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### Executive Summary: scope and approach
- Paper investigates consequences of global shocks on a sample of low- and lower-middle-income countries with a particular focus on fragile and conflict-affected states (FCS).
- FCS are defined as countries that display institutional weakness and/or are negatively affected by active conflict, thereby facing challenges in macroeconomic policy management.
- Three types of global shocks are analyzed:
  - (i) commodity price fluctuations,
  - (ii) shifts in external demand, and
  - (iii) changes in financial market conditions (proxied by changes in U.S. interest rates).
- Empirical approach:
  - Country-by-year panel dataset containing 85 low- and middle-income countries over 2006-2021.
  - Shocks are identified and dynamic effects estimated using a local projection method.

### Key empirical findings
- FCS economies are more sensitive to all three analyzed global shocks compared to non-FCS economies.
  - Example: three years after a commodity-price shock, the response of GDP per capita in FCS is almost twice as large as that of non-FCS.
- Procyclical fiscal responses drive higher sensitivity in FCS:
  - Governments in FCS generally unable to smooth spending in the absence of meaningful buffers; spending increases with revenue gains and decreases with revenue losses.
  - Governments in FCS exhibit “hand-to-mouth” behavior of cash-constrained consumers, amplifying shock impacts.
- Global financial conditions (U.S. interest rate changes) affect fiscal responses in FCS more than in non-FCS through:
  - Reduced availability of financial resources for governments, and
  - Indirect global demand shifts following changes in global financial conditions.
- Underlying amplifiers in FCS:
  - Weak institutions,
  - Lack of economic diversification,
  - Lower level of financial development,
  - Limited pre-existing buffers such as fiscal space and international reserves.
- External financing:
  - Concessional external finance is a stable funding source for FCS but appears largely acyclical and of limited help in directly facilitating counter-cyclical policy during global shocks.
  - The difference in shock propagation between FCS and non-FCS is muted among high recipients of concessional external financing, suggesting concessional finance helps alleviate financial constraints.

### Illustrative outcomes and risks
- FCS suffered deeper scarring from recent shocks (pandemic and subsequent shocks) relative to Advanced Economies (AEs) and other Emerging Markets and Developing Economies (EMDEs).
- Median per capita GDP in FCS is expected to recover to the pre-pandemic level only in 2026.
- Inflation in FCS economies has been highest among all country groups with more lingering effects expected.
- These dynamics create a significant risk of FCS falling further behind and not achieving their Sustainable Development Goals (SDGs) by the planned timeframe.

### Conceptual and methodological notes
- FCS classification follows the World Bank list (annual, since 2006); the FCS list for FY2024 contains 39 economies.
- Comparison group: non-FCS low-income and lower-middle-income countries based on World Bank income classification (currently GDP per capita below US$1,135 and US$4,465 as of 2022 define LICs and lower MICs, respectively).
- Identification of shocks:
  - Commodity ToT shock: Δtot_{i,t} = Σ_{j=1}^{J} Δp_{j,t} w_{i,j,t} with J=45; w_{i,j,t} = (1/3) Σ_{τ=1}^{3} (X_{i,j,t-τ} − M_{i,j,t-τ}) / GDP_{i,t-τ}.
  - Global demand shock: shift-share instrument z_{i,t} normalized to a 1 percent of GDP shock to nominal exports.
  - U.S. interest rate shock: changes in 10-year U.S. Treasury rates; benchmark is a 1 percentage point decline.
- Estimation method: Local projection (Jorda, 2005) with Lags L=2, country fixed effects μ_{i,s}, year fixed effects λ_{t,s}, and clustered standard errors by country; interaction with FCS dummy I_{i,t−1} yields IRFs for FCS ({β_{1,s}}) and non-FCS ({β_{0,s}}).

### Stylized facts and sample statistics (FCS vs non-FCS; pooled 2006–2021)
- Sample trimming: top and bottom 0.5 percentiles removed.
- FCS (observations and key statistics)
  - GNI per capita (US$): Obs. 517; Mean 1832.98; Std. dev. 1886.07; 10th pct. 410.00; 90th pct. 4400.00
  - GDP growth per capita (percent): Obs. 528; Mean 1.28; Std. dev. 4.84; 10th pct. -4.14; 90th pct. 6.28
  - Unemployment rate (percent): Obs. 500; Mean 8.50; Std. dev. 7.01; 10th pct. 1.28; 90th pct. 19.56
  - Poverty rate (percent): Obs. 61; Mean 28.72; Std. dev. 23.65; 10th pct. 0.80; 90th pct. 68.40
  - CPIA score (index): Obs. 480; Mean 2.84; Std. dev. 0.43; 10th pct. 2.35; 90th pct. 3.30
  - Conflict fatalities (per mil. population): Obs. 507; Mean 21.71; Std. dev. 48.91; 10th pct. 0.00; 90th pct. 77.76
  - Revenues excluding grants (percent of GDP): Obs. 492; Mean 19.74; Std. dev. 12.93; 10th pct. 8.27; 90th pct. 38.51
  - Grants (percent of GDP): Obs. 478; Mean 7.09; Std. dev. 9.44; 10th pct. 0.27; 90th pct. 22.68
  - Primary expenditure (percent of GDP): Obs. 508; Mean 30.54; Std. dev. 26.61; 10th pct. 11.77; 90th pct. 63.94
  - Interest payments (percent of GDP): Obs. 508; Mean 1.01; Std. dev. 1.27; 10th pct. 0.07; 90th pct. 2.22
  - Overall fiscal balance (percent of GDP): Obs. 509; Mean -2.21; Std. dev. 6.89; 10th pct. -8.02; 90th pct. 3.88
  - Exports (percent of GDP): Obs. 460; Mean 26.86; Std. dev. 23.11; 10th pct. 8.78; 90th pct. 45.18
  - Imports (percent of GDP): Obs. 460; Mean 46.45; Std. dev. 25.66; 10th pct. 23.67; 90th pct. 81.39
  - Trade balance (percent of GDP): Obs. 456; Mean -18.87; Std. dev. 21.67; 10th pct. -47.61; 90th pct. 3.18
  - Current account balance (percent of GDP): Obs. 511; Mean -3.53; Std. dev. 11.98; 10th pct. -16.19; 90th pct. 11.70
  - International reserves (months of imports): Obs. 441; Mean 4.36; Std. dev. 3.31; 10th pct. 0.58; 90th pct. 9.06
- Non-FCS (observations and key statistics)
  - GNI per capita (US$): Obs. 942; Mean 2300.57; Std. dev. 1461.81; 10th pct. 610.00; 90th pct. 4230.00
  - GDP growth per capita (percent): Obs. 939; Mean 2.70; Std. dev. 3.79; 10th pct. -1.39; 90th pct. 6.59
  - Unemployment rate (percent): Obs. 917; Mean 7.15; Std. dev. 5.91; 10th pct. 1.85; 90th pct. 13.68
  - Poverty rate (percent): Obs. 299; Mean 12.81; Std. dev. 17.81; 10th pct. 0.10; 90th pct. 43.00
  - CPIA score (index): Obs. 639; Mean 3.51; Std. dev. 0.29; 10th pct. 3.16; 90th pct. 3.86
  - Conflict fatalities (per mil. population): Obs. 948; Mean 3.59; Std. dev. 16.09; 10th pct. 0.00; 90th pct. 5.67
  - Revenues excluding grants (percent of GDP): Obs. 888; Mean 21.05; Std. dev. 9.20; 10th pct. 11.55; 90th pct. 32.04
  - Grants (percent of GDP): Obs. 811; Mean 2.87; Std. dev. 5.20; 10th pct. 0.07; 90th pct. 6.53
  - Primary expenditure (percent of GDP): Obs. 925; Mean 25.21; Std. dev. 11.89; 10th pct. 14.22; 90th pct. 37.69
  - Interest payments (percent of GDP): Obs. 925; Mean 1.71; Std. dev. 1.63; 10th pct. 0.36; 90th pct. 3.84
  - Overall fiscal balance (percent of GDP): Obs. 940; Mean -2.96; Std. dev. 4.07; 10th pct. -7.46; 90th pct. 1.31
  - Exports (percent of GDP): Obs. 886; Mean 31.79; Std. dev. 18.40; 10th pct. 13.35; 90th pct. 50.56
  - Imports (percent of GDP): Obs. 885; Mean 44.12; Std. dev. 21.46; 10th pct. 21.34; 90th pct. 70.29
  - Trade balance (percent of GDP): Obs. 887; Mean -12.69; Std. dev. 15.22; 10th pct. -30.20; 90th pct. 2.40
  - Current account balance (percent of GDP): Obs. 940; Mean -5.22; Std. dev. 8.80; 10th pct. -14.58; 90th pct. 3.64
  - International reserves (months of imports): Obs. 868; Mean 5.31; Std. dev. 3.44; 10th pct. 2.11; 90th pct. 9.59
- Key descriptive conclusions:
  - FCS economies show lower growth, higher unemployment, higher poverty, lower institutional quality (CPIA/WGI), and greater exposure to violent conflict.
  - FCS governments rely more on external support: grants (mean 7.09 percent of GDP) vs non-FCS (mean 2.87 percent of GDP).
  - FCS economies are on average less diversified with limited export bases and larger trade deficits (trade balance mean -18.87 percent of GDP for FCS vs. -12.69 percent for non-FCS).

### Determinants of fragility (probit results)
- Significant determinants of higher probability of being FCS:
  - Number of conflict events per capita: positive and significant (e.g., 0.070*** in column (1); 0.175*** in column (4)).
  - WGI (Worldwide Governance Indicator): negative and significant (e.g., -0.937*** in column (1); -3.078*** in column (4)).
  - Export diversification: positive and significant (e.g., 0.117*** in column (1); 0.368*** in column (4)).
  - Financial development: negative and significant (e.g., -4.861*** in column (1); -14.971*** in column (4)).
  - Log (Per capita income): negative and significant in full samples (e.g., -0.387*** and -1.230***), but not significant when limited to LICs/lower-MICs (columns (3) and (4): -0.002 and -0.571).
- Observations: 2,795 for full-sample specifications; 1,316 for LICs/lower-MICs specifications.
- Model: Probit with year dummies; column (2) and (4) include country random effects (RE).

### Descriptive statistics of shock variables
- Commodity ToT shock (percent of GDP)
  - FCS: Obs. 479; Mean 0.10; Std. dev. 4.82; 10th percentile -3.21; 90th percentile 4.08
  - Non-FCS: Obs. 920; Mean 0.08; Std. dev. 3.13; 10th percentile -2.47; 90th percentile 3.30
- Commodity export price (percent of GDP)
  - FCS: Obs. 479; Mean 0.22; Std. dev. 4.94; 10th percentile -2.98; 90th percentile 4.54
  - Non-FCS: Obs. 920; Mean 0.22; Std. dev. 3.02; 10th percentile -1.68; 90th percentile 2.30
- Global demand shock (percent of GDP)
  - FCS: Obs. 430; Mean 0.24; Std. dev. 7.80; 10th percentile -7.16; 90th percentile 8.22
  - Non-FCS: Obs. 871; Mean 0.76; Std. dev. 7.17; 10th percentile -6.54; 90th percentile 8.30
- Notable: commodity ToT shocks are more volatile in FCS relative to GDP (Std. dev. 4.94 percent for FCS vs. 3.02 percent for non-FCS in commodity export price).

### Impact of global shocks (quantified responses)
- Commodity ToT shock (one percent of GDP)
  - In FCS, a commodity ToT shock equal to one-percent of GDP leads to a 0.4 percent change in GDP per capita.
  - The magnitude in FCS is twice as large as in non-FCS; difference significant at 5 percent in years two to four.
  - Channels: procyclical fiscal responses (public consumption and public investment rise persistently), private consumption responds significantly (household cash constraints), real exports show insignificant responses in FCS while imports offset domestic activity increases.
- Global demand shock (one percent of GDP)
  - Stronger GDP per capita responses in FCS driven by more procyclical fiscal policy.
  - FCS: large and persistent increases in public consumption and public investment; fiscal balance deteriorates in later years.
  - Non-FCS: muted expenditure responses, indicating slightly counter-cyclical fiscal policy.
  - Real exports: no increase in FCS; slight increases in non-FCS in years three and four.
- U.S. interest rate shock (1 percentage point decline in 10-year rate)
  - A 1 percentage point decline tends to raise GDP per capita about 2 percent more in FCS than in non-FCS over a 5-year horizon; difference initially significant at 5 percent, less so after four years.
  - Channel: increases in public investment in FCS over five years raise total expenditure while revenue remains unchanged, deteriorating fiscal balance.
  - Public consumption does not respond differently across groups.

### External financing and heterogeneity
- Cross-country averages (pooled 2006–2021):
  - FCS rely more on concessional supports (ODA, grants).
  - FCS receive significantly lower portfolio flows than non-FCS but rely on FDI at a similar level.
  - Other investment (including external loans) tends to be lower in FCS.
- Responses to commodity ToT shocks:
  - ODA and grants: No significant response in either group; inflows are a-cyclical.
  - FDI: Initially declines in FCS and remains insignificantly different from zero after year two; no significant difference across groups overall.
  - IMF lending increased notably after the pandemic (counter-cyclical example).
- Heterogeneous impact by recipient status:
  - Higher sensitivity of FCS versus non-FCS arises primarily from countries that are low recipients of ODA and grants.
  - Among high recipients of ODA and grants, per capita GDP responses in FCS and non-FCS are quite similar.
  - No distinct patterns across low and high FDI recipients; FDI linked to long-term projects and not a short-term shock absorber.
- Caveat: Potential omitted third factors may influence both concessional inflows and sensitivity to shocks.

### Robustness checks and sample variations
- Variations tested:
  - Add lagged controls (conflict events per capita, average WGI, export diversification index, financial development index, FCS indicator).
  - Further add lagged macroeconomic conditions (public external debt-to-GDP, current account-to-GDP, international reserves-to-imports, fiscal balance-to-GDP, CPI inflation, per capita GDP growth).
  - Exclude small states with population lower than 1.5 million (7 FCS small states and 6 non-FCS small states listed for 2021).
  - Exclude large commodity exporters with export share higher than 10 percent (exclusions enumerated).
- Finding: Estimated IRFs remain close to main specification across robustness checks; IRF patterns in panels (A)–(D) mostly similar to main specification.

### Potential drivers of amplified responses and policy-relevant implications
- Cross-cutting drivers associated with excess sensitivity:
  - Low institutional quality (WGI): bottom 25th percentile countries display excess sensitivity.
  - Lack of export diversification: amplifies ToT shock impacts.
  - Low financial development: limited access to financing to smooth shocks.
  - Interdependence: around 80 percent of countries in the bottom 25th percentile on at least one of these indicators also display weakness in another (as of 2021).
- Role of buffers:
  - Countries with lower buffers (government debt, current account, FX reserves) tend to have wider IRF confidence bands and greater volatility.
- Policy-relevant observation:
  - Fiscal rules and improved institutional capacity can reduce fiscal procyclicality, but adoption and enforcement in FCS can be lengthy.
  - Multi-faceted approaches are needed to address interlinked fragility features.

### Policy recommendations (heuristic and targeted)
- Fiscal policy and buffers:
  - Create fiscal buffers and preserve room for counter-cyclical fiscal policies.
  - Limit pro-cyclical spending in times of positive shocks to strengthen fiscal and external buffers.
  - Establish (resource-based) frameworks for medium-term fiscal policy to support resilience and smooth pent-up demand in positive shocks.
- Institutional and structural reforms:
  - Improve public finance and investment management.
  - Improve transparency, reduce corruption, and target social spending to address roots of fragility and improve trust in economic institutions.
  - Pursue well-sequenced structural reforms to improve public finance management, strengthen institutions, diversify the economy, and increase financial inclusion.
- External support and international community role:
  - International financial institutions and development partners should provide timely and efficient external financial support and enhance the counter-cyclicality of support.
  - Tailor policy advice to country-specific characteristics: nature of vulnerabilities (conflict vs. institutional fragility), economic structure (commodity exporters, tourism-dependent), and geographical factors (small island states).
- Urgency and broader context:
  - The global economy is more shock-prone with increased uncertainty and rising fragility.
  - Building economic buffers and sound institutions is crucial to enhance resilience and prevent long-run scarring.
  - Granular and timely risk assessments are essential to detect potential sources of instability.

*Source: EXECUTIVE SUMMARY and Annexes (wpiea2024214-print-pdf).*

### EXECUTIVE SUMMARY _______________________________________________________________ 4

### wpiea2024214-print-pdf - EXECUTIVE SUMMARY _______________________________________________________________ 4

### Executive Summary: scope and approach
- Paper investigates consequences of global shocks on a sample of low- and lower-middle-income countries with a particular focus on fragile and conflict-affected states (FCS).
- FCS are defined as countries that display institutional weakness and/or are negatively affected by active conflict, thereby facing challenges in macroeconomic policy management.
- Three types of global shocks are analyzed: (i) commodity price fluctuations, (ii) shifts in external demand, and (iii) changes in financial market conditions (proxied by changes in U.S. interest rates).
- Empirical approach: country-by-year panel dataset containing 85 low- and middle-income countries over 2006-2021; shocks are identified and dynamic effects estimated using a local projection method.

### Key empirical findings
- FCS economies are more sensitive to all three analyzed global shocks compared to non-FCS economies.
  - Example: three years after a commodity-price shock, the response of GDP per capita in FCS is almost twice as large as that of non-FCS.
- The higher sensitivity of FCS is mainly driven by procyclical fiscal responses:
  - Governments in FCS are generally unable to smooth their spending in the absence of meaningful buffers, increasing (or decreasing) spending together with revenue gains (or losses).
  - Governments in FCS exhibit the “hand-to-mouth” behavior of cash-constrained consumers, amplifying shock impacts.
- Global financial conditions (U.S. interest rate changes) affect fiscal responses in FCS more than in non-FCS through:
  - Reduced availability of financial resources for governments, and
  - Indirect channel of global demand shifts following changes in global financial conditions.
- Underlying factors amplifying shock propagation in FCS:
  - Weak institutions,
  - Lack of economic diversification,
  - Lower level of financial development,
  - Limited pre-existing buffers such as fiscal space and international reserves.
- External financing:
  - Concessional external finance serves as a stable funding source for FCS but appears largely acyclical and is of limited help in directly facilitating a counter-cyclical policy response during global shocks.
  - The difference in shock propagation between FCS and non-FCS is muted among high recipients of concessional external financing, suggesting concessional finance helps alleviate financial constraints and mitigate excessive sensitivity.

### Illustrative outcomes and risks
- FCS suffered significantly deeper scarring from recent shocks (pandemic and subsequent shocks) relative to Advanced Economies (AEs) and other Emerging Markets and Developing Economies (EMDEs).
- Median per capita GDP in FCS is expected to recover to the pre-pandemic level only in 2026.
- Inflation in FCS economies has been highest among all country groups with more lingering effects expected in the coming years.
- These dynamics create a significant risk of FCS falling further behind the rest of the world and not achieving their Sustainable Development Goals (SDGs) by the planned timeframe.

### Policy implications and recommendations
- Limit pro-cyclical spending in times of positive shocks to strengthen fiscal and external buffers.
- Pursue well-sequenced structural reforms to:
  - Improve public finance management,
  - Strengthen institutions,
  - Diversify the economy,
  - Increase financial inclusion.
- International community and external partners (including international financial institutions) should:
  - Provide efficient and timely external financial support,
  - Enhance the counter-cyclicality of support to help countries implement counter-cyclical responses and achieve macroeconomic stability.
- Addressing the cycle from poor economic outcomes to decreased trust in institutions is critical; policy misalignment in response to global shocks may also trigger conflicts and exacerbate fragility.

### Conceptual and methodological notes
- FCS classification follows the World Bank list (annual, since 2006); the FCS list for FY2024 contains 39 economies.
- Comparison group: non-FCS low-income and lower-middle-income countries based on World Bank income classification (currently GDP per capita below US$1,135 and US$4,465 as of 2022 define LICs and lower MICs, respectively).
- The study leverages identification strategies to extract exogenous variations in global economic dynamics and applies local projections to analyze dynamic effects on macroeconomic variables.

*Source: EXECUTIVE SUMMARY (wpiea2024214-print-pdf).*

### Annex I.

### Annex I.

### Geography and persistence of FCS listing
- The number shown for each country indicates the frequency of being classified as FCS during 2006 and 2023 (18 years); “18” means the country was on the FCS list in every year.
- Source of harmonized list referenced: World Bank.

### Stylized facts from descriptive statistics (Table 1)
- Sample pooled in 2006-2021; top and bottom 0.5 percentiles removed as outliers.
- FCS (observations and key statistics)
  - GNI per capita (US$): Obs. 517; Mean 1832.98; Std. dev. 1886.07; 10th pct. 410.00; 90th pct. 4400.00
  - GDP growth per capita (percent): Obs. 528; Mean 1.28; Std. dev. 4.84; 10th pct. -4.14; 90th pct. 6.28
  - Unemployment rate (percent): Obs. 500; Mean 8.50; Std. dev. 7.01; 10th pct. 1.28; 90th pct. 19.56
  - Poverty rate (percent): Obs. 61; Mean 28.72; Std. dev. 23.65; 10th pct. 0.80; 90th pct. 68.40
  - CPIA score (index): Obs. 480; Mean 2.84; Std. dev. 0.43; 10th pct. 2.35; 90th pct. 3.30
  - Conflict fatalities (per mil. population): Obs. 507; Mean 21.71; Std. dev. 48.91; 10th pct. 0.00; 90th pct. 77.76
  - Revenues excluding grants (percent of GDP): Obs. 492; Mean 19.74; Std. dev. 12.93; 10th pct. 8.27; 90th pct. 38.51
  - Grants (percent of GDP): Obs. 478; Mean 7.09; Std. dev. 9.44; 10th pct. 0.27; 90th pct. 22.68
  - Primary expenditure (percent of GDP): Obs. 508; Mean 30.54; Std. dev. 26.61; 10th pct. 11.77; 90th pct. 63.94
  - Interest payments (percent of GDP): Obs. 508; Mean 1.01; Std. dev. 1.27; 10th pct. 0.07; 90th pct. 2.22
  - Overall fiscal balance (percent of GDP): Obs. 509; Mean -2.21; Std. dev. 6.89; 10th pct. -8.02; 90th pct. 3.88
  - Exports (percent of GDP): Obs. 460; Mean 26.86; Std. dev. 23.11; 10th pct. 8.78; 90th pct. 45.18
  - Imports (percent of GDP): Obs. 460; Mean 46.45; Std. dev. 25.66; 10th pct. 23.67; 90th pct. 81.39
  - Trade balance (percent of GDP): Obs. 456; Mean -18.87; Std. dev. 21.67; 10th pct. -47.61; 90th pct. 3.18
  - Current account balance (percent of GDP): Obs. 511; Mean -3.53; Std. dev. 11.98; 10th pct. -16.19; 90th pct. 11.70
  - International reserves (months of imports): Obs. 441; Mean 4.36; Std. dev. 3.31; 10th pct. 0.58; 90th pct. 9.06
- Non-FCS (observations and key statistics)
  - GNI per capita (US$): Obs. 942; Mean 2300.57; Std. dev. 1461.81; 10th pct. 610.00; 90th pct. 4230.00
  - GDP growth per capita (percent): Obs. 939; Mean 2.70; Std. dev. 3.79; 10th pct. -1.39; 90th pct. 6.59
  - Unemployment rate (percent): Obs. 917; Mean 7.15; Std. dev. 5.91; 10th pct. 1.85; 90th pct. 13.68
  - Poverty rate (percent): Obs. 299; Mean 12.81; Std. dev. 17.81; 10th pct. 0.10; 90th pct. 43.00
  - CPIA score (index): Obs. 639; Mean 3.51; Std. dev. 0.29; 10th pct. 3.16; 90th pct. 3.86
  - Conflict fatalities (per mil. population): Obs. 948; Mean 3.59; Std. dev. 16.09; 10th pct. 0.00; 90th pct. 5.67
  - Revenues excluding grants (percent of GDP): Obs. 888; Mean 21.05; Std. dev. 9.20; 10th pct. 11.55; 90th pct. 32.04
  - Grants (percent of GDP): Obs. 811; Mean 2.87; Std. dev. 5.20; 10th pct. 0.07; 90th pct. 6.53
  - Primary expenditure (percent of GDP): Obs. 925; Mean 25.21; Std. dev. 11.89; 10th pct. 14.22; 90th pct. 37.69
  - Interest payments (percent of GDP): Obs. 925; Mean 1.71; Std. dev. 1.63; 10th pct. 0.36; 90th pct. 3.84
  - Overall fiscal balance (percent of GDP): Obs. 940; Mean -2.96; Std. dev. 4.07; 10th pct. -7.46; 90th pct. 1.31
  - Exports (percent of GDP): Obs. 886; Mean 31.79; Std. dev. 18.40; 10th pct. 13.35; 90th pct. 50.56
  - Imports (percent of GDP): Obs. 885; Mean 44.12; Std. dev. 21.46; 10th pct. 21.34; 90th pct. 70.29
  - Trade balance (percent of GDP): Obs. 887; Mean -12.69; Std. dev. 15.22; 10th pct. -30.20; 90th pct. 2.40
  - Current account balance (percent of GDP): Obs. 940; Mean -5.22; Std. dev. 8.80; 10th pct. -14.58; 90th pct. 3.64
  - International reserves (months of imports): Obs. 868; Mean 5.31; Std. dev. 3.44; 10th pct. 2.11; 90th pct. 9.59
- Key descriptive conclusions:
  - FCS economies show lower growth, higher unemployment, higher poverty, lower institutional quality (CPIA/WGI), and greater exposure to violent conflict.
  - FCS governments rely more on external support: grants (mean 7.09 percent of GDP) are larger than in non-FCS (mean 2.87 percent of GDP).
  - FCS economies are on average less diversified with limited export bases and larger trade deficits (trade balance mean -18.87 percent of GDP for FCS vs. -12.69 percent for non-FCS).
  - Average fiscal and external positions not substantively different, but FCS exhibit larger standard deviations.

### Determinants of fragility (Table 2, probit results)
- Results indicate probability of being FCS is significantly affected by:
  - Number of conflict events per capita: positive and significant across specifications (e.g., 0.070*** in column (1); 0.175*** in column (4)).
  - WGI (Worldwide Governance Indicator): negative and significant (e.g., -0.937*** in column (1); -3.078*** in column (4)).
  - Export diversification: positive and significant (e.g., 0.117*** in column (1); 0.368*** in column (4)).
  - Financial development: negative and significant (e.g., -4.861*** in column (1); -14.971*** in column (4)).
  - Log (Per capita income): negative and significant in full samples (e.g., -0.387*** and -1.230***), but not significant when limited to LICs/lower-MICs (columns (3) and (4): -0.002 and -0.571).
- Observations: 2,795 for full-sample specifications; 1,316 for LICs/lower-MICs specifications.
- Model: Probit with year dummies; column (2) and (4) include country random effects (RE).

### Identification of global shocks
- Commodity terms-of-trade (ToT) shock:
  - ToT index constructed from 45 global commodity prices and country-specific net export shares.
  - Formula: Δtot_{i,t} = Σ_{j=1}^{J} Δp_{j,t} w_{i,j,t} with J=45.
  - Country-specific commodity net trade share: w_{i,j,t} = (1/3) Σ_{τ=1}^{3} (X_{i,j,t-τ} − M_{i,j,t-τ}) / GDP_{i,t-τ}.
  - Interpreted as windfall gains and losses in aggregate income associated with international commodity price changes.
- Global demand shock:
  - Instrumented via a shift-share strategy using product-destination bilateral trade flows (Baci/Comtrade).
  - Constructed as z_{i,t} = [Σ (X_{idp,0}/X_{i,0}) (m_{dp,t}^{-i} − m_{dp,t−1}^{-i})] (X_{i,t−1}/GDP_{i,t−1}), normalized to a 1 percent of GDP shock to nominal exports.
- U.S. interest rate shock:
  - Proxy for global financial conditions: changes in 10-year U.S. Treasury rates used.
  - A 1 percentage point decline in the 10-year U.S. interest rate is the benchmark shock examined.

### Descriptive stats of shock variables (Table 3)
- Commodity ToT shock (percent of GDP)
  - FCS: Obs. 479; Mean 0.10; Std. dev. 4.82; 10th percentile -3.21; 90th percentile 4.08
  - Non-FCS: Obs. 920; Mean 0.08; Std. dev. 3.13; 10th percentile -2.47; 90th percentile 3.30
- Commodity export price (percent of GDP)
  - FCS: Obs. 479; Mean 0.22; Std. dev. 4.94; 10th percentile -2.98; 90th percentile 4.54
  - Non-FCS: Obs. 920; Mean 0.22; Std. dev. 3.02; 10th percentile -1.68; 90th percentile 2.30
- Commodity import price (percent of GDP)
  - FCS: Obs. 479; Mean 0.13; Std. dev. 2.37; 10th percentile -2.00; 90th percentile 2.37
  - Non-FCS: Obs. 920; Mean 0.13; Std. dev. 2.30; 10th percentile -2.47; 90th percentile 2.44
- Global demand shock (percent of GDP)
  - FCS: Obs. 430; Mean 0.24; Std. dev. 7.80; 10th percentile -7.16; 90th percentile 8.22
  - Non-FCS: Obs. 871; Mean 0.76; Std. dev. 7.17; 10th percentile -6.54; 90th percentile 8.30
- Notable descriptive conclusion: commodity ToT shocks are more volatile in FCS relative to GDP (Std. dev. 4.94 percent for FCS vs. 3.02 percent for non-FCS in commodity export price).

### Empirical strategy
- Local projection (LP) method (Jorda, 2005) used to estimate impulse responses:
  - Outcome: y_{i,t+s} − y_{i,t−1} regressed on contemporaneous shock Δshock_{i,t}, lagged Δy and lagged Δshock terms, country fixed effects μ_{i,s}, year fixed effects λ_{t,s}, and clustered standard errors by country.
  - Interaction allows different responses for FCS vs non-FCS via I_{i,t−1} dummy.
  - Lag length L set to 2.
  - Coefficients {β_{1,s}} and {β_{0,s}} form IRFs for FCS and non-FCS, respectively.

### Impact of global shocks (main empirical findings)
- Commodity ToT shock (one percent of GDP)
  - In FCS, a commodity ToT shock equal to one-percent of GDP leads to a 0.4 percent change in GDP per capita.
  - The magnitude in FCS is twice as large as in non-FCS; difference significant at 5 percent in years two to four.
  - Primary channel: procyclical fiscal responses in FCS—public consumption and public investment move sharply with the shock, persistent increases in expenditure offset initial revenue gains and deteriorate fiscal balance.
  - Private consumption responds significantly in FCS, suggesting households are cash-constrained and lack smoothing mechanisms.
  - Real exports show insignificant responses in FCS, implying low elasticity to global commodity prices and income effects dominate; larger imports offset parts of domestic activity increases.
- Global demand shock (one percent of GDP)
  - Both FCS and non-FCS show stronger GDP per capita responses in FCS driven by more procyclical fiscal policy.
  - FCS experience large and persistent increases in public consumption and public investment, deteriorating fiscal balance in later years.
  - Non-FCS expenditure responses are muted, indicating slightly counter-cyclical fiscal policy.
  - Real exports in FCS do not increase in response, whereas non-FCS show slight increases in years three and four; suggests FCS face constraints scaling up production capacity.
- U.S. interest rate shock (1 percentage point decline in 10-year rate)
  - A 1 percentage point decline tends to raise GDP per capita about 2 percent more in FCS than in non-FCS over a 5-year horizon; difference initially significant at 5 percent, less so after four years.
  - Channel: increases in public investment in FCS over five years raise total expenditure while revenue remains unchanged, deteriorating fiscal balance.
  - Public consumption does not respond differently across groups.
  - Interpretation: easier global financial conditions can magnify financing prospects for some FCS (despite limited access), with heterogeneous channels (e.g., currency pegs, pass-through to domestic policy).

### Potential drivers of amplified responses and policy-relevant implications
- Cross-cutting drivers associated with excess sensitivity to shocks:
  - Low institutional quality (WGI): countries in bottom 25th percentile of WGI display excess sensitivity; weak governance underpins procyclical fiscal responses and weak control over spending.
  - Lack of export diversification: amplifies impact of ToT shocks due to inability to reallocate export revenues across products.
  - Low financial development: associated with higher sensitivity, reflecting limited access to financing to smooth shocks.
  - Interdependence: around 80 percent of countries in the bottom 25th percentile on at least one of the three indicators also display weakness in another indicator (as of 2021).
- Role of buffers:
  - Countries with lower buffers (government debt, current account, FX reserves) tend to have wider IRF confidence bands and greater volatility, complicating inference.
- Policy-relevant observation:
  - Fiscal rules and improved institutional capacity can reduce procyclicality of fiscal responses, but adoption and enforcement of fiscal rules in FCS can be lengthy given fragility of institutions.
  - Heuristic, multi-faceted approaches are needed to address interlinked fragility features (institutions, diversification, financial development, buffers).

*Sources: WEO database, World Bank, Uppsala Conflict Data Project (UCDP), and IMF staff calculations.*

### conclusion. That said, across all three indicators, lower buffers tend to be associated with higher

### Conclusion

### Robustness Check
- Purpose: Test whether results on the impact of commodity Terms of Trade (ToT) shocks are driven by endogenous country characteristics other than fragility and conflict.
- Variations examined (Figure 7):
  - Panel (A): Adds one-year lagged controls used in Table 2 regressions—number of conflict events per capita, average WGI score, export diversification index, financial development index, and an indicator of FCS.
  - Panel (B): Further adds lagged macroeconomic conditions—public external debt-to-GDP ratio, current account-to-GDP ratio, international reserve-to-imports ratio, fiscal balance-to-GDP ratio, CPI inflation, and per capita GDP growth rate.
  - Panel (C): Excludes small states with population lower than 1.5 million. Sample small-state composition in 2021: 7 FCS small states (Comoros, Kiribati, Marshall Islands, Micronesia, Solomon Islands, Timor-Leste, and Tuvalu) and 6 non-FCS small states (Bhutan, Cabo Verde, Djibouti, Eswatini, São Tomé and Príncipe, and Vanuatu).
  - Panel (D): Excludes large commodity exporters by removing countries with an export share higher than 10 percent for any commodity (UN Comtrade 2018). This led to exclusion of 2 FCS (Niger and Zimbabwe) and 8 non-FCS (Bolivia, Côte d’Ivoire, Ghana, India, Kenya, Philippines, Rwanda, Vietnam) in 2021.
- Findings:
  - The estimated impulse response functions (IRFs) remain close to the main specification across these robustness checks, confirming the exogeneity of the shock variable.
  - Overall IRF patterns in panels (A)–(D) are mostly similar to the main specification.

### External Financing
- Objectives:
  - Assess the response of external capital inflows to shocks and whether this depends on FCS status.
  - Evaluate how important external capital inflows are in mitigating shock impacts.
- Cross-country averages (pooled sample 2006–2021; Figure 8) — descriptive patterns:
  - FCS rely more on concessional supports from donors (ODA, grants) to fill financing needs.
  - Trade deficits are larger in FCS compared to non-FCS on average.
  - FCS receive significantly lower portfolio flows than non-FCS but rely on FDI inflows at a similar level.
  - Other investment (including external loans) tends to be lower in FCS, consistent with greater reliance on grant supports.
- Responses to commodity ToT shocks (Figure 9):
  - ODA and grants: No significant response either in FCS or non-FCS; these inflows are a-cyclical.
  - FDI: Initially declines in FCS in response to a positive shock (may reflect GDP denominator dynamics) and remains insignificantly different from zero after the second year. No significant difference in the overall response of FDI across FCS and non-FCS.
  - Interpretation: ODA and grants include project financing and are largely driven by long-term development needs rather than short-term cycles. Other financing (e.g., IMF lending) can be counter-cyclical—IMF lending increased notably after the pandemic (Figure 10).
- Heterogeneous impact analysis (Figure 11):
  - Method: Split sample into low (below sample average) and high (above sample average) recipients of ODA, grants, and FDI (percent of GDP) and estimate IRFs of per capita GDP to a 1 percent of GDP commodity ToT shock.
  - Findings:
    - The higher sensitivity of FCS versus non-FCS to commodity ToT shocks arises primarily from countries that are low recipients of ODA and grants.
    - Among high recipients of ODA and grants, responses of per capita GDP in FCS and non-FCS are quite similar (responses marginally significant).
    - No distinct patterns across low and high FDI recipients—FDI is mostly linked to long-term projects (e.g., commodity exploitation) and does not serve as a short-term shock absorber.
  - Caveat: The analysis does not exclude the possibility of a third factor determining both low levels of concessional inflows and greater sensitivity to shocks (e.g., countries in more stable political/economic situations may have greater absorption capacity; conflict-intense cases may make donor support infeasible).
  - Policy implication: Development partners should remain engaged when feasible to enable counter-cyclical policy responses.

### Concluding Remarks (policy-relevant findings and recommendations)
- Main empirical conclusions:
  - FCS economies are more sensitive to global shocks compared to non-FCS economies.
  - A key driver of higher sensitivity in FCS is procyclical fiscal responses.
  - Common features of FCS—weak institutions, lack of economic diversification, and low financial development—contribute to procyclical fiscal responses and propagation of global shocks.
  - Lower buffers before shocks (limited fiscal space and inadequate international reserves) exacerbate the effects of global shocks.
- Policy recommendations (heuristic approach across macroeconomic policy institutions):
  - Create fiscal buffers and preserve room for counter-cyclical fiscal policies.
  - Strengthen external balance by diversifying the export base and building international reserves.
  - Strengthen public finance and investment management.
  - Establish (resource-based) frameworks for medium-term fiscal policy to support resilience and smooth pent-up demand in positive shocks.
  - Improve transparency, reduce corruption, and target social spending to address roots of fragility and improve trust in economic institutions.
  - International financial institutions should continue to provide timely and efficient financial support during/after global shocks to enable counter-cyclical policies.
  - Tailor policy advice to country-specific characteristics: nature of vulnerabilities (conflict vs. institutional fragility), economic structure (commodity exporters, tourism-dependent), and geographical factors (small island states).
- Broader context and urgency:
  - The global economy is in a more shock-prone world with increased uncertainty and rising fragility.
  - Building economic buffers and sound institutions is crucial to enhance resilience and prevent long-term scarring that could weigh on long-run growth.
  - Multidimensional sources of excess sensitivity include fiscal and external buffers, institutional, and structural factors; vulnerabilities can fluctuate over time.
  - Granular and timely risk assessments are essential to detect potential sources of instability.

*IMF Working Paper — conclusion section*

### Annex II. Additional Empirical Results

### Annex II. Additional Empirical Results

### Impulse Response Figures (Full Results)
- Annex II. Figure 1. IRFs to a Commodity ToT Shock, FCS (blue) vs. non-FCS (gray) – full results
- Annex II. Figure 2. IRFs to a Global Demand Shock, FCS (blue) vs. non-FCS (gray) – Full Results
- Annex II. Figure 3. IRFs to a U.S. Interest Rate Decline Shock, FCS (blue) vs. non-FCS (gray) – Full Results

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*Macroeconomic Shocks and Conflict — Working Paper No. WP/2024/214*

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