05751oam 22013094 450 991096554420332120250426110721.0978661284117097814623134191462313418978145274908214527490869781451870244145187024897812828411781282841173(CKB)3170000000055071(EBL)1607942(SSID)ssj0001477988(PQKBManifestationID)11892589(PQKBTitleCode)TC0001477988(PQKBWorkID)11453221(PQKB)10440308(OCoLC)761928073(IMF)WPIEE2008166(MiAaPQ)EBC1607942(IMF)WPIEA2008166WPIEA2008166(EXLCZ)99317000000005507120020129d2008 uf 0engur|n|---|||||txtccrThe Information Content of Money in Forecasting Euro Area Inflation /Emil Stavrev, Helge Berger1st ed.Washington, D.C. :International Monetary Fund,2008.1 online resource (31 p.)IMF Working PapersIMF working paper ;WP/08/166Description based upon print version of record.9781451914771 1451914776 Includes bibliographical references.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 ModelsTables1. Out-of-Sample Forecasting Performance of Models; VI. Conclusions; References; Appendices; I. Empirical Specifications; II. Bayesian PriorsThis 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.IMF Working Papers; Working Paper ;No. 2008/166Monetary policyEconometric modelsMoneyEconometric modelsInflation (Finance)ForecastingEconometric modelsClassification MethodsimfCluster AnalysisimfComputable and Other Applied General Equilibrium ModelsimfDeflationimfDemand for MoneyimfDemand for moneyimfDynamic stochastic general equilibrium modelsimfEconometric modelsimfEconometrics & economic statisticsimfEconometricsimfEconomic ForecastingimfEconomic forecastingimfFactor ModelsimfFactor modelsimfForecasting and Other Model ApplicationsimfForecastingimfInflationimfMacroeconomicsimfMonetary economicsimfMoney and Monetary PolicyimfMoneyimfPrice LevelimfPricesimfPrincipal ComponentsimfNew ZealandimfMonetary policyEconometric models.MoneyEconometric models.Inflation (Finance)ForecastingEconometric models.Classification MethodsCluster AnalysisComputable and Other Applied General Equilibrium ModelsDeflationDemand for MoneyDemand for moneyDynamic stochastic general equilibrium modelsEconometric modelsEconometrics & economic statisticsEconometricsEconomic ForecastingEconomic forecastingFactor ModelsFactor modelsForecasting and Other Model ApplicationsForecastingInflationMacroeconomicsMonetary economicsMoney and Monetary PolicyMoneyPrice LevelPricesPrincipal Components332.46Stavrev Emil1815673Berger Helge1803593DcWaIMFBOOK9910965544203321The Information Content of Money in Forecasting Euro Area Inflation4371784UNINA