## PREFACE — Technical Assistance on Public Debt Projections (tarea2026061)

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---

### Project overview and timeline
- The project concluded the technical assistance to develop a Public Debt Dynamics Tool (DDT) for the National Public Debt Committee (CNDP) of the Islamic Republic of Mauritania.
- Project initiation: January 2024.
- Missions:
  - Exploratory TA mission: Nouakchott, January 8 to January 19, 2024.
  - Second TA mission: August 26 to September 4, 2024.
  - Third TA mission: Nouakchott, January 9 to 15, 2025 (with preparatory work in November and December 2024).
- Mission leadership and team:
  - Head of Mission and Project Manager: Marie Pierre Aquino Coste
  - Senior Economist: Naomitsu Yashiro
  - Economist: Ha Minh Nguyen
- Implementing IMF unit: Institute for Capacity Development (ICD).
- Requesting authority: Ministry of Finance (MoF) of Mauritania.

### Objectives, deliverables, and capacity outcomes
- Primary objective:
  - Strengthen CNDP analytical capacity in public debt analysis and projections; improve coordination and communication among institutions responsible for debt policy.
- Deliverables and outcomes:
  - Customized DDT adopted, including DDT RRC for resource-rich countries and ND_DDT for natural-disaster scenarios.
  - User manuals developed (ND_DDT and DDT RRC) and shared with authorities.
  - CNDP technical team produced a comprehensive public debt report with baseline projections, alternative scenarios, and policy recommendations.
  - Core technical team demonstrated ability to conduct independent debt sustainability assessments and to present the report to General Directors chairing the CNDP.
- Capacity building activities:
  - Online course completed prior to first mission: "Projecting Public Debt – Public Debt Dynamics Tool (DDTx)" (French, edX).
  - Weekly virtual meetings; six virtual meetings between missions.
  - In-person trainings across missions; hands-on sessions to build independent operation capacity of the DDT.
  - A process document created to define roles, responsibilities, data update protocols, and continuity measures.

### Key institutional arrangements and continuity challenges
- CNDP composition:
  - Inter-agency group of six General Directors from the Ministry of Finance, Ministry of Economy and Sustainable Development (MEDD), and Central Bank of Mauritania (BCM).
  - Responsibilities include debt policymaking, sustainability assessments, inter-institutional coordination, and publication of debt statistics.
- Continuity risks and mitigation:
  - Retention of technical staff amid departmental reorganization is critical.
  - Regular training recommended to avoid knowledge fade; mission recommended training new technical team members Twice a year.
  - Recommendation to integrate the DDT and ND_DDT into regular CNDP processes to ensure sustained use.

### Summary of final project recommendations (indicative horizons)
- Recommendation 1: Integrate public debt projections and analyses using the DDT into CNDP policymaking on a regular and more comprehensive basis.
  - Indicative horizon: December 2026
- Recommendation 2: Establish a clear division of tasks and deadlines among public stakeholders involved in projection and drafting of the public debt report.
  - Indicative horizon: December 2026
- Recommendation 3: Provide regular training to new technical team members on the public debt projection tool.
  - Indicative horizon: Twice a year

---

### DDT and DRR DDT customizations (features and rationale)
- DDT core capabilities:
  - Projects public debt as a percentage of GDP.
  - Computes fiscal paths to achieve a user-defined debt target.
  - Performs pre-defined and customized stress tests, produces fan charts, and presents results in standardized output tables.
  - Requires only 10 macro-fiscal variables to perform analyses.
- DRR DDT customization for resource-rich countries (RRC):
  - Structural change: disaggregation of the regular primary balance into:
    - primary balance excluding extractive revenue (non-extractive primary balance), and
    - extractive revenue.
  - Rationale: extractive revenues are volatile and largely exogenous to the state; the non-extractive primary balance is an appropriate policy instrument in resource-intensive countries.
  - Capabilities: simulate fiscal adjustment scenarios, assess long-term impacts, and align debt strategy with long-term objectives.
  - Applicability: potential broader use for other resource-rich countries.

### DDT scenarios and stress-testing mechanics
- Scenarios available:
  - Baseline: inputs provided by authorities (nominal effective interest rates in local and foreign currency, GDP growth, inflation, nominal exchange rate depreciation, primary balance, other net debt-creating flows). DDT takes these inputs as given.
  - Historical scenario: each macro-fiscal variable set to its historical average throughout projection horizon.
  - Constant primary balance scenario: primary balance fixed from second year onward at first projection year level.
  - Shock scenarios: adverse shocks to the primary balance, GDP growth, local and foreign interest rates, and exchange rates; shocked variables equal baseline plus a multiple of historical standard deviations.
  - Customized scenario: user-calibrated combination of shocks (e.g., natural disasters, commodity price shocks).
- Stress testing inputs and operation:
  - Users input shock sizes as scalar multiples of historical standard deviations (e.g., "-1").
  - Only one macro-fiscal variable is shocked at a time in standard stress tests; customized scenarios can combine multiple shocks.
- Fan charts (stochastic simulations):
  - Based on Debt Sustainability Analysis for Market Access Countries (2013 model).
  - Four variables shocked: 푟̂푡푑, 푔푡, augmented primary balance 푠푝푡푚표푦, and augmented foreign real interest rate 푟̂푡푓,푎푢푔.
  - Using 1,000 shocks, the DDT computes 1,000 debt paths to construct fan charts over a 12-year projection horizon.
  - Fan charts rely on nine years of historical data and projections (cells AS7:BA10); users must activate an embedded Excel macro to generate fan charts.

---

### Natural Disasters Debt Dynamics Tool (ND_DDT): approaches, calibration, and integration
- ND_DDT overview:
  - Excel-based tool that computes shocks to macro-fiscal variables for natural disaster scenarios.
  - Automatically imports baseline from DDT and exports the constructed disaster scenario to DDT.
  - Follows DDT color codes for inputs and formulas.
- Three calibration approaches:
  1. Event study (individual-event approach using WEO vintages or pre/post averages).
     - Caveats: one-year vintage gap and confounding events.
     - Example: 1969 drought event-study for Mauritania: GDP growth decline of 3.4 percentage points relative to three-year pre-1969 average.
  2. Econometric approach (local projections and quantile regressions) using international historical data and user inputs: pre-disaster primary fiscal balance, income group, small island indicator, adaptive capacity (ND GAIN index), damages (% of GDP), and disaster type.
     - Example econometric-input calibration for a hypothetical drought in 2025:
       - Pre-disaster primary balance: -0.58 percent of GDP (projected level in 2024).
       - Income group: "Low-Income and Developing Countries."
       - Small island: Mauritania is not a small island.
       - Adaptation capacity: 0.7585 (average for Mauritania between 1995 and 2020).
       - Damage size: 11.5 percent of GDP (equivalent to the 1969 drought damage).
       - Type of disaster: "Drought".
     - Example econometric outputs (illustrative):
       - Exchange rate depreciation: 5.2 percent (econometric forecast) and 6.2 percent (quantile regressions); historical event suggests 5.4 percent.
       - Imported inflation example: 5.4% depreciation * 60% import share = 3.2 percentage points increase in inflation.
       - Predicted impacts over a three-year horizon are subject to judgment and country knowledge.
  3. Country-specific judgment-based calibration (manual adjustments and combination with econometric outputs).
- Combining methods and manual calibration:
  - Users can choose manual adjustments, combine approaches, deactivate shocks for certain variables, and set number of shock years and first shock year.
  - Example judgment-based drought calibration:
    - Average and end-of-year nominal exchange rates calibrated to depreciate by 5.4 percent relative to baseline (econometric approach forecast: 5.2 percent).
    - Inflation calibrated to increase by 3.2 percentage points.
    - Output growth calibrated to decline by 3.4 percentage points relative to baseline.
    - Primary balance calibrated to deteriorate by 1.4 percent of GDP.
    - Impacts calibrated over a period of two years.

### ND_DDT illustrative impacts and example applications
- Natural disaster (drought) example hitting in 2025:
  - Public debt projected to increase by about 4 percent of GDP in 2025 versus baseline.
  - Drivers: lower GDP growth, deterioration in the primary balance, and exchange rate depreciation.
  - By 2026, a pick-up in growth helps reduce the rise in public debt.
- Commodity price shock example (negative 5 percent shock to commodity prices):
  - Calibration:
    - Output growth: fall by 1 percent relative to baseline in year of shock.
    - Primary balance: decrease by 1 percent of GDP in year of shock and by 0.5 percent of GDP one year after shock.
  - Debt impacts:
    - Public debt projected to increase by about 1.5 percent of GDP in 2025.
    - In 2026, public debt projected to increase by another 0.5 percent of GDP.
- Scenario analysis key findings:
  - Alternative scenarios include baseline, one-standard-deviation shocks to non-extractive primary balance, real interest rate, exchange rate, commodity price shocks, and natural disasters.
  - The one-standard-deviation shock to the non-extractive primary deficit is the most important, increasing public debt by almost 6 percent of GDP in 2026.
  - None of the alternative scenario debt levels converge to the baseline during the forecast period.
  - Natural disaster and commodity price shock scenarios are not directly comparable to standard macroeconomic shock scenarios due to different construction approaches.

---

### Operational guidance: Inputs, outputs, and procedural annexes
- Required DDT annual inputs (exact variables preserved):
  - Debt-related: stock of total gross public debt (historical), uncalled guarantees (% of GDP) if included, share of public debt in foreign currency (% of total debt).
  - Macro-fiscal indicators: average and end-of-period nominal exchange rates; effective nominal interest rates on domestic and foreign-currency debt; GDP deflator inflation; Real GDP growth; Non-extractive primary balance; extractive revenue; Other net debt-creating flows; Foreign GDP deflator inflation for fan charts.
- Projection mechanics:
  - Default projection period pre-specified to be 12 years; extending horizon requires manual updates across relevant tabs.
  - Users populate Basic Inputs in the Readme tab and macro-fiscal data in the Data Inputs tab; yellow-shaded cells are user inputs, light yellow allow dropdowns, white cells contain formulas not to be overridden.
- Adjustment path exercises:
  - Debt-stabilizing balances, constant primary and overall balance exercises, constant annual adjustment exercises, and customized adjustment scenarios for non-extractive primary balance are available with specified input cells and procedures.
- Standardized outputs:
  - Output - RefScenario tab: baseline debt evolution, standardized decomposition of contributions to debt changes, "Realism and Fiscal Adjustments" box reporting medium-term indicators, debt-stabilizing non-extractive primary balance, adjustments needed to reach debt target, and probabilities relative to historical debt or user-defined target.
  - Output - Shocks tab: debt dynamics for alternative scenarios and fan charts.
- Annex highlights:
  - Annex I: Guide to Public Debt Report (structure, data sources, stress testing coverage, review and approval process). Data sources listed include: DDE, DCCGT, BCM, ANSADE, IMF, World Economic Outlook, etc.
  - Annex II: Indicative schedule for public debt projection (phase tasks and indicative durations):
    - Assembling data: Responsible: DDE, DPAE, DOB, DCCGT, BCM. Indicative duration: 1 week.
    - Data Validation: Responsible: CNDP. Indicative duration: 5 days.
    - Analysis of debt projections: Responsible: DDE. Indicative duration: 2 weeks.
    - Risk assessment: Responsible: DDE. Indicative duration: 1 week.
    - Draft report: Responsible: DDE. Indicative duration: 1 week.
    - Validation and approval: Responsible: CNDP. Indicative duration: 1 week.
    - Publication: Responsible: MEF, CNDP.
  - Annex III: User manual (Public Debt Dynamics Tool for Resource Rich Countries) — procedural guidance for inputs, adjustment paths, and tool features.
  - Annex IV: ND_DDT user manual (disaster calibration methods, examples, and integration with DDT).

---

### Project assessment, key operational recommendations, and next steps
- Project assessment:
  - Almost all interim milestones scored 4 on a scale of 1 to 4 and were considered fully achieved by the IMF team.
  - Main objective—improving public debt forecasting and analysis capacities to support economic policy decisions—was fully achieved.
- Main operational recommendations to strengthen integration into CNDP policymaking:
  Recommendation 1 — Move towards regular and more comprehensive integration of DDT debt analyses into CNDP policymaking:
  - Establish a formal system specifying:
    1) Regular use of the DDT with a pre-defined schedule for conducting regular DSAs (Annex II provides an indicative timetable).
    2) Standardized data inputs with clear definitions of needs and data sources.
    3) Institutional responsibilities assigning roles within CNDP and its technical committee to oversee the tool.
    4) Integration of decision-making workflow to formally discuss and incorporate DDT and ND_DDT outputs into CNDP recommendations.
    5) Documentation and reporting requiring periodic reports documenting tool findings and policy impact.
  Recommendation 2 — Formalize division of tasks and timely data provision among stakeholders:
  - Define data collection cycle, timing of discussions and agreements on assumptions, contributions of each organization, and timelines for inputs.
  - Develop Excel templates specifying quantitative/qualitative information requested from each organization and deadlines aligned with fiscal planning; submit to CNDP management to agree timetable.
  Recommendation 3 — Train new technical team members on the tool regularly:
  - Retain technical capacity and continuity through regular training; experienced staff should train new members and use the prepared user manuals (Annex III, IV and V).
- ICD roadmap for further integration:
  - Train in DDT first, then progress to more integrated Debt Sustainability Analysis (DSA) exercises using the macroeconomic and fiscal frameworks tool.
  - Combining the macroeconomic and fiscal frameworks tool with DDT is essential for a complete assessment of public debt sustainability.

*IMF | Mauritania — Technical Assistance on Public Debt Projections — PREFACE (tarea2026061)*

### PREFACE __________________________________________________________________________  7

### PREFACE

### PREFACE (project overview and mission)
- The report concludes the technical assistance project to develop a Public Debt Dynamics Tool (DDT) for use by the National Public Debt Committee (CNDP) of the Islamic Republic of Mauritania.
- Project initiation: January 2024.
- The project included three missions; the last mission was conducted from January 9 to 15, 2025, with preparatory work in November and December 2024.
- Mission leadership and team:
  - Head of Mission and Project Manager: Marie Pierre Aquino Coste
  - Senior Economist: Naomitsu Yashiro
  - Economist: Ha Minh Nguyen
- Two key pillars emphasized during the last mission:
  1. Strengthening the capacity of the CNDP technical team to use the DDT.
  2. Developing a manual on how to use the tool in collaboration with the authorities.
- Main in-country activities during the mission:
  - Hands-on sessions to build independent operation capacity of the DDT.
  - Strengthening skills for routine public debt projection tasks.
  - Definition of roles and responsibilities for data provision and inter-agency coordination.
  - Harmonization of data assumptions and reconciliation of inputs across institutions.
  - Completion of the public debt report structure with baseline projections and alternative scenarios using the most recent data.
- Acknowledgements: director-level support from the Directorate General of Public Debt, collaboration with MCD Mission Chief for Mauritania, FAD resident advisor for AFRITAC West, ICDMF administrative support, IMF Resident Representative offices, and colleagues in the Fiscal Affairs Department (FAD).

### SUMMARY (project objectives, implementation, and outcomes)
- Requesting authority: Ministry of Finance (MoF) of Mauritania.
- Implementing IMF unit: Institute for Capacity Development (ICD).
- Objective: Strengthen CNDP analytical capacity in public debt analysis and projections; improve coordination and communication among institutions responsible for debt policy.
- Scoping mission: January 2024 assessed capacity development needs and led to a TA plan based on adoption and customization of the DDT.
- CNDP composition and role:
  - Includes representatives from the Ministry of Finance, the Ministry of Economy and Sustainable Development (MEDD), and the Central Bank of Mauritania (BCM).
  - Responsible for debt policymaking, sustainability assessments, and inter-institutional coordination.
- Customizations introduced:
  - Adoption of the Debt Dynamics Tool (DDT).
  - Customized version for resource-rich countries (DDT RRC) to account for extractive-revenue dependence.
  - Integration of the Natural Disasters Public Debt Dynamics Tool (ND DDT) to assess climate shocks and commodity price fluctuations.
- Delivery and capacity outcomes:
  - Three missions plus remote training sessions, in-person workshops, and continuous technical exchanges.
  - CNDP successfully implemented the DDT and produced a comprehensive public debt report with baseline projections, risk scenarios, and policy recommendations.
  - Core technical team demonstrated ability to conduct independent debt sustainability assessments.
  - User manuals developed to ensure continued use and knowledge retention within the CNDP.
- Policy relevance:
  - Tools enable analysis of economic and environmental uncertainties.
  - Strengthened inter-institutional collaboration and analytical capacity to inform more resilient public debt management.

### Summary of Final Project Recommendations (indicative horizons)
- Recommendation 1: Integrate public debt projections and analyses using the DDT into CNDP policymaking on a regular and more comprehensive basis.
  - Indicative horizon: December 2026
- Recommendation 2: Establish a clear division of tasks and deadlines, congruent with the overall policy planning process, among the public stakeholders involved in the projection of public debt and the drafting of the report on public debt.
  - Indicative horizon: December 2026
- Recommendation 3: Provide regular training to new technical team members on the public debt projection tool.
  - Indicative horizon: Twice a year

### SECTION I. GENERAL INFORMATION — A. Mauritania's Macroeconomic Background (key points)
- Exposure and vulnerabilities:
  - Mauritania is highly exposed to commodity price fluctuations and natural disasters.
  - The war in Ukraine led to a surge in food prices and increased food insecurity for 20 percent of the population.
  - Higher global food and energy prices, combined with lower iron ore prices, contributed to a widening trade deficit and declining external reserves in 2022.
  - Recurrent droughts and floods pose risks to macroeconomic stability and growth and require significant adaptation measures.
- IMF support and financing:
  - Mauritania secured the Extended Credit Facility (ECF) and the Extended Fund Facility (EFF) from the IMF for a total amount of US$86.9 million in February 2022.
  - Mauritania obtained US$258.21 million under the Resilience and Sustainability Facility (RSF) in December 2023 to finance climate adaptation investments and promote the green transition.
- Fiscal and external pressures: commodity price volatility, climate shocks, and recent external shocks have weighed on the fiscal balance and external buffers.

### SECTION I. GENERAL INFORMATION — B. Authorities' request for technical assistance from ICD (timeline and actions)
- CNDP role (from footnote):
  - Inter-agency group of six General Directors from the Ministry of Finance, MEDD, and BCM.
  - Coordinates formulation and implementation of debt policy, advises the Minister of Finance on debt sustainability and restructuring, facilitates exchange of information, supervises publication of debt statistics, and produces public debt projections and sustainability analyses.
- TA timeline and missions:
  - Exploratory TA mission: Nouakchott, January 8 to January 19, 2024 — assessed capacity to project public debt and identified capacity development needs.
  - Second TA mission: August 26 to September 4, 2024 — focused on implementing the DDT within the CNDP technical support committee and developed a customized DDT for resource-rich countries (RRC).
  - Third TA mission: Nouakchott, January 9 to 15, 2025 — strengthened technical capacities, ownership of the DDT, reviewed project documents and customizations, delivered user manuals (ND_DDT and DDT RRC), and promoted independent debt sustainability analyses.
- Outputs prepared by CNDP technical team:
  - A public debt report presenting baseline public debt projections and alternative scenarios, including fiscal paths congruent with debt objectives and scenarios considering natural disasters and commodity price shocks.
- Implementation actions:
  - Definition of roles and responsibilities, harmonization of data assumptions, reconciliation of inputs, and completion of the public debt report structure.
  - Creation of protocols and procedures for consistent use of tools and training additional staff to ensure continuity.
- CNDP commitment:
  - Expressed intention to use the tool for the next committee meeting.

### SECTION II. PROJECT ACHIEVEMENTS — A. Public Debt Dynamics Tool (DDT) (features and scenarios)
- DDT capabilities:
  - Projects public debt as a percentage of GDP.
  - Computes fiscal paths to achieve a user-defined debt target.
  - Performs pre-defined and customized stress tests.
  - Produces fan charts.
  - Presents results in standardized output tables.
  - Integrable into a country's broader macroeconomic framework.
- Data requirements:
  - Requires only 10 macro-fiscal variables, often publicly available, to perform a rich analysis (enables projections without detailed issuance/amortization data).
- DDT scenarios described:
  - Baseline scenario: public debt projections based on macroeconomic and fiscal inputs provided by the authorities (inputs typically drawn from the latest program or budget projections), including nominal effective interest rates in local and foreign currency, GDP growth, inflation, nominal exchange rate depreciation, the primary balance, and other net debt-creating flows. The DDT takes these inputs as given and does not generate the baseline forecasts itself.
  - Historical scenario: sets each macroeconomic and fiscal variable to its historical average, held constant throughout the projection horizon; useful as a realism check relative to the baseline.
  - Constant primary balance scenario: sets key inputs as in the baseline, except the primary balance is set at the level of the first projection year starting in the second year; differences vs. baseline indicate assumptions about fiscal adjustment magnitude.
  - Shock scenarios: examine public debt projections under adverse shocks to the primary balance, GDP growth, local and foreign currency effective nominal interest rates, and average and end-of-period nominal exchange rates; shocked variables equal baseline plus a multiple of historical standard deviations between shock start and end years.
  - Customized scenario: allows calibration of a combination of shocks to capture specific events (e.g., natural disasters or commodity price shocks).

*IMF | Mauritania — Technical Assistance on Public Debt Projections — PREFACE (tarea2026061)*

### 15.        Given Mauritania's status as a resource-rich country (RRC), a customized version of the

### 15.        Given Mauritania's status as a resource-rich country (RRC), a customized version of the

### DRR DDT customization and rationale
- A customized version of the Debt Dynamics Tool (DDT), called the DRR DDT, was developed to account for Mauritania's status as a resource-rich country (RRC).
- Key structural change: the regular primary balance is disaggregated into:
  - primary balance excluding extractive revenue (non-extractive primary balance), and
  - extractive revenue.
- Rationale:
  - Extractive revenues tend to be volatile and are usually determined by international prices and are thus not under the control of the state.
  - The non-extractive primary balance is defined as an appropriate policy instrument in Mauritania and other resource-intensive countries.
- Tool capabilities:
  - Simulate various fiscal adjustment scenarios.
  - Assess long-term impacts of different policy choices.
  - Improve understanding of how non-extractive revenues can support sustainable debt levels.
  - Support policy coordination and alignment of debt strategy with long-term economic objectives.
- Applicability: the DDT customization has potential for broader application to other resource-rich countries.

### Public debt projections under illustrative baseline (DDT outputs)
- Projection summary:
  - Public debt is projected to increase in 2024 and 2025, driven by high non-extractive primary deficits relative to extractive revenues.
  - From 2026 to 2028, public debt is projected to decline as the contribution of non-extractive primary deficits to debt increase is less than the contribution to debt reduction from a higher share of GDP growth and extractive revenues.
- Note: The projections presented in the related figures are for illustrative purposes only.

### Natural Disasters Debt Dynamics Tool (ND_DDT) — approaches and calibration
- ND_DDT overview:
  - Calibrates shocks to construct natural disaster scenarios.
  - Automatically imports the public debt projection scenario from the DDT and exports the natural disaster scenario developed with the ND_DDT.
  - Developed by ICD for training and technical assistance on macroeconomic frameworks for forecasting and policy analysis.
- Three approaches to construct a natural disaster scenario:
  1. Event study (observing a past disaster via WEO vintages or pre/post averages).
     - Caveats: one-year vintage gap and confounding events.
  2. Econometric approach using international historical data (local projections and quantile regressions).
     - Requires user inputs on country and disaster characteristics:
       - Pre-disaster primary fiscal balance: pre-disaster primary fiscal balance (% of GDP).
       - Income group: advanced economies, emerging market and middle-income economies, low-income countries, and developing economies.
       - Small island: if the country is a small island.
       - Adaptive capacity: the Notre-Dame ND Gain index.
       - Damages: property damage caused by the disaster (% of GDP).
       - Type of disaster: "storm", "flood", "drought", or "other disaster".
  3. Country-specific judgment-based calibration.

- Event-study example (1969 drought):
  - Using deviations from three-year pre-1969 averages, the 1969 drought caused a drop in GDP growth in 1969 of 3.4 percentage points.

- Econometric-input example for a hypothetical drought in 2025:
  - Pre-disaster primary balance: -0.58 percent of GDP (projected level in 2024).
  - Income group: "Low-Income and Developing Countries."
  - Small island: Mauritania is not a small island.
  - Adaptation capacity: 0.7585 (average for Mauritania between 1995 and 2020). Note: index range between 0 and 1, with 1 being the lowest capacity and 0 the highest.
  - Damage size: 11.5 percent of GDP (equivalent to the damage caused by the 1969 drought).
  - Type of disaster: "Drought".
- Econometric output:
  - Predicted impacts over a three-year horizon are generated and then subject to judgment and country knowledge.

- Judgment-based calibration (final shocks for drought):
  - Average and end-of-year nominal exchange rates calibrated to depreciate by 5.4 percent relative to the baseline (econometric approach forecast: 5.2 percent).
  - Inflation calibrated to increase by 3.2 percentage points.
  - Output growth calibrated to decline by 3.4 percentage points relative to the baseline (consistent with the event study).
  - Primary balance calibrated to deteriorate by 1.4 percent of GDP.
  - Impacts calibrated over a period of two years.

### ND_DDT illustrative debt impacts (drought example)
- Scenario timing: natural disaster hits the economy in 2025.
- Debt impact:
  - Public debt is projected to increase by about 4 percent of GDP in 2025, compared to the baseline.
  - Drivers of the 2025 increase: lower GDP growth, deterioration in the primary balance, and exchange rate depreciation.
  - By 2026, a pick-up in growth helps reduce the rise in public debt.
- Note: The projections presented in the related figures are for illustrative purposes only.

### Commodity price shock application (DDT with ND_DDT flexibility)
- Context: Mauritania relies largely on exports of iron ore, fish, and gold and is highly exposed to global price fluctuations and environmental risks.
- Hypothetical calibration for a negative 5 percent commodity price shock:
  - Output growth: calibrated to fall by 1 percent relative to the baseline in the year of the shock.
  - Primary balance: calibrated to decrease by 1 percent of GDP in the year of the shock and by 0.5 percent of GDP one year after the shock (based on empirical estimates using Mauritania's data).
- Debt impacts after -5 percent commodity price shock:
  - Public debt projected to increase by about 1.5 percent of GDP in 2025.
  - In 2026, public debt projected to increase by another 0.5 percent of GDP due to continued deterioration of the primary balance.
- Note: The projections presented in the related figures are for illustrative purposes only.

### Scenario analysis and key risk findings
- Alternative scenarios considered:
  - Baseline.
  - One-standard-deviation shocks to: the non-extractive primary balance, the real interest rate, the exchange rate.
  - Commodity price shocks and natural disasters.
- Key risk observation:
  - The one-standard-deviation shock to the non-extractive primary deficit is the most important, increasing public debt by almost 6 percent of GDP in 2026.
  - None of the alternative scenario debt levels converge to the baseline during the forecast period.
  - Natural disaster and commodity price shock scenarios are not directly comparable to standard macroeconomic shock scenarios due to different construction approaches.

### Project results, capacity building, and operational integration
- Project objectives achieved (summary of main objectives):
  - (A) Improve capacity of Mauritanian civil servants to make public debt projections and analyses by adapting, documenting, updating, modifying, and exploiting ICD's Public Debt Dynamics Tool to enable the technical subcommittee’s support to the CNDP and produce a debt report with baseline and scenario analyses to define fiscal paths to achieve target debt-to-GDP ratios.
  - (B) Customize the DDT by adding features accounting for the current macroeconomic context and risks relevant to Mauritania (e.g., debt-stabilizing non-extractive primary balance, natural disaster scenarios such as droughts and floods).
  - (C) Further improve macroeconomic policy decision-making by increasing analytical capacity.
- Capacity building activities:
  - Prior to first mission: CNDP technical team completed online course "Projecting Public Debt – Public Debt Dynamics Tool (DDTx)" (French, edX).
  - Weekly virtual meetings to monitor progress and provide guidance.
  - Shared materials: technical note and manual for the DDT, full calculation of the debt dynamics equation, explanations of key debt drivers.
  - In-person training during the first mission tailored to Mauritania.
  - Six virtual meetings between missions to exchange on data and concepts (non-extractive primary balance, climate considerations).
  - Second mission: comprehensive study of the DDT and introduction to ND_DDT.
  - Third mission: strengthened skills on ND_DDT and capacity to incorporate climate risks into debt projections.
- Deliverables and outcomes:
  - By the end of the second mission, the technical team produced a comprehensive public debt report covering baseline projections and alternative scenarios; the team prepared documents and drafted the report in two days.
  - The report integrates baseline and shock scenarios and identifies the size of aggregate fiscal adjustments needed to restore debt stability.
  - The technical team presented the report to the General Directors who chair the CNDP.
  - The CNDP technical team produced an independent debt report and, with IMF support, developed user manuals to document important procedures for public debt projections and analyses.
- Institutional arrangements and continuity measures:
  - Participants defined roles and responsibilities for data updates and sharing to improve coordination across institutions.
  - A process document was jointly prepared to create protocols and procedures for consistent tool use and to ensure continuity amid staff or departmental changes.
- Challenges:
  - Retaining the technical team in the context of departmental reorganization and future changes is critical to avoid loss of capacity developed using the DDT.
  - Consolidating and expanding technical skills requires frequent exposure to the projection tools; knowledge can decline quickly without regular use, even with a user manual.
  - It is important to integrate the DDT and ND_DDT into the country’s regular debt management and analysis processes.

*IMF | MauritaniaTechnical Assistance on Public Debt Projections.*

### 44.        A key challenge is to better integrate these tools into the CNDP policymaking framework.

### tarea2026061 - 44.        A key challenge is to better integrate these tools into the CNDP policymaking framework.

### Integration challenge and operational context
- CNDP leadership and its technical committee expressed a desire to integrate analyses produced with the DDT and ND_DDT tools into CNDP policymaking processes.
- With CNDP commitment to regular use, the technical committee can regularly update data and perform analyses using the DDT tool.
- The DDT tool does not cover all aspects of debt dynamics analysis for the country: specifically, it does not link the current account balance (structural deficit in the balance of payments) to the debt rate and targeted debt trajectories.
- The ICD roadmap: train in the DDT tool first, then progress to more integrated Debt Sustainability Analysis (DSA) exercises using the macroeconomic and fiscal frameworks tool. Combining the macroeconomic and fiscal frameworks tool with DDT is described as essential for a complete assessment of public debt sustainability.

### Results against the project objectives framework
- Project assessment:
  - Almost all interim milestones were considered fully achieved by the IMF team (with a score of 4 on a scale of 1 to 4).
  - Relevant milestones included development, discussion, and adoption of an action plan early in the project, full completion of the tool, and sufficient use of the tool for public debt forecasting and for scenario design and sensitivity analysis.
- Main objective:
  - The main objective—to improve public debt forecasting and analysis capacities to support economic policy decisions—has been fully achieved.
  - Development of the team's capacity has been achieved; CNDP technical team has become familiar with DDT and ND_DDT.
  - Integration of these tools into CNDP policies depends on successful use of the tools in CNDP debt projections.

### Authorities' views and technical capacity gains
- ICD technical assistance significantly strengthened CNDP technical committee capacities in analyzing public debt projections.
- Training covered three modules enabling the team (including two academics) to independently produce comprehensive public debt reports with detailed determinants of debt changes and consistent projections.
- Functional capabilities of DDT:
  - Calculates public debt ratios (actual and projections).
  - Constructs debt trajectories according to debt-ratio objectives.
  - Performs analyses of shock impacts, including natural shocks and commodities, on debt dynamics variables.
- Data constraints:
  - Relevance and quality of DDT results depend heavily on data availability and reliability.
  - DDT exercises revealed several data issues; ICD management incorporated these into a capacity-building program with Ministry of Economy and Finance staff.
- Ownership objective:
  - Authorities expressed desire to take ownership of the DSA tool to form a national team capable of in-depth public debt sustainability analysis to strengthen in-house skills and systematic analysis.

### Country team views
- The Mauritania country team welcomes CNDP progress in improving debt sustainability analysis through the debt dynamics tool.
- These tools support both CNDP policy formulation and country team discussions with authorities.
- Implementing the report’s recommendations is essential for continuity and sustainability of tool use.

### Key recommendations to strengthen integration of tools into CNDP policies
Recommendation 1 — Move towards regular and more comprehensive integration of DDT debt analyses into the CNDP policymaking process:
- Establish a formal system specifying:
  1) Regular use of the DDT (a pre-defined schedule for conducting regular DSAs so that the information from the tool consistently feeds into key fiscal and debt policy decisions (Annex II provides an indicative timetable)).
  2) Standardized data inputs (clear definition of needs and data sources for running projections, ensuring consistent application of the tool in different policy discussions).
  3) Institutional responsibilities (Assign specific roles within the CNDP and its technical committee to oversee the use of the tool, maintain updates and ensure smooth integration of results in debt management strategy discussions).
  4) Integration of decision-making (Establishment of a workflow in which DDT and ND_DDT outputs are formally discussed and incorporated into CNDP recommendations to the Minister of Finance and other key stakeholders).
  5) Documentation and reporting (Require periodic reports that document the findings of the tool and their impact on policy decisions, improve transparency and institutional memory).

Recommendation 2 — Formalize division of tasks and provision of data among stakeholders participating in public debt projection and the public debt report:
- Establish clear assignment of duties and timely data provision among departments involved in producing the public debt report.
- Define the data collection cycle, timing of discussions and agreements on assumptions, contributions of each organization, and timelines for inputs.
- Develop a set of Excel files specifying quantitative and/or qualitative information requested from each organization and corresponding deadlines aligned with fiscal planning; submit these files to CNDP management to agree a timetable, coordinated by the technical committee.

Recommendation 3 — Train new technical team members on the tool regularly:
- Retention of technical capacity and continuity is critical to preserve capacity built with DDT and ND_DDT.
- The mission team prepared user manuals (Annex III, IV and V) explaining procedures for consistent tool use and enabling future CNDP technical committee members to familiarize themselves.
- Recommend that experienced staff provide regular training to new members to ensure continuity.

### Operational guidance and annex highlights
- Annex I: Guide to Public Debt Report
  - Purpose: standardized instructions to produce consistent, accurate, and comprehensive public debt reports; details structure, data sources, analytical approach, and alignment with international best practices.
  - Structure sections include: Cover page; Executive Summary; Introduction; Debt projection and dynamics; Stress testing and risk scenarios; Writing and Data Guidelines.
  - Stress testing should cover sensitivity analysis, economic slowdowns, interest rate increases, currency devaluation, commodity price fluctuations, exposure to natural disasters and climate risks.
  - Data sources and institutional responsibilities enumerated (examples preserved exactly as used in the guide: DDE, DCCGT, BCM, ANSADE, IMF, World Economic Outlook, etc.).
  - Review and approval process:
    - The DDE coordinates preparation and consolidation.
    - The CNDP validates macroeconomic assumptions and main findings.
    - The MEF approves and finalizes the document.
  - Dissemination steps:
    - Submit to the Minister of Economy and Finance.
    - Distribute to relevant stakeholders, including financial institutions and policy advisors.
    - Publish on the official website of the Ministry of Economy and Finance.

- Annex II: Indicative schedule for public debt projection (phase tasks and indicative durations preserved verbatim):
  - Assembling data: Assemble macroeconomic and fiscal data and assumptions. Responsible: DDE, DPAE, DOB, DCCGT, BCM. Indicative duration: 1 week.
  - Data Validation: Review and validate historical data and assumptions. Responsible: CNDP. Indicative duration: 5 days.
  - Analysis of debt projections: Prepare projections and baseline analysis. Responsible: DDE. Indicative duration: 2 weeks.
  - Risk assessment: Simulate economic and fiscal shocks. Responsible: DDE. Indicative duration: 1 week.
  - Draft report: Compile findings and recommendations. Responsible: DDE. Indicative duration: 1 week.
  - Validation and approval: Review and finalize the report. Responsible: CNDP. Indicative duration: 1 week.
  - Publication: Official publication of the report. Responsible: MEF, CNDP.

- Annex III: User manual (Public Debt Dynamics Tool for Resource Rich Countries)
  - Purpose: explains projection of public debt, computation of fiscal adjustment paths to achieve a public debt target using non-extractive primary balance or overall balance, and estimation of associated interest costs.
  - DDT features: computes user-defined fiscal adjustment paths toward a debt target within an adjustment period, performs predefined and standardized stress tests, produces fan charts, and identifies key drivers of public debt dynamics.
  - Inputs guidance:
    - Country-specific macro-fiscal data must be entered only into yellow shaded cells in tabs with yellow tabs; light yellow shaded cells allow dropdown selections; white cells contain formulas users should not override.
    - First step: populate Basic Inputs via dropdown menus in Readme tab under "Basic Inputs" (Source Data Input).

*Italic: tarea2026061 - 44.        A key challenge is to better integrate these tools into the CNDP policymaking framework.*

### 1. The country of interest,

### 1. The country of interest,

### Overview
- The readme tab requires users to enter:
  - the country of interest (1),
  - the first year of projections (2),
  - the "Year for medium-term indicators" used to report debt under historical and constant primary balance scenarios and the debt-stabilizing primary balance in the medium term (3),
  - coverage of the public sector (4),
  - whether uncalled guarantees (and similar contingent liabilities) are included in the definition of public debt (5). If guarantees are included, users must indicate the type of guarantee and this information is captured automatically in footnote "1/" of the main results table on the Output - RefScenario tab.

- Users are recommended to populate the macro-fiscal data on the Data Inputs tab before making selections for fiscal adjustment paths and stress tests. Data on the Data Inputs tab serve as reference to define the key drivers of debt in fiscal adjustments inputs.

### Input — Data (Data Inputs tab)
- The Data Inputs tab provides the DDT 10 years of data and assumptions for macro-fiscal variables to generate the debt-to-GDP ratio projection.
- The projection period is pre-specified to be 12 years; extending the projection horizon must be done manually across all relevant tabs.
- Required DDT annual inputs (used to project public debt using equation (8), plus uncalled guarantees if included, plus foreign inflation for fan charts using (10)):

  i. Debt-related data:
  - Stock of total gross public debt, up to the year before the projection period starts (row 9, historical data only).
  - Uncalled guarantees as percentage of GDP in local and foreign currency (only if these are included in the definition of reported debt, rows 10-11).
  - Share of public debt in foreign currency as percent of total debt (excluding uncalled guarantees, row 12). The template automatically computes the share of debt denominated in domestic currency (excluding uncalled guarantees) as percent of total debt.

  ii. Macro-fiscal indicators:
  - average and end-of-period nominal exchange rates (domestic per unit of foreign currency, rows 13-14).
  - effective nominal interest rates on domestic and foreign-currency debt (rows 15-16).
  - GDP deflator inflation (row 17).
  - Real GDP growth (row 18).
  - Non-extractive primary balance (row 19).
  - extractive revenue (line 20).
  - Other net debt-creating flows (row 21).
  - Foreign GDP deflator inflation (e.g., that of the US) to be used only for fan charts (row 22).

### Input into adjustment paths (Readme tab — "Adjustment paths data inputs")
- Users specify the "Public debt-to-GDP target" and the years in which "Adjustment paths" start and end.
- Example: the DDT would compute adjustment paths to achieve a debt ratio of 60 percent of GDP in 2030, with fiscal adjustments starting in 2022.
- Fiscal adjustment scenarios allow users to choose macro-fiscal variable values for the debt dynamics equation different from those in Input Data. Users can input parameters as:
  - constant values, or
  - "time-varying values".

- Constant values options:
  - historical data or projection assumptions: 10-year or 5-year historical averages, or 5-year or 10-year projection averages, or latest year before projections start,
  - or "Setting constant values manually" in the yellow shaded cells of column C rows 31-38.
  - If a historical or projected value is chosen, column D (rows 31-38) reproduces the appropriate value automatically.

- Time-varying values:
  - DDT computes fiscal adjustment paths using baseline assumptions in Input Data plus the "Additions to Baseline Assumptions for Fiscal Adjustment Paths" chosen by users.
  - Example: to assume GDP growth during adjustment is 1 percentage point lower than baseline, enter "-1" for corresponding years in line 38, columns H-V.
  - Resulting values of key variables are shown above the "Additions" in the Readme tab; "Additions" equal to zero implies fiscal adjustments use baseline values.

### Stress Testing Inputs (Readme tab — "Stress Tests Data Inputs")
- Users provide:
  1. The size of the shock to each relevant variable: extractive revenues, non-extractive primary balance, GDP growth, interest rate, and exchange rate depreciation. The size of the shock is measured as a scalar factor that multiplies the historical standard deviation of each variable (column B rows 43-47).
     - Example: "-1" indicates shocks to the primary balance and GDP growth are calibrated as a reduction in the values of these two variables by 1 historical standard deviation relative to the baseline.
  2. The years in which each shock starts and finishes.

- In stress tests, only one macro-fiscal variable is shocked at a time; all other variables remain at baseline levels. Example: the primary balance shock scenario impacts only the primary balance.

### Fiscal paths to achieve a public debt target (automatic calculations in green tabs; results in Output - RefScenario)
- Debt-stabilizing balances:
  - Tabs DebtStabilizingPrimaryBalance and DebtStabilizingOverallBalance compute the non-extractive primary balance and overall balance required to stabilize debt at the level of the previous year, either in the first projection year or in the "Year for medium-term indicators" defined in Readme. Results are reported in Output - RefScenario. (See Annex IV.A for the underlying equation.)

- Constant primary and overall balance excluding extractive revenues to reach a debt target:
  - Tabs CibleDetteConstante_sp and CibleDetteConstante_sg compute the non-extractive primary and overall balances that, if applied every adjustment year, would achieve the debt target. Output - RefScenario shows the resulting primary balance. (See Annex IV.B for an equation.)

- Constant annual adjustment of the primary balance and the overall non-extractive revenue balance to achieve a debt target:
  - Tabs CibleDetteAjustementConstant_sp and CibleDetteAjustementConstant_sg present the constant annual non-extractive fiscal adjustment (change in non-extractive primary or overall balance) that would achieve the debt target. The adjustment is indicated in Output - ScenarioRef.

- Primary and overall non-extractive balances aimed at reaching a debt target through constant annual debt reductions:
  - Tabs CibleDetteVarConstantDette_pb and CibleDetteVarConstantDette_sg present paths for the non-extractive primary and overall fiscal balance that would achieve constant annual reductions in the debt ratio reaching the debt target. Standardized results do not present summary statistics for this exercise.

- Customized Adjustment Scenario:
  - Users can combine a first period of constant NEPB (as in Subsection C) and a second period of constant NEPB (as in Subsection B) such that the debt target is reached at the end of the second period. Inputs required in Tailored Adjustment tab:
    - first adjustment period start and end years in cells B52 and B53,
    - year in which the debt target is reached in cell D53,
    - constant non-extractive primary balance for the second period in cell B55.
  - The debt target and key variable values are those defined in Readme. This exercise is defined for the non-extractive primary balance; similar exercises can be carried out for the overall non-extractive balance.

### Realism, Stress Tests, and Fan Charts
- Historical Scenario:
  - Assumes macro-fiscal variables remain at historical averages throughout the projection period: nominal effective interest rates in local and foreign currencies, growth, inflation, nominal exchange rate depreciation, non-extractive and extractive primary balance, and other net debt-creating flows.
  - Adds the average residual term 푟푒푠푡 to other net debt-creating flows to capture historical contributions fully.
  - Assumptions affect debt dynamics from the second year of projection.
  - Historical scenario is created in HistoricalScenario tab. Debt level in the historical scenario corresponding to the "Year for medium-term indicators" is reported in Output - RefScenario (cell W23).

- Constant non-extractive primary balance scenario:
  - Sets the non-extractive primary balance at the level of the first year of projection for the entire projection period; other variables remain baseline. Created automatically in SPConstant Scenario table. Debt level for the "Year for medium-term indicators" is reported in Output - RefScenario (cell Y23).

- Shock scenarios:
  - Tabs Ch-spne, Ch-spe, Ch-g, Ch-int, and Ch-er present shocks to the non-extractive primary balance, extractive revenues, GDP growth, effective nominal interest rates in local and foreign currencies, and average and end-of-period nominal exchange rates, respectively.
  - Between shock start and end years (defined in Readme), the shocked variable equals baseline value plus a multiple (defined in Readme) of its historical standard deviations. All other macro-fiscal variables remain at baseline.

- Customized scenario:
  - Customized Scenario tab allows any value input in yellow-shaded cells among key variables to model events such as natural disasters, PPP failures, bailouts of SOEs and subnational governments.
  - Two additional worksheets, ScénarioSurMesure_MP and ScénarioSurMesure_CN, for commodities and natural disasters, should be used to introduce ND_DDT impacts into yellow cells (cells B49:G59).

- Fan charts (stochastic simulations):
  - Based on the 2013 model of the Debt Sustainability Analysis for Market Access Countries.
  - Fan charts summarize possible evolution of debt-to-GDP by incorporating shocks into relevant macro-fiscal variables and ordering resulting debt paths through confidence intervals.
  - For simplicity, shocks are drawn considering only contemporaneous correlations among variables (correlations and autocorrelations are ignored).
  - Fan charts rely on historical annual data for four variables to generate sample means and variance-covariance matrix defining the joint normal distribution of shocks.
  - The four shocked variables are 푟̂푡푑, 푔푡, the augmented primary balance 푠푝푡푚표푦 = 휇푡(푠푝푡 − 푎푓푡) − 푟푒푠푡 (where 푟푒푠푡 is the residual in period t), and the augmented real effective foreign interest rate 푟̂푡푓,푎푢푔 with 1+푟̂푡푓,푎푢푔 ≡ (1+푟̂푡푓)(1+푧푡).
  - Variable behavior summarized as Yt = θ + εt, where Yt = (푟̂푡푑, 푔푡, 푠푝푡푎푢푔, 푟̂푡푓,푎푢푔), θ includes baseline means, and εt ~ N(0, Ω) with Ω the variance-covariance matrix.
  - Using 1,000 shocks, the DDT computes 1,000 debt paths to construct the fan charts.
  - Fan charts tab uses nine years of historical data and projections for the four variables automatically populated (cells AS7:BA10); additional historical years can be included (cells C7:AR10).
  - Stochastic simulations produce fan charts over a projection horizon of 12 years. Users must activate an embedded Excel macro by clicking the blue button to generate fan charts.
  - Users can opt off shocks to any of the four variables (cells B42:45). Symmetric shocks produce symmetric fan charts; users can build asymmetric fan charts by restricting shock values (cells D42:45).

### Standardized Outputs (blue tabs)
- After completing yellow-tab inputs, the DDT automatically generates baseline and alternative scenarios, output tables and charts.
- Output - Ref Scenario tab:
  - Shows evolution of public debt under baseline.
  - Provides standard decomposition of contributions to debt changes in table and chart, reporting the stock-flow adjustment as a stand-alone item due to intra-year exchange rate fluctuations.
  - Includes a "Realism and Fiscal Adjustments" box with indicators:
    - (i) Medium-term debt levels ("Year for medium-term indicators" in Readme) under the historical and constant primary balance scenarios.
    - (ii) Debt stabilizing non-extractive primary balance in the first year of projections and over the medium term ("Year for medium-term indicators" in Readme).
    - (iii) The level and annual change in the NEPB needed to reach the debt target after the adjustment period (under parameters chosen by the user in Readme).
    - (iv) The probability that the debt level will be below that of the last historical year, as well as the probability that the debt will reach the target defined by users in the final year of adjustment (as defined by the user in Readme).

- Output - Shocks tab:
  - Presents debt dynamics for alternative scenarios, the assumptions underpinning these scenarios, and fan charts.

*IMF | MauritaniaTechnical Assistance on Public Debt Projections — Content unit: tarea2026061 - 1. The country of interest,*

### ANNEX IV. USER MANUAL: NATURAL

### ANNEX IV. USER MANUAL: NATURAL

### Overview of the ND_DDT tool
- The Excel-based Disaster Debt Dynamics Tool (ND_DDT) computes shocks to macro-fiscal variables to construct natural disaster scenarios.
- Developed by the IMF's Institute for Capacity Development (ICD) for training and technical assistance on macroeconomic frameworks for forecasting and policy analysis.
- ND_DDT automatically imports the public debt projection scenario from the Public Debt Dynamics Tool (DDT) and exports the constructed natural disaster scenario back to DDT.
- ND_DDT follows DDT color codes:
  - Yellow cells (only in yellow tabs): user inputs.
  - Light yellow cells: user inputs from a drop-down menu.
  - White cells: formulas (do not replace).
  - Green tabs: data and calculations.

### Responding to natural disaster shocks — methods available
- Two primary calibration methods:
  - Comparison of pre- and post-disaster values of each variable for a particular event (individual-event approach).
  - Econometric estimation of shocks (local projections and quantile regressions).
- In the "Options" worksheet users choose the estimation method and must select options each time to enable the macro that updates data.

### Calibration using an individual event (steps and example)
- Select an event using the event code from the Natural_Disasters worksheet (EM-DAT disasters with material damage > 1% of GDP).
- Users may select an event from their own country or another country as a baseline.
- Pre-disaster value options:
  - Predicted values from the last WEO vintage before the disaster (previous WEO vintage).
  - Average value of the macro-fiscal variable before the shock (user selects number of years for the average).
- Post-disaster value options:
  - Predicted values in the first edition of the post-disaster WEO (post-WEO edition).
  - Published post-disaster values in the WEO.
- Example (Senegal drought, Event number 16):
  - Disaster year: 1977.
  - Property damage: 12.92% of GDP.
  - Shocks are calculated as differences between post-disaster and pre-disaster values for year t (1977) and subsequent five years.
  - Example results (relative to the average of 1975 and 1976):
    - GDP growth decline in drought year: 7.1 percentage points.
    - GDP growth decline in the following year: 14.1 percentage points.
  - Note: data for other macroeconomic variables may be unavailable for some events.
- Application to Mauritania:
  - ND_DDT database lacks disasters for Mauritania with damages > 1% of GDP (EM-DAT).
  - Users can replicate the approach manually for Mauritania events (example: 1969 drought).
    - Difference between GDP growth in 1969 and the three-year average preceding 1969: -3.4%.

### Calibration using econometric approaches (local projections and quantile regressions)
- Users enter country and disaster characteristics in the Options sheet:
  - Pre-disaster primary fiscal balance: pre-disaster primary fiscal balance (percent of GDP).
  - Income group: advanced economies, emerging market and middle economies, low-income and developing economies.
  - Small island: indicator if the country is a small island.
  - Adaptive capacity: ND GAIN Adaptive Capacity Index (historical data in worksheet Adaptive capacity).
  - Damage: physical damage (% of GDP) from EM-DAT.
  - Disaster Type: Storm, Flood, Drought, or others.
- Methods produce predictions of macroeconomic variables used in public debt projections.
- Example calibration for a hypothetical storm/drought hitting Mauritania in 2025:
  - Country characteristics chosen:
    - Pre-disaster primary balance (year 2024): -0.58% of GDP.
    - Income group: low-income developing country.
    - Small island: no.
    - Adaptive capacity: 0.758.
    - Disaster: drought causing 11.5% of GDP damage.
  - In the "Shocks" worksheet:
    - Local projections: user may choose point estimates or bounds of confidence intervals.
    - Quantile regressions: user may choose median, 5th percentile or 95th percentile.
  - Example numeric outputs:
    - GDP growth (g_t) expected decline:
      - 0.1 percentage point relative to the local projection approach (point estimates).
      - 0.2 percentage point lower than the quantile regression approach.
    - Primary balance projected fall in the drought year:
      - Econometric baseline: 0.9 percent of GDP.
      - Alternate calibration (government responds with more expansionary fiscal policy): deterioration of 1.4 percent of GDP in the year of the drought and improvement of 0.4 percent of GDP one year later (relative to baseline).
    - Inflation and exchange rate example:
      - Econometric approach may predict a decline in inflation of 2.5 percentage points (counterintuitive in some drought cases).
      - Exchange rate depreciation estimates: 5.2 percent (local projections) and 6.2 percent (quantile regressions).
      - Historical event (1969 drought) suggests depreciation of 5.4%.
      - Imported inflation calculation example: 5.4% depreciation * 60% import share = 3.2 percentage points increase in inflation.

### Combining methods, manual adjustments, and scenario configuration
- Users can:
  - Use judgment and external information to modify calibrations from individual events and econometric outputs.
  - Insert manual calculations of macro-fiscal impacts (e.g., for specific Mauritania disasters such as the 1969 drought: -3.4 percentage points GDP growth impact).
  - Calibrate a recovery scenario beyond the disaster year. Example:
    - Historical evidence suggests partial recovery one year after disasters.
    - Example calibration: GDP growth recovers half the decline one year after drought (1.7 percentage points above baseline following the initial -3.4 percentage points).
- Final shocks selection:
  - Users choose shocks using different approaches (individual, local projections, quantile regression, or manual) and may deactivate shocks for certain variables.
  - Example: select "manual" option for relevant macroeconomic variables to incorporate judgment.
- Options worksheet parameters for scenario duration:
  - 'Number of years' of the shocks (number of years shocks will be applied in DDT). Example: selecting "2" applies impacts in years t and t+1.
  - 'First year of the shock' to set timing of the customized scenario.

### Integrating ND_DDT shocks with the Public Debt Dynamics Tool (DDT) and outputs
- To create a customized scenario in DDT:
  - In the Options worksheet: select the "File Name" button in the DDT tool, then press "Import Baseline" and "Export Scenario".
- Tab export_DDT:
  - Shows debt dynamics for the natural disaster scenario versus the baseline.
  - Example visualization described:
    - Natural disaster scenario (dashed line) with disaster occurring in 2025.
    - Baseline scenario (straight blue line).
  - Tab export_DDT decomposes differences in debt-creating flows between customized scenario and baseline:
    - Example (2025): primary deficit, exchange rate depreciation, and decline in real GDP growth contribute to an increase in public debt-to-GDP under the natural disaster scenario versus baseline.
    - Higher inflation can lower the real interest rate and therefore reduce the public debt-to-GDP ratio under the customized scenario in some cases.
    - By 2026, recovery in growth can reduce the debt-to-GDP ratio.
- Output-Shocks tab in DDT:
  - Presents the stress test of the natural disaster shock (customized scenario) alongside other shocks.

*Source: ANNEX IV. USER MANUAL: NATURAL — Disaster Debt Dynamics Tool (ND_DDT), as provided in the supplied content unit.*

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_Source: https://www.imf.org/-/media/files/publications/tar/2026/english/tarea2026061.pdf_