## 1.  External Aid and Selected Macroeconomic Indicators, 1985–2001

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---

### Introduction and framing
- Since the late 1990s, the international community has increased focus on poverty reduction as the overarching objective of economic policy for low-income countries (LICs).
- Official development assistance (ODA) per capita and ODA as percent of gross national income (GNI) of recipient countries has been trending down, even though many countries still rely heavily on it to finance investment.
- For the few countries whose ODA inflows have increased, the large government spending that aid allows tends to create macroeconomic management problems that raise concerns of undermining prospects for long-term growth through Dutch-disease-type effects: real exchange rate (RER) appreciation and a shrinkage of the tradables sector.
- The paper analyzes the Dutch disease model to contextualize concerns about adverse effects of large aid flows on export growth, presenting a variant of the core Dutch disease model and modifications that make its predictions avoidable.
- A correct diagnosis of Dutch disease resulting from large ODA inflows carries important policy implications; misdiagnosis can either allow harmful developments to continue or lead to counterproductive adjustments that impede long-term growth and poverty reduction.

### Key conceptual points on Dutch disease and aid
- Dutch-disease-type effects cited as a potential channel for diminishing returns to aid.
- Core model premises identify circumstances under which:
  - RER appreciation can occur,
  - Lower exports can result,
  - A wider trade deficit can develop.
- The paper emphasizes that these premises "may not be present in many LICs" and provides model modifications that can avoid such outcomes.
- Diagnosis must consider interaction of ODA-induced public spending with other factors affecting economic performance.

### Table 1 — External aid and selected macroeconomic indicators, 1985–2001 (selected series)
- Periods: 1985-89 1990-94 1995-99 2000-01

- Aid per capita (annual average; current US dollars)
  - World 8.1 12.1 10.5 9.6
  - Low-income countries 10.0 13.0 10.5 9.8
  - Sub-Saharan Africa 27.2 34.5 25.7 20.5
  - Benin 36.5 53.8 41.9 40.2
  - The Gambia 107.9 93.3 33.0 37.8
  - Mali 51.0 48.8 43.2 32.4
  - Tanzania 34.4 60.5 59.2 35.6
  - Rwanda 34.1 40.8 29.9 33.1
  - Uganda 20.2 39.2 35.1 35.6

- Aid in percent of GNI (annual average)
  - Low-income countries 2.7 3.4 2.5 2.3
  - Sub-Saharan Africa 5.5 6.6 5.0 4.5
  - Benin 11.3 15.6 11.1 11.1
  - The Gambia 40.6 28.5 9.7 12.6
  - Mali 23.2 18.6 17.2 14.4
  - Tanzania 10.5 32.3 27.6 17.6
  - Rwanda 21.2 25.4 13.4 12.3
  - Uganda 6.0 20.1 11.8 14.1

- Aid in percent of gross capital formation (annual average)
  - Low-income countries 11.3 13.9 10.7 10.8
  - Sub-Saharan Africa 34.7 40.7 26.3 23.2
  - Benin 91.4 103.7 61.1 58.0
  - The Gambia 225.0 129.1 50.8 70.6
  - Mali 117.1 78.4 78.2 65.6
  - Tanzania 68.5 276.4 192.1 97.0
  - Rwanda ... 94.1 81.6 70.8
  - Uganda 59.9 133.2 69.4 69.6

### Selected macroeconomic performance indicators

- GDP growth (annual average; in percent)
  - World — 3.72.12.92.5
  - Low-income countries — 4.92.14.04.4
  - Sub-Saharan Africa — 2.20.63.43.0
  - Benin — 1.84.05.05.4
  - The Gambia — 3.22.63.95.8
  - Mali — 2.01.45.82.6
  - Tanzania — 2.9-11.515.76.3
  - Rwanda — 3.82.53.85.4
  - Uganda — 3.16.07.74.1

- External trade balance (annual average; in percent of GDP)
  - Sub-Saharan Africa
  - Benin — -14.8-12.5-12.5-12.9
  - The Gambia — -9.5-13.6-16.6-15.7
  - Mali — -20.0-17.1-12.3-11.3
  - Tanzania — -10.1-21.1-18.7-16.3
  - Rwanda — ...-25.6-13.5-8.6
  - Uganda — -6.8-13.3-10.4-13.4

- Real effective exchange rate (1990=100; annual average change in percent) 1/
  - Benin — -0.1-6.13.8-0.5
  - The Gambia — -4.1-1.1-0.7-8.6
  - Mali — -4.8-9.62.2-1.7
  - Tanzania — -28.7-3.88.81.3
  - Rwanda — -2.22.6-2.6-6.2
  - Uganda — 2.6-8.2-2.8-3.6

- Inflation (GDP deflator, annual average percentage change)
  - Sub-Saharan Africa
  - Benin — -0.88.16.83.2
  - The Gambia — 24.47.33.25.4
  - Mali — 0.97.95.44.8
  - Tanzania — 1.113.415.31.7
  - Rwanda — 20.626.318.57.0
  - Uganda — 148.830.55.06.6

- Note: The figures shown under 1985-89 represent averages for the 4-year period ended in 1989.

### Key findings and analytical framework on ODA, growth, and the Dutch disease
- ODA definition and intended roles:
  - ODA comprises medium- and long-term concessional loans and grants from bilateral and multilateral sources; some researchers define ODA as grants plus the grant element of concessional loans.
  - Intended functions: support infrastructure and human capital, alleviate foreign exchange constraints by financing imports, ease external debt service, raise foreign exchange reserves, and provide incentives for private sector development.

- Empirical evidence on ODA and growth:
  - Hadjimichael and others (1995) and Lesink and White (2001) find ODA has a positive impact on growth, with diminishing marginal returns.
  - Burnside and Dollar (2000) find ODA is growth-enhancing only in a good policy environment; Dalgaard and Hansen (2001) find this result not robust.
  - Collier and Dollar (2002) confirm the Burnside-Dollar result using the World Bank CPIA and find diminishing returns; Collier (1999) argues ODA continues to benefit growth until the ODA-to-GDP ratio reaches 30 percent.
  - Easterly (2003) and Easterly, Levine, and Roodman (2003) highlight fragility of the Burnside-Dollar result to sample size, averaging period, and policy indicators.
  - Elbadawi (1999) finds ODA-to-GNP ratio positively associated with nontraditional exports up to a threshold, beyond which ODA hinders exports; also finds nontraditional exports positively associated with human capital, imports of machinery, and RER undervaluation, and negatively associated with RER variability.

- Core Dutch disease model (Salter-Swan framework; Corden and Neary, 1982):
  - Assumptions: full and efficient employment of production factors, a mobile production factor transferable between sectors, and perfectly elastic demand for tradable goods (small-country assumption).
  - Mechanisms:
    - Spending effect: increased aggregate expenditure raises demand for nontradables and their price, causing RER appreciation and discouraging tradables production.
    - Resource transfer effect: labor reallocates from tradables to booming nontradables due to higher marginal product of labor in nontradables.
    - Expenditure-switching effect: relative price changes alter consumption and import patterns, potentially widening the trade deficit.

- Empirical country evidence is mixed:
  - Ghana: Younger (1992) links increased ODA with high inflation, appreciating RER, and tight credit to nonbank private sector; Sackey (2001) finds aid dampens the RER and undermines Dutch-disease applicability.
  - Tanzania: Nyoni (1998) finds aid associated with RER depreciation despite increased ODA.
  - CFA countries (Burkina Faso, Côte d’Ivoire, Senegal, Togo): Adenauer and Vagassky (1998) find aid linked to RER appreciation, higher government deficits, and wider trade balances, consistent with Dutch disease; interpretation complicated by external price movements and currency effects.
  - Sri Lanka: White and Wignaraja (1992) find aid and remittances related to RER appreciation and manufacturing underperformance; Bandara (1995) finds no support for Dutch disease using a CGE model.
  - Botswana: Despite a mining boom (mining output grew to 50 percent of GDP in 1989), the REER depreciated on trend, exports other than diamond increased, employment rose sharply, and average annual growth was 8.5 percent during 1965-89—evidence against Dutch disease in that case.

### Modified Dutch disease model and implications
- Key departures from the core model:
  - Relax full employment: many LICs operate below potential because of supply bottlenecks and underutilized factors; ODA can mobilize idle capacity.
  - Relax small-country assumption: demand for tradables can be downward-sloping; imperfect substitutability between domestic importables and imports can mitigate deindustrialization risks.

- Modified model outcomes:
  - Large ODA flows can finance government socioeconomic programs, lead to RER appreciation, and still permit increased production of both tradables and nontradables.
  - If supply elasticities are sufficiently high (especially supply of nontradables), RER appreciation may be mild or absent.
  - Increased use of idle resources can narrow the trade deficit rather than widen it.

- Determinants of magnitude and direction:
  - Higher income elasticity of demand for nontradables → larger RER appreciation.
  - Higher price elasticity of demand for nontradables → smaller RER appreciation.
  - Higher price elasticity of supply → smaller real appreciation.
  - Complementarities between imported and domestic inputs can allow manufacturing to expand even with RER appreciation.

### Policy implications and recommendations
- Country-specific diagnosis:
  - Assessing whether aid causes Dutch disease requires full account of country-specific circumstances, supply bottlenecks, and cost structures of critical sectors.
  - Constant monitoring of key macroeconomic variables and cost structures is important; when sectoral data are lacking, short- to medium-term analysis can focus on ODA-enabled investment in infrastructure and human capital and macro variables affecting private sector development.

- Role of policies and institutions:
  - Demand management (fiscal and monetary policy) can limit real income increases that spur nontradables demand and resource transfer effects.
  - Deepening structural reforms and monitoring efficiency of public spending are essential for poverty reduction and economic transformation.
  - Improved transparency and efficiency in the use of ODA is crucial; mismanagement and wasteful spending can be more damaging than RER appreciation.

- Caution on policy prescriptions:
  - Avoid hard-line prescriptions based on models whose key assumptions may not apply.
  - Where data do not permit meaningful cost-benefit analyses, policy recommendations should be prudent.

*Source: IMF working paper section "1.  External Aid and Selected Macroeconomic Indicators, 1985–2001" (excerpt).*

### 1.  External Aid and Selected Macroeconomic Indicators, 1985–2001..............................................4

### 1.  External Aid and Selected Macroeconomic Indicators, 1985–2001..............................................4

### Introduction and framing
- Since the late 1990s, the international community has increased focus on poverty reduction as the overarching objective of economic policy for low-income countries (LICs).
- Official development assistance (ODA) per capita and ODA as percent of gross national income (GNI) of recipient countries has been trending down, even though many countries still rely heavily on it to finance investment (see Table 1).
- For the few countries whose ODA inflows have increased, the large government spending that aid allows tends to create macroeconomic management problems that raise concerns of undermining prospects for long-term growth through Dutch-disease-type effects: real exchange rate (RER) appreciation and a shrinkage of the tradables sector.
- The paper analyzes the Dutch disease model to contextualize concerns about adverse effects of large aid flows on export growth, presenting a variant of the core Dutch disease model and modifications that make its predictions avoidable.
- A correct diagnosis of Dutch disease resulting from large ODA inflows carries important policy implications; misdiagnosis can either allow harmful developments to continue or lead to counterproductive adjustments that impede long-term growth and poverty reduction.

### Key conceptual points on Dutch disease and aid
- Dutch-disease-type effects cited as a potential channel for diminishing returns to aid.
- Core model premises identify circumstances under which:
  - RER appreciation can occur,
  - Lower exports can result,
  - A wider trade deficit can develop.
- The paper emphasizes that these premises "may not be present in many LICs" and provides model modifications that can avoid such outcomes.
- Diagnosis must consider interaction of ODA-induced public spending with other factors affecting economic performance.

### Table 1 — External aid and selected macroeconomic indicators, 1985–2001 (selected series)
- Periods: 1985-89 1990-94 1995-99 2000-01

1. External aid indicators
- Aid per capita (annual average; current US dollars)
  - World 8.1 12.1 10.5 9.6
  - Low-income countries 10.0 13.0 10.5 9.8
  - Sub-Saharan Africa 27.2 34.5 25.7 20.5
  - Benin 36.5 53.8 41.9 40.2
  - The Gambia 107.9 93.3 33.0 37.8
  - Mali 51.0 48.8 43.2 32.4
  - Tanzania 34.4 60.5 59.2 35.6
  - Rwanda 34.1 40.8 29.9 33.1
  - Uganda 20.2 39.2 35.1 35.6
- Aid in percent of GNI (annual average)
  - Low-income countries 2.7 3.4 2.5 2.3
  - Sub-Saharan Africa 5.5 6.6 5.0 4.5
  - Benin 11.3 15.6 11.1 11.1
  - The Gambia 40.6 28.5 9.7 12.6
  - Mali 23.2 18.6 17.2 14.4
  - Tanzania 10.5 32.3 27.6 17.6
  - Rwanda 21.2 25.4 13.4 12.3
  - Uganda 6.0 20.1 11.8 14.1
- Aid in percent of gross capital formation (annual average)
  - Low-income countries 11.3 13.9 10.7 10.8
  - Sub-Saharan Africa 34.7 40.7 26.3 23.2
  - Benin 91.4 103.7 61.1 58.0
  - The Gambia 225.0 129.1 50.8 70.6
  - Mali 117.1 78.4 78.2 65.6
  - Tanzania 68.5 276.4 192.1 97.0
  - Rwanda ... 94.1 81.6 70.8
  - Uganda 59.9 133.2 69.4 69.6

### Policy implications emphasized
- Because Dutch disease diagnosis is consequential, policy responses should be conditioned on careful country-specific analysis of:
  - Whether the core premises of the Dutch disease model hold,
  - How ODA-induced public spending interacts with factors affecting tradables and nontradables sectors,
  - Trade-offs between curbing aid-induced macroeconomic distortions and sustaining programs essential for growth and poverty reduction.

*Source: IMF working paper section "1.  External Aid and Selected Macroeconomic Indicators, 1985–2001" (excerpt).*

### 2. Selected macroeconomic performance indicators

### 2. Selected macroeconomic performance indicators

### GDP growth (annual average; in percent)
- World — 3.72.12.92.5
- Low-income countries — 4.92.14.04.4
- Sub-Saharan Africa — 2.20.63.43.0
- Benin — 1.84.05.05.4
- The Gambia — 3.22.63.95.8
- Mali — 2.01.45.82.6
- Tanzania — 2.9-11.515.76.3
- Rwanda — 3.82.53.85.4
- Uganda — 3.16.07.74.1

### External trade balance (annual average; in percent of GDP)
- Sub-Saharan Africa
- Benin — -14.8-12.5-12.5-12.9
- The Gambia — -9.5-13.6-16.6-15.7
- Mali — -20.0-17.1-12.3-11.3
- Tanzania — -10.1-21.1-18.7-16.3
- Rwanda — ...-25.6-13.5-8.6
- Uganda — -6.8-13.3-10.4-13.4

### Real effective exchange rate (1990=100; annual average change in percent) 1/
- Benin — -0.1-6.13.8-0.5
- The Gambia — -4.1-1.1-0.7-8.6
- Mali — -4.8-9.62.2-1.7
- Tanzania — -28.7-3.88.81.3
- Rwanda — -2.22.6-2.6-6.2
- Uganda — 2.6-8.2-2.8-3.6

### Inflation (GDP deflator, annual average percentage change)
- Sub-Saharan Africa
- Benin — -0.88.16.83.2
- The Gambia — 24.47.33.25.4
- Mali — 0.97.95.44.8
- Tanzania — 1.113.415.31.7
- Rwanda — 20.626.318.57.0
- Uganda — 148.830.55.06.6

*Source: World Bank, World Development Indicators, 2003.  
1/ The figures shown under 1985-89 represent averages for the 4-year period ended in 1989.*

### Key findings and analytical framework on ODA, growth, and the Dutch disease
- ODA definition and intended roles:
  - ODA comprises medium- and long-term concessional loans and grants from bilateral and multilateral sources; some researchers define ODA as grants plus the grant element of concessional loans.
  - Intended functions: support infrastructure and human capital, alleviate foreign exchange constraints by financing imports, ease external debt service, raise foreign exchange reserves, and provide incentives for private sector development.
- Empirical evidence on ODA and growth:
  - Hadjimichael and others (1995) and Lesink and White (2001) find ODA has a positive impact on growth, with diminishing marginal returns.
  - Burnside and Dollar (2000) find ODA is growth-enhancing only in a good policy environment; Dalgaard and Hansen (2001) find this result not robust.
  - Collier and Dollar (2002) confirm the Burnside-Dollar result using the World Bank CPIA and find diminishing returns; Collier (1999) argues ODA continues to benefit growth until the ODA-to-GDP ratio reaches 30 percent.
  - Easterly (2003) and Easterly, Levine, and Roodman (2003) highlight fragility of the Burnside-Dollar result to sample size, averaging period, and policy indicators.
  - Elbadawi (1999) finds ODA-to-GNP ratio positively associated with nontraditional exports up to a threshold, beyond which ODA hinders exports; also finds nontraditional exports positively associated with human capital, imports of machinery, and RER undervaluation, and negatively associated with RER variability.
- Core Dutch disease model (Salter-Swan framework; Corden and Neary, 1982):
  - Assumptions: full and efficient employment of production factors, a mobile production factor transferable between sectors, and perfectly elastic demand for tradable goods (small-country assumption).
  - Mechanisms:
    - Spending effect: increased aggregate expenditure raises demand for nontradables and their price, causing RER appreciation and discouraging tradables production.
    - Resource transfer effect: labor reallocates from tradables to booming nontradables due to higher marginal product of labor in nontradables.
    - Expenditure-switching effect: relative price changes alter consumption and import patterns, potentially widening the trade deficit.
- Empirical country evidence is mixed:
  - Ghana: Younger (1992) links increased ODA with high inflation, appreciating RER, and tight credit to nonbank private sector; Sackey (2001) finds aid dampens the RER and undermines Dutch-disease applicability.
  - Tanzania: Nyoni (1998) finds aid associated with RER depreciation despite increased ODA.
  - CFA countries (Burkina Faso, Côte d’Ivoire, Senegal, Togo): Adenauer and Vagassky (1998) find aid linked to RER appreciation, higher government deficits, and wider trade balances, consistent with Dutch disease; interpretation complicated by external price movements and currency effects.
  - Sri Lanka: White and Wignaraja (1992) find aid and remittances related to RER appreciation and manufacturing underperformance; Bandara (1995) finds no support for Dutch disease using a CGE model.
  - Botswana: Despite a mining boom (mining output grew to 50 percent of GDP in 1989), the REER depreciated on trend, exports other than diamond increased, employment rose sharply, and average annual growth was 8.5 percent during 1965-89—evidence against Dutch disease in that case.

### Modified Dutch disease model and implications
- Key departures from the core model:
  - Relax full employment: many LICs operate below potential because of supply bottlenecks and underutilized factors; ODA can mobilize idle capacity.
  - Relax small-country assumption: demand for tradables can be downward-sloping; imperfect substitutability between domestic importables and imports can mitigate deindustrialization risks.
- Modified model outcomes:
  - Large ODA flows can finance government socioeconomic programs, lead to RER appreciation, and still permit increased production of both tradables and nontradables.
  - If supply elasticities are sufficiently high (especially supply of nontradables), RER appreciation may be mild or absent.
  - Increased use of idle resources can narrow the trade deficit rather than widen it.
- Determinants of magnitude and direction:
  - Higher income elasticity of demand for nontradables → larger RER appreciation.
  - Higher price elasticity of demand for nontradables → smaller RER appreciation.
  - Higher price elasticity of supply → smaller real appreciation.
  - Complementarities between imported and domestic inputs can allow manufacturing to expand even with RER appreciation.

### Policy implications and recommendations
- Country-specific diagnosis:
  - Assessing whether aid causes Dutch disease requires full account of country-specific circumstances, supply bottlenecks, and cost structures of critical sectors.
  - Constant monitoring of key macroeconomic variables and cost structures is important; when sectoral data are lacking, short- to medium-term analysis can focus on ODA-enabled investment in infrastructure and human capital and macro variables affecting private sector development.
- Role of policies and institutions:
  - Demand management (fiscal and monetary policy) can limit real income increases that spur nontradables demand and resource transfer effects.
  - Deepening structural reforms and monitoring efficiency of public spending are essential for poverty reduction and economic transformation.
  - Improved transparency and efficiency in the use of ODA is crucial; mismanagement and wasteful spending can be more damaging than RER appreciation.
- Caution on policy prescriptions:
  - Avoid hard-line prescriptions based on models whose key assumptions may not apply.
  - Where data do not permit meaningful cost-benefit analyses, policy recommendations should be prudent.

*Italic: Source: _wp0449 - 2. Selected macroeconomic performance indicators (extracted content).*

### References

### References

### Dutch Disease, Natural Resources, and Real Exchange Rate Effects
- Adenauer, Isabell, and Laurence Vagassky, 1998, “Aid and the Real Exchange Rate: Dutch Disease Effects in African Countries,” Intereconomics: Review of International Trade and Development, Vol. 33 (July/August), pp. 177–85.
- Auty, Richard M., 2001, “The Political State and the Management of Mineral Rents in Capital-surplus Economies: Botswana and Saudi Arabia,” Resource Policy, Vol. 27 (June), pp.77–86.
- Bandara, Jayatilleke S., 1995, “‘Dutch’ Disease in a Developing Country: The Case of Foreign Capital Inflows to Sri Lanka,” Seoul Journal of Economics, Vol. 8 (Fall), pp. 314–29.
- Benjamin, Nancy C., Shantayanan Devarajan, and Robert J. Weiner, 1989, “Dutch Disease in a Developing Country: Oil Reserves in Cameroon,” Journal of Development Economics, Vol. 30 (January), pp. 71–92.
- Corden, Max W., 1984, “Booming Sector and Dutch Disease Economics: Survey and Consolidation,” Oxford Economic Papers, Vol. 36 (November), pp. 359–80.
- Corden, Max W., and Peter J. Neary, 1982, “Booming Sector and De-Industrialisation in a Small Open Economy,” The Economic Journal, Vol. 92 (December), pp. 825–48.
- Torvik, Ragnar, 2001, “Learning by Doing and the Dutch Disease,” European Economic Review, Vol. 45, pp. 285–306.
- Vos, Rob, 1998, “Aid Flows and Dutch Disease in a General Equilibrium Framework for Pakistan,” Journal of Policy Modeling, Vol. 20 (February) pp. 77–109.
- Younger, Stephen D., 1992, “Aid and the Dutch Disease: Macroeconomic Management When Everybody Loves You,” World Development, Vol. 20 (November), pp. 1587–97.
- Sackey, Harry A., 2001, “External Aid Flows and the Real Exchange Rate in Ghana,” AERC Research Paper No. 110 (Nairobi: African Economic Research Consortium).

### Aid Effectiveness, Aid and Growth, and Methodological Debates
- Burnside, Craig, and David Dollar, 2000, “Aid, Policies, and Growth,” American Economic Review, Vol. 90 (September), pp. 847–68.
- Chang, Charles, Eduardo Fernandez-Arias, and Luis Serven, 1998, “Measuring Aid Flows: A New Approach”, World Bank Policy Research Working Paper, No. 2050 (Washington: World Bank).
- Collier, Paul, 1999, “Aid Dependency: A Critique,” Journal of African Economies, Vol. 8 (December), pp. 528–45.
- Collier, Paul, and David Dollar (2002), “Aid Allocation and Poverty Reduction,” European Economic Review, Vol. 46 (September), pp. 1475–500.
- Dalgaard, Carl-Johan, and Henrik Hansen, 2001, “On Aid, Growth, and Policies,” Journal of Development Studies, Vol. 37 (August), pp. 17–41.
- Dalgaard, Carl-Johan, Henrik Hansen, and Finn Tarp, 2002, “On the Empirics of Foreign Aid and Growth,” CREDIT Research Paper No. 02/08 (Nottingham: Centre for Research in Economic Development and International Trade).
- Easterly, William, 2003, “Can Foreign Aid Buy Growth?” Journal of Economic Perspectives, Vol. 17 (Summer), pp. 23–48.
- Easterly, William, Ross Levine, and David M. Roodman, 2003, “New Data, New Doubts: A Comment on Burnside and Dollar’s  ‘Aid, Policies, and Growth’,” NBER Working Paper No. 9846 (Cambridge, Massachussetts: National Bureau of Economic Research).
- Hansen, Henrik, and Finn Tarp, 2000, “Aid Effectiveness Disputed,” Journal of International Development, Vol. 12 (April), pp. 375–98.
- Lesink, Robert, and Howard White, 2001, “Are There Negative Returns to Aid?” Journal of Development Studies, Vol. 37 (August), pp. 42-65.
- Tsikata, Tsidi, M. 1999, “Aid Effectiveness: A Survey of the Recent Empirical Literature,” in International Economic Policy Review, Vol. 1, ed. by Paul Mason, Podma Gotur, and Timothy Lane (Washington: International Monetary Fund), pp. 73–90.

### Country- and Region-Specific Studies and Macroeconomic Impacts
- Elbadawi, Ibrahim A., 1999, “External Aid: Help or Hindrance to Export Orientation in Africa?” Journal of African Economies, Vol. 8, (December), pp. 578–616.
- Hadjimichael, Michael T., and others, 1995, Sub-Saharan Africa: Growth, Savings, and Investment, 1986–93, IMF: Occasional Paper No. 118 (Washington: International Monetary Fund).
- Harvey, Charles, 1992, “Botswana: Is the Economic Miracle Over?” Journal of African Economies, Vol.1, (November), pp. 335–68.
- Nyoni, Timothy S., 1998, “Foreign Aid and Economic Performance in Tanzania,” World Development, Vol. 26 (July), pp. 1235–40.
- Vos, Rob, and Sara Johansson, 1994, “Macroeconomic Impact of Aid in Nicaragua,” Department of Economics Reprint Series No. 134 (Stockholm: Handelshögskolan I Stockholm).
- White, Howard, and Ganeshan Wignaraja, 1992, “Exchange Rates, Trade Liberalization and Aid: The Sri Lankan Experience,” World Development, Vol. 20 (October), pp. 1471–80.

*Source: _wp0449 - References*

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