## _wp14202

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---

### Introduction and research motivation
- Research question: Do IMF-supported programs in low-income countries (LICs) catalyze significantly higher donor Official Development Assistance (ODA) relative to non-program countries facing similar economic difficulties?
- Two catalytic channels:
  - IMF conditionality: restoring macroeconomic stability and advancing reform.
  - IMF financing: easing the burden of adjustment to shocks.
- Methodological challenge: selection bias because countries approaching the IMF typically face or anticipate economic difficulties.
- Key methodological response: estimate determinants of IMF-supported program participation (selection model) and focus on more homogeneous subsets of programs.

### Scope and empirical strategy
- Focus: financing arrangements with LICs addressing policy and exogenous shocks.
- Main empirical methods:
  - Propensity score matching (PSM) to address selection bias.
  - Two-step PSM: (1) estimate probability of program participation (selection model); (2) nearest neighbor matching (choose four non-program countries closest in propensity score) to estimate average treatment effect on the treated (ATT).
- Outcome measures tested:
  - Four ODA measures: gross disbursements, net disbursements, net commitments, untied disbursements.
  - Aid modality measures: proportions of general budget support from IDA and EC; proportion of untied aid (excluding technical cooperation and humanitarian aid).
- Donor heterogeneity examined: bilateral versus multilateral donors.
- Program implementation explicitly accounted for in estimating catalytic impact.

### Selection model and key determinants of IMF financing probability
- Preferred selection model: correlated random effects probit; dependent variable = panel dummy (1 if new IMF shock financing approved; 0 otherwise).
- Included arrangements: SBA, SAF/ESAF/PRGF/ECF augmentations, ESF, SCF, RCF, CFF (with refinements excluding precautionary SBAs/SCFs and including some SAF/ESAF/PRGF/ECF addressing policy shocks).
- Significant determinants (coefficients and t-stats from Bal Gündüz (2009), Table 1):
  - Current account balance to GDP (t-1): -0.076*** (t-stat -4.61)
  - Reserve coverage (CFA) (t-1): -0.478*** (-6.08)
  - Reserve coverage (non-CFA) (t-1): -0.769*** (-8.71)
  - Macroeconomic stability indicator (t-1): 0.068*** (2.89)
  - Real GDP growth (t-1): -0.113*** (-4.24)
  - Change in terms of trade (t-1): -0.022*** (-2.8)
  - Change in real oil prices in previous two years: 0.009*** (2.85)
  - Real world trade, cyclical component: -0.099** (-2.53)
  - Real growth of goods exports (t-1): -0.009* (-1.79)
  - Paris Club dummy: 0.774*** (3.24)
  - Country-specific averages: Total debt service to exports: 0.044*** (2.63); FDI to GDP: -0.105* (-1.76)
  - Pseudo R2 0.58; Number of observations 532; Number of countries 55; Sample probability 0.44.

### Key empirical findings — catalytic impact on ODA (summary)
- IMF-supported programs with LICs are associated with significantly higher ODA.
- Magnitude on gross disbursements (excluding debt relief): increase amounting to 1.9 percent of GDP (reported as 1.992*** (SE 0.572) in first-differenced, scaled by lagged GDP).
- Catalytic impact does not vary much for program countries experiencing substantial prior macroeconomic imbalances or large exogenous shocks.
- Commitments effects appear larger than disbursement effects, implying potential issues with utilization and predictability of aid disbursements.
- Donor heterogeneity:
  - Multilateral donors: IMF-supported programs are associated with significantly higher ODA from multilateral donors; multilateral flows are the principal driver of aggregate effects.
  - Bilateral donors: estimated impact is positive but weaker; bilateral catalytic impact is sensitive to hidden bias and becomes insignificant after controlling for “donor favorites.”

### Quantitative results — selected estimates (exact reported values)
- Sample period: 1980–2010; outcome variables generally analyzed as (Xt – Xt-1) / GDPt-1.
- Heterogeneity by propensity score (PS) groups: low (PS < 0.3), medium to high (0.3 < PS < 0.7), very high (PS > 0.7).
- Control-to-treated ratio: overall 2.1; PS<0.3 = 7.0; 0.3<PS<0.7 = 1.5; PS>0.7 = 1.1.

Disbursements excluding debt relief (first-differenced, scaled by lagged GDP; Table 3):
- Gross disbursement (All LICs): 1.992*** (SE 0.572); observations 584.
  - PS<0.3: 0.964 (0.898); 232 obs.
  - 0.3<PS<0.7: 2.087*** (0.629); 118 obs.
  - PS>0.7: 2.165** (0.906); 234 obs.
- Net disbursement (All LICs): 2.405*** (0.871); 584 obs.
  - PS<0.3: 1.978 (2.118)
  - 0.3<PS<0.7: 2.635*** (0.998)
  - PS>0.7: 2.359* (1.301)
- Untied ODA disbursement (All LICs): 1.688*** (0.498); 584 obs.
  - PS<0.3: 0.776 (0.758)
  - 0.3<PS<0.7: 1.840*** (0.549)
  - PS>0.7: 1.812** (0.790)
- Bilateral gross disbursement (All LICs): 0.854** (0.420); 567 obs.
  - Bilateral significance driven by 0.3<PS<0.7: 1.099** (0.529).
- Multilateral gross disbursement (All LICs): 1.394*** (0.308); 567 obs.
  - PS<0.3: 1.604*** (0.394).

Disbursements including debt relief (first-differenced):
- Gross disbursement (All LICs): 2.347** (0.967); 584 obs.
  - PS<0.3: -0.173 (2.449)
  - 0.3<PS<0.7: 1.747** (0.734)
  - PS>0.7: 3.211** (1.474)
- Multilateral gross disbursement (All LICs): 1.459*** (0.452); 567 obs.
- Bilateral gross disbursement including debt relief becomes insignificant in aggregate.

Levels (% of GDP) results (Table 4):
- Gross disbursement (level, All LICs): 2.224** (0.992); 584 obs.
- Net disbursement (level, All LICs): 2.240** (1.056); 584 obs.
- Untied ODA disbursement (level, All LICs): 2.217*** (0.707); 584 obs.
- Multilateral gross disbursement (level, All LICs): 1.420*** (0.477).

Commitments (first-differenced, including debt relief; Table 5):
- Commitment (All LICs): 2.632** (1.074); 567 obs.
  - PS>0.7: 3.495** (1.674)
- Multilateral commitment (All LICs): 1.817*** (0.566); 567 obs.
- Bilateral commitment insignificant in aggregate.

Aid modality — general budget support (first-differenced; Table 6):
- Proportion general budget support from IDA: 18.58*** (5.318); 146 observations.
- Proportion general budget support from EC: 18.59*** (3.776); 212 observations.
- Interpretation: IMF-supported programs tend to induce significantly higher proportions of aid allocated as general budget support from IDA and EC (caveat: small sample sizes).

### Robustness and sensitivity
- Rosenbaum sensitivity analysis (selected Γ parameters, Table 7):
  - Gross Disbursement (Excluding Debt Relief): All LICs Γ = 1.74; PS<0.3 = 1.00; 0.3<PS<0.7 = 1.79; PS>0.7 = 1.77.
  - Multilateral Gross Disbursement (Excluding Debt Relief): All LICs Γ = 2.18; PS>0.7 Γ = 2.53.
  - Bilateral Gross Disbursement (Excluding Debt Relief): All LICs Γ = 1.24 (relatively sensitive).
  - Commitments: All LICs Γ = 2.07; Multilateral Commitment Γ = 2.56.
- Interpretation: Results generally robust to hidden bias except for bilateral ODA (more sensitive) and low propensity score group (very sensitive).
- Inclusion of ECF programs (Table 8):
  - Results weaken for full sample and sub-groups.
  - Gross disbursement (All LICs) becomes 0.724*** (0.280) when ECFs included.
  - Net disbursement loses significance in aggregate.
  - ECFs predominantly add to low propensity score group; participation equation for immediate financing needs may not be appropriate for ECFs.
- Matching on propensity score and lagged ODA (to control for “donor favorites”; Table 9):
  - Results qualitatively similar for total and multilateral disbursements.
  - Estimated catalytic impact on bilateral disbursements (gross and net) becomes insignificant for the full sample after controlling for lagged ODA.
  - After controlling for donor favorites, bilateral support is significant for PS<0.3 in some specifications.

### Heterogeneity of effects
- Catalytic impact primarily driven by countries with medium to high and very high propensity scores (0.3<PS<0.7 and PS>0.7).
- For many specifications, the catalytic impact is not significant for low propensity scores (PS<0.3).
- Multilateral flows are the robust driver of aggregate catalytic effects; bilateral flows are weaker and more sensitive to hidden bias and donor-favoritism controls.

### Conclusions (section VI)
- IMF-supported programs addressing immediate balance of payments needs in LICs:
  - Have a significant catalytic impact on the change in ODA and on aid modality (increase in general budget support from IDA and EC).
  - Effects are primarily driven by countries with sizeable initial macroeconomic imbalances or large exogenous shocks (medium to high and very high propensity scores); catalytic impact not significant for low propensity scores.
  - Both multilateral and bilateral donors raise ODA excluding debt relief for program countries, but multilateral flows are the principal driver of aggregate effects.
  - In levels analysis, bilateral flows’ catalytic impact is insignificant in aggregate and multilateral flows drive the significant aggregate effect—consistent with political/strategic determinants in bilateral aid allocation.
  - After controlling for “donor favorites,” the catalytic impact on bilateral disbursements becomes insignificant; bilateral results are highly sensitive to hidden bias.
  - Inclusion of ECF-supported programs weakens results; further research could analyze ECF catalytic impacts using a participation model tailored to ECF determinants.

### Annex 1 highlights — average annual ODA disbursements to GDP (1980–2010), selected country ratios (exact values)
- Albania — Gross: 9.03; Net Untied ODA: 9.20; Bilateral Gross: 6.57; Multi Gross: 5.32; Gross: 3.71
- Burundi — Gross: 25.83; Net Untied ODA: 24.48; Bilateral Gross: 16.03; Multi Gross: 12.16; Gross: 13.67
- Mozambique — Gross: 25.10; Net Untied ODA: 24.17; Bilateral Gross: 18.64; Multi Gross: 16.80; Gross: 8.30
- Malawi — Gross: 21.76; Net Untied ODA: 19.29; Bilateral Gross: 15.89; Multi Gross: 10.79; Gross: 10.98
- Rwanda — Gross: 19.18; Net Untied ODA: 18.09; Bilateral Gross: 12.45; Multi Gross: 10.82; Gross: 8.36
- Nigeria — Gross: 0.68; Net Untied ODA: 0.74; Bilateral Gross: 0.46; Multi Gross: 0.36; Gross: 0.32
- India — Gross: 0.40; Net Untied ODA: 0.54; Bilateral Gross: 0.31; Multi Gross: 0.07; Gross: 0.32
- Zambia — Gross: 16.01; Net Untied ODA: 15.51; Bilateral Gross: 12.52; Multi Gross: 9.30; Gross: 6.71

*Source: IMF staff paper, "Demand for Fund Financing in Response to Policy and/or External Shocks" (section text supplied).

### 1. Demand for Fund Financing in Response to Policy and/or External Shocks ......................15

### 1. Demand for Fund Financing in Response to Policy and/or External Shocks

### Introduction and research motivation
- The catalytic effect of IMF-supported programs on donor flows in low-income countries (LICs) has received scant attention; existing empirical research has focused mainly on private capital flows to emerging market economies with mixed findings.
- Catalytic effects are likely heterogeneous across program types and recipient countries; in LICs the relevant test is whether IMF-supported programs lead to significantly higher donor assistance (Official Development Assistance, ODA).
- Two potential channels for catalysis:
  - IMF conditionality: restoring macroeconomic stability and advancing reform to increase resilience to shocks.
  - IMF financing: easing the burden of adjustment to shocks to support stabilization and near-term growth.
- Major methodological challenge: selection bias, since countries that approach the IMF typically face economic difficulties or expect problems; causal inference requires comparing program and non-program countries with similar prior economic conditions.
- Key methodological response: estimate determinants of IMF-supported program participation (selection model) and focus on more homogeneous subsets of programs to improve model performance.

### Scope and empirical strategy
- Focus: a unique set of financing arrangements with LICs addressing policy and exogenous shocks.
- Methodology highlights:
  - Implements propensity score matching (PSM) technique to address selection bias.
  - Examines catalytic impact not only on amounts but also on the modality of ODA.
  - Tests a comprehensive set of ODA measures, including gross and net disbursements (both including and excluding debt relief), net commitments, and untied disbursements.
  - Explores heterogeneity of the catalytic impact by donor type (bilateral versus multilateral).
  - Explicitly accounts for program implementation in estimating catalytic impact.

### Key empirical findings
- IMF-supported programs with LICs are associated with significantly higher ODA.
- Magnitude of catalytic impact on gross disbursements (excluding debt relief):
  - Increase amounting to 1.9 percent of GDP.
- The size of the estimated catalytic impact does not vary much for program countries experiencing substantial prior macroeconomic imbalances or large exogenous shocks.
- Catalytic impact on commitments appears larger than the impact on disbursements, suggesting potential room to improve:
  - utilization of aid by recipients, and
  - predictability of aid disbursements.
- Donor heterogeneity:
  - IMF-supported programs are associated with significantly higher ODA from multilateral donors.
  - The estimated impact is positive but weaker for bilateral donors.

### Findings on aid modality
- Countries with IMF-supported programs tend to receive a higher proportion of aid in general budget support from:
  - International Development Association (IDA), and
  - European Commission (EC).
- The proportion of untied aid (excluding technical cooperation and humanitarian aid) in total aid is higher for countries with IMF-supported programs.

### Contributions to the literature
- First study to explore the catalytic impact for the specific subset of LIC financing arrangements addressing policy and exogenous shocks.
- Uses PSM to address selection bias in the context of catalytic financing impact.
- Broadens outcome measures to include multiple ODA metrics and aid modalities.
- Investigates donor heterogeneity and accounts for program implementation.

*Source: IMF staff paper, "Demand for Fund Financing in Response to Policy and/or External Shocks" (section text supplied).*

### conclusions are summarized in section VI.

### _wp14202 - conclusions are summarized in section VI

### Literature Review
- Existing literature on the catalytic financing effect of IMF-supported programs focuses on private capital flows in emerging market economies and finds no uniform positive effect; catalytic effects vary with initial economic conditions and flow type.
- Studies find non-monotonic effects: positive catalytic effects tend to arise for countries in a middle range of economic indicators for wealth or financial stability.
- Mody and Saravia (2006): IMF program participation lowers bond spreads for countries with medium levels of foreign reserves; countries with higher reserves experience negative catalytic effects (higher bond spread); at the lower end there is neither positive nor negative catalytic effect.
- Bird and Rowlands (2007) is the only prior paper examining catalytic impact on donor assistance to LICs; it finds a strong positive association and suggests conditionality may matter more than IMF resources, but it does not correct for selection bias and aggregates heterogeneous program types.

### Defining the Catalytic Impact on ODA
- Catalytic impact on private flows: IMF involvement increases propensity of private investors to lend, reducing adjustment burden (Cottarelli and Giannini, 2002).
- Catalytic impact on ODA: IMF programs act as a simultaneous, collaborative coordination device among donors; IMF financing arrangements require that programs be fully financed with donor and creditor assurances (no unfilled financing gaps over the 12 months immediately following approval/completion of reviews).
- Research question: How effective are IMF-supported programs in LICs as coordinating devices for donor support compared to non-program countries experiencing similar economic difficulties?

### Methodology — Data
- Focus on ODA (official development assistance) rather than FDI given ODA’s predominance for LICs over 1980–2010.
- Data source: OECD/DAC disaggregated donor–recipient series.
- Four ODA measures used: gross disbursements, net disbursements, net commitments, and untied disbursements.
- Adjustments:
  - Deduct debt forgiven and rescheduled from gross disbursements (following Claessens, Cassimon, Campenhout (2009) and Roodman (2012)).
  - Adjusted gross disbursement formula used: Gross disbursement = (total ODA grants – debt forgiveness grants) + (total gross loans extended – rescheduled debt).
  - Remove offsetting entries for OOF loan repayment treatment to refine net disbursements.
  - Gross commitments cannot be adjusted for debt relief due to data limitations; commitments reported including debt relief.
- Aid modality: use ODA commitments for general budget support by IDA and EU using Clist, Isopi, Morrissey (2012) dataset (EU: 1997–2009; IDA: 1995–2007).

### Methodology — Propensity Score Matching (PSM) and Selection Model
- Treatment: participation in an IMF-supported program addressing policy or exogenous shocks.
- Two-step PSM:
  1. Estimate probability of participating in IMF-supported programs conditional on observable pre-treatment characteristics (selection model).
  2. Match program countries to non-program countries on propensity scores to construct control group and estimate average treatment effect on the treated (ATT).
- Matching method: nearest neighbor matching (choose four non-program countries with probabilities closest to program country).
- Key identification assumptions: (i) conditional independence (program participation depends only on observed pre-treatment characteristics); (ii) common support (comparable control units exist for each treated unit).
- Selection model: correlated random effects probit preferred; dependent variable = panel dummy (1 if new IMF shock financing approved; 0 otherwise). Included arrangements: SBA, SAF/ESAF/PRGF/ECF augmentations, ESF, SCF, RCF, CFF, with refinements to exclude precautionary SBAs/SCFs and to include some SAF/ESAF/PRGF/ECF addressing policy shocks.
- Significant determinants of IMF financing probability (from Bal Gündüz (2009), Table 1):
  - Current account balance to GDP (t-1): -0.076*** (t-stat -4.61)
  - Reserve coverage (CFA) (t-1): -0.478*** (-6.08)
  - Reserve coverage (non-CFA) (t-1): -0.769*** (-8.71)
  - Macroeconomic stability indicator (t-1): 0.068*** (2.89)
  - Real GDP growth (t-1): -0.113*** (-4.24)
  - Change in terms of trade (t-1): -0.022*** (-2.8)
  - Change in real oil prices in previous two years: 0.009*** (2.85)
  - Real world trade, cyclical component: -0.099** (-2.53)
  - Real growth of goods exports (t-1): -0.009* (-1.79)
  - Paris Club dummy: 0.774*** (3.24)
  - Country-specific averages: Total debt service to exports: 0.044*** (2.63); FDI to GDP: -0.105* (-1.76)
  - Pseudo R2 0.58; Number of observations 532; Number of countries 55; Sample probability 0.44.

### Results — Summary and Key Quantitative Findings
- Sample period: 1980–2010; outcome variables generally analyzed in first differences scaled by lagged GDP: (Xt – Xt-1) / GDPt-1.
- Heterogeneity by propensity score (PS) groups: low (PS < 0.3), medium to high (0.3 < PS < 0.7), very high (PS > 0.7). Control-to-treated ratio overall 2.1; by subgroup: 7.0 (PS<0.3), 1.5 (0.3<PS<0.7), 1.1 (PS>0.7).

Findings on disbursements excluding debt relief (Table 3, first-differenced, scaled by lagged GDP):
- Gross disbursement (All LICs): 1.992*** (SE 0.572); observations 584.
  - PS<0.3: 0.964 (0.898); 232 obs.
  - 0.3<PS<0.7: 2.087*** (0.629); 118 obs.
  - PS>0.7: 2.165** (0.906); 234 obs.
- Net disbursement (All LICs): 2.405*** (0.871); 584 obs.
  - PS<0.3: 1.978 (2.118)
  - 0.3<PS<0.7: 2.635*** (0.998)
  - PS>0.7: 2.359* (1.301)
- Untied ODA disbursement (All LICs): 1.688*** (0.498); 584 obs.
  - PS<0.3: 0.776 (0.758)
  - 0.3<PS<0.7: 1.840*** (0.549)
  - PS>0.7: 1.812** (0.790)
- Bilateral gross disbursement (All LICs): 0.854** (0.420); 567 obs.
  - Significance of bilateral increases driven by 0.3<PS<0.7 (1.099** (0.529)).
- Multilateral gross disbursement (All LICs): 1.394*** (0.308); 567 obs.
  - Significant across PS groups, including PS<0.3: 1.604*** (0.394).

Findings including debt relief (Table 3, first-differenced):
- Gross disbursement (All LICs): 2.347** (0.967); 584 obs.
  - PS<0.3: -0.173 (2.449)
  - 0.3<PS<0.7: 1.747** (0.734)
  - PS>0.7: 3.211** (1.474)
- Multilateral gross disbursement (All LICs): 1.459*** (0.452); 567 obs.
- Bilateral gross disbursement including debt relief becomes insignificant in aggregate.

Findings using levels (% of GDP) (Table 4):
- Gross disbursement (level, All LICs): 2.224** (0.992); 584 obs.
- Net disbursement (level, All LICs): 2.240** (1.056); 584 obs.
- Untied ODA disbursement (level, All LICs): 2.217*** (0.707); 584 obs.
- Multilateral gross disbursement (level, All LICs): 1.420*** (0.477).

Commitments (first-differenced, including debt relief) (Table 5):
- Commitment (All LICs): 2.632** (1.074); 567 obs.
  - PS>0.7: 3.495** (1.674)
- Multilateral commitment (All LICs): 1.817*** (0.566); 567 obs.
- Bilateral commitment insignificant in aggregate.

Aid modality — general budget support (first-differenced) (Table 6):
- Proportion general budget support from IDA: 18.58*** (5.318); 146 observations.
- Proportion general budget support from EC: 18.59*** (3.776); 212 observations.
- Interpretation: IMF-supported programs tend to induce significantly higher proportions of aid allocated as general budget support from IDA and EC (caveat: small sample sizes; interpret with caution).

Heterogeneity:
- Catalytic impact primarily driven by countries with medium to high and very high propensity scores; impact not significant for low propensity scores in many specifications.
- Both multilateral and bilateral donors raise ODA excluding debt relief for program countries, but multilateral flows are the more robust driver of aggregate effects.

### Robustness Checks
- Rosenbaum sensitivity analysis (Table 7) — Γ parameters indicating sensitivity to hidden bias (selected values):
  - Gross Disbursement (Excluding Debt Relief): All LICs Γ = 1.74; PS<0.3 = 1.00; 0.3<PS<0.7 = 1.79; PS>0.7 = 1.77.
  - Multilateral Gross Disbursement (Excluding Debt Relief): All LICs Γ = 2.18; PS>0.7 Γ = 2.53.
  - Bilateral Gross Disbursement (Excluding Debt Relief): All LICs Γ = 1.24 (relatively sensitive).
  - Commitments: All LICs Γ = 2.07; Multilateral Commitment Γ = 2.56.
- Interpretation: Results across different ODA measures are generally robust to hidden bias except for bilateral ODA (more sensitive). Results for low propensity score group are very sensitive to hidden bias.
- Inclusion of ECF programs (protracted balance of payments needs) in treatment (Table 8):
  - Results weaken for full sample and sub-groups; gross disbursement (All LICs) becomes 0.724*** (0.280) when ECFs included; net disbursement loses significance in aggregate.
  - ECF observations predominantly add to low propensity score group; using the participation equation estimated for immediate financing needs may not be appropriate for ECFs.
- Matching on propensity score and lagged ODA (to control for “donor favorites”) (Table 9):
  - Results qualitatively similar for total and multilateral disbursements.
  - Estimated catalytic impact on bilateral disbursements (gross and net) becomes insignificant for the full sample after controlling for lagged ODA; suggests bilateral donors may support “donor favorites” irrespective of program status.
  - After controlling for donor favorites, bilateral support is significant for PS<0.3 in some specifications.

### Conclusions (section VI)
- Focus: IMF-supported programs addressing immediate balance of payments needs arising from policy or exogenous shocks in LICs.
- Main conclusions:
  - IMF-supported programs in LICs have a significant catalytic impact on the change in ODA and on aid modality (increase in general budget support from IDA and EC).
  - Effects are primarily driven by countries experiencing sizeable initial macroeconomic imbalances or large exogenous shocks (medium to high and very high propensity scores); catalytic impact is not significant for countries with low propensity scores.
  - Both multilateral and bilateral donors significantly raise ODA excluding debt relief to countries with IMF-supported programs, but multilateral flows are the principal driver of aggregate effects.
  - When analyzing levels, bilateral flows’ catalytic impact is insignificant in aggregate and multilateral flows drive the significant aggregate effect — consistent with literature that political/strategic factors guide bilateral aid allocation.
  - After controlling for “donor favorites,” the catalytic impact on bilateral disbursements becomes insignificant, and bilateral results are highly sensitive to hidden bias — indicating that the catalytic impact is primarily attributed to multilateral flows.
  - Inclusion of ECF-supported programs weakens results; further research could analyze ECF catalytic impacts using a participation model tailored to ECF determinants.

*Source: _wp14202 - conclusions are summarized in section VI.*

### Annex 1. List of Countries and Average Annual ODA Disbursements to GDP (1980–2010)

### Annex 1. List of Countries and Average Annual ODA Disbursements to GDP (1980–2010)

### Country ODA ratios (1980–2010)
- 1 Albania — Gross: 9.03; Net Untied ODA: 9.20; Bilateral Gross: 6.57; Multi Gross: 5.32; Gross: 3.71
- 2 Armenia — Gross: 5.64; Net Untied ODA: 5.66; Bilateral Gross: 1.50; Multi Gross: 0.37; Gross: 5.27
- 3 Azerbaijan — Gross: 1.02; Net Untied ODA: 1.03; Bilateral Gross: 0.55; Multi Gross: (0.56); Gross: 1.58
- 4 Bangladesh — Gross: 2.42; Net Untied ODA: 2.71; Bilateral Gross: 1.61; Multi Gross: 0.30; Gross: 2.12
- 5 Benin — Gross: 10.34; Net Untied ODA: 10.02; Bilateral Gross: 7.69; Multi Gross: 5.67; Gross: 4.67
- 6 Bolivia — Gross: 5.14; Net Untied ODA: 5.31; Bilateral Gross: 2.84; Multi Gross: 2.36; Gross: 2.78
- 7 Burkina Faso — Gross: 13.79; Net Untied ODA: 13.64; Bilateral Gross: 9.74; Multi Gross: 8.17; Gross: 5.62
- 8 Burundi — Gross: 25.83; Net Untied ODA: 24.48; Bilateral Gross: 16.03; Multi Gross: 12.16; Gross: 13.67
- 9 Cambodia — Gross: 5.69; Net Untied ODA: 5.78; Bilateral Gross: 3.19; Multi Gross: 2.31; Gross: 3.38
- 10 Cameroon — Gross: 3.52; Net Untied ODA: 3.54; Bilateral Gross: 2.56; Multi Gross: 2.38; Gross: 1.14
- 11 Central African Republic — Gross: 12.63; Net Untied ODA: 12.19; Bilateral Gross: 8.67; Multi Gross: 7.25; Gross: 5.38
- 12 Chad — Gross: 12.59; Net Untied ODA: 13.01; Bilateral Gross: 8.84; Multi Gross: 6.43; Gross: 6.16
- 13 Comoros — Gross: 20.04; Net Untied ODA: 20.58; Bilateral Gross: 13.45; Multi Gross: 11.34; Gross: 8.70
- 14 Congo, Republic of — Gross: 5.29; Net Untied ODA: 5.82; Bilateral Gross: 3.73; Multi Gross: 4.09; Gross: 1.20
- 15 Cote Divoire — Gross: 4.35; Net Untied ODA: 4.83; Bilateral Gross: 3.42; Multi Gross: 2.62; Gross: 1.72
- 16 Democratic Republic of Congo — Gross: 8.15; Net Untied ODA: 8.20; Bilateral Gross: 5.19; Multi Gross: 4.11; Gross: 4.04
- 17 Ethiopia — Gross: 9.59; Net Untied ODA: 8.84; Bilateral Gross: 5.97; Multi Gross: 4.95; Gross: 4.64
- 18 Gambia — Gross: 16.16; Net Untied ODA: 16.45; Bilateral Gross: 11.82; Multi Gross: 7.70; Gross: 8.46
- 19 Georgia — Gross: 3.86; Net Untied ODA: 3.87; Bilateral Gross: 1.66; Multi Gross: (0.26); Gross: 4.11
- 20 Ghana — Gross: 6.12; Net Untied ODA: 5.80; Bilateral Gross: 5.18; Multi Gross: 3.08; Gross: 3.04
- 21 Guinea — Gross: 9.01; Net Untied ODA: 9.84; Bilateral Gross: 6.62; Multi Gross: 4.51; Gross: 4.49
- 22 Guinea-Bissau — Gross: 21.92; Net Untied ODA: 21.52; Bilateral Gross: 15.45; Multi Gross: 11.49; Gross: 10.43
- 23 Guyana — Gross: 3.21; Net Untied ODA: 4.06; Bilateral Gross: 1.87; Multi Gross: (4.23); Gross: 7.44
- 24 Haiti — Gross: 13.92; Net Untied ODA: 14.00; Bilateral Gross: 7.44; Multi Gross: 9.51; Gross: 4.41
- 25 Honduras — Gross: 6.41; Net Untied ODA: 6.16; Bilateral Gross: 4.60; Multi Gross: 3.86; Gross: 2.55
- 26 India — Gross: 0.40; Net Untied ODA: 0.54; Bilateral Gross: 0.31; Multi Gross: 0.07; Gross: 0.32
- 27 Kenya — Gross: 5.94; Net Untied ODA: 6.77; Bilateral Gross: 4.09; Multi Gross: 3.87; Gross: 2.06
- 28 Kyrgyz Republic — Gross: 5.08; Net Untied ODA: 5.10; Bilateral Gross: 2.36; Multi Gross: (1.29); Gross: 6.37
- 29 Laos PDR — Gross: 6.28; Net Untied ODA: 6.35; Bilateral Gross: 3.90; Multi Gross: 0.65; Gross: 5.63
- 30 Madagascar — Gross: 10.65; Net Untied ODA: 9.95; Bilateral Gross: 8.02; Multi Gross: 5.38; Gross: 5.27
- 31 Malawi — Gross: 21.76; Net Untied ODA: 19.29; Bilateral Gross: 15.89; Multi Gross: 10.79; Gross: 10.98
- 32 Mali — Gross: 17.07; Net Untied ODA: 16.81; Bilateral Gross: 12.63; Multi Gross: 10.28; Gross: 6.78
- 33 Mauritania — Gross: 19.92; Net Untied ODA: 20.43; Bilateral Gross: 15.13; Multi Gross: 10.38; Gross: 9.55
- 34 Moldova — Gross: 6.39; Net Untied ODA: 6.51; Bilateral Gross: 3.78; Multi Gross: 3.35; Gross: 3.04
- 35 Mongolia — Gross: 6.37; Net Untied ODA: 6.50; Bilateral Gross: 3.62; Multi Gross: 2.99; Gross: 3.63
- 36 Mozambique — Gross: 25.10; Net Untied ODA: 24.17; Bilateral Gross: 18.64; Multi Gross: 16.80; Gross: 8.30
- 37 Nepal — Gross: 4.90; Net Untied ODA: 4.98; Bilateral Gross: 2.97; Multi Gross: 1.24; Gross: 3.66
- 38 Nicaragua — Gross: 15.61; Net Untied ODA: 14.41; Bilateral Gross: 11.42; Multi Gross: 10.50; Gross: 5.11
- 39 Niger — Gross: 14.54; Net Untied ODA: 13.78; Bilateral Gross: 10.16; Multi Gross: 8.61; Gross: 5.93
- 40 Nigeria — Gross: 0.68; Net Untied ODA: 0.74; Bilateral Gross: 0.46; Multi Gross: 0.36; Gross: 0.32
- 41 Pakistan — Gross: 1.20; Net Untied ODA: 1.46; Bilateral Gross: 0.82; Multi Gross: 0.02; Gross: 1.18
- 42 Papua New Guinea — Gross: 7.80; Net Untied ODA: 8.10; Bilateral Gross: 5.78; Multi Gross: 6.56; Gross: 1.23
- 43 Rwanda — Gross: 19.18; Net Untied ODA: 18.09; Bilateral Gross: 12.45; Multi Gross: 10.82; Gross: 8.36
- 44 Senegal — Gross: 10.99; Net Untied ODA: 10.85; Bilateral Gross: 7.73; Multi Gross: 7.15; Gross: 3.84
- 45 Sierra Leone — Gross: 19.08; Net Untied ODA: 18.11; Bilateral Gross: 12.96; Multi Gross: 9.22; Gross: 9.87
- 46 Sri Lanka — Gross: 3.94; Net Untied ODA: 4.59; Bilateral Gross: 2.90; Multi Gross: 1.84; Gross: 2.11
- 47 Sudan — Gross: 8.52; Net Untied ODA: 8.85; Bilateral Gross: 4.93; Multi Gross: 5.33; Gross: 3.19
- 48 Tajikistan — Gross: 4.25; Net Untied ODA: 4.28; Bilateral Gross: 1.07; Multi Gross: (1.33); Gross: 5.62
- 49 Tanzania — Gross: 14.07; Net Untied ODA: 13.85; Bilateral Gross: 11.15; Multi Gross: 9.22; Gross: 4.86
- 50 Togo — Gross: 10.65; Net Untied ODA: 12.04; Bilateral Gross: 7.94; Multi Gross: 6.05; Gross: 4.60
- 51 Uganda — Gross: 12.06; Net Untied ODA: 11.22; Bilateral Gross: 9.41; Multi Gross: 6.10; Gross: 5.96
- 52 Uzbekistan — Gross: 0.75; Net Untied ODA: 0.77; Bilateral Gross: 0.43; Multi Gross: 0.57; Gross: 0.17
- 53 Vietnam — Gross: 1.95; Net Untied ODA: 2.07; Bilateral Gross: 1.45; Multi Gross: 0.84; Gross: 1.11
- 54 Zambia — Gross: 16.01; Net Untied ODA: 15.51; Bilateral Gross: 12.52; Multi Gross: 9.30; Gross: 6.71
- 55 Zimbabwe — Gross: 9.57; Net Untied ODA: 9.66; Bilateral Gross: 4.35; Multi Gross: 7.28; Gross: 2.30

*Annex 1. List of Countries and Average Annual ODA Disbursements to GDP (1980–2010)*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2014/_wp14202.pdf_