## 1. Macroeconomic Impact of Natural Disasters and Inclusive Growth

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---

### A. Introduction and framing
- Publication date: November 14, 2025.
- Central thesis: Climate shocks are a recurrent macroeconomic risk for Rwanda that harm growth, fiscal stability, and household welfare; gender inclusion is macro-critical because women’s concentration in agriculture and informal employment, and limited access to finance and assets, heighten vulnerability and slow recovery.
- Core data-driven policy tools highlighted: Climate Budget Tagging (CBT), Gender Budget Tagging (GBT), and the dynamic social registry.
- Institutional leads and coordination:
  - Ministry of Gender and Family Promotion (MIGEPROF): policy lead on gender equality.
  - Gender Monitoring Office (GMO): oversight and accountability for gender mainstreaming.
  - Ministry of Finance and Economic Planning (MINECOFIN): integration of gender objectives into budgets and macroframeworks via GBT and CBT.
- Complementary initiatives cited: Ireme Invest, Financial Sector Development Strategy (FSDS), Technical and Vocational Education and Training (TVET) policy, Women Entrepreneurs Finance Code.

### B. Major findings on climate shocks and gender
- Climate shocks: floods, droughts, landslides, heavy rainfall already inflict substantial damage to farmland and housing and are projected to cause significant economic damage as temperatures rise.
- Women’s exposure and vulnerability drivers:
  - High concentration in agriculture and informal employment, which are more climate-sensitive and lower-productivity.
  - Heavier care responsibilities that constrain adaptive capacity and rebuild efforts.
  - Limited access to credit, productive assets, disaster communications/early warnings, and financial buffers.
  - Time poverty (higher household chore burdens) increases vulnerability to disasters.
- Labor force contribution: Women accounted for about a half of the increase in the labor force in the last 20 years (statement preserved verbatim).
- Gender gap measures:
  - Gender gap in wages is expressed as male-to-female ratio of average hourly wages.
  - LFS-based gender gap by sector plotted as Man-to-Woman Ratio of Average Hourly Wages across All, Agriculture, Industry, Services (figure referenced).

### C. Micro-level evidence and household responses (EICV7, LFS)
- Primary microdata: Integrated Household Living Conditions Survey (EICV7), conducted between October 2023 and October 2024.
- Supplementary microdata: Labor Force Survey (LFS) with wage data available from 2021 onward, aggregated at the district-year level across Rwanda’s 30 districts.
- Disaster exposure variable: household self-reports of heavy rainfall, floods, droughts, landslides or mudslides in the preceding 12 months; household classified as having experienced a climate-related shock if it reported at least one such event.
- VUP components captured in EICV7:
  - Direct Support (DS)
  - Classic Public Works (cPW)
  - Expanded Public Works (ePW)
  - Nutrition-Sensitive Direct Support (NSDS)
- Empirical micro patterns:
  - Women in private agriculture and domestic work are disproportionately hit by climate-related shocks.
  - Affected individuals allocate more time to domestic responsibilities, reducing time for productive work.
  - Household coping responses: worked longer hours, reduced consumption, drew down savings; majority had not fully recovered at survey time.
  - Recovery is slower for female-headed households.

### D. Aggregated district-level disaster damage index (LFS linkage)
- Data source: MINEMA district-level reports on number of houses and hectares of crops damaged by natural disasters.
- Normalization/scaling:
  - Houses destroyed scaled by district population.
  - Crop losses scaled by corresponding farmland area.
  - Composite “disaster damage” index: normalized scaled indicators, equally weighted average.

### E. Institutional framework (summary)
- Pillar: Policy Coordination and Oversight
  - Institutional anchors: MIGEPROF, GMO, National Women’s Council, MINECOFIN.
  - Recent reforms/documents: GMO five-year plan (2024–29); Revised National Gender Policy (2021); Laws & Policies for Gender – GMO repository.
  - Gender–climate relevance: embeds gender equality goals into climate, economic, and social policies; strengthens oversight and accountability.
- Pillar: Financing and Implementation Tools
  - Institutional anchors: MINECOFIN (GBT and CBT), BRD, FONERWA, Ireme Invest.
  - Recent reforms/documents: Financial Sector Development Strategy (FSDS) and WE Finance Code (2025); FinScope 2024 Gender Thematic Report (BNR); FSDS 2024–29 and Strategic Plan 2018–24 notes.
  - Gender–climate relevance: directs resources toward green sectors; GBT and CBT integrate gender and climate into budget allocations; Ireme Invest and FSDS expand green employment opportunities for women.
- Pillar: Capacity and Inclusion Enablers
  - Institutional anchors: Rwanda TVET Board (RTB), Dynamic Social Registry, VUP, Ejo Heza, National Bank of Rwanda (BNR), MINECOFIN.
  - Recent reforms/documents: RTB Strategic Plan 2021–24; National FinTech Strategy 2024–29; National Employment and Skills Strategy.
  - Gender–climate relevance: builds human capital for green and digital economies; expands TVET and digital skills to enable women’s participation in resilient, higher-productivity sectors and improves targeting via CBT, GBT, social registry.

### F. Methodology overview
- Micro-level (EICV7) estimation:
  - Dependent variable: log(hourly wage) of individual i.
  - Key regressors: climate-disaster exposure dummy, woman dummy, their interaction, VUP support dummies, and controls.
  - Controls include: area of residence, household position, educational attainment, employment sector, housing materials, province.
  - Main coefficient of interest: interaction term between the climate shock and gender indicators, denoted 휷_퐶퐶퐶퐶.
  - Standard errors: clustered at the district level.
- District–year (LFS) estimation:
  - Dependent variable: log(gender wage gap) in district j in year t (ratio of average hourly wage of men to that of women).
  - Regressor: “disaster damage” index.
  - Fixed effects: year and district fixed effects.
  - Subsample analyses: by sector—agriculture, industry, services.

### G. Empirical results — EICV7 (individual-level)
- Broad pattern: climate disasters are generally associated with lower hourly wages across most population subsets (Table 2 referenced).
- Gender differential:
  - No additional adverse effect observed for women in agriculture and industry.
  - In services, the estimated effect is positive—suggesting that women’s wages increase relative to men’s following natural disasters (counterintuitive).
- Triple interaction with NSDS VUP support:
  - Positive association between wages and the triple interaction term climate shocks × gender × NSDS VUP support.
  - Statistical significance: significant for the full sample and for agriculture and industry subsamples, but not for services.
  - Interpretation: NSDS support (targeting pregnant women and households with young children in poverty) may cushion vulnerable women from income losses associated with climate shocks.
  - Caveat: the positive and unexplained climate×gender interaction in services warrants further investigation.

### H. Empirical results — LFS (district-level)
- Main finding: positive relationship between disaster damages and the gender wage gap.
  - Statistical significance: significant for the full sample and the services subsample; 훽_퐷 not significant in agriculture and industry (Table 3 referenced).
- Interpretation:
  - Districts with greater natural disaster damages tend to exhibit wider gender wage gaps among workers in the services sector.
  - Possible mechanisms: damage to infrastructure critical for services (roads, business premises) reduces earnings indirectly; aggregated damage index captures such indirect effects better than self-reported household shocks.
  - Gender vulnerability channel: women’s greater likelihood of vulnerable employment and lower seniority implies disasters affecting workplaces may disproportionately impact women.

### I. Macro-level model: Small open-economy with gender dimension
- Purpose: analyze complementarities between disaster-resilience policies and policies fostering female labor force participation; assess recovery differences with resilient infrastructure and reduced wage gap.
- Model features:
  - Inspired by the DIGNAD model; simple structure with added gender dimension.
  - Government can invest in standard infrastructure and adaptation capital (flood defenses, resilient roads, drought-ready irrigation).
  - Adaptation capital raises effective infrastructure, improves productivity, depreciates at a lower rate, and reduces disaster damages (modeled as temporary productivity losses).
  - Gender empowerment: modeled as a mechanical reduction in the wage gap, calibrated to a 50 percent reduction in the steady state for the experiment.

### J. Calibration targets and shock
- Calibration targets (Table 4 highlights):
  - Value-added in non-tradable sector: Data 48.0% ; Model 41.6%
  - External private debt to GDP ratio: Data 20.4% ; Model 20.5%
  - Domestic public debt to GDP ratio: Data 15.7% ; Model 11.5%
  - Imports to GDP ratio: Data 35.5% ; Model 35.5%
  - Public infrastructure investment to GDP ratio: Data 13.1% ; Model 16.9%
  - Average wage gap between men and women: Data 30.5% ; Model 29.8%
- Labor sector distribution targets:
  - Average wage gap targeted: 30 percent (for every RWF 1,000 a man earns, women earn RWF 700).
  - Roughly half of working men work in agriculture; 72 percent of female workers work in agriculture.
- Disaster shock calibration: an extreme flood event associated with a 7.5 percent reduction in total factor productivity.

### K. Simulation 1: Long-term steady-state comparison (wage-gap × adaptation capital)
- Experiment: compare two economies differing only in wage gap (current gap vs. low gap = observed gap cut by half); increase adaptation capital stock by 5-percentage-point steps up to 50 percent and recompute steady states.
- Key quantitative outcomes:
  - A 1 percent increase in the adaptation capital stock yields GDP that is 0.13 percentage point larger in the low-gap economy.
  - For a 30 percent increase in adaptation capital stock, the low-gap economy grows 1.15 percentage point higher.
  - For a 50% increase it reaches 1.73 percentage point larger GDP.
- Mechanisms for complementarities:
  - Misallocation channel: narrower gaps improve use of skills across sectors, raising effective labor input.
  - External constraint channel: more equal wages attract labor into tradables, expanding exports and relaxing balance-of-payments constraints.
  - Fiscal base channel: higher female earnings broaden the tax base, reducing the fiscal cost of public investment.
    - Numerical example: at a given 1 percent increase in adaptation capital, the tax-revenue-to-GDP ratio in the low-gap economy is about 4.25 percentage points higher than in the current-gap economy. Even with no additional adaptation, the low-gap economy already raises roughly 4.1 percentage points more.
- Additional note: adaptation alone slightly narrows the wage gap through a composition effect by protecting the sector where women are over-represented.

### L. Simulation 2: Short-to-medium-term disaster recovery
- Experiment: hit both economies with the same natural-disaster shock (temporary TFP drop modeled as AR(1)) and compare recovery paths under alternative pre-shock adaptation capital stocks and wage gap settings.
- Principal findings:
  - Pre-positioning resilience and narrowing the wage gap slightly reduce peak-to-trough output loss and speed up post-disaster recovery.
  - Three forces underpin gains:
    1. Smaller effective supply shock due to resilience lifting underlying productivity and attenuating the TFP hit.
    2. Faster reallocation as a tighter wage gap improves incentives to supply labor—especially women—toward higher-return margins (notably tradables).
    3. Stronger automatic stabilizers: broader tax base from higher female earnings cushions revenue shortfalls and lowers required fiscal adjustment.
  - Outcome: milder output contraction and steeper recovery of output and employment relative to the current-gap, low-resilience baseline.

### M. Policy instruments and data systems for inclusive climate resilience
- Data-driven frameworks:
  - CBT and GBT improve visibility of spending on climate adaptation and programs benefiting women, aligning resources with NST2 and the Green Growth and Climate Resilience Strategy.
  - Tagging frameworks track share of public investment devoted to resilience and inclusion, enhancing transparency and monitoring.
- Functional benefits:
  - CBT: identifies and classifies expenditures contributing to climate mitigation and adaptation across sectors (agriculture, energy, infrastructure).
  - GBT: provides information on how public spending supports women’s economic participation and welfare outcomes.
  - Combined use: enables cross-analysis linking adaptation spending with gender impacts to evaluate inclusiveness of climate investment.
- Social protection and targeting tools:
  - Rwanda’s digital registry expands social protection coverage through real-time household data, enabling rapid targeting of disaster-affected and female-headed households through VUP.
  - NSDS and VUP features highlighted as relevant to cushioning vulnerable women.

### N. Dynamic Social Registry (Imibereho System)
- LaunchedFebruary 29, 2024
- 2.7 out of 3 million households already included in the system
- Collaboration with: Land Registry, Rwanda Information Society Authority, National Identification Agency, Rwanda Revenue Authority
- Innovative features: constant data updates through exchanging data with other government systems
- Role: integrates household-level data to enable rapid identification of vulnerable households during shocks and improve fiscal response efficiency
- Linkages: connected to programs such as the VUP to allow temporary scaling-up of assistance to those most affected, including women and informal-sector workers
- Recommendation: continue improving coverage, interoperability, and real-time updating to allow programs—particularly the VUP—to scale up efficiently during shocks while maintaining fiscal discipline

### O. Opportunities and risks in the green transition; capacity building
- Opportunities:
  - Investments in renewable energy, climate-smart agriculture, and the circular economy can generate employment and productivity gains.
  - Strengthening MSME finance initiatives and expanding access to TVET can facilitate women’s participation in green industries.
- Risks:
  - Women remain under-represented in many emerging green sectors; without targeted interventions, the transition could widen existing labor-market gaps.
  - Digitalization risks: women are less likely to own smartphones, access the internet, or possess digital literacy needed for e-finance, e-commerce, and online training.
- Existing initiatives:
  - RTB Strategic Plan 2021-24 and recent investments in TVET centers of excellence; National FinTech Strategy 2024–29; FSDS 2025–29 and FinScope 2024 Gender Report commitments to dedicate at least half of microfinance and SACCO lending to women.
- Recommendations:
  - Expand access to TVET and strengthen MSME finance initiatives to help women participate in green industries.
  - Integrate gender criteria into green-investment facilities such as Ireme Invest.
  - Continue investment in data systems like CBT, GBT, and the social registry to track outcomes and inform course corrections.

### P. Table 5 — Largest CBT and GBT Projects in FY25/26 (projects larger than USD10 million) — selected figures (RWF Billion)
- Agriculture
  - GBT Improved access to farm inputs for women: 53.9
  - CBT Climate-smart agriculture and input access: 71.0
- Employment
  - GBT Job creation and training for women: 84.7
  - GBT Employment in housing/construction for women: 48.1
  - GBT Employment in road construction for women: 97.4
- Energy
  - GBT Expansion of electricity access for women: 128.0
  - CBT Renewable energy and energy efficiency: 169.9
  - CBT Resilience-focused energy infrastructure: 44.6
- Environment
  - CBT Integrated environmental protection: 67.9
- Transport
  - CBT Road rehabilitation and resilient transport: 88.1
- Social Protection
  - GBT Direct VUP support to women: 36.3
  - GBT Support to female genocide survivors: 16.4
  - CBT Support to households affected by climate shocks: 39.1
- Education
  - CBT Climate-resilient schools; awareness programs: 15.3
- Health
  - GBT HIV prevention and treatment for women: 15.0
- Water and Sanitation
  - GBT Improved access to water/sanitation for women: 55.7
  - CBT Expansion of water and sanitation infrastructure: 47.1
  - CBT Improved water treatment and sanitation systems: 34.3

### Q. Trade and export context — selected numeric indicators and priorities
- External imbalances:
  - Current account deficit averaged well above 10 percent of GDP and reached nearly 15 percent in recent years.
- Export concentration and partners:
  - Gold accounted for nearly one-third of total goods exports by 2022, up from less than 1 percent in 2010.
  - By 2022, exports had become heavily concentrated in the United Arab Emirates (36 percent) and the Democratic Republic of Congo (24 percent).
- Export sophistication:
  - Medium- and high-technology products account for less than 10 percent of exports.
  - Average wage gap targeted in model: 30 percent (for every RWF 1,000 a man earns, women earn RWF 700).
- Trade facilitation gains (selected measurable impacts):
  - ReSW: clearance time reduced from 11 days (2012) to 1.5 days (2014).
  - Rusumo OSBP: truck clearance time cut to under 30 minutes.
  - EAC Single Customs Territory: transit times from Dar es Salaam and Mombasa reduced from 21 and 18 days to 7 and 4 days; transport costs decreased from US$3,100 to US$1,025.
  - Inland dry Port Kigali Logistics Platform: truck turnaround time reduced from about 2 weeks to 3 days.
  - Air Cargo Hub supports high-value agriculture and horticulture, which comprise 50 percent of non-traditional exports.
- Policy priorities:
  - Broaden export base into horticulture, light manufacturing, and services; improve logistics capacity and reduce transport costs; deepen integration within EAC and AfCFTA.

### R. Policy implications and priority actions (diagnostic focus)
- Strengthen and leverage data-driven fiscal instruments (CBT, GBT, dynamic social registry) to improve targeting and efficiency of adaptation spending and social protection.
- Close gender gaps in labor markets, skills, finance, and asset ownership to:
  - Reduce women’s exposure and vulnerability to climate shocks.
  - Enhance the effectiveness of adaptation investments.
  - Accelerate post-shock recovery and support sustained long-term growth.
- Promote women’s participation in the green transition via TVET modernization, inclusive finance (FSDS, WE Finance Code), and green-finance facilities (BRD, FONERWA, Ireme Invest).
- Expand adaptive social protection through the social registry: continue improving coverage, interoperability, and real-time updating to allow programs—particularly the VUP—to scale up efficiently during shocks while maintaining fiscal discipline.
- Enhance access to productive assets and finance: broaden financial inclusion, strengthen women’s property and land rights, and expand tailored support for women-owned MSMEs.
- Invest in data and evaluation: expand the use of gender-disaggregated and climate-tagged data to assess program effectiveness and guide evidence-based policy refinement.

*Source: IMF staff summary of "Macroeconomic Impact of Natural Disasters and Inclusive Growth" (chapter content provided).*

### 1. Macroeconomic Impact of Natural Disasters and Inclusive Growth  __________________ 4

### 1. Macroeconomic Impact of Natural Disasters and Inclusive Growth

### A. Introduction and framing
- Publication date: November 14, 2025.
- Central thesis: Climate shocks are a recurrent macroeconomic risk for Rwanda that harm growth, fiscal stability, and household welfare; gender inclusion is macro-critical because women’s concentration in agriculture and informal employment, and limited access to finance and assets, heighten vulnerability and slow recovery.
- Core data-driven policy tools highlighted: Climate Budget Tagging (CBT), Gender Budget Tagging (GBT), and the dynamic social registry.
- Institutional leads and coordination:
  - Ministry of Gender and Family Promotion (MIGEPROF): policy lead on gender equality.
  - Gender Monitoring Office (GMO): oversight and accountability for gender mainstreaming.
  - Ministry of Finance and Economic Planning (MINECOFIN): integration of gender objectives into budgets and macroframeworks via GBT and CBT.
- Complementary initiatives cited: Ireme Invest, Financial Sector Development Strategy (FSDS), Technical and Vocational Education and Training (TVET) policy, Women Entrepreneurs Finance Code.

### B. Major findings on climate shocks and gender
- Climate shocks (floods, droughts, landslides, heavy rainfall) already inflict substantial damage to farmland and housing and are projected to cause significant economic damage as temperatures rise.
- Women’s exposure and vulnerability drivers:
  - High concentration in agriculture and informal employment, which are more climate-sensitive and lower-productivity.
  - Heavier care responsibilities that constrain adaptive capacity and rebuild efforts.
  - Limited access to credit, productive assets, disaster communications/early warnings, and financial buffers.
  - Time poverty (higher household chore burdens) increases vulnerability to disasters.
- Labor force contribution: Women accounted for about a half of the increase in the labor force in the last 20 years (statement preserved verbatim).
- Gender gap measures:
  - Gender gap in wages is expressed as male-to-female ratio of average hourly wages (Figure descriptions preserved).
  - LFS-based gender gap by sector plotted as Man-to-Woman Ratio of Average Hourly Wages across All, Agriculture, Industry, Services (figure referenced).

### C. Micro-level evidence and household responses
- Primary microdata: Integrated Household Living Conditions Survey (EICV7), conducted between October 2023 and October 2024.
- Supplementary microdata: Labor Force Survey (LFS) with wage data available from 2021 onward, aggregated at the district-year level across Rwanda’s 30 districts.
- Construction of disaster exposure variable: household self-reports of climate-related events (heavy rainfall, floods, droughts, landslides or mudslides) in the preceding 12 months; household classified as having experienced a climate-related shock if it reported at least one such event.
- VUP (Vision Umurenge Program) components captured in EICV7:
  - Direct Support (DS)
  - Classic Public Works (cPW)
  - Expanded Public Works (ePW)
  - Nutrition-Sensitive Direct Support (NSDS)
- Empirical patterns from EICV7 and LFS:
  - Women in private agriculture and domestic work are disproportionately hit by climate-related shocks.
  - Individuals affected by shocks report allocating more time to domestic responsibilities, reducing time for productive work.
  - Household coping responses: worked longer hours, reduced consumption, drew down savings; majority had not fully recovered at survey time.
  - Recovery is slower for female-headed households.

### D. Aggregated district-level disaster damage index (LFS linkage)
- MINEMA district-level reports used: number of houses and hectares of crops damaged by natural disasters.
- Normalization/scaling approach:
  - Houses destroyed scaled by district population.
  - Crop losses scaled by corresponding farmland area.
  - Composite “disaster damage” index: normalized scaled indicators, equally weighted average.

### E. Institutional framework (summary of Table 1)
- Pillars and relevance:
  - Policy Coordination and Oversight:
    - Institutional anchors: MIGEPROF, GMO, National Women’s Council, MINECOFIN.
    - Recent reforms/documents: GMO five-year plan (2024–29); Revised National Gender Policy (2021); Laws & Policies for Gender – GMO repository.
    - Gender–climate relevance: embeds gender equality goals into climate, economic, and social policies; strengthens oversight and accountability.
  - Financing and Implementation Tools:
    - Institutional anchors: MINECOFIN (GBT and CBT), BRD, FONERWA, Ireme Invest.
    - Recent reforms/documents: Financial Sector Development Strategy (FSDS) and WE Finance Code (2025); FinScope 2024 Gender Thematic Report (BNR); FSDS 2024–29 and Strategic Plan 2018–24 notes.
    - Gender–climate relevance: directs resources toward green sectors; GBT and CBT integrate gender and climate into budget allocations; Ireme Invest and FSDS expand green employment opportunities for women.
  - Capacity and Inclusion Enablers:
    - Institutional anchors: Rwanda TVET Board (RTB), Dynamic Social Registry, VUP, Ejo Heza, National Bank of Rwanda (BNR), MINECOFIN.
    - Recent reforms/documents: RTB Strategic Plan 2021–24; National FinTech Strategy 2024–29; National Employment and Skills Strategy.
    - Gender–climate relevance: builds human capital for green and digital economies; expands TVET and digital skills to enable women’s participation in resilient, higher-productivity sectors and improves targeting via CBT, GBT, social registry.

### F. Methodology overview
- Micro-level estimation of climate impacts on the gender wage gap uses EICV7 individual- and household-level variables: gender, education level, housing materials, hourly wages, sector of employment, receipt of government support, and climate-disaster exposure.
- LFS-based repeated cross-section constructed from annual surveys (wage data from 2021 onward) aggregated at district-year level and merged with MINEMA disaster reports to analyze district-level disaster impacts on average male and female wages.

### G. Key policy implications and priorities (diagnostic focus)
- Strengthen and leverage data-driven fiscal instruments (CBT, GBT, dynamic social registry) to improve targeting and efficiency of adaptation spending and social protection.
- Close gender gaps in labor markets, skills, finance, and asset ownership to:
  - Reduce women’s exposure and vulnerability to climate shocks.
  - Enhance the effectiveness of adaptation investments.
  - Accelerate post-shock recovery and support sustained long-term growth.
- Promote women’s participation in the green transition via TVET modernization, inclusive finance (FSDS, WE Finance Code), and green-finance facilities (BRD, FONERWA, Ireme Invest).

*Source: IMF staff summary of "Macroeconomic Impact of Natural Disasters and Inclusive Growth" (chapter content provided).*

### 13.      The analysis based on the EICV7 dataset employs a cross-sectional regression at the

### 13.      The analysis based on the EICV7 dataset employs a cross-sectional regression at the 

### Empirical specification: Individual-level (EICV7)
- Empirical equation (as specified):  
  log(푊푊푊푊푊푊 푒푒_푖푖) = 훼훼 + 훽훽_퐶퐶퐶퐶퐶퐶퐶퐶 푊푊퐶퐶 푒푒_푖푖 + 훽훽_푊푊 푊푊푊푊 퐶퐶푊푊 푛푛_푖푖 + 훽훽_퐶퐶푊푊 퐶퐶퐶퐶퐶퐶퐶퐶 푊푊퐶퐶푒푒_푖푖 × 푊푊푊푊 퐶퐶푊푊 푛푛_푖푖  
  + ∑_푉푉=1^푀 훽훽_푉푉 푉푉푉푉푃푃_푖푖푉푉 + ∑_푉푉=1^푀 훽훽_퐶퐶푉푉푉푉 퐶퐶퐶퐶퐶퐶퐶퐶푊푊  퐶퐶푒푒_푖푖 × 푉푉푉푉푃푃_푖푖푉푉  
  + ∑_푉푉=1^푀 훽훽_푊푊푉푉푉푉 푊푊푊푊퐶퐶 푊푊푛푛_푖푖 × 푉푉푉푉푃푃_푖푖푉푉  
  + ∑_푉푉=1^푀 훽훽_퐶퐶푊푊푉푉 퐶퐶퐶퐶퐶퐶퐶퐶푊푊  퐶퐶푒푒_푖푖 × 푊푊푊푊퐶퐶 푊푊푛푛_푖푖 × ∑_푉푉=1^푀 푉푉푉푉푃푃_푖푖푉푉  
  + ∑_푘푘=1^퐾 푋푋_푖푖𝑖𝑖 + 휖휖_푖푖.  
- Definitions:  
  - log(푊푊푊푊푊푊 푒푒_푖푖): natural logarithm of the hourly wage of individual i.  
  - 퐶퐶퐶퐶퐶퐶퐶퐶 푊푊퐶퐶푒푒_푖푖: dummy indicating whether the individual suffered from a climate-related disaster.  
  - 푊푊푊푊 퐶퐶푊푊 푛푛_푖푖: dummy indicating whether the individual is a woman.  
  - 푉푉푉푉푃푃_푖푖푉푉: dummy for the type of VUP support (among M options) the individual is receiving.  
  - {푋푋_푖푖𝑖𝑖}_푘=1^𝐊: set of additional control variables.  
  - 휖휖_푖푖: error term.  
- Estimation details:  
  - Main coefficient of interest: interaction term between the climate shock and gender indicators, denoted 휷휷_푪푪푪푪.  
  - Interpretation: 휷휷_푪푪푪푪 captures the differential impact of climate-related shocks on women’s wages compared to men’s (the additional effect on hourly wages experienced by women, relative to men, when both are exposed to a climate-related disaster), holding other factors constant.  
  - Standard errors: clustered at the district level.

### Controls and sample partitions (EICV7)
- Control variables included:  
  - binary indicators for area of residence (urban or rural), household position (household head or not), level of educational attainment, employment sector, housing materials, and province of residence (Rwanda comprises five provinces).  
- Rationale: including these controls mitigates omitted variable bias (example given: inexpensive housing materials associated with lower income may be less resilient to shocks, confounding disaster exposure and wages).  
- Subsample regressions:  
  - By employment sector: agriculture, industry, services.  
  - By educational attainment: distinguishing between primary and secondary education levels.  
  - Final specification: restricted to household heads.

### Empirical specification: District–year level (LFS)
- Empirical equation (as specified):  
  log(푊푊푊푊푊푊 푒푒_퐺퐺푊푊 퐺퐺_푗푗푗푗) = 훼훼 + 훽훽_퐷퐷 퐶퐶퐶퐶퐶퐶퐶퐶 푊푊퐶퐶 푒푒_퐷퐷푊푊퐶퐶푊푊푊푊푒푒_푗푗푗푗 + 휖휖_푗푗푗푗.  
- Definitions:  
  - log(푊푊푊푊푊푊 푒푒_퐺퐺푊푊 퐺퐺_푗푗푗푗): natural logarithm of the gender wage gap in district j in year t.  
  - 퐶퐶퐶퐶퐶퐶퐶퐶 푊푊퐶퐶푒푒_퐷퐷푊푊퐶퐶푊푊푊푊푒푒_푗푗푗푗: “disaster damage” index.  
  - Gender wage gap measure: ratio of the average hourly wage of men to that of women.  
- Estimation details:  
  - Coefficient of interest: 휷휷_퐷퐷, capturing the relationship between natural disaster damages and the gender wage gap.  
  - Fixed effects: year and district fixed effects included.  
  - Subsample analyses: by employment sector—agriculture, industry, services.

### Results: Individual-level (EICV7)
- Broad pattern: climate disasters are generally associated with lower hourly wages across most population subsets (as reported in Table 2).  
- Gender differential:  
  - No additional adverse effect observed for women in agriculture and industry.  
  - In services, the estimated effect is positive—suggesting that women’s wages increase relative to men’s following natural disasters (counterintuitive).  
- Triple interaction with NSDS VUP support:  
  - A positive association emerges between wages and the triple interaction term capturing climate shocks × gender × NSDS VUP support.  
  - Statistical significance: significant for the full sample and for agriculture and industry subsamples, but not for services.  
  - Interpretation: NSDS support (targeting pregnant women and households with young children in poverty) may cushion vulnerable women from income losses associated with climate shocks, potentially explaining the absence of an additional adverse effect of climate shocks on women’s wages relative to men’s in those sectors.  
  - Caveat: the positive and unexplained relationship between the climate×gender interaction and wages in the services sector warrants further investigation.

### Results: Aggregate/district-level (LFS)
- Main finding: positive relationship between disaster damages and the gender wage gap.  
  - Statistical significance: significant for the full sample and the services subsample; 훽훽_퐷퐷 not significant in agriculture and industry (Table 3).  
  - Interpretation: districts experiencing greater natural disaster damages tend to exhibit wider gender wage gaps among workers in the services sector.  
- Reconciliation with individual-level findings:  
  - Possible explanation: services-sector effects may operate through damage to infrastructure critical to service-related activities (e.g., roads for traders, business premises for hospitality workers), reducing earnings indirectly.  
  - Measurement distinction: the self-reported disaster variable in EICV7 may not capture such indirect effects, whereas aggregated LFS district-level damage indexes do.  
  - Gender vulnerability channel: women’s greater likelihood of vulnerable employment and lower seniority implies disasters affecting workplaces may disproportionately impact women, widening the gender wage gap in services.

### Macro-level model: Small open-economy with gender dimension
- Purpose: analyze interplay between disaster-resilience policies and policies fostering female labor force participation; questions addressed:  
  - (i) whether complementarities exist between disaster-resilience policies and women economic empowerment policies; and  
  - (ii) how recovery from a major flood differs if resilient infrastructure were in place and the wage gap had been reduced ex ante.  
- Model features:  
  - Inspired by the DIGNAD model, with a simple and transparent structure and an added gender dimension.  
  - Government can invest in standard infrastructure and in adaptation capital (flood defenses, resilient roads, drought-ready irrigation).  
  - Adaptation capital: raises effective infrastructure for firms, improves productivity, depreciates at a lower rate, and reduces disaster damages (modeled as temporary productivity losses).  
  - Gender empowerment: captured through a reduction of the wage gap between men and women.  
    - Calibration exercise: the wage gap is reduced mechanically to achieve a 50 percent reduction in the steady state while holding other parameters fixed (noting in practice such reduction requires comprehensive policy packages).

### Calibration targets and shock
- Calibration targets (Table 4): matched moments and data vs. model values:  
  - Value-added in non-tradable sector: Data 48.0% ; Model 41.6%  
  - External private debt to GDP ratio: Data 20.4% ; Model 20.5%  
  - Domestic public debt to GDP ratio: Data 15.7% ; Model 11.5%  
  - Imports to GDP ratio: Data 35.5% ; Model 35.5%  
  - Public infrastructure investment to GDP ratio: Data 13.1% ; Model 16.9%  
  - Average wage gap between men and women: Data 30.5% ; Model 29.8%  
- Labor sector distribution targets:  
  - Average wage gap targeted: 30 percent (for every RWF 1,000 a man earns, women earn RWF 700).  
  - Roughly half of working men work in agriculture; 72 percent of female workers work in agriculture.  
- Disaster shock calibration: an extreme flood event associated with a 7.5 percent reduction in total factor productivity.

### Simulation 1: Long-term steady-state comparison
- Experiment design: two economies differing only in wage gap—current gap vs. low gap (observed gap cut by half); start with low adaptation infrastructure and raise public investment so adaptation capital stock increases in 5-percentage-point steps up to a 50 percent increase. For each step, recompute balanced growth steady state.  
- Key quantitative outcomes:  
  - A 1 percent increase in the adaptation capital stock yields GDP that is 0.13 percentage point larger in the low-gap economy.  
  - For a 30 percent increase in adaptation capital stock, the low-gap economy grows 1.15 percentage point higher.  
  - For a 50% increase it reaches 1.73 percentage point larger GDP.  
- Mechanisms for complementarities:  
  - Misallocation channel: narrower gaps allow better use of women’s and men’s skills across sectors, raising effective labor input and amplifying output response to TFP-like boosts.  
  - External constraint channel: more equal wages attract labor into the tradable (agriculture) sector, expanding exports and relaxing balance-of-payments constraints, facilitating adaptation investment.  
  - Fiscal base channel: higher female earnings broaden the tax base, making public investment less fiscally expensive in general equilibrium.  
    - Numerical example: at a given 1 percent increase in adaptation capital, the tax-revenue-to-GDP ratio in the low-gap economy is about 4.25 percentage points higher than in the current-gap economy. Even with no additional adaptation, the low-gap economy already raises roughly 4.1 percentage points more.  
- Additional note: adaptation alone slightly narrows the wage gap through a composition effect by protecting the sector where women are over-represented.

### Simulation 2: Short-to-medium-term disaster recovery
- Experiment design: hit both economies with the same natural-disaster shock (temporary TFP drop modeled as AR(1)) and compare recovery paths under alternative pre-shock adaptation capital stocks and wage gap settings.  
- Principal findings:  
  - Pre-positioning resilience and narrowing the wage gap slightly reduce the peak-to-trough output loss and speed up post-disaster recovery.  
  - Three forces underpin gains:  
    1. Smaller effective supply shock due to resilience lifting underlying productivity and attenuating the TFP hit.  
    2. Faster reallocation as a tighter wage gap improves incentives to supply labor—especially women—toward higher-return margins (notably tradables).  
    3. Stronger automatic stabilizers: broader tax base from higher female earnings cushions revenue shortfalls and lowers required fiscal adjustment.  
  - Outcome: milder output contraction and steeper recovery of output and employment relative to the current-gap, low-resilience baseline.

### Policy instruments and data systems for inclusive climate resilience
- Data-driven policy frameworks in Rwanda:  
  - CBT (climate budget tagging) and GBT (gender budget tagging) improve visibility of spending on climate adaptation and programs benefiting women, aligning resources with NST2 and the Green Growth and Climate Resilience Strategy.  
  - These tagging frameworks allow tracking of the share of public investment devoted to resilience and inclusion, enhancing transparency and monitoring.  
- Functional benefits:  
  - CBT identifies and classifies expenditures that contribute to climate mitigation and adaptation across sectors (agriculture, energy, infrastructure), enabling assessment of fiscal priorities against resilience targets.  
  - GBT provides information on how public spending supports women’s economic participation and welfare outcomes, strengthening gender-responsive budgeting.  
  - Combined use: creates scope for cross-analysis linking adaptation spending with gender impacts to evaluate inclusiveness of climate investment.  
- Social protection and targeting tools:  
  - Rwanda’s digital registry expands social protection coverage through real-time household data, enabling rapid targeting of disaster-affected and female-headed households through VUP.  
  - NSDS (Nutrition-Sensitive Direct Support) and VUP (Vision 2020 Umurenge Program) features highlighted as relevant to cushioning vulnerable women (program details and beneficiary statistics presented in figures).

*Italic: Source — content unit: 1rwaea2025003-source-pdf (excerpts as provided).*

### 33.      Complementing these tools, the dynamic social registry has become central to adaptive

### Complementing these tools, the dynamic social registry has become central to adaptive social protection

### Dynamic Social Registry (Imibereho System)
- LaunchedFebruary 29, 2024
- 2.7 out of 3 million households already included in the system
- Collaboration with various government agencies to integrate information systems, including Land Registry, Rwanda Information Society Authority, National Identification Agency, and Rwanda Revenue Authority
- Innovative features allowing for constant data updates including through exchanging data with other government systems
- Collects vital socioeconomic data to support poverty alleviation efforts
- Role: integrates household-level data from multiple sources, enabling rapid identification of vulnerable households during shocks and improving the efficiency of fiscal responses
- Linkages: connected to programs such as the VUP to allow temporary scaling-up of assistance to those most affected, including women and informal-sector workers
- Benefit: supports timely, well-targeted, and fiscally sustainable responses to climate events
- Recommendation (from text): continue improving coverage, interoperability, and real-time updating to allow programs—particularly the VUP—to scale up efficiently during shocks while maintaining fiscal discipline

### Opportunities and Risks in the Green Transition
- Opportunities:
  - Investments in renewable energy, climate-smart agriculture, and the circular economy can generate employment and productivity gains
  - Strengthening MSME finance initiatives and expanding access to TVET can facilitate women’s participation in green industries
- Risks:
  - Women remain under-represented in many emerging green sectors; without targeted interventions, the transition could widen existing labor-market gaps
  - Digitalization risks: women are less likely to own smartphones, access the internet, or possess digital literacy needed to benefit from e-finance, e-commerce, and online training
- Existing initiatives:
  - RTB Strategic Plan 2021-24 and recent investments in TVET centers of excellence aim to modernize curricula, integrate ICT skills, and build stronger links with employers, yet gaps remain in digital infrastructure and female enrolment in technical fields
  - 2025-29 Financial Sector Development Strategy and the FinScope 2024 Gender Report highlight commitments to dedicate at least half of microfinance and SACCO lending to women
- Recommendations:
  - Expand access to TVET and strengthen MSME finance initiatives to help women participate more fully in green industries
  - Integrate gender criteria into green-investment facilities such as Ireme Invest to ensure new financing channels support women entrepreneurs and employment creation in sustainable sectors
  - Continue investment in data systems like CBT, GBT, and the social registry to track outcomes, inform course corrections, and ensure Rwanda’s climate and gender agendas reinforce each other

### Policy Findings and Macroeconomic Insights
- Key findings:
  - Closing gender gaps and building climate resilience are mutually reinforcing goals that strengthen macroeconomic stability and inclusive growth
  - Microdata analysis: women’s concentration in agriculture and informal employment heightens their vulnerability to climate shocks and slows household recovery
  - Macroeconomic simulations: reducing gender wage gaps amplifies the growth and fiscal benefits of adaptation investment
- Data-driven frameworks:
  - Integration of CBT, GBT, and the dynamic social registry has enhanced fiscal transparency, improved targeting, and strengthened adaptive social protection
  - Deepening coordination across these systems would enable systematic tracking of how adaptation spending affects women’s livelihoods and resilience outcomes
- Priority actions (as listed in the source):
  - Strengthen the integration of CBT and GBT. Establish consistent cross-analysis of adaptation and gender-related expenditures, supported by clear institutional responsibilities and regular reporting by MINECOFIN, sector ministries, and the Rwanda Gender Monitoring Office.
  - Expand adaptive social protection through the social registry. Continue improving coverage, interoperability, and real-time updating to allow programs—particularly the VUP—to scale up efficiently during shocks while maintaining fiscal discipline.
  - Promote women’s participation in the green transition. Facilitate access to green finance, technical and vocational training, and digital skills to ensure women benefit from employment opportunities in renewable energy, sustainable agriculture, and the circular economy. Integrate gender criteria into green-investment facilities such as Ireme Invest.
  - Enhance access to productive assets and finance. Broaden financial inclusion, strengthen women’s property and land rights, and expand tailored support for women-owned MSMEs to raise productivity and resilience.
  - Invest in data and evaluation. Expand the use of gender-disaggregated and climate-tagged data to assess the effectiveness of adaptation and inclusion programs and guide evidence-based policy refinement.
- Conclusion: Together, these measures would help Rwanda consolidate its progress toward a resilient, low-carbon, and inclusive economy; institutional innovation, data-driven policymaking, and sustained attention to gender equality can reinforce both economic resilience and fiscal sustainability

### Trade and Export Context (selected findings with numeric indicators)
- External imbalances:
  - Current account deficit averaged well above 10 percent of GDP and reached nearly 15 percent in recent years
- Export concentration and partners:
  - Gold accounted for nearly one-third of total goods exports by 2022, up from less than 1 percent in 2010
  - By 2022, exports had become heavily concentrated in the United Arab Emirates (36 percent) and the Democratic Republic of Congo (24 percent)
- Structural drivers of the persistent trade deficit:
  - Sticky imports: more than half of the increase in exports-to-GDP since 2016 came from gold and re-exports, which require high import content
  - Limited contribution of services: travel and ICT exports expanded but were fully offset by deficits in transport services
- Export development priorities:
  - Broaden export base beyond primary products (coffee, tea, minerals) into horticulture, light manufacturing, and services
  - Improve logistics capacity, reduce transport costs, strengthen role as services and trade hub, complement with broader reforms to realize spillovers from large-scale FDI
  - Deepen integration within EAC and fuller participation in AfCFTA to deliver growth dividends

### Table 5 — Largest CBT and GBT Projects in FY25/26 (Projects larger than USD10 million)
- Agriculture
  - GBT Improved access to farm inputs for women: 53.9 (RWF Billion)
  - CBT Climate-smart agriculture and input access: 71.0 (RWF Billion)
- Employment
  - GBT Job creation and training for women: 84.7 (RWF Billion)
  - GBT Employment in housing/construction for women: 48.1 (RWF Billion)
  - GBT Employment in road construction for women: 97.4 (RWF Billion)
- Energy
  - GBT Expansion of electricity access for women: 128.0 (RWF Billion)
  - CBT Renewable energy and energy efficiency: 169.9 (RWF Billion)
  - CBT Resilience-focused energy infrastructure: 44.6 (RWF Billion)
- Environment
  - CBT Integrated environmental protection: 67.9 (RWF Billion)
- Transport
  - CBT Road rehabilitation and resilient transport: 88.1 (RWF Billion)
- Social Protection
  - GBT Direct VUP support to women: 36.3 (RWF Billion)
  - GBT Support to female genocide survivors: 16.4 (RWF Billion)
  - CBT Support to households affected by climate shocks: 39.1 (RWF Billion)
- Education
  - CBT Climate-resilient schools; awareness programs: 15.3 (RWF Billion)
- Health
  - GBT HIV prevention and treatment for women: 15.0 (RWF Billion)
- Water and Sanitation
  - GBT Improved access to water/sanitation for women: 55.7 (RWF Billion)
  - CBT Expansion of water and sanitation infrastructure: 47.1 (RWF Billion)
  - CBT Improved water treatment and sanitation systems: 34.3 (RWF Billion)

*Source: IMF staff summary of the Rwanda section (selected pages).*

### 11.      To boost economic gains from trade, Rwanda would therefore need to enhance the

### To boost economic gains from trade, Rwanda would therefore need to enhance the composition, quality, and skill intensity of its export basket.

### Export composition, sophistication, and survival
- Current export products are characterized by low technology and skills utilization; medium- and high-technology products account for less than 10 percent of exports.
- Primary commodities and resource-based products dominate; the overall export sophistication of Rwanda has declined largely due to the rising dominance of gold.
- Gold’s share was too small (below 0.1 percent) in 2010 to show in the chart, but has since increased sufficiently to lower aggregate export sophistication.
- Rwanda’s export basket is highly concentrated and low-skilled, which can impede economic gains from trade.
- New products exhibit low survival rates, with many disappearing after a short period, indicating nascent industrial development, weak competitiveness, and lack of scale.

### Diversification dynamics and product-space constraints
- Diversification into new products typically proceeds gradually through intermediate stages that build on existing comparative advantages.
- The product-space framework (Hidalgo et al. 2007) implies that moving to more complex products is easier when a country already produces goods located in the dense core of the product space.
- Upgrading Rwanda’s export base will take time and sustained policy effort, including targeted investments in skills, technology, and supporting industries.
- Broadening the scope of foreign direct investment and fostering linkages between services, agro-processing, and light manufacturing could help reposition Rwanda in the product space.

### Impediments to export diversification and growth
- Key drivers identified (per the IMF study applied to SSA) include logistics and infrastructure quality, human capital and skills development, institutional strength (governance, labor market flexibility, SOEs), and tariff barriers.
- Geography and landlockedness complicate logistics and increase transportation costs; much of Rwanda’s international trade flows through Kenya and Tanzania, creating dependence on the Mombasa and Dar es Salaam corridors and vulnerability to regional shocks.
- Trade complementarity with regional partners has improved, but Rwandan export products remain broadly similar to neighboring Kenya, Uganda, and Tanzania.
- Rwanda ranks low historically in global logistics performance but showed improvement: LPI ranking improved from 151st in 2010 to 57th in 2018 before declining to 73rd.
- Two LPI subcomponents primarily drove the improvement and subsequent decline: timeliness and international shipments.
- Substantial progress in cost of trading with neighbors was made up to 2010 due to trade reforms, but momentum has stalled.
- Human capital: Rwanda performs below SSA and EAC neighbors on human capital indicators; more investment is needed in secondary and tertiary enrollment, technical and vocational training, and STEM competencies.
- Institutional issues: Rwanda stands out in SSA for strong governance and ease of doing business, yet challenges remain in reducing the prominence of SOEs in competitive sectors and improving SOE governance.

### Selected measurable impacts from trade and logistics reforms (Box 2)
- Rwanda Electronic Single Window (ReSW): clearance time reduced from 11 days (2012) to 1.5 days (2014).
- Alibaba eWTP and digital infrastructure: Rwandan coffee sales volumes on Alibaba rose by seven folds.
- One-Stop Border Post (Rusumo OSBP): truck clearance time cut to under 30 minutes at Rusumo.
- EAC Single Customs Territory: transit times from Dar es Salaam and Mombasa reduced from 21 and 18 days to 7 and 4 days, respectively; transport costs decreased from US$3,100 to US$1,025.
- Inland dry Port Kigali Logistics Platform (KLP): truck turnaround time reduced from about 2 weeks to 3 days.
- Air Cargo Hub development: supports high-value agriculture and horticulture, which comprise 50 percent of non-traditional exports.
- Quality/safety licenses broadly extended from 2 to 5 years; export licenses are no longer required.
- Rwanda Development Board (RDB) as a one-stop shop: consolidates 22 institutions to provide 440 services.
- Rwanda's World Bank Doing Business rank surged from 158th to 38th (2007–2020); ranked No. 2 in Africa for Ease of Doing Business (after Mauritius).
- Preferential CIT rate of 15 percent for companies exporting ≥50 percent of production or in priority sectors (0 percent for regional HQs).
- Provides 50 percent accelerated first-year depreciation and exemption from capital gains on assets sold.
- Kigali ranked the 2nd most popular MICE destination in Africa (ICCA ranking) 5 consecutive years.
- Rwanda has one of the most liberal visa regimes in Africa (leading Visa Openness index rank in 2023 and 2024).
- 10 industrial parks and Special Economic Zones (SEZs); Kigali SEZ provides serviced land and reduced regulatory compliance costs.

### Price competitiveness and external sustainability
- Since 2015, the nominal effective exchange rate (NEER) has depreciated steadily; the real effective exchange rate (REER) has also trended downward but to a lesser extent due to episodes of relatively high domestic inflation.
- IMF’s EBA-lite suggests Rwanda’s REER is moderately undervalued relative to model-implied norms, consistent with a current account gap of about 3–5 percent of GDP.
- Structural factors—high trade costs, limited export diversification, and quality gaps—remain the main impediments to external sustainability despite exchange rate support.

### Policy implications and recommendations
- Overcoming export diversification impediments requires a comprehensive approach addressing logistics, skills, institutions, and macroeconomic stability.
- Addressing logistics and infrastructure bottlenecks:
  - Continue developing high-value, low-volume exports that leverage air connectivity and skills.
  - Planned complementary investments in dry ports in Tanzania and Kenya, along with customs modernization, will enhance integration into regional and global value chains.
  - Long-term projects: complete New Kigali International Airport and improve road and rail connectivity to Mombasa and Dar es Salaam.
  - Connect farmers to markets via investment in storage, cold chains, and post-harvest loss reduction.
  - Improve digital literacy and increase smartphone access to fully benefit from digitized customs procedures and digital services.
- Improving the business environment:
  - Systematically reduce the role of the state in commercial activities, strengthen SOE governance, and ensure a level playing field.
  - Invest in skills development and ICT to support goods and services exports, including capabilities in product design, quality assurance, data analytics, and emerging technologies.
  - Support the sustainability of new firms and products to reduce high exit rates and ensure lasting export diversification.
- Capitalizing on regional integration:
  - Deepen participation in EAC and AfCFTA to expand market access, reduce non-tariff barriers, and attract FDI.
  - Improve trade facilitation, harmonize standards, and strengthen regional transport corridors.
- Safeguarding and enhancing price competitiveness:
  - Maintain inflation close to the center of the target band and allow the exchange rate to act as a shock absorber.
  - Use opportunistic sterilized FX purchases to build reserves while mitigating exchange rate overshooting during large inflows.
  - Complement macro policies with structural reforms to address high trade costs and the narrow export base.

*Source: IMF staff report content provided in the supplied PDF chapter excerpt.*

### References

### References (chapter/section)

### Major thematic clusters in the references
- Trade, growth, and inequality
  - Beaton, Kimberly, Aliona Cebotari,, and Andras Komaromi . 2017. "Revisiting the Link between Trade, Growth and Inequality:." IMF Working Papers 2017 (046): 42.
  - Behar, Alberto, and Caroline Freund. 2011. "The trade performance of the Middle East and North Africa (English)." World Bank Policy Research Working Paper .
  - Ghosh, Atish R., and Jonathan David Ostry. 1994. "Export Instability and the External Balance in Developing Countries." IMF Staff papers: Volume 41 ( No.2): 220.
  - Mishra, Saurabh, Susanna Lundström, and Rahul Anand. 2011. "Service Export Sophistication and Economic Growth." Policy Research Working Paper, March 1: .
  - Raei, Faezeh, and Anna Ignatenko. 2019. "Global Value Chains: What are the Benefits and Why Do Countries Participate?" (IMF) 2019 (018): 31; doi:
  - Twum, Anna. 2022. Using trade to propel high growth: lessons from Rwanda’s export performance in the past decade. International Growth Centre(IGC) Rwanda.

- Export composition, product space, and diversification
  - Hausmann, Ricardo, Jason Hwang, and Dani Rodrik. 2007. "What you export matters." Journal of Economic Growth 12: 1-25.
  - Hidalgo, C A, B Klinger, and R Hausmann. 2007. "The Product Space Conditions the Development of Nations." Science 482–487.
  - Imbs, Jean, and Romain Wacziarg. 2003. "Stages of Diversification." American Economic Review Vol. 93 (No.1): 63–86.
  - Salinas, Gonzalo. 2021. "Proximity and Horizontal Policies: The Backbone of Export Diversification and Complexity." IMF Working Paper, IMF, Washington, DC.
  - The Growth Lab at Harvard University. 2025. International Trade Data (HS92) 1995-2023. Accessed March 2025. https://doi.org/10.7910/DVN/T4CHWJ.

- Terms of trade, exchange rate volatility, and investment/growth in SSA
  - Bleaney, Michael, and David Greenaway. 2001. "The impact of terms of trade and real exchange rate volatility on investment and growth in sub-Saharan Africa." Journal of Development Economics 65: 491-500.
  - Ghosh, Atish R., and Jonathan David Ostry. 1994. "Export Instability and the External Balance in Developing Countries." IMF Staff papers: Volume 41 ( No.2): 220.

- Institutions, geography, and policy drivers of development
  - Rodrik, D., A. Subramanian, and F. Trebbi. 2004. "The Primacy of Institutions Over Geography and Integration in Economic Development." Journal of Economic Growth 131-165.
  - Beaton, Kimberly, Aliona Cebotari,, and Andras Komaromi . 2017. "Revisiting the Link between Trade, Growth and Inequality:." IMF Working Papers 2017 (046): 42.

### Rwanda-specific sources and diagnostics
- National policy and legal analyses
  - ALN. n.d. "Impact of Rwanda’s New Investment Facilitation and Promotion Law on Doing Business." Rwanda Finance Limited. https://www.rfl.rw/docs/LEGAL_ALERT_ALN.pdf.
  - IFC. 2019. CREATING MARKETS IN RWANDA: Transforming for the Jobs of Tomorrow. Country Private Sector Diagnostic, Washington, D.C: World Bank Group. https://www.ifc.org/content/dam/ifc/doc/mgrt/201906-cpsd-rwanda.pdf.
  - Steenbergen, Victor, and Beata Javorcik. 2017. Analysing the impact of the Kigali Special Economic Zone on firm behaviour. International Growth Centre. doi:F-38419-RWA-1.
  - Twum, Anna. 2022. Using trade to propel high growth: lessons from Rwanda’s export performance in the past decade. International Growth Centre(IGC) Rwanda.

- National and regional trade institutions and portals
  - Rwanda Trade Portal. n.d. Rwanda Trade Portal. Accessed 2025. https://rwandatrade.rw/.
  - East African Community. n.d. Customs Union. Accessed 2025. https://www.eac.int/customs-union.
  - East African Community. n.d. Single Customs Territory. Accessed 2025. https://www.eac.int/customs/single-customs-territory.

- Analyses of export sophistication, proximate policies, and value chains relevant to Rwanda
  - Mishra, Saurabh, Susanna Lundström, and Rahul Anand. 2011. "Service Export Sophistication and Economic Growth." Policy Research Working Paper, March 1: .
  - Salinas, Gonzalo. 2021. "Proximity and Horizontal Policies: The Backbone of Export Diversification and Complexity." IMF Working Paper, IMF, Washington, DC.
  - Raei, Faezeh, and Anna Ignatenko. 2019. "Global Value Chains: What are the Benefits and Why Do Countries Participate?" (IMF) 2019 (018): 31; doi:
  - Steenbergen, Victor, and Beata Javorcik. 2017. Analysing the impact of the Kigali Special Economic Zone on firm behaviour. International Growth Centre. doi:F-38419-RWA-1.

### Data, indexes, and online repositories cited
- Growth Lab at Harvard University. 2024. The Atlas of Economic Complexity. Accessed July 2025. https://atlas.hks.harvard.edu.
- The Growth Lab at Harvard University. 2025. International Trade Data (HS92) 1995-2023. Accessed March 2025. https://doi.org/10.7910/DVN/T4CHWJ.
- UNCOMTRADE. 2025. https://wits.worldbank.org/about_wits.html. September 1. https://wits.worldbank.org/about_wits.html.
- UNOSSC. 2025. United Nations Office for South-South Cooperation (UNOSSC). May 23. https://unsouthsouth.org/2025/05/23/rwandas-implementation-of  -trade-facilitation-measures-and-the-leveraging-of-south-south-and-triangular-cooperation-unossc-2025/.

### Methodological and conceptual contributions referenced
- Product space and export complexity frameworks
  - Hausmann, Ricardo, Jason Hwang, and Dani Rodrik. 2007. "What you export matters." Journal of Economic Growth 12: 1-25.
  - Hidalgo, C A, B Klinger, and R Hausmann. 2007. "The Product Space Conditions the Development of Nations." Science 482–487.
  - Imbs, Jean, and Romain Wacziarg. 2003. "Stages of Diversification." American Economic Review Vol. 93 (No.1): 63–86.

- Trade policy, export performance, and development outcomes
  - Behar, Alberto, and Caroline Freund. 2011. "The trade performance of the Middle East and North Africa (English)." World Bank Policy Research Working Paper .
  - Ghosh, Atish R., and Jonathan David Ostry. 1994. "Export Instability and the External Balance in Developing Countries." IMF Staff papers: Volume 41 ( No.2): 220.
  - Rodrik, D., A. Subramanian, and F. Trebbi. 2004. "The Primacy of Institutions Over Geography and Integration in Economic Development." Journal of Economic Growth 131-165.

*References list extracted from the source PDF chapter/section titled "References".*

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_Source: https://www.imf.org/-/media/files/publications/cr/2025/english/1rwaea2025003-source-pdf.pdf_