -0.00687 (0.00585)
  - Column (8): -0.00710 (0.00588)
  - Column (9): -0.00715 (0.00558)
  - Column (10): -0.0118* (0.00614)
  - Column (11): -0.0125** (0.00598)
- Trade Openness:
  - Selected coefficients (not statistically significant in most specifications): -0.304 (0.357), -0.319 (0.350), -0.375 (0.322), -0.334 (0.312), -0.422 (0.292), -0.515* (0.295), -0.363 (0.274)
- VIX (global volatility):
  - Column examples: 0.158*** (0.0544), 0.140** (0.0539), 0.152*** (0.0509), 0.0590 (0.0653), 0.129** (0.0611), 0.122** (0.0565)
- WGI – Effectiveness:
  - Coefficients include: -0.584*** (0.126), -0.376*** (0.138), -0.244* (0.142), -0.324** (0.124), -0.275** (0.118)
- WGI – Regulatory Quality:
  - Coefficients include: -0.468*** (0.174), -0.521*** (0.168), -0.696*** (0.120), -0.701*** (0.122)
- HDI:
  - Coefficients include: -4.310*** (1.493), -2.243** (0.973), -2.080** (1.013)
- Total Arrears to GDP:
  - Column (9): 0.00614** (0.00291)
  - Column (10): 0.00625** (0.00282)
- ND-GAIN, Adaptive Capacity:
  - Coefficient shown: 0.798 (0.881) (not statistically significant)
- Constants and model fit:
  - Example constants: 5.221*** (0.0664), 5.425*** (0.0936), 5.397*** (0.0908), 5.629*** (0.307), 5.209*** (0.342), 5.238*** (0.331), 5.198*** (0.318), 3.945*** (0.406), 4.383*** (0.367), 4.921*** (0.726)
  - Observations by specification: 720, 720, 720, 718, 718, 718, 718, 710, 534, 482
  - R-squared by specification: 0.114, 0.150, 0.160, 0.167, 0.179, 0.246, 0.269, 0.332, 0.453, 0.476
  - Number of countries: 76, 76, 76, 76, 76, 76, 76, 75, 54, 52
- Notes: Robust standard errors in parentheses; significance levels: *** p<0.01, ** p<0.05, * p<0.1.

### Key empirical takeaways
- Higher Debt to GDP is robustly associated with higher sovereign spreads (positive and highly significant coefficients across specifications).
- Better macroeconomic performance (higher Real GDP Growth, stronger Primary Balance to GDP) is associated with lower spreads (negative coefficients, many statistically significant).
- Global risk sentiment (VIX) raises spreads in several specifications (positive and often significant coefficients).
- Governance indicators (WGI – Effectiveness; WGI – Regulatory Quality) and HDI are strongly negatively associated with spreads (improved governance and development lower spreads).
- Total Arrears to GDP is positively associated with spreads where included (coefficients 0.00614** and 0.00625**), indicating arrears raise borrowing costs.
- ND-GAIN adaptive capacity does not show a statistically significant association in the reported specification (0.798 (0.881)).

### Implications for analysis of Gabon
- Arrears are empirically associated with higher sovereign borrowing costs; given Gabon’s history of repeated arrears, arrears are a relevant country-specific determinant of spreads.
- Governance and macroeconomic fundamentals remain important levers for lowering sovereign spreads.
- Global financial conditions (VIX) can materially affect short-term spread movements and liquidity pressures.
- ESG/climate exposure (ND-GAIN adaptive capacity) merits attention but is not robustly significant in the reported specification.

*Box 1. Literature Review on Determinants of Spreads — IMF mission materials as presented in the source content.*

### 8. The PIH is    becoming increasingly less relevant as the oil wealth horizon shortens,

### 8. The PIH is    becoming increasingly less relevant as the oil wealth horizon shortens,

### Limitations of the Permanent Income Hypothesis (PIH)
- PIH is becoming increasingly less relevant as the oil wealth horizon shortens, leaving little time to increase savings sufficiently to stabilize spending out of the permanent wealth.
- Past fiscal advice in Gabon has relied on this framework (Leigh and Olters, 2006), but:
  - The PIH does not consider returns on higher investment (IMF, 2012).
  - It suffers from other practical limitations (Eyraud and others, 2023).

### Proposed New Fiscal Framework for Gabon — Overview
- Framework includes three main elements:
  - (i) a long-term anchor for the debt to be inherited by post-oil generations;
  - (ii) interim debt anchors while oil production continues, if needed;
  - (iii) operational rules to achieve these anchors.

### Debt Anchors — Long-term Post-oil Target
- Staff recommendation: target a debt ratio of at most 50 percent of GDP (lower levels may be preferred).
- Rationale and supporting approaches:
  - Comelli et al. (2023) approach: with a buffer of 20 percent of GDP to account for oil price volatility, an appropriate operational debt target would range between 41 and 50 percent of GDP.
  - Eyraud and others (2018) approach: stochastic simulations to keep debt below the 70 percent CEMAC ceiling with 90 percent probability suggest an operational debt target of about 45 percent of GDP.
  - Both approaches point to an operational target of 41-50 percent of GDP; staff advice is to target at most 50 percent of GDP.
- Note: In the post-oil world (staff baseline starting around 2050), the 50 percent ratio refers to both GDP and nonoil GDP as oil GDP would no longer be relevant.

### Interim Debt Anchors — Two Options
- General rules for interim anchors:
  - Intermediate debt anchors needed until debt is reduced to post-oil target.
  - Deviations from the anchor by more than 5 percentage points (or another tolerance level) would trigger an automatic adjustment effort until the anchor is reached again.

- Option D1 — Traditional Anchor: Debt-to-GDP Ratio
  - Example path: set near-term debt anchor to 70 percent until consolidation brings debt below this level, then 60 percent over a 5–10-year period after initial consolidation, and 50 percent thereafter.
  - Advantage: familiar metric.
  - Disadvantage: volatility of the anchor due to oil price fluctuations makes it harder to gauge policy compliance.

- Option D2 — More Stable Anchor: Debt-to-Nonoil-GDP
  - Nonoil economy currently accounts for 60–70 percent of total GDP.
  - Start from terminal post-oil target of 50 percent of nonoil GDP and reduce anchor gradually by 5–10 percentage points at the turn of every decade.
  - Illustrative sequence: reduce debt to 90 percent of nonoil GDP by 2030 (from 115 percent currently), then 80, 70, 60 and finally 50 percent of nonoil GDP.
  - Advantages: less fluctuation with oil prices, better accountability, clearly defined triggers, and consistency with bringing debt back to the 50 percent target.
  - Note: debt reporting as share of nonoil GDP is conceptually consistent with prior practice (e.g., nonoil primary balances).

### Stock and Flow Corrections; Triggers
- Stock correction:
  - Trigger: debt ratio is 5-10 percentage points above its target.
  - Action: reduce the deficit sufficiently to return debt to the anchor within five years.
  - Stock corrections apply once the initial adjustment period has ended and the debt target has been reached; before this, scheduled adjustment should be maintained.
- Flow correction:
  - Trigger: cumulative deviations from the primary balance target exceed 3 percentage points of (nonoil) GDP.
  - Action: corrections can be carried out over a period not exceeding three years to avoid fiscal fatigue.
- Escape clauses:
  - The rule should set forth specific conditions and procedures for temporary and exceptional suspension in response to large exogenous shocks.

### Operational Deficit Targets and Rules
- Near-term operational objective:
  - Bring the nonoil primary deficit from 14–15 percent of nonoil GDP to around 2 percent of nonoil GDP by 2027–28.
  - This 2 percent of nonoil GDP nonoil primary deficit is consistent with advice in the staff report and with the optimal policy path derived from PIH for these years.
- Once achieved, authorities can:
  - Maintain the nonoil primary deficit at this level until the debt anchor is reached.
  - Advantages of a fixed nonoil primary balance rule:
    - Insulates fiscal policy from oil price fluctuations.
    - With stock adjustments, fiscal policy can be automatically adjusted to declining oil wealth if persistent deviations occur.
    - Operationalizable via a simple expenditure growth rule (example: primary spending grows in line with potential GDP, e.g., 5 percent nominal or 3 percent real).
  - Disadvantages:
    - If debt-to-GDP anchor is used, link to unstable anchor complicates triggers due to oil price randomness.
    - A rule that prohibits any spending increase in response to oil prices may be unsustainable.
- Alternative: Switch to the CEMAC structural balance rule after consolidation achieves the anchor.
  - Advantages of CEMAC rule:
    - Automatically and gradually tightens the nonoil primary balance in response to declining oil revenues.
    - Debt targets would be reached automatically as oil production declines, no rule modification required.
    - Already embedded in existing CEMAC framework.
    - Allows authorities to use high oil prices to increase spending for growth and development, potentially enhancing sustainability.
  - Disadvantage:
    - Fiscal spending would absorb most oil price fluctuations.
  - Probabilistic outcomes with CEMAC rule:
    - Debt-to-nonoil GDP ratio would be below 70 percent (60 percent) by 2040 (2050) with a 93 (97) percent probability.

### Design Criteria for the Final Rule and Implementation Requirements
- The ultimate choice of rule should meet four implementation criteria:
  - The rule should be fully objective (no room for subjective interpretation or dependence on projections).
  - All phase transitions (e.g., triggers for policy adjustments) should be clearly defined and definable.
  - The rule should work across different states of the world (high or no oil reserves, high or low oil prices); parameters (e.g., potential growth) should be reviewed regularly.
  - Any government policy changes must be deficit-neutral so policies do not create permanent deviations from the rule.
- Implementation needs:
  - More transparent, accurate and timely fiscal reporting.
  - Credible budgeting and expenditure execution frameworks prior to introducing the rules.
  - Final decision on the rule should be taken closer to legislation adoption and ideally with targeted technical assistance from the Fiscal Affairs Department.

### Appendix I — Methodology (high-level)
- Oil price simulation:
  - Oil prices follow a first-order autoregressive logarithmic process estimated over 1975–2023.
  - Simulations: generate an N×T matrix of normal random numbers and winsorize using 1.5 times the estimated standard deviation (no winsorization on lower tail).
  - Strategy allows oil prices to hit $120 per barrel; references include Boer et al. (2023) range (around 25 USD per barrel in 2030 under demand-side emission reductions, up to around $130 per barrel under supply-side production cuts).
  - 2023 price level set using WEO projected price with slight perturbation; 2024 set as starting period to generate series.
- Theoretical model:
  - Intertemporal optimization with habit formation (Leigh and Olters, 2006); assumes finite oil reserves and uses PIH to analyze fiscal sustainability.
  - Government maximizes utility dependent on primary spending, subject to budget constraints and transversality condition (debt limit as horizon→∞ equals 0).
  - Variables are expressed relative to nonoil GDP; habit formation parameter 0≤α<1 reflects adjustment costs.
  - Under assumptions of constant gross interest rate and β(1+S)=1, closed-form solution expressed with horizon H for oil depletion.

*Source: IMF staff chapter text.*

### 6. In the analysis, we assume that the effective interest rate is higher than the nonoil growth

### 1gabea2024002 - 6. In the analysis, we assume that the effective interest rate is higher than the nonoil growth rate (푆푆>훾훾), which makes the sustainability issue binding.

### Key model assumptions and parameters
- The analysis assumes the effective interest rate is higher than the nonoil growth rate (푆푆>훾훾), which makes the sustainability issue binding. When rate (푆푆<훾훾), it is not necessary to run primary fiscal surpluses to reduce the debt-to-GDP to zero.
- Equation (4) implies current government primary spending depends on permanent income and last period’s level of spending. If previous period’s spending exceeds current permanent income, current spending gradually adjusts to permanent income.
  - Without habits (훼훼=0), the optimal spending path depends on permanent income and adjustment is immediate.
  - Adjustment is slow when 훼훼 is high (훼훼 →1) and fast when 훼훼 is low (훼훼 →0).

Appendix Table 1. Gabon: Assumptions Used in The Analysis — Parameters and Values:
- Nonoil GDP growth (휸휸): 4.3 percent
- Nonoil revenue to nonoil GDP (풚풚풔풔풏풏): 16.1 percent
- Oil revenue to oil GDP: 23.1 percent
- Interest rate (풓풓): 4.4 percent
- Habit parameter (휶휶): 0.7 (0.5 and 0.9)
- Time to oil depletion (푻푻): 30 years
- Number of simulations (푵푵): 10,000

Supplementary assumption details:
- Nonoil GDP growth is set to the average nominal growth rate over the period 2014–23.
- Nonoil revenues increase with nonoil GDP, so that 푦푦푡푡푛푛 is constant over time and equals medium-term nonoil revenue estimates; this is approximately in line with the average nonoil revenue to nonoil GDP ratio over 2015–23, which is 16.3.
- Oil GDP depends on oil production and prices. Assumptions:
  - Gabon has 2,000 million barrels of proven crude oil reserves in 2022 (as reported by OPEC).
  - Production declines by one percent each year from 2026 onwards.
  - Oil production follows authorities’ projections between 2024 and 2025.
  - With these assumptions, oil will run out in 30 years.
  - The generation of the oil price distribution is described above (in source).
- Oil revenues are a constant share of oil GDP; this constant share is estimated as the average over the 2014–23 period, acknowledging a decline from 46.5 percent of oil GDP in 2000 to 19.2 percent in 2022.
- Interest rate is constant and estimated as the average effective interest rate over the 2019–23 period.
- Habit formation parameter is initially set at 0.7 (Leigh and Olters, 2006); robustness checks use 0.5 and 0.9. Havranek et al. (2017) report median habit parameter of 0.7 in macro studies.
- Exchange rate is the October 2023 WEO forecast up to 2029; from 2030 onwards, exchange rate is assumed constant equal to its 2029 value.

### Debt anchor design and calibration
- Challenge: select a target debt level that is feasible, sustainable, and safe given Gabon’s dependence on primary commodities and structural decline of oil production.

D.1. Calibration Based on Comelli and Others (2023)
- Debt ceiling formula (as presented):
  - 푆푆 = 휏휏 × 퐼퐼푆푆푅푅 / 푖푖 − 퐹퐹퐹퐹
  - 휏휏 is threshold for interest expense to revenues set at 19 percent
  - 퐼퐼푆푆푅푅 is fiscal revenue-to-GDP ratio
  - 푖푖 is effective interest rate on public debt
  - 퐹퐹퐹퐹 is fiscal buffer set at 20 percent of GDP based on volatility of Gabon’s primary balance
- Using medium-term projections for Gabon 2025–29, this approach yields:
  - Debt target of approximately 43 percent of GDP on average, with values ranging from 41 to 50.

D.2. Calibration Based on Eyraud and Others (2018)
- Three-step implementation used:
  - Step 1: Maximum debt limit set to 70 percent of GDP (in line with CEMAC ceiling).
  - Step 2: Perform stochastic simulations using joint distribution of macroeconomic variables: real GDP (level and growth rate), primary balance to GDP, debt to GDP, effective interest rates on foreign and domestic debt, real exchange rate, terms of trade, foreign loan disbursements to GDP and stock-flow adjustment from debt accumulation equation.
  - Step 3: Calibrate debt rule ceiling by choosing initial debt level such that debt remains below maximum debt limit with a 90 percent probability over the medium term despite negative shocks.
- Result: debt ceiling found to be about 45 percent of GDP.

D.3. Final assessment and recommended anchor
- Based on both approaches, the debt anchor should be 41–50 percent of GDP.
- Staff advice: set a ceiling of at most 50 percent of GDP (also equivalent to 50 percent of nonoil GDP in the post-oil era).
- Comparison: 50 percent is consistent with median debt of countries with BBB (excluding Italy, Greece, and Cyprus) or AA ratings in 2022 and aligns with literature on debt intolerance and the link between debt and growth.
- Note: Gabon is currently rated Caa1 by Moody’s and B- by Fitch (not investment grade).

### Context: diversification and macro vulnerabilities (selected highlights)
- Gabon is highly dependent on hydrocarbons:
  - Oil accounts for about ⅓ of nominal GDP and 40 percent of government revenues, and more than ⅔ of merchandise exports.
- Historical episodes illustrating exposure: 2008/2009 global financial crisis, 2014–2016 commodity crisis, 2020 COVID-19 pandemic.
- Oil production trends and reserves:
  - Oil production peaked in 1997 and has been declining since.
  - Proven oil reserves are estimated at 2 billion barrels (equivalent to a decade of production and exports at current level, per source footnote).
  - Private investment in the oil sector peaked in 2014; little rise in exploration investment since.
- Export diversification progress:
  - Gabon intensified diversification focused on wood and mining, using fiscal tools and regulatory measures, and created a special economic zone (SEZ).
  - Exports of wood and manganese increased; product export concentration fell significantly compared to regional peers.
  - Export sophistication decreased, with exports concentrated in low value-added products.
  - Partner diversification: dependence on US and EU decreased, dependence on China increased.
- Government strategy (transitional government) priorities:
  - Expand hydrocarbon, mining, agriculture, wood, and tourism industries.
  - Enhance infrastructure, education, governance, and regulation.
  - On hydrocarbons: increase national control including purchase of large operators and development of local capacity to support exploration (including deep offshore).
  - Mining and forestry priorities: improve regulatory framework to combat illegal activity, assess mining potential, start iron production.
  - Agriculture: modernize production, sales, distribution; encourage production clusters; reduce import dependence.
  - Tourism: create dedicated fund and ecotourist zones; launch a new airline to increase tourist traffic.

*Source: IMF — content unit 1gabea2024002 (excerpts and figures summarized from the provided chapter).*

### 7. To assess Gabon’s readiness for diversification, staff constructed a diversification

### 7. To assess Gabon’s readiness for diversification

### Diversification Readiness Index (DRI) and evidence
- Staff constructed a Diversification Readiness Index (DRI) combining measures of:
  - (i) the business environment (governance, infrastructure, access to finance, and human capital),
  - (ii) macroeconomic policies,
  - (iii) trade policy and performance,
  - (iv) data quality, and
  - (v) manufacturing performance.
- The indicator is an index constructed by averaging the z-score related to indicators in the 5 categories listed above.
- There is a strong correlation between the DRI and the Economic Complexity Index, suggesting that greater readiness is associated with greater ability to diversify into higher value-added activities.
- The DRI indicates that Gabon’s current capacity to diversify is weak compared to regional and middle-income peers, mostly due to a weak business environment.

### Main obstacles to diversification (readiness factors)
- Weak business environment — governance:
  - Significant shortcomings in regulatory quality, government effectiveness, the rule of law and corruption control.
  - Legal and regulatory landscape lacks transparency, provides limited investor protection, and is inefficient in resolving disputes.
- Weak business environment — access to finance:
  - Domestic credit is low compared to peers and financing costs are high.
  - Banks reluctant to lend due to elevated credit risk perceptions, lack of credit information on companies, weak payment culture, and low recovery in case of default.
  - Government reliance on domestic arrears threatens liquidity and solvency of suppliers.
  - Credit market distortions with incentives to lend to government rather than private sector (e.g., automatic repayments from the central bank for certain government securities; zero risk weighting of assets).
  - Banks’ deposits account for about 22 percent of GDP.
  - Private sector external finance is mainly FDI and highly concentrated on primary commodities.
- Weak business environment — infrastructure:
  - World Bank Logistic Performance Index: Gabon ranks higher than regional peers but much lower than upper middle-income peers.
  - Significant shortcomings in soft infrastructure, especially customs performance and logistic competence.
  - Access to electricity and internet is uneven and expensive.
    - Gabon access rate for electricity is about 92 percent (sub-Saharan Africa average 51 percent).
    - Urban electricity access 99 percent; rural about 30 percent.
    - Global petrol prices rank Gabon 104 out of 148 countries in terms of electricity cost.
    - About 72 percent of the population use the internet (SSA average 36 percent); Cable ranks Gabon 153rd out of 187 countries for internet package cost.
  - Domestic transport infrastructure underdeveloped; production disruptions from transportation bottlenecks (two railway stoppages in 2023 affected manganese and wood exports).
  - Expansion of recently initiated iron production delayed by limited railway transportation capacity.
- Weak business environment — human capital and labor costs:
  - Health and education outcomes better than SSA average but weaker than middle-income peers.
  - Primary and secondary education widely available; universities face funding, classroom, professor shortages and extended strikes that prevent completion of annual curriculum.
  - Education system predominantly traditional; needs more practical skills and vocational training.
  - Skilled labor scarce and labor costs reported as high compared to neighboring countries.
  - Authorities have launched initiatives (e.g., International Multisectoral Centre for Vocational Education and Training in the Nkok zone).
- Weak macroeconomic policies:
  - High public debt and small but recurring external debt arrears raise borrowing costs and affect credit rating.
  - Large domestic arrears undermine liquidity and solvency of businesses.
  - CEMAC membership has delivered exchange rate stability and relatively low and stable inflation but not large reserve buffers due to procyclical spending and weak repatriation of oil and mining export receipts.
  - New tightening of CEMAC foreign exchange regulation on repatriation of oil receipts helped reserve accumulation but increased regulatory burden for international payments.
- Trade barriers and limited partnerships:
  - WTO data show Gabon applies high import tariffs compared to other SSA countries.
  - Considerable nontariff barriers increase trade costs; in 2022 Gabon ranked in the bottom 10 percent of countries on OECD’s Trade Facilitation Indicators.
  - Upper middle-income status reduces eligibility for some preferential programs (e.g., ineligible for GSP in one main export market—the EU).
  - Gabon signed the CEMAC Economic Partnership Agreement with the EU but has not ratified it.
  - Recently excluded from US AGOA beneficiary list.
  - AfCFTA signing in 2018 offers potential for reduced tariffs and nontariff measures.
- Weak data quality:
  - Poor data quality hinders assessment of diversification progress, accurate external information, and development of well-informed strategy.
- Industrial policy outcomes and fiscal cost:
  - Industrial policy focused on manganese and wood with tax incentives and regulatory measures (e.g., bans on log exports).
  - Strategy expanded local processing of wood (notably via Nkok economic zone) and advanced wood products production, but reliance on extended tax exemptions elevated fiscal cost.
  - Wood sector: 0.4 percent of total fiscal revenues while producing 2.3 percent of nominal GDP in 2022.
  - Total tax expenditures estimated between 4 and 5 percent of GDP.

### Business survey results (staff survey of 37 companies)
- Survey of 37 companies on the three main obstacles to economic diversification corroborated DRI findings:
  - Main obstacle: weak business environment (weak governance and transparency; unpredictable tax environment; numerous parafiscal charges and uneven implementation).
  - Poor infrastructure (poor roads, limited access to electricity, high usage costs; intranational trade disruptions due to poor infrastructure).
  - Access to finance and human capital (government arrears’ impact on liquidity; high labor costs and lack of adequate skills).

### Policy priorities to enhance diversification framework
- Governance and transparency reforms:
  - Improve transparency of fiscal position, public finance management, accountability and efficiency.
  - Broad anti-corruption measures to bolster private sector confidence and investment.
- Improve financing conditions for companies:
  - Near term: accelerate repayment of government domestic arrears; initiate decisive fiscal consolidation to prevent further accumulation and reduce borrowing costs.
  - Establish a comprehensive credit bureau to increase information for banks.
  - Refine regulatory framework for debt recovery; strengthen judicial system and consider establishing a commercial court.
  - Medium term: promote financial deepening and financial inclusion to increase domestic savings and expand banks’ ability to finance the economy.
    - Account ownership at financial institutions: Gabon 66 percent; middle-income countries average 72 percent.
- Strengthen fiscal position:
  - Reduce public debt and permanently clear external arrears to improve external borrowing costs and investor confidence.
  - Example: reducing public debt to 55 percent of GDP and clearing arrears could bring about 0.1 percent of GDP in interest savings.
  - Consider alternatives to fiscal incentives for attracting firms to special economic zones to limit fiscal cost (see accompanying SIP “A Menu of Fiscal Adjustment Options” referenced in source).
- Trade policy reforms:
  - Remove trade barriers and facilitate expansion into new markets.
  - Simplify implementation of import tariffs (agreed at CEMAC level) by avoiding exemptions and ad hoc safeguard measures.
  - Work regionally to gradually reduce tariffs to lower import costs.
  - Use nontariff fiscal measures (taxes or subsidies) cautiously to avoid distortions and ensure consistency with WTO national treatment principles.
  - Avoid excessive national preference in hiring that would discourage investors.
  - Reinforce trade diplomacy to regain access to AGOA and strengthen EU integration.
- Strengthen statistical capacity and communication:
  - Improve statistical capacity and communication to underpin strategy, policymaking and monitoring of progress.
- Reduce costs and distortions of industrial policy:
  - Favor cost-effective approaches focusing on institutional functioning (fast delivery of secured land titles; stronger governance and transparency).
  - Invest in transport networks and access to electricity around key production sites as low-risk, high-return measures to support industries.

### Box 1 — International lessons and DRI composition
- International lessons:
  - Conducive business environment (governance, infrastructure, access to finance, skilled workforce) catalyzes diversification (examples: Singapore, UAE).
  - Solid fiscal and monetary frameworks attract investors and allow accumulation of resources for diversification (examples: UAE, Chile, Malaysia).
  - Trade policies lowering trade barriers, spatial policies (special economic zones), and new trade partnerships support diversification (examples: China’s SEZs; NAFTA’s role for Mexico).
  - Credible, well-promoted diversification strategy requires accurate statistics, realistic policy choices, strong reform track record, and active marketing.
  - Industrial policy can be justified by externalities but must be used prudently to avoid market distortions and excessive fiscal cost.
- DRI components (as combined into a single score):
  - Business climate: World Governance Indicators; Logistics performance index; Access to electricity (% urban population); Access to electricity (% rural population); Domestic credit to the private sector (% GDP); Gross enrollment in secondary education.
  - Macroeconomic policies: Public debt to GDP; Government interest expense to revenue; Net international investment position (percent GDP).
  - Trade policy and performance: Trade openness; Simple average of MFN/applied import tariffs; Trade facilitation index.
  - Data quality: Statistical capacity score.
  - Manufacturing performance: Manufacturing share of GDP; Medium- and high-tech exports (share of manufactured imports).

*Source: IMF staff analysis in the chapter describing Gabon’s diversification readiness and policy recommendations.*

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_Source: https://www.imf.org/-/media/files/publications/cr/2024/english/1gabea2024002.pdf_