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  • 1
    Online Resource
    Online Resource
    [Washington, District of Columbia] :International Monetary Fund,
    UID:
    edoccha_9958124720302883
    Format: 1 online resource (31 p.)
    Edition: 1st ed.
    ISBN: 1-4623-1341-8 , 1-4527-4908-6 , 1-4518-7024-8 , 1-282-84117-3 , 9786612841170
    Series Statement: IMF working paper ;
    Content: This paper contributes to the debate on the role of money in monetary policy by analyzing the information content of money in forecasting euro-area inflation. We compare the predictive performance within and among various classes of structural and empirical models in a consistent framework using Bayesian and other estimation techniques. We find that money contains relevant information for inflation in some model classes. Money-based New Keynesian DSGE models and VARs incorporating money perform better than their cashless counterparts. But there are also indications that the contribution of money has its limits. The marginal contribution of money to forecasting accuracy is often small, money adds little to dynamic factor models, and it worsens forecasting accuracy of partial equilibrium models. Finally, non-monetary models dominate monetary models in an all-out horserace.
    Note: Description based upon print version of record. , Contents; I. Introduction; II. Related Literature; III. Models of Inflation; A. DSGE Models; B. Partial Equilibrium Models; C. Empirical Models; IV. Empirical Methods and Data; A. Estimation Techniques; B. Prior Distribution of Parameters for the Bayesian Estimates; C. Forecasting and the Information Content of Money; D. Data; V. Results; A. The Marginal Contribution of Money; Figures; 1. Forecast Performance of DSGE Models; 2. Forecast Performance of Empirical Models; 3. Forecast Performance of P* and Phillips Curve Models; B. Comparison of Money-Based Models; C. Comparison Across All Models , Tables1. Out-of-Sample Forecasting Performance of Models; VI. Conclusions; References; Appendices; I. Empirical Specifications; II. Bayesian Priors , English
    Additional Edition: ISBN 1-4519-1477-6
    Language: English
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