Back Matter

Appendix 1

Aid-Funded Expenditures Under Gleneagles Scenario By Sector (Billion CFAF)*

article image

AIDEI: Early Impact aid. AIDLI: Late Impact aid. AIDNI: No Impact aid

Appendix 2

Scenarios of Foreign Aid from 2007 to 2010 (CFAF billion)

article image
Source: Staff Projections based on Gleneagles template provided by the United Nations

Appendix 3

Assumed Values of Key Parameters for General Equilibrium Simulation

article image

Appendix 4


Main Macroeconomic Indicators With or Without Gleneagles

Citation: Policy Papers 2008, 059; 10.5089/9781498334112.007.A999

Appendix 5

Selected Macroeconomic Indicators in Niger Under Gleneagles Scenario

article image
Source: Staff Estimates

Appendix 6


DSA Based on Gleneagles Assumptions and Composition of Aid of One Third Loans - Two Thirds Grants

Citation: Policy Papers 2008, 059; 10.5089/9781498334112.007.A999

Source: Staff projections and simulations.* Grant-equivalent includes grants provided directly to the government and through new borrowing (difference bewteen the face value and the NPV of new debt). Rate of Debt Accumulation is the annual change in NPV of debt divided by GDP

Appendix 7


Macroeconomic and Debt Assessment Assuming 80 Percent Efficiency of Additional Expenditures16

Citation: Policy Papers 2008, 059; 10.5089/9781498334112.007.A999

Appendix 1 The DSGE model

The model represents a small open economy model, with multiple sectors (exportables, non-traded and imports) and economic agents (firms, households, a government and a central bank). It can be summarized as follows:

  • Consumers/Workers decide how much labor to supply, make savings decision, invest in different types of financial assets (domestic government debt, foreign assets and money) and allocate consumption between different goods (non-traded, exportables and imports).

  • Firms in different sectors must decide the optimal amount of labor to hire, how much real investment to undertake, and how to set prices. Firms in the non-traded sector are subject to price adjustment costs, which leads to a new-Keynesian Phillips curve for non-traded goods inflation. Firms in the exporting sector are exposed to potential learning by doing effects, which imply that a temporary contraction in exports— resulting from a real exchange rate depreciation— can have near-permanent effects (what is often referred as “Dutch Disease”).

  • There is a single labor market, where firms from both traded and non-traded sectors interact with workers to determine wages and employment. Wage setting is also subject to adjustment costs.

  • The government must choose how to allocate the aid transfer between public savings, consumption or investment and whether to spend on local goods and services or imports. The government also taxes labor income and receives seignoriage revenue from the Central Bank.

  • The Central Bank intervenes in both FX and domestic debt markets to accumulate reserves, sterilize foreign inflows and/or ensure the stability of the fixed exchange rate regime.

  • Additional features include limited international capital mobility and steady state growth.

The output of the model is a sequence of all macroeconomic variables (prices and quantities, real and nominal variables) which clears all markets for goods, factors and financial assets over time. For more details, see Berg, Andrew, Tokhir Mirzoev, Rafael Portillo and Felipe Zanna, “Large aid flows and monetary policy in a DSGE model: the case of Uganda” IMF Working Paper (forthcoming).


  • Arestoff, Florence, and Christophe Hurlin, 2005, The Productivity of Public Capital in Developing Countries, unpublished, University of Orléans.

    • Search Google Scholar
    • Export Citation
  • Clemens, M.A., Radelet, S., and Bhavnani, R. 2004. Counting chickens when they hatch: The short-term effect of aid on growth. Center for Global Development working paper no. 44

    • Search Google Scholar
    • Export Citation
  • Farah, Abdikarim, Emilio Sacerdoti, and Gonzalo Salinas (upcoming), The Macroeconomic Impact of Scaled Up Aid: The Case of Niger, IMF Mimeo

    • Search Google Scholar
    • Export Citation
  • Kraay, Aart, and Vikram Nehru, 2004When is Debt Sustainable?”, World Bank Policy Research Working Paper No. 3200.

  • Pritchett, Lant, 1996, “Mind your P’s and Q’s. The Cost of Public Investment is not the Value of Capital,” Policy Research Working Paper No. 1660

    • Search Google Scholar
    • Export Citation
  • World Bank (2006), Niger: Accelerating Growth and Achieving the Millennium Development Goals: Diagnosis and the Policy Agenda, World Bank Country Economic Memorandum. October, 2006.

    • Search Google Scholar
    • Export Citation

The notes were prepared by J. Mongardini and I. Samake (Benin); E. Sacerdoti and G. Salinas (Niger); and C. Mumssen and S. Rosa (Togo) with contributions from J. Gottschalk and R. Portillo.


Based on Farah, Sacerdoti and Salinas, (forthcoming), “The Macroeconomic Impact of Scaling Up Aid: The Case of Niger”.


See Berg, Andrew, Tokhir Mirzoev, Rafael Portillo and Felipe Zanna, “Large aid flows and monetary policy in a DSGE model: the case of Uganda” IMF Working Paper (forthcoming).


National poverty line in 2006 US dollar.


The aid inflows presented in text table 1 refer to ODA (official development assistance), following the OECD DAC definition, i.e., grants or loans with a least a 25 percent grant element. These differ from the aid inflows presented in Figure 1 which only include grants recorded in the central government budget.


It is assumed that, under the Gleneagles scenario, the additional aid would consist of both grants and loans with a combined grant element of 80 percent.


We employ the model of by Farah, Sacerdoti and Salinas (upcoming) “The Macroeconomic Impact of Scaling Up Aid: The Case of Niger”. In order to ensure robustness of the findings, the results are compared with those derived from the model used in “Large aid flows and monetary policy in a DSGE model: the case of Uganda” by Rafael Portillo, Tokhir Mirzoev, Felipe Zanna, and Andy Berg (forthcoming). The preliminary results of the latter model are broadly consistent with the former. In addition, the results for Benin are broadly in line with the ones for Niger, although with some significant differences related to the underlying structure of the two economies.


While subject to significant uncertainty about calibration and long-term inference, DGE models provide a consistent theoretical framework to estimating the impact of additional aid inflows. The simulation results in this note should therefore be considered more qualitative than quantitative in nature, and are subject to a higher degree of uncertainty in the outer years of the simulation.


The dynamic of the model is straightforward. Consider an increase in foreign aid in year t. Aggregate demand increases that same year as the increase in government consumption and investment is only partially leaked out as imports. Aggregate supply does not increase in year t and therefore the increase in demand leads to price adjustments to equilibrate demand and supply: i.e., domestic inflation increases and the real exchange rate appreciates reducing net exports and the current account balance. In year t+1, the increase in foreign aid boosts production through its effect on physical capital, and a few years later through its effect on human capital. The increase of production since year t+1 raises income and this in turn expands the main aggregate demand components, including investment. This implies that the increase in foreign aid crowds-in private investment. The expansion of supply since year t+1 also eases the pressure on domestic inflation and the real exchange rate.


It should be noted that the results of these models applied to LICs are subject to significant uncertainties since: (i) the quality of the data is weak; (ii) parameters are highly unstable through time; and (iii) elasticities are roughly approximated from cross-country calculations.


The higher impact of scaled up aid on the accumulation of human capital relative to its impact on physical capital reflects the fact that the increase in government expenditures in health and education implied by Gleneagles more than doubles these expenditures between 2007 and 2010, whereas the funds devoted to physical capital increases this type of investment by less than 50 percent in the same period.


Niger is considered a Medium policy performer under the template of the IMFAVB Debt Sustainability Analysis since the country’s latest CPIA rating was 3.32, below the minimum 3.75 rating established for strong policy performance.


These projections incorporate macroeconomic projections using the General Equilibrium model in (Farah et al, forthcoming), adding also the impact to exports and fiscal revenues from the planned Imourarem project, which will almost triple the current volume of Uranium exports by 2014.


The thresholds for Strong policy performers are: 50% for NPV of debt-to-GDP, 200% for NPV of debt-to-exports, 300% for NPV of debt-to-revenue, 25% for debt service-to-exports, and 35% for debt service-to-revenue.


We simulate this scenario by assuming that while 100 percent of aid augmentation has an impact on aggregated demand, only 80 percent of it leads to the accumulation of K or H.


This scenario assumes that due to implementation constraints, additional expenditures envisioned under Gleneagles are only 80 percent as efficient as current expenditures in accumulating factors of production.


The price elasticities of imports and exports to the real exchange rate help determine the required real appreciation in the model in response to the increase in aid. The price elasticity of import is set to 1.5. While there is no parameter in the model that directly captures the price elasticity of exports, the reduced form elasticity is close to 1.2.


It is assumed that 70 percent of all public investment projects are efficient, while the remaining 30 percent would not lead to an increase in public capital.

The Macroeconomics of Scaling-up Aid: the Cases of Benin, Niger, and Togo
Author: International Monetary Fund