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Oya Celasun, Jungjin Lee, Mr. Mico Mrkaic, and Mr. Allan Timmermann

forecast error (RMSE). A measure of “absolute” forecast accuracy, the RMSE indicates by how many units (e.g., percentage points of GDP growth) the forecast differed from the outcome on average over the sample period. It is given by the square root of the average squared error. For a sample [ t 0 : t 1 ] and a forecast horizon of h , the RMSE for country i is computed as: R M S E i , h = ( t 1 − t 0 + 1 ) − 1 ∑ t = t 0 t 1 e i t | t − h . 2 ( 2 ) Figure 1 displays the inter-quartile ranges, medians, and GDP-weighted means of the RMSE values for each of the

International Monetary Fund

Front Matter Page Research Department Table of Contents Summary I. Introduction II. Instruments, Indicators, Targets, and Goals III. Nominal Income and Price Level Targets IV. The Role of Indicator Variables V. An Alternative Instrument VI. Concluding Remarks Appendix Tables 1. RMSE Values for Nominal Income Target Simulation Results, 1954.1-1985.4 2. RMSE Values for Price Level Target Simulation Results, 1954.1-1985.4 3. RMSE Values for Price Level Target Simulation Results, 1954.1-1985.4 4. RMSE Values for Real GNP

International Monetary Fund
This paper seeks to advance the discussion of monetary policy strategies in several ways. One involves a comparison of targets for nominal GNP and the price level, with emphasis on specificational robustness and implications for output variability. A second pertains to various “indicator” variables recently suggested by Federal Reserve officials. In this regard, a careful review of the relevant conceptual distinctions--concerning instruments, targets, indicators, etc.--is required. Finally, the proposal that strategy should be conducted so as to place minimal reliance on quantity variables is given attention, in the context of evidence concerning the merits of an interest rate instrument.
Oya Celasun, Jungjin Lee, Mr. Mico Mrkaic, and Mr. Allan Timmermann
This paper examines the performance of World Economic Outlook (WEO) growth forecasts for 2004-17. Short-term real GDP growth forecasts over that period exhibit little bias, and their accuracy is broadly similar to those of Consensus Economics forecasts. By contrast, two- to five-year ahead WEO growth forecasts in 2004-17 tend to be upward biased, and in up to half of countries less accurate than a naïve forecast given by the average growth rate in the recent past. The analysis suggests that a more efficient use of available information on internal and external factors—such as the estimated output gap, projected terms of trade, and the growth forecasts of major trading partners—can improve the accuracy of some economies’ growth forecasts.
International Monetary Fund. Monetary and Capital Markets Department
The currency in circulation forecasting model presently used by the Central Bank of Jordan is aligned with international practices and provides a solid basis for liquidity management. The central bank uses an Auto Regressive Integrated Moving Average (ARIMA) model with many indicator variables to model binary seasonality and to capture special events. The ARIMA model is fitted on daily currency in circulation data using a standard maximum likelihood estimator. This ARIMA approach is aligned with the models traditionally used by central banks in emerging and middle-income countries.
Mr. Aasim M. Husain and Chakriya Bowman
This paper assesses the performance of three types of commodity price forecasts—those based on judgment, those relying exclusively on historical price data, and those incorporating prices implied by commodity futures. For most of the 15 commodities in the sample, spot and futures prices appear to be nonstationary and to form a cointegrating relation. Spot prices tend to move toward futures prices over the long run, and error-correction models exploiting this feature produce more accurate forecasts. The analysis indicates that on the basis of statistical- and directional-accuracy measures, futures-based models yield better forecasts than historical-data-based models or judgment, especially at longer horizons.
Mr. Paul R Masson and Mr. Steven A. Symansky
Evaluations of European monetary integration using model simulations have given conflicting results, and the paper attempts to elucidate the reasons for the differences. Several features stand out: how to model realignments; how monetary policy is set for individual countries or for Europe; and how large are risk premium shocks in exchange markets. We quantify the effects of different assumptions relating to these features using MULTIMOD.
International Monetary Fund. Monetary and Capital Markets Department
The new Dirham Monetary Framework developed by the Central Bank of the United Arab Emirates (CBUAE) operationalizes a floor system and provides a complete set of instruments to manage liquidity under a fixed exchange rate arrangement and capital mobility. This technical assistance report presents an overview of this operational framework and a set of recommendations to streamline and further improve it especially with regards to: (i) the discontinuation of the FX swap facility; (ii) the issuance of central bank bills; (iii) the design of fine-tuning operations; and (iv) the design and calibration of the reserves requirements. Moreover, the report provides a complete liquidity forecasting infrastructure, using cutting-edge statistical methods, to project the changes in the supply of banks reserves through the forecast of the three main autonomous factors. It also offers a statistical approach to estimate the optimal liquidity surplus and calibrate the operational mix between the different liquidity absorptions instruments. At last, the report investigates the functioning and structure of the UAE money markets.
Mr. Steven T Phillips, Mr. Luis Catão, Mr. Luca A Ricci, Mr. Rudolfs Bems, Ms. Mitali Das, Mr. Julian Di Giovanni, Ms. Filiz D Unsal, Marola Castillo, Jungjin Lee, Jair Rodriguez, and Mr. Mauricio Vargas
The External Balance Assessment (EBA) methodology has been developed by the IMF’s Research Department as a successor to the CGER methodology for assessing current accounts and exchange rates in a multilaterally consistent manner. Compared to other approaches, EBA emphasizes distinguishing between the positive empirical analysis and the normative assessment of current accounts and exchange rates, and highlights the roles of policies and policy distortions. This paper provides a comprehensive description and discussion of the 2013 version (“2.0”) of the EBA methodology, including areas for its further development.
International Monetary Fund

x * t are logarithms, these RMSE values can be interpreted as percentage deviations, with (e.g.) 0.02 corresponding to 2.0 percent. From the reported figures it can be seen that the rule (1) performs satisfactorily for intermediate values of A, that is, values between 0.1 and 0.25. Despite the variety of models, x t values are kept close to the x t target path, thereby implying inflation rates close to zero for the period. Targeting errors are smaller than with λ = 0 in all cases, and with the VAR model they are much smaller than when λ = 0.5. This last