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References

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Appendix 1: Calibration

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APPENDIX II: ESTIMATION RESULTS

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Appendix III: Prior and Posterior Distributions

Appendix IV: Actual and One-Step Ahead Forecasts

1

We would like to thank Andrew Berg, Doug Laxton, Jean A. P. Clément, Michel Juillard, Catherine Pattillo, Steven O’Connell, Manrique Saenz, Tsidi Tsikata, Reza Vaez-Zadeh, and participants in seminars in the African Department and Small Modelling Group of the IMF. An earlier version of the paper is also in Clément, Jean A.P., and Shanaka J. Peiris (eds.), forthcoming, Post-Stabilization Economics in Sub-Saharan Africa: Lessons from Mozambique (Washington: International Monetary Fund).

2

This partly reflects the preoccupation with the need for fiscal control and effective nominal anchors to bring down inflation from very high levels, which have now been largely achieved in a group of post-stabilization countries dubbed “mature stabilizers” (see Adam and O’Connell 2005, Clément and Peiris (eds.), forthcoming, and IMF 2006).

3

A key issue in SSA concerns the impact of spending scaled-up foreign aid on the real exchange rate, exports, and competitiveness, which according to Rajan and Subramanian (2005) explains the weak link between aid inflows and growth in developing countries. Similar assertions have been made regarding the poor growth performance of natural resource rich economies (Sachs and Warner 1995).

4

Pallage and Robe (2003) estimates the median welfare cost of business cycles in developing countries between 10 and 30 times that of the United States.

5

It is now widely accepted that the primary role of monetary policy is to maintain price stability (IMF 2005b and Batini and Yates, 2003). This is often thought to correspond to an annual rate of inflation in the low single digits in industrial countries (Bernanke et al, 1999) and single-digit levels in low-income countries (Fischer 1993, Ghosh and Philips 1998).

6

Further, “lite” inflation targeting regimes employ less market oriented monetary targets and instruments are relatively nontransparent in the operation and objectives of monetary policy owing to shallow financial markets.

7

The product market as modelled in this paper is equivalent to a more realistic model with monopolistically competitive final goods firms. The approach adopted in this paper is common in the literature because it allows the model to be somewhat simplified.

8

For example, aid inflows ranging between 10 to 20 percent of GDP have been mostly spent in Mozambique (Clément and Peiris 2007), requiring a monetary policy response to maintain macroeconomic stability in the face of large aid-financed liquidity injections.

9

The estimation is carried out using the software package DYNARE (Juillard, 2004) which utilizes Chris Sims’ CSMINWEL routine for to maximize the likelihood of the model and the Metropolis-Hasting algorithm with two separate chains of 100000 draws each so as to eliminate the importance of the steady-state.

10

It is well known (see inter alia Schmitt-Grohe and Uribe (2004) and Saxegaard (2006b)) that up to a first-order approximation, monetary policy is neutral in the sense that the policy rules we consider imply the same (nonstochastic) steady-state for the economy. We therefore follow the literature in evaluating welfare using a second-order approximation to the model where the expected variability of the economy will have an effect on welfare.

11

It should be noted, however, that the costs of interest rate volatility on the real economy may be lower in low income countries compared to more developed economies due to a weak interest rate channel.

12

The similarity between CPI and nontradable inflation targeting is consistent with findings in Kollmann (2002) and Saxegaard (2006b).