The Reliability of Inflation Forecasts Bases on Output Gap Estimates in Real Time PDF Download
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Author: Athanasios Orphanides
Publisher:
ISBN:
Category :
Languages : en
Pages : 49
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Book Description
Author: Athanasios Orphanides
Publisher:
ISBN:
Category :
Languages : en
Pages : 49
Get Book Here
Book Description
Author: Athanasios Orphanides
Publisher:
ISBN:
Category : Inflation (Finance)
Languages : en
Pages : 52
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Book Description
"A stable predictive relationship between inflation and the output gap, often referred to as a Phillips curve, provides the basis for countercyclical monetary policy in many models. In this paper, we evaluate the usefulness of alternative univariate and multivariate estimates of the output gap for predicting inflation. Many of the ex post output gap measures we examine appear to be quite useful for predicting inflation. However, forecasts using real-time estimates of the same measures do not perform nearly as well. The relative usefulness of real-time output gap estimates diminishes further when compared to simple bivariate forecasting models which use past inflation and output growth. Forecast performance also appears to be unstable over time, with models often performing differently over periods of high and low inflation. These results call into question the practical usefulness of the output gap concept for forecasting inflation"--Abstract.
Author: Orphanides, Athanasios
Publisher: Montréal : CIRANO
ISBN:
Category :
Languages : en
Pages : 49
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Author: Athanasios Orphanides
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Mr.Jens R. Clausen
Publisher: International Monetary Fund
ISBN: 1451963386
Category : Business & Economics
Languages : en
Pages : 23
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Book Description
This paper simulates out-of-sample inflation forecasting for Germany, the UK, and the US. In contrast to other studies, we use output gaps estimated with unrevised real-time GDP data. This exercise assumes an information set similar to that available to a policymaker at a given point in time since GDP data is subject to sometimes substantial revisions. In addition to using real-time datasets for the UK and the US, we employ a dataset for real-time German GDP data not used before. We find that Phillips curves based on ex post output gaps generally improve the accuracy of inflation forecasts compared to an AR(1) forecast but that real-time output gaps often do not help forecasting inflation. This raises the question how operationally useful certain output gap estimates are for forecasting inflation.
Author: Pierre Guérin
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Josefine Quast
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Mr. Jens R. Clausen
Publisher: INTERNATIONAL MONETARY FUND
ISBN: 9781451990133
Category : Business & Economics
Languages : en
Pages : 21
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Book Description
This paper simulates out-of-sample inflation forecasting for Germany, the UK, and the US. In contrast to other studies, we use output gaps estimated with unrevised real-time GDP data. This exercise assumes an information set similar to that available to a policymaker at a given point in time since GDP data is subject to sometimes substantial revisions. In addition to using real-time datasets for the UK and the US, we employ a dataset for real-time German GDP data not used before. We find that Phillips curves based on ex post output gaps generally improve the accuracy of inflation forecasts compared to an AR(1) forecast but that real-time output gaps often do not help forecasting inflation. This raises the question how operationally useful certain output gap estimates are for forecasting inflation.
Author: Todd E. Clark
Publisher:
ISBN:
Category : Economic forecasting
Languages : en
Pages : 102
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Book Description
Small-scale VARs have come to be widely used in macroeconomics, for purposes ranging from forecasting output, prices, and interest rates to modeling expectations formation in theoretical models. However, a body of recent work suggests such VAR models may be prone to instabilities. In the face of such instabilities, a variety of estimation or forecasting methods might be used to improve the accuracy of forecasts from a VAR. These methods include using different approaches to lag selection, observation windows for estimation, (over-) differencing, intercept correction, stochastically time--varying parameters, break dating, discounted least squares, Bayesian shrinkage, detrending of inflation and interest rates, and model averaging. Focusing on simple models of U.S. output, prices, and interest rates, this paper compares the effectiveness of such methods. Our goal is to identify those approaches that, in real time, yield the most accurate forecasts of these variables. We use forecasts from simple univariate time series models, the Survey of Professional Forecasters and the Federal Reserve Board's Greenbook as benchmarks
