## 1. Inflation Dynamics in CFA Sub-Saharan African Economies

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### Major themes and analytical focus
- Contribution of Supply Shocks to Inflation Variations (Figure 1: "Selected NCFA-SSA: Contribution of Supply Shocks to Inflation Variations" — p. 12).
- Contribution of Global Oil Shocks to Inflation and Oil Intensity (Figure 2: "NCFA-SSA: Contribution of Global Oil Shocks to Inflation and Oil Intensity" — p. 12).
- Role of Weather Shocks and Agriculture in Domestic Supply Shock contributions to inflation (Figure 3: "The Contribution from Domestic Supply Shocks to Inflation: The role of Weather Shocks and Agriculture" — p. 13).
- Impulse responses of output and inflation to negative domestic supply shocks (Figure 4: "Selected NCFA-SSA: Impulse Responses of Output and Inflation to a Negative Domestic Supply Shock" — p. 14).
- Contribution of Demand Shocks to Inflation Variations (Figure 5: "Selected NCFA-SSA: Contribution of Demand Shocks to Inflation Variations" — p. 14).
- Domestic demand shocks and their contribution to inflation (Figure 6: "Selected NCFA-SSA: Contribution of Domestic Demand Shocks to Inflation" — p. 15).
- Mean and standard deviation dynamics of inflation (rolling average) (Figure 7: "NCFA-SSA: Mean and Standard Deviation of Inflation (rolling average)" — p. 16).
- Changes in the relative contribution of shocks in 1999–2013 (Figure 8: "Selected NCFA-SSA: Changes in the Relative Contribution of Shocks in 1999–2013" — p. 17).
- Changes in the contribution of domestic supply shocks in 1999–2013 (Figure 9: "Select NCFA-SSA. Changes in the Contribution of Domestic Supply Shocks in 1999–2013" — p. 17).
- Changes in the contribution of domestic shocks to monetary variables in 1999–2013 (Figure 10: "Selected NFA-SSA. Changes in the Contribution of Domestic Shocks to Monetary Variables in 1999–2013" — p. 18).
- Cross-group comparison of inflation drivers (Figure 11: "Inflation Drivers in NCFA-SSA vs. Other Developing Countries and Advanced Economies" — p. 20).

### Data and methodology
- Model and sample:
  - Global VAR (GVAR) framework for 65 countries including 33 SSA countries, aggregated into 35 countries/regions (8 Euro area grouped, 14 CFA countries grouped, 33 modeled individually).
  - Estimation period: 1998:1–2013:1 using quarterly data.
  - Country variables: CPI, nominal effective exchange rate (NEER), broad money (M), nominal interest rates (NIR), real GDP (RGDP); global oil and food prices included.
- Pre-estimation tests and variable properties:
  - Unit root tests: Dickey-Fuller (DF) and weighted symmetric (WS) ADF.
  - Findings: nominal interest rate, oil and food prices are I(1); CPI, NEER, RGDP, and broad money appear to be I(2) in most countries, so first differences used.
- GVAR estimation details:
  - Two-step estimation: country-specific VARX* models with domestic and trade-weighted foreign variables treated as weakly exogenous; then stack and solve simultaneously.
  - Trade weights w_ij used to construct foreign variables; PPP-GDP weights used for regional aggregation (averaged over 2000–10).
  - Lag orders p_i and q_i selected by Akaike information criterion (maximum lag = 2).
  - Cointegration ranks by Johansen’s trace statistic.
  - Weak exogeneity rejected in only 25 out of 264 cases.
  - Stability condition: eigenvalues of the GVAR model not greater than one.
- Analytical tools:
  - Generalized forecast error variance decomposition (FEVD) over 10 quarters used to quantify contributions to inflation variation.
  - Generalized impulse responses used for dynamic analysis.

### Aggregate empirical findings (NCFA-SSA; full sample 1988:1–2013:1; generalized FEVD over 10 quarters)
- Overall decomposition:
  - Supply shocks explain about 45 percent of inflation fluctuations in the region on average.
  - Demand shocks explain about 55 percent of inflation fluctuations in the region on average.
- Supply-side details:
  - One-third of the supply-shock contribution reflects shocks to global commodity prices and inflation spillovers from other countries.
  - Two-thirds of the supply-shock contribution reflect domestic supply shocks (e.g., weather-related shortfalls).
  - Global oil and food prices explain about 7 percent of inflation fluctuations on average.
  - Domestic supply shocks average about 30 percent of inflation variation; in weather-vulnerable and agriculture-intensive economies (Ethiopia and Sierra Leone) domestic supply shocks explain ~40 percent.
- Demand-side details:
  - Shocks to exchange rate and monetary variables account for nearly three-quarters of the demand-shock contribution.
  - Money supply and interest rate changes explain about 26 percent of inflation fluctuations.
  - Exchange rate changes explain about 16 percent of inflation fluctuations (larger role in Malawi, Seychelles, Zambia).
  - Output (output gap) shocks explain about 13 percent of inflation fluctuations.
- Geographic origin of demand shocks:
  - Domestic demand factors explain about 15 percent of inflation variation on average.
  - Foreign demand shocks explain about 40 percent of inflation fluctuations: regional factors about 15 percent and global factors about 25 percent.
  - Contribution of foreign demand spillovers increases with trade openness (example: Mauritius, Seychelles, Swaziland with average trade openness ~130 percent have foreign factors >50 percent).
- Country-characteristics influence:
  - Oil intensity, import shares, vulnerability to weather shocks, agriculture’s GDP share, trade openness, and policy regime explain cross-country heterogeneity in shock contributions.

### Changes in drivers over time (sub-sample 1987:1–1998:4 vs. 1999:1–2013:1; structural break analysis and robustness checks reported)
- Broad shifts in 1999–2013 relative to full sample:
  - Role of regional and global factors rose in most countries by about 20 percent in total on average.
  - Importance of global oil and food prices doubled to 13 percent in recent period.
  - Domestic supply shocks declined to 13 percent on average from 30 percent for the full sample.
  - Domestic demand shocks became relatively more important among domestic factors (about a 30 percent increase in their role relative to supply-side factors).
  - Within domestic demand, contributions of exchange rate and monetary policy shocks declined by about 4 percent on average.
  - Output shocks’ contribution to inflation increased by about 5 percent on average in recent period (from 10 percent over whole period); in frontier economies increase averaged about 10 percent.
- Drivers of these changes:
  - Increased trade openness and capital openness (Jahan and Wang, 2015) — trade and capital openness increased by more than half over the last two decades.
  - Large commodity price shocks since 2000 (notably 2007–2008 and 2010–2011).
  - Reduced wars/conflicts, economic diversification, infrastructure improvements, strengthened institutions and policies.

### Box: Key properties and changes specific to CFA-SSA (Box 1 summary)
- Geographic composition and decomposition:
  - The CFA franc zone includes 14 Sub‑Saharan African countries.
  - Domestic factors account for 45 percent of inflation variations in CFA-SSA.
  - Regional factors account for 23 percent of inflation variations in CFA-SSA.
  - Global factors account for 32 percent of inflation variations in CFA-SSA.
- Demand vs. supply:
  - Demand shocks explain 65 percent of inflation fluctuations in CFA-SSA.
  - Supply shocks explain 35 percent of inflation fluctuations in CFA-SSA.
  - Within demand-side shocks, shocks to the exchange rate account for about 40 percent of the demand-side shocks in CFA countries (compared to about 30 percent in NCFA countries).
  - Domestic supply shocks constitute 60 percent of domestic factors in CFA-SSA, which is 10 percent smaller than in NCFA countries.
- Changes over time in CFA-SSA:
  - The role of foreign factors has almost doubled in CFA-SSA, mainly driven by non-regional factors.
  - Contribution of foreign supply factors increased by about 30 percent.
  - Contribution of foreign demand factors increased by about 8 percent.
  - Global oil and food prices contributed 23 percent to the increase from global factors.
  - Contribution of domestic factors to inflation variations fell from both the demand and supply sides by about 15 and 20 percent respectively.
  - In the more recent period, demand shocks have become relatively less important than supply shocks in CFA-SSA (a contrast with NCFA economies).
- Methodology and robustness notes:
  - Decomposition results are derived from generalized forecast error variance decomposition over 10 quarters.
  - Robustness checks include alternative break point selection (e.g., starting sample from 1997:1 versus 1999:1) with results showing very similar differences "with only a couple of percentage points differences" across geographic origins and nature of shocks.

### Policy implications
- Monetary policy stance:
  - Prevalent supply-side drivers (global commodity prices, weather-related shocks) imply limited short-run monetary policy effectiveness, but do not invalidate monetary stabilization role in the medium term.
  - Growing role of demand-driven pressures calls for an active monetary policy role in aggregate demand management.
- Recommended actions:
  - Adopt a coherent, forward-looking monetary policy framework with clear objectives and instruments to dampen aggregate demand fluctuations and anchor inflation expectations.
  - Strengthen monetary policy frameworks to manage inflation and limit non-systemic policy actions and associated shocks.
  - Maintain price stability and anchor long-term expectations to low and stable inflation to reduce economic uncertainty and support long-term growth.
- Evidence:
  - Decline in role of monetary policy shocks in NCFA-SSA where clearer objectives, transparency, market-based instruments, and in some cases inflation targeting, have been adopted.

### Comparison with other country groups
- Cross-group patterns (generalized FEVD over 10 quarters):
  - Domestic factors play a somewhat more important role in NCFA-SSA and other developing economies than in advanced economies.
  - Foreign factors’ contribution in developing countries increased by about 20 percent on average, matching NCFA-SSA’s increase and approaching advanced-economy levels.
  - Contributions of global oil and food shocks and inflation spillovers are about 8 percent higher on average among advanced economies.
  - Role of domestic supply shocks is much higher in NCFA-SSA than in other developing countries; all groups show declines in variation of inflation explained by domestic supply shocks over time.
  - Declines in the role of domestic shocks to exchange rate and monetary variables occurred in both NCFA-SSA and other developing countries; advanced economies have smaller contributions from these shocks throughout the period.

*Source: _wp15189 - 1. Inflation Dynamics in CFA Sub-Saharan African Economies — PDF chapter/section.*

### 1. Inflation Dynamics in CFA Sub-Saharan African Economies  ______________________ 21

### 1. Inflation Dynamics in CFA Sub-Saharan African Economies

### Major themes and analytical focus
- Contribution of Supply Shocks to Inflation Variations (Figure 1: "Selected NCFA-SSA: Contribution of Supply Shocks to Inflation Variations" — p. 12)
- Contribution of Global Oil Shocks to Inflation and Oil Intensity (Figure 2: "NCFA-SSA: Contribution of Global Oil Shocks to Inflation and Oil Intensity" — p. 12)
- Role of Weather Shocks and Agriculture in Domestic Supply Shock contributions to inflation (Figure 3: "The Contribution from Domestic Supply Shocks to Inflation: The role of Weather Shocks and Agriculture" — p. 13)
- Impulse responses of output and inflation to negative domestic supply shocks (Figure 4: "Selected NCFA-SSA: Impulse Responses of Output and Inflation to a Negative Domestic Supply Shock" — p. 14)
- Contribution of Demand Shocks to Inflation Variations (Figure 5: "Selected NCFA-SSA: Contribution of Demand Shocks to Inflation Variations" — p. 14)
- Domestic demand shocks and their contribution to inflation (Figure 6: "Selected NCFA-SSA: Contribution of Domestic Demand Shocks to Inflation" — p. 15)
- Mean and standard deviation dynamics of inflation (rolling average) (Figure 7: "NCFA-SSA: Mean and Standard Deviation of Inflation (rolling average)" — p. 16)
- Changes in the relative contribution of shocks in 1999–2013 (Figure 8: "Selected NCFA-SSA: Changes in the Relative Contribution of Shocks in 1999–2013" — p. 17)
- Changes in the contribution of domestic supply shocks in 1999–2013 (Figure 9: "Select NCFA-SSA. Changes in the Contribution of Domestic Supply Shocks in 1999–2013" — p. 17)
- Changes in the contribution of domestic shocks to monetary variables in 1999–2013 (Figure 10: "Selected NFA-SSA. Changes in the Contribution of Domestic Shocks to Monetary Variables in 1999–2013" — p. 18)
- Cross-group comparison of inflation drivers (Figure 11: "Inflation Drivers in NCFA-SSA vs. Other Developing Countries and Advanced Economies" — p. 20)

### Data coverage and tabulated summaries
- Historical inflation comparisons by period (Table 1: "Inflation in SSA. 1985–1995, 1995–2005, 2005–2013" — p. 4)
- Countries and regions included in the GVAR model (Table 2: "Countries and regions in the GVAR model" — p. 7)
- Additional tabular material referenced in main content (Table 3 — listed)

### Appendices, structural break analysis, and robustness testing
- Structural Break Analysis and Robustness Tests (Appendices header — p. 23)
- Break Point Analysis and Structural Break Tests (Appendix A.1: "Break Point Analysis and Structural Break Tests" — p. 23)
- Robustness Tests on the Break Points (Appendix A2: "Robustness Tests on the Break Points" — p. 24)
- Appendix figures:
  - "Appendix Figure A.1. NCFA-SSA. Structural Break Point Estimates" — p. 23
  - "Appendix Figure A.2. Changes in the Contribution of Shocks to Inflation in NCFA-SSA: Break.Point 1997:1 vs. 199:1" — p. 25
- Appendix table:
  - "Appendix Table A.1: Number of Rejections of the Null of Parameter Constancy per. Variable Across the Country-Specific Models at 5 Percent Significance Level" — p. 24

*Source: _wp15189 - 1. Inflation Dynamics in CFA Sub-Saharan African Economies — PDF chapter/section (page and figure/table listings as given in the source content).*

### REFERENCES ___________________________________________________________________________  26

### _wp15189 - REFERENCES ___________________________________________________________________________  26

### I. INTRODUCTION
- Inflation and inflation volatility in Sub-Saharan Africa (SSA) have been gradually declining.
- Historical drivers and policy context:
  - In the 1980s, monetary policy was subordinated to financing large fiscal deficits, leading to high inflation and, with fixed exchange rates, overvalued real exchange rates (Berg et al., 2015).
  - From the mid–1980s to the late 1990s: exchange rate unifications, movement toward more market-determined exchange rates, reductions in central bank financing of government, financial liberalizations, substantial debt relief, and improved external environment supported fiscal discipline and money-based disinflation to single digits by the late 1990s.
- Challenges for policymakers:
  - Headline inflation is considerably more volatile in SSA relative to other regions due to high share of food in the CPI and volatile food prices (unstable agricultural production).
  - Output and inflation tend to be negatively correlated, intensifying the tradeoff between inflation and output stability.
  - Supply-side shocks reduce short-run efficacy of monetary policy.
  - Weaker money–inflation relationship over time limits money-targeting regimes’ effectiveness (IMF 2014).
- Objective of the paper:
  - Identify forces driving inflation dynamics across SSA by explicitly incorporating domestic, regional, and global factors and their interactions.
  - Distinguish supply factors (commodity prices and inflation) and demand factors (shocks to money supply, nominal interest rates, exchange rates, and real activity).
  - Improvements over prior literature: (i) explicit accounting for trade and financial linkages across economies; (ii) study of how drivers changed over time.

### II. DATA AND METHODOLOGY
- Model and sample:
  - Global VAR (GVAR) framework for 65 countries including 33 SSA countries, aggregated into 35 countries/regions (8 Euro area grouped, 14 CFA countries grouped, 33 modeled individually).
  - Estimation period: 1998:1–2013:1 using quarterly data.
  - Country variables: CPI, nominal effective exchange rate (NEER), broad money (M), nominal interest rates (NIR), real GDP (RGDP); global oil and food prices included.
  - Data sources: IMF International Financial Statistics (IFS), World Economic Outlook (WEO), Smith and Galesi (2014) dataset for some non-SSA variables, World Bank WDI for PPP-GDP, IMF Direction of Trade for trade weights.
- Pre-estimation tests and variable properties:
  - Unit root tests: Dickey-Fuller (DF) and weighted symmetric (WS) ADF (Park and Fuller, 1995).
  - Findings: nominal interest rate, oil and food prices are I(1); CPI, NEER, RGDP, and broad money appear to be I(2) in most countries, so first differences used.
- GVAR approach summary:
  - Two-step approach: (1) estimate country-specific VARX* models with domestic and trade-weighted foreign variables treated as weakly exogenous; (2) stack and solve simultaneously to form a global VAR.
  - Trade weights w_ij used to construct foreign variables; PPP-GDP weights used for regional aggregation (averaged over 2000–10).
  - Lag orders p_i and q_i selected by Akaike information criterion (maximum lag = 2).
  - Cointegration ranks determined by Johansen’s trace statistic.
  - Weak exogeneity tests for foreign and global variables: exogeneity rejected in only 25 out of 264 cases; majority non-SSA and frequency reduced with higher lag length.
  - Stability condition: eigenvalues of the GVAR model not greater than one.
- Model specification:
  - Country-specific VARX* includes five domestic variables: (CPI, NEER, M, NIR, RGDP).
  - All models (except the U.S.) include country-specific weakly exogenous foreign variables: (trade-weighted foreign CPI, trade-weighted foreign RGDP, trade-weighted foreign M, trade-weighted foreign NEER).
  - Global oil and food prices modeled weakly exogenous for all countries except the U.S.
- Analytical tools:
  - Generalized forecast error variance decomposition (FEVD) used to quantify contributions to inflation variation (Koop, Pesaran and Potter, 1996; Pesaran and Shin, 1998).
  - Generalized impulse responses used for dynamic analysis.

### III. EMPIRICAL RESULTS AND DISCUSSIONS — DRIVERS OF INFLATION IN NCFA-SSA
- Definitions:
  - Supply shocks: shocks to oil prices, food prices, and inflation itself.
  - Demand shocks: shocks to real activity, NEER, money supply, and nominal interest rates.
  - Domestic factors: impact of domestic supply and demand shocks on domestic inflation.
  - Regional factors: impact of shocks in other SSA economies.
  - Global factors: impact of shocks in the 32 non-SSA economies of the model including global oil and food shocks.
- Aggregate contributions (generalized FEVD over 10 quarters; full-sample 1988:1–2013:1):
  - Supply shocks explain about 45 percent of inflation fluctuations in the region on average.
    - One-third of the supply-shock contribution reflects shocks to global commodity prices and inflation spillovers from other countries.
    - Two-thirds reflect domestic supply shocks (e.g., weather-related shortfalls).
  - Global oil and food prices explain about 7 percent of inflation fluctuations on average.
    - Contribution of global commodity prices is larger in economies with higher oil intensity (kg oil equivalent per capita per $1000 GDP, constant 2011 PPP).
    - Largest oil/food importers relative to GDP (Botswana, Mauritius, Seychelles, Swaziland) show particularly significant contributions from global oil and food price shocks.
  - Foreign inflation spillovers contribute about 8 percent on average.
    - Importance increases with higher import shares; Mauritius, Seychelles, Cabo Verde noted as more exposed.
  - Domestic supply shocks average about 30 percent of inflation variation, especially in weather-vulnerable and agriculture-intensive economies (e.g., Ethiopia and Sierra Leone: domestic supply shocks explain ~40 percent).
  - Demand shocks explain about 55 percent of inflation fluctuations, broken down as:
    - Shocks to exchange rate and monetary variables: nearly three-quarters of the demand-shock contribution.
      - Money supply and interest rate changes explain about 26 percent of inflation fluctuations.
      - Exchange rate changes explain about 16 percent of inflation fluctuations (larger role in Malawi, Seychelles, Zambia).
    - Output (output gap) shocks explain about 13 percent of inflation fluctuations.
  - Geographic origin of demand shocks:
    - Domestic demand factors explain about 15 percent of inflation variation on average.
      - Larger domestic demand impacts in frontier economies (Ghana, Kenya, Uganda, Zambia).
      - In commodity exporters (Burundi, Malawi) domestic demand shocks also relatively important, potentially via volatile commodity prices and government spending linkages.
    - Foreign demand shocks explain about 40 percent of inflation fluctuations:
      - Regional factors contribute about 15 percent.
      - Global factors contribute about 25 percent.
      - Contribution of foreign demand spillovers increases with trade openness (e.g., Mauritius, Seychelles, Swaziland with average trade openness ~130 percent have foreign factors >50 percent).
- Country-characteristics influence:
  - Oil intensity, import shares, vulnerability to weather shocks, agriculture’s GDP share, trade openness, and policy regime explain cross-country heterogeneity in shock contributions.

### IV. HAVE DRIVERS OF INFLATION IN NCFA-SSA CHANGED OVER TIME?
- Sub-sample split and rationale:
  - Full sample divided into two sub-samples: 1987:1–1998:4 and 1999:1–2013:1 (guided by rolling mean and standard deviation of inflation).
  - Structural break analysis and robustness checks (including GARCH(1,1) for conditional standard errors) referenced; appendix elaborates.
- Key changes in 1999–2013 relative to full sample:
  - Role of regional and global factors rose in most countries by about 20 percent in total on average.
    - Attributed to increases in trade openness (sum of exports and imports as percent of GDP) and capital openness (Jahan and Wang, 2015) increasing by more than half over the last two decades.
    - Importance of global oil and food prices doubled to 13 percent in recent period, driven by large commodity price shocks since 2000 (notably 2007–2008 and 2010–2011).
  - Domestic supply shocks declined across NCFA-SSA:
    - Domestic supply shocks reduced to 13 percent on average from 30 percent for the full sample.
    - Potential causes: reduced wars/conflicts, economic diversification, infrastructure improvements, strengthened institutions and policies.
  - Domestic demand shocks became relatively more important among domestic factors:
    - About a 30 percent increase in their role relative to supply-side factors.
    - Within domestic demand, contributions of exchange rate and monetary policy shocks declined by about 4 percent on average.
      - Reasons: movement toward more flexible exchange rate regimes (mid-1980s to late 1990s) and more flexible/forward-looking monetary policy frameworks in the 2000s (greater central bank independence, reduced fiscal dominance, more market-based policies).
  - Output shocks’ contribution to inflation increased by about 5 percent on average in recent period (from 10 percent over whole period); in frontier economies increase averaged about 10 percent due to higher growth and demand base.

### V. POLICY IMPLICATIONS
- Monetary policy role:
  - Prevalent supply-side drivers (global commodity prices, weather-related shocks) imply limited short-run monetary policy effectiveness, but do not invalidate monetary stabilization role in the medium term.
  - Growing role of demand-driven pressures calls for an active monetary policy role in aggregate demand management.
  - Recommendations:
    - Adopt a coherent, forward-looking monetary policy framework with clear objectives and instruments to dampen aggregate demand fluctuations and anchor inflation expectations.
    - Strengthen monetary policy frameworks to manage inflation and limit non-systemic policy actions and associated shocks.
    - Maintaining price stability and anchoring long-term expectations to low and stable inflation reduces economic uncertainty and supports long-term growth.
  - Evidence: decline in role of monetary policy shocks in NCFA-SSA where clearer objectives, transparency, market-based instruments, and in some cases inflation targeting, have been adopted.

### VI. COMPARISON WITH OTHER DEVELOPING AND ADVANCED ECONOMIES
- Broad comparisons (generalized FEVD over 10 quarters):
  - Domestic factors play a somewhat more important role in NCFA-SSA and other developing economies than in advanced economies.
  - Foreign factors’ contribution in developing countries increased by about 20 percent on average, matching NCFA-SSA’s increase and approaching advanced-economy levels.
  - Contributions of global oil and food shocks and inflation spillovers are about 8 percent higher on average among advanced economies.
  - The role of domestic supply shocks is much higher in NCFA-SSA than in other developing countries, reflecting frequent and large supply shocks in the region.
  - All groups show declines in variation of inflation explained by domestic supply shocks over time.
  - Declines in the role of domestic shocks to exchange rate and monetary variables occurred in both NCFA-SSA and other developing countries, consistent with moves toward more flexible exchange rate regimes and stronger monetary frameworks; advanced economies have smaller contributions from these shocks throughout the period.

*Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2015/_wp15189.pdf*

### Box 1. Inflation Dynamics in CFA Sub-Saharan African Economies

### Box 1. Inflation Dynamics in CFA Sub‑Saharan African Economies

### Key properties of inflation dynamics
- The CFA franc zone includes 14 Sub‑Saharan African countries (see Table 2 in source).
- Domestic factors account for 45 percent of inflation variations in CFA-SSA.
- Regional factors account for 23 percent of inflation variations in CFA-SSA.
- Global factors account for 32 percent of inflation variations in CFA-SSA.
- Demand shocks explain 65 percent of inflation fluctuations in CFA-SSA.
- Supply shocks explain 35 percent of inflation fluctuations in CFA-SSA.
- Within demand-side shocks, shocks to the exchange rate account for about 40 percent of the demand-side shocks in CFA countries (compared to about 30 percent in NCFA countries).
- Domestic supply shocks constitute 60 percent of domestic factors in CFA-SSA, which is 10 percent smaller than in NCFA countries.
- The decomposition is based on generalized forecast error variance decomposition over 10 quarters.

### Changes in inflation dynamics over time
- The role of foreign factors has almost doubled in CFA-SSA, mainly driven by non-regional factors.
- The contribution of foreign supply factors increased by about 30 percent.
- The contribution of foreign demand factors increased by about 8 percent.
- Global oil and food prices contributed 23 percent to the increase from global factors.
- The contribution of domestic factors to inflation variations fell from both the demand and supply sides by about 15 and 20 percent respectively.
- In the more recent period, demand shocks have become relatively less important than supply shocks in CFA-SSA (a contrast with NCFA economies).

### Implications and interpretation
- The geographic origins of shocks in CFA-SSA broadly align with the decomposition: domestic (45 percent), regional (23 percent), global (32 percent).
- The increased role of global oil and food shocks and inflation spillovers implies greater exposure to global inflation and growth developments.
- Structural differences relative to NCFA countries include a larger role for exchange rate shocks within demand-side drivers in CFA countries.

### Methodology and robustness notes (as presented)
- Decomposition results are derived from generalized forecast error variance decomposition over 10 quarters.
- Source data: IFS Database of the IMF, and authors' calculations.
- Structural break and robustness analyses (presented elsewhere in the chapter) use methods including Bai and Perron (1998) break tests, Ploberger and Krämer (1992) CUSUM statistics, Nyblom (1989) tests, and sequential Wald-type tests (QLR, MW, APW) with heteroscedasticity-robust variants.
- Robustness checks include alternative break point selection (e.g., starting sample from 1997:1 versus 1999:1) with results showing very similar differences "with only a couple of percentage points differences" across geographic origins and nature of shocks.

*Source: IFS Database of the IMF, and authors' calculations (from Box 1. Inflation Dynamics in CFA Sub‑Saharan African Economies).*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2015/_wp15189.pdf_