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International Monetary Fund. Monetary and Capital Markets Department
The purpose of the mission was to improve the understanding of the conduct of monetary policy in an inflation targeting (IT) central bank. During the September visit, the mission provided capacity building through daily morning seminars, giving an introduction to modern theory of monetary policy in small-open economies, and by performing monetary policy analyses based on BM’s quarterly projection model (QPM) in the afternoons.
Mokhtar Benlamine, Mr. Ales Bulir, Meryem Farouki, Ágnes Horváth, Faical Hossaini, Hasnae El Idrissi, Zineb Iraoui, Mihály Kovács, Mr. Douglas Laxton, Anass Maaroufi, Katalin Szilágyi, Mohamed Taamouti, and David Vávra

Front Matter Page Research Department Contents Abstract I. Introduction II. Morocco: Monetary Independence Under a Peg and Capital Controls III. Morocco: Main Features A. Capital controls and other regulations B. The fixed exchange rate regime and monetary policy C. Structure of the economy IV. The Moroccan Quarterly Projection Model (MQPM) A. A model for transition B. Special Features of the Moroccan QPM Model C. Selected Impulse Response Functions V. Conclusions and the Policy Uses of the QPM in Morocco References

International Monetary Fund. Monetary and Capital Markets Department

developments in Mozambique if the standard deviations are not estimated properly. 13. It appears that the QPM implies a constant nominal exchange rate in the long run. The version of the QPM model used by DEE, was developed for a policy regime that can be characterized as a hybrid regime—partly exchange rate targeting and partly inflation targeting. A property of this version of the model is that the nominal exchange rate is automatically reverting to the (implicit/explicit) exchange rate target in the long run. This also implies that the domestic price-level is mean

International Monetary Fund. Asia and Pacific Dept

(CIT)” scenario examines the benefits of a comprehensive transition to IT. Third, by using these two alternative model specifications we conduct counterfactual simulations of the policy response to the exchange rate devaluation of 2011 — to demonstrate potential macroeconomic benefits of a comprehensive IT framework during the times of crisis. 3 B. A QPM for Bangladesh 5. To facilitate monetary policy analysis and examine the tradeoffs between different monetary policy regimes, we developed a semi-structural QPM model that reflects closely the structure of

International Monetary Fund. Monetary and Capital Markets Department

BM in making improvements in the QPM model and the forecasting process. Table 1. Key Recommendations Recommendations and Authority Responsible for Implementation Priority Timeframe 1 DEE arrange seminars for MPC on; (i) the reforming of the monetary policy f ramework into a system closer to IT; and (ii) the merits of the modeling system to support interest rate decisions. High Near-term Revise the modeling of the exchange rate in QPM High Near-term Actively use tools introduced by the July and September missions

International Monetary Fund. Western Hemisphere Dept.

monetary policy rate and r ¯ t is the neutral (nominal) interest rate. Finally, the error term in each equation, ε t , is a linear combination of forecast errors and an exogenous disturbance (by assumption, this error term is orthogonal to the set of instruments). 8. The QPM model gives a neutral interest rate of 4.4 percent . The model consist of four basic behavioral equations—for aggregate demand (IS curve), (short term) aggregate supply (Phillips curve), the UIP condition, and a Monetary Policy rule—and several identities. The aggregate demand equation includes

Mokhtar Benlamine, Mr. Ales Bulir, Meryem Farouki, Ágnes Horváth, Faical Hossaini, Hasnae El Idrissi, Zineb Iraoui, Mihály Kovács, Mr. Douglas Laxton, Anass Maaroufi, Katalin Szilágyi, Mohamed Taamouti, and David Vávra
The Central Bank of Morocco has been working on developing a Forecasting and Policy Analysis System (FPAS) to support a gradual move toward a more flexible exchange rate regime and the eventual adoption of a full-fledged inflation-targeting (IT) regime. At the center of the FPAS is a quarterly projection model that was tailored for two different types of exchange rate regimes. Presently, the fixed exchange rate model version is to be used during the pre-IT period, while the flexible exchange rate model version is to be used to prepare alternative scenarios for monetary policy decision makers to discuss the potential policy implications of shocks under an IT regime.
Nils Mæhle, Tibor Hlédik, Mikhail Pranovich, Carina Selander, and Mikhail Pranovich

MT is formed and tasked to develop and maintain semistructural QPM model. October 2016 MT is trained in using the software for macroeconomic modeling and forecasting, and the first version of the QPM and adjacent codes infrastructure is developed. end-2016 MT staff is trained in operating the model codes infrastructure and in using the QPM to produce baseline projections, conditioning on available information (domestic and foreign sector data, NTF), and expert judgment. April 2017 MT is trained in conducting scenario analysis and in

Mr. Douglas Laxton, Mr. Andrew Berg, and Mr. Philippe D Karam

exchange rate. These two parameters combined with a large values on the lagged gap term ( β lag = 0.85) and a small value on the lead of the output gap ( β lead = 0.10) result in hump-shaped dynamics in response to monetary induced interest rate shocks that do a satisfactory job replicating what is found in the Bank of Canada’s QPM model of the Canadian economy. To explain the strong correlation between the U.S. and the Canadian output gaps, we employ a fairly large parameter on the U.S. output gap in the Canadian output gap ( β USygap = 0.25). For the United States

Mr. Douglas Laxton, Mr. Andrew Berg, and Mr. Philippe D Karam
This paper provides a how-to guide to model-based forecasting and monetary policy analysis. It describes a simple structural model, along the lines of those in use in a number of central banks. This workhorse model consists of an aggregate demand (or IS) curve, a price-setting (or Phillips) curve, a version of the uncovered interest parity condition, and a monetary policy reaction function. The paper discusses how to parameterize the model and use it for forecasting and policy analysis, illustrating with an application to Canada. It also introduces a set of useful software tools for conducting a model-consistent forecast.