## 2. External Financing to Mali

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---

### Evidence of Heightened Uncertainty in Mali
- Mentions of ‘uncertainty’ and related terms in economic reports:
  - Between 2012 and 2022 this index was over 50 percent higher on average than the previous decade.
  - The number of mentions more than doubled in the second half of 2023 and rose further at the start of 2024; the series fell back somewhat during the rest of 2024 but remains elevated relative to the past.
  - The level of measured uncertainty at the start of 2025 is comparable to 2020 (coup d’état and COVID pandemic).
- Structural and situational drivers:
  - Longstanding security challenges, including multiple coups d’état; Mali ranks fourth globally in a list of countries most affected by terrorism and has the lowest score of all countries for perceptions of safety (Institute for Economics and Peace, 2023 and 2024).
  - Extreme weather and natural disasters have become more prevalent; agriculture is the main source of employment and income for 60 percent of the active population.
- Survey evidence and business sentiment:
  - Surveys by the Conseil National du Patronat du Mali (CNPM) show that over 70 percent of businesses report the lack of security, the general economic climate and the social and political situation each have a negative effect on their performance.
- External financing developments:
  - Budgetary loans to Mali have fallen to zero since 2022.
  - Project loans are much lower than in the past, while amortization costs continue.
  - Net external financing components shown in Figure 2 include Project loans, Budgetary loans, Amortization, Other (which includes debt relief and any changes in external arrears).

### Mali-Specific Policy Announcements and Financial Market Signals
- Recent policy announcements increasing uncertainty:
  - June 2023: request for withdrawal of UN peacekeeping forces (MINUSMA); exit from the G5 Sahel Alliance and Algiers Peace Accord.
  - January 2024: Mali, Burkina Faso and Niger announced they would leave the ECOWAS trading bloc.
  - Presidential elections originally scheduled for February 2024 were cancelled.
- Country-specificity:
  - Recent increases in measured uncertainty are not mirrored to the same extent in Burkina Faso and Niger during 2024, suggesting domestic policy choices explain some of the rise.
  - Ongoing IMF-supported programs in Burkina Faso and Niger may have had some role in reducing uncertainty in those countries.
- Interest premia and market spreads:
  - Interest rate spreads for most WAEMU countries relative to the euro area have only risen modestly since the start of 2023; spreads for Mali, Burkina Faso and Niger increased by more.
  - Mali paid the highest interest premia of these countries during the second half of 2023.
  - By May 2025:
    - The interest yield on one-year T-bills in Mali was 2.2 percentage points higher than in the rest of the WAEMU.
    - The interest rate premium on three-year bonds was 1.2 percentage points higher.
  - Note: Comparisons between Mali and Niger are not possible for the second half of 2023 because Niger was under economic sanctions and did not issue debt on the regional market.

### The Impact of Heightened Uncertainty on Economic Activity
- Channels through which uncertainty reduces activity:
  - Business investment:
    - Heightened uncertainty increases the ‘option value of waiting’ and reduces capital spending, especially for irreversible investment with large up-front costs.
    - Private and public investment in Mali have been extremely low for a number of years; further reductions would shrink the capital stock and reduce future productivity.
  - Trade:
    - Reduced investment can lower cross-border trade and prevent firms from realizing productivity gains associated with exporting.
    - Uncertainty around tariffs and regulatory alignment (e.g., ECOWAS exit) would be expected to affect trade with non-WAEMU ECOWAS countries more than general economic uncertainty alone.
    - Uncertainty around the implementation of the revised mining code could discourage future investment in a sector that makes up a large share of Mali’s GDP.
  - Households:
    - Households facing uncertainty undertake precautionary saving, reducing consumption where possible—especially durable goods.
    - Many households are near subsistence levels, limiting their ability to cut consumption further.
  - Credit and fiscal constraints:
    - Increased interest premia or reduced credit availability would further reduce spending by businesses and households and could create difficulties financing the fiscal deficit.
    - In less-developed financial markets, credit constraints may prevent smoothing of shock impacts.

### Quantitative Effects on GDP and Growth-at-Risk Analysis
- Short-run correlation:
  - A two-standard deviation increase in uncertainty is associated with a 0.9 percentage point fall in GDP growth in the following quarter.
  - Note: These results do not necessarily imply causality.
- Growth-at-risk distributional effects:
  - A growth-at-risk model (quantile regression with annual GDP as dependent variable and uncertainty citations as the explanatory variable of interest, controlling for gold and cotton prices, money supply, inflation, and coups d’état) shows that higher uncertainty widens the distribution of possible annual GDP outcomes.
  - Example: The model suggests that the probability of a recession (defined as negative annual growth) increases by just under 20 percentage points when uncertainty rises by two standard deviations.

### Conclusions and Policy Recommendations
- Key conclusions:
  - Economic uncertainty in Mali is high and is weighing on GDP growth, with private capital spending particularly affected.
  - Some uncertainty is unavoidable due to external shocks, but recent unexpected policy announcements have further increased difficulty for businesses and households to plan.
  - Low existing investment and limited access to credit could exacerbate the negative impacts of heightened uncertainty.
- Policy directions to reduce uncertainty and fragility:
  - Address the many sources of fragility to resolve longstanding uncertainty.
  - Remove constraints to good policy decision-making, including increasing transparency and ensuring accurate statistics are available.
  - Remove other constraints to growth, for example by raising education levels and improving governance.
  - Mitigate stressors such as climate risks and protect the most vulnerable segments of the population to help Mali exit the fragility trap.
  - Reference: Country Engagement Strategy in the 2023 Staff Report for Mali for more details on these recommendations.

### Policy recommendations to reduce uncertainty (detailed)
- Set out a transparent and detailed medium-term policy framework to provide the basis for strong and sustainable economic growth in Mali and to help households and businesses plan ahead.
- Communicate effective and timely policy changes to avoid unwanted responses and speculation around other possible announcements.
  - Example: setting out expected future corporate tax rates would help businesses to prepare their budgets.
  - If the ECOWAS exit leads to changes in tariff rates or product regulations, communicate these changes well in advance to avoid costly disruption.

### Fiscal policy and buffers
- Sustainable and growth-friendly fiscal policy can reduce policy uncertainty by creating a buffer to deal with future shocks.
- Build fiscal buffers to ensure sufficient resources to respond to negative shocks when they occur.
- Any fiscal consolidation should be achieved in a sustainable way, with emphasis on revenue mobilization as opposed to cutting growth-enhancing capital spending.
- Rebuilding relationships with international development partners could help, particularly if it led to a resumption of external budget support.

### Measuring uncertainty and Growth-at-Risk model (technical notes)
- Uncertainty indicators and measurement:
  - One prominent indicator uses the number of references to ‘uncertainty’ in economic reports (Ahir and others, 2018). Series are available on a quarterly basis; producers recommend using the three-quarter rolling average due to volatility of the underlying data.
  - A news-based indicator records the number of times that ‘uncertainty’ is mentioned within ten words of the country name, divided by the total number of news articles in the period, then standardized to give a z-score Z_t,i.
- Empirical observations and limitations:
  - Based on references in published reports, uncertainty has risen by much more in Mali than in Burkina Faso or Niger over recent quarters.
  - Large spikes in uncertainty across Mali, Burkina Faso and Niger generally coincide with the most high-profile periods of instability; the large spikes in news-based indicators correspond reasonably well with coups d’état and episodes of wider political instability.
  - Methodological limitations include volatility, many observations of zero (notably for Burkina Faso and Niger), potential inconsistency over time due to changing global attention, and influence from other prominent global events.
  - News-based searches include related terms and both English and French variations; for Niger, references related to ‘Nigeria’ are removed; news articles with fewer than ninety-nine words are excluded.
- Growth-at-Risk model framework and estimation:
  - Uses a single-equation quantile regression methodology based on Koenker and Machado, 1999 and Koenker, 2005.
  - Let Δ_h Y_{t+h} denote the log change in real GDP h periods ahead (GDP growth) and X_t denote a vector of key determinants, including past log changes in real GDP:
    - ∆_h ∆Y_{t+h,q} = α_{h,q} + b_{x,h,q} X_t + e_{t,h,q}
  - Estimation uses a linear programming algorithm to estimate quantile regression coefficients β(q) by minimizing weighted deviations via the check function ρ_q(u); coefficients are asymptotically normally distributed under mild regularity conditions.
  - A bootstrap resampling technique is used to generate a distribution of sample statistics.
  - Estimation of extreme quantiles (5 percent and 95 percent) can be inaccurate with large confidence error bands; to address tail fit, a parametric t-skew distribution (skewed Student t, Azzalini, 2003) is used following Adrian and others, 2018.
  - Interpretation: the sequence of b_{x,h,q} coefficients estimated at different horizons h provides a “term structure” of growth-at-risk for each determinant x and quantile q.

### Key statistics and technical specifics preserved from the source
- Frequency and smoothing: three-quarter rolling averages recommended for World Uncertainty Index series.
- Quantiles explicitly noted: 5 percent and 95 percent quantiles for extreme-tail estimation.
- Exclusion rule for news articles: fewer than ninety-nine words are excluded in the news-based indicator construction.
- Countries explicitly compared: Mali, Burkina Faso, Niger.
- Methodological references: Koenker and Machado, 1999; Koenker, 2005; Adrian and others, 2018; Azzalini, 2003.

*Source: Excerpts from the IMF country report content unit provided in the source PDF.*

### 2. External Financing to Mali ____________________________________________________________ 3

### 2. External Financing to Mali

### Evidence of Heightened Uncertainty in Mali
- Mentions of ‘uncertainty’ and related terms in economic reports:
  - Between 2012 and 2022 this index was over 50 percent higher on average than the previous decade.
  - The number of mentions more than doubled in the second half of 2023 and rose further at the start of 2024; the series fell back somewhat during the rest of 2024 but remains elevated relative to the past.
  - The level of measured uncertainty at the start of 2025 is comparable to 2020 (coup d’état and COVID pandemic).
- Structural and situational drivers:
  - Longstanding security challenges, including multiple coups d’état; Mali ranks fourth globally in a list of countries most affected by terrorism and has the lowest score of all countries for perceptions of safety (Institute for Economics and Peace, 2023 and 2024).
  - Extreme weather and natural disasters have become more prevalent; agriculture is the main source of employment and income for 60 percent of the active population.
- Survey evidence and business sentiment:
  - Surveys by the Conseil National du Patronat du Mali (CNPM) show that over 70 percent of businesses report the lack of security, the general economic climate and the social and political situation each have a negative effect on their performance.
- External financing developments:
  - Budgetary loans to Mali have fallen to zero since 2022.
  - Project loans are much lower than in the past, while amortization costs continue.
  - Net external financing components shown in Figure 2 include Project loans, Budgetary loans, Amortization, Other (which includes debt relief and any changes in external arrears).

### Mali-Specific Policy Announcements and Financial Market Signals
- Recent policy announcements increasing uncertainty:
  - June 2023: request for withdrawal of UN peacekeeping forces (MINUSMA); exit from the G5 Sahel Alliance and Algiers Peace Accord.
  - January 2024: Mali, Burkina Faso and Niger announced they would leave the ECOWAS trading bloc.
  - Presidential elections originally scheduled for February 2024 were cancelled.
- Country-specificity:
  - Recent increases in measured uncertainty are not mirrored to the same extent in Burkina Faso and Niger during 2024, suggesting domestic policy choices explain some of the rise.
  - Ongoing IMF-supported programs in Burkina Faso and Niger may have had some role in reducing uncertainty in those countries.
- Interest premia and market spreads:
  - Interest rate spreads for most WAEMU countries relative to the euro area have only risen modestly since the start of 2023; spreads for Mali, Burkina Faso and Niger increased by more.
  - Mali paid the highest interest premia of these countries during the second half of 2023.
  - By May 2025:
    - The interest yield on one-year T-bills in Mali was 2.2 percentage points higher than in the rest of the WAEMU.
    - The interest rate premium on three-year bonds was 1.2 percentage points higher.
  - Note: Comparisons between Mali and Niger are not possible for the second half of 2023 because Niger was under economic sanctions and did not issue debt on the regional market.

### The Impact of Heightened Uncertainty on Economic Activity
- Channels through which uncertainty reduces activity:
  - Business investment:
    - Heightened uncertainty increases the ‘option value of waiting’ and reduces capital spending, especially for irreversible investment with large up-front costs.
    - Private and public investment in Mali have been extremely low for a number of years; further reductions would shrink the capital stock and reduce future productivity.
  - Trade:
    - Reduced investment can lower cross-border trade and prevent firms from realizing productivity gains associated with exporting.
    - Uncertainty around tariffs and regulatory alignment (e.g., ECOWAS exit) would be expected to affect trade with non-WAEMU ECOWAS countries more than general economic uncertainty alone.
    - Uncertainty around the implementation of the revised mining code could discourage future investment in a sector that makes up a large share of Mali’s GDP.
  - Households:
    - Households facing uncertainty undertake precautionary saving, reducing consumption where possible—especially durable goods.
    - Many households are near subsistence levels, limiting their ability to cut consumption further.
  - Credit and fiscal constraints:
    - Increased interest premia or reduced credit availability would further reduce spending by businesses and households and could create difficulties financing the fiscal deficit.
    - In less-developed financial markets, credit constraints may prevent smoothing of shock impacts.

### Quantitative Effects on GDP and Growth-at-Risk Analysis
- Short-run correlation:
  - A two-standard deviation increase in uncertainty is associated with a 0.9 percentage point fall in GDP growth in the following quarter.
  - Note: These results do not necessarily imply causality.
- Growth-at-risk distributional effects:
  - A growth-at-risk model (quantile regression with annual GDP as dependent variable and uncertainty citations as the explanatory variable of interest, controlling for gold and cotton prices, money supply, inflation, and coups d’état) shows that higher uncertainty widens the distribution of possible annual GDP outcomes.
  - Example: The model suggests that the probability of a recession (defined as negative annual growth) increases by just under 20 percentage points when uncertainty rises by two standard deviations.

### Conclusions and Policy Recommendations
- Key conclusions:
  - Economic uncertainty in Mali is high and is weighing on GDP growth, with private capital spending particularly affected.
  - Some uncertainty is unavoidable due to external shocks, but recent unexpected policy announcements have further increased difficulty for businesses and households to plan.
  - Low existing investment and limited access to credit could exacerbate the negative impacts of heightened uncertainty.
- Policy directions to reduce uncertainty and fragility:
  - Address the many sources of fragility to resolve longstanding uncertainty.
  - Remove constraints to good policy decision-making, including increasing transparency and ensuring accurate statistics are available.
  - Remove other constraints to growth, for example by raising education levels and improving governance.
  - Mitigate stressors such as climate risks and protect the most vulnerable segments of the population to help Mali exit the fragility trap.
  - Reference: Country Engagement Strategy in the 2023 Staff Report for Mali for more details on these recommendations.

*From: THE ECONOMIC IMPACT OF UNCERTAINTY IN MALI (INTERNATIONAL MONETARY FUND), July 16, 2025.*

### 19.      The authorities could reduce policy uncertainty by setting out medium-term economic

### The authorities could reduce policy uncertainty by setting out medium-term economic plans and demonstrating their commitment to announced reforms.

### Policy recommendations to reduce uncertainty
- Set out a transparent and detailed medium-term policy framework to provide the basis for strong and sustainable economic growth in Mali and to help households and businesses plan ahead.
- Communicate effective and timely policy changes to avoid unwanted responses and speculation around other possible announcements.
- Example: setting out expected future corporate tax rates would help businesses to prepare their budgets.
- If the ECOWAS exit leads to changes in tariff rates or product regulations, communicate these changes well in advance to avoid costly disruption.

### Fiscal policy and buffers
- Sustainable and growth-friendly fiscal policy can reduce policy uncertainty by creating a buffer to deal with future shocks.
- Build fiscal buffers to ensure sufficient resources to respond to negative shocks when they occur.
- Any fiscal consolidation should be achieved in a sustainable way, with emphasis on revenue mobilization as opposed to cutting growth-enhancing capital spending.
- Rebuilding relationships with international development partners could help, particularly if it led to a resumption of external budget support.

### Measuring uncertainty using economic reports and global news coverage (Annex I)
- Uncertainty indicators:
  - One prominent indicator uses the number of references to ‘uncertainty’ in economic reports (Ahir and others, 2018). Series are available on a quarterly basis; producers recommend using the three-quarter rolling average due to volatility of the underlying data.
  - A news-based indicator records the number of times that ‘uncertainty’ is mentioned within ten words of the country name, divided by the total number of news articles in the period, then standardized to give a z-score Z_t,i.
- Empirical observations:
  - Based on references in published reports, uncertainty has risen by much more in Mali than in Burkina Faso or Niger over recent quarters.
  - Large spikes in uncertainty across Mali, Burkina Faso and Niger generally coincide with the most high-profile periods of instability; the large spikes in news-based indicators correspond reasonably well with coups d’état and episodes of wider political instability.
- Methodological notes and limitations:
  - News-based searches include related terms and both English and French variations; for Niger, references related to ‘Nigeria’ are removed; news articles with fewer than ninety-nine words are excluded.
  - Limitations include volatility, many observations of zero (notably for Burkina Faso and Niger), potential inconsistency over time due to changing global attention, and influence from other prominent global events.

### Growth-at-Risk model for Mali (Annex II)
- Framework:
  - Uses a single-equation quantile regression methodology based on Koenker and Machado, 1999 and Koenker, 2005.
  - Let Δ_h Y_{t+h} denote the log change in real GDP h periods ahead (GDP growth) and X_t denote a vector of key determinants, including past log changes in real GDP:
    - ∆_h ∆Y_{t+h,q} = α_{h,q} + b_{x,h,q} X_t + e_{t,h,q}
- Estimation:
  - A linear programming algorithm estimates quantile regression coefficients β(q) by minimizing weighted deviations via the check function ρ_q(u); coefficients are asymptotically normally distributed under mild regularity conditions.
  - A bootstrap resampling technique is used to generate a distribution of sample statistics.
  - Estimation of extreme quantiles (5 percent and 95 percent) can be inaccurate with large confidence error bands; to address tail fit, a parametric t-skew distribution (skewed Student t, Azzalini, 2003) is used following Adrian and others, 2018.
- Interpretation:
  - For a given output determinant x and quantile q, the sequence of b_{x,h,q} coefficients estimated at different horizons h shows how an increase in x changes the q_t+h quantile of future GDP growth, providing a “term structure” of growth-at-risk.

### Key statistics and technical specifics preserved from the source
- Frequency and smoothing: three-quarter rolling averages recommended for World Uncertainty Index series.
- Quantiles explicitly noted: 5 percent and 95 percent quantiles for extreme-tail estimation.
- Exclusion rule for news articles: fewer than ninety-nine words are excluded in the news-based indicator construction.
- Countries explicitly compared: Mali, Burkina Faso, Niger.
- Methodological references: Koenker and Machado, 1999; Koenker, 2005; Adrian and others, 2018; Azzalini, 2003.

*Source: Excerpts from the IMF country report content unit provided in the source PDF.*

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_Source: https://www.imf.org/-/media/files/publications/cr/2025/english/1mliea2025003-source-pdf.pdf_