Forecast Content And Content Horizons For Some Important Macroeconomic Time Series
AbstractFor quantities that are approximately stationary, the information content of statistical forecasts tends to decline as the forecast horizon increases, and there exists a maximum horizon beyond which forecasts cannot provide discernibly more information about the variable than is present in the unconditional mean (the content horizon). The pattern of decay of forecast content (or skill) with increasing horizon is well known for many types of meteorological forecasts; by contrast, little generally-accepted information about these patterns or content horizons is available for economic variables. In this paper we attempt to develop more information of this type by estimating content horizons for variety of macroeconomic quantities; more generally, we characterize the pattern of decay of forecast content as we project farther into the future. We find wide variety of results for the different macroeconomic quantities, with models for some quantities providing useful content several years into the future, for other quantities providing negligible content beyond one or two months or quarters.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by McGill University, Department of Economics in its series Departmental Working Papers with number 2007-01.
Length: 20 pages
Date of creation: 2007
Date of revision:
Other versions of this item:
- John W. Galbraith & Greg Tkacz, 2007. "Forecast content and content horizons for some important macroeconomic time series," Canadian Journal of Economics, Canadian Economics Association, vol. 40(3), pages 935-953, August.
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-04-21 (All new papers)
- NEP-ETS-2007-04-21 (Econometric Time Series)
- NEP-FOR-2007-04-21 (Forecasting)
- NEP-MAC-2007-04-21 (Macroeconomics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Francis X. Diebold & Lutz Kilian, 1997.
"Measuring Predictability: Theory and Macroeconomic Applications,"
NBER Technical Working Papers
0213, National Bureau of Economic Research, Inc.
- Francis X. Diebold & Lutz Kilian, 2001. "Measuring predictability: theory and macroeconomic applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(6), pages 657-669.
- Diebold, Francis X & Kilian, Lutz, 2000. "Measuring Predictability: Theory And Macroeconomic Applications," CEPR Discussion Papers 2424, C.E.P.R. Discussion Papers.
- Francis X. Diebold & Lutz Kilian, 1997. "Measuring predictability: theory and macroeconomic applications," Working Papers 97-23, Federal Reserve Bank of Philadelphia.
- Francis X. Diebold & Lutz Kilian, 1998. "Measuring Predictability: Theory and Macroeconomic Applications," Working Papers 98-16, New York University, Leonard N. Stern School of Business, Department of Economics.
- Marc Brisson & Bryan Campbell & John Galbraith, 2001. "Forecasting Some Low-Predictability Time Series Using Diffusion Indices," CIRANO Working Papers 2001s-46, CIRANO.
- Granger, Clive W. J. & Hyung, Namwon, 2004. "Occasional structural breaks and long memory with an application to the S&P 500 absolute stock returns," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 399-421, June.
- Galbraith, John W. & KI[#x1e63]Inbay, Turgut, 2005. "Content horizons for conditional variance forecasts," International Journal of Forecasting, Elsevier, vol. 21(2), pages 249-260.
- Granger, Clive W J, 1996. "Can We Improve the Perceived Quality of Economic Forecasts?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 455-73, Sept.-Oct.
- Li Fuchun & Tkacz Greg, 2004. "Combining Forecasts with Nonparametric Kernel Regressions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(4), pages 1-18, December.
- Kajal Lahiri & Xuguang Sheng, 2009.
"Learning and Heterogeneity in GDP and Inflation Forecasts,"
09-05, University at Albany, SUNY, Department of Economics.
- Lahiri, Kajal & Sheng, Xuguang, 2010. "Learning and heterogeneity in GDP and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 26(2), pages 265-292, April.
- Lahiri, Kajal & Sheng, Xuguang, 2009. "Learning and heterogeneity in GDP and inflation forecasts," MPRA Paper 21448, University Library of Munich, Germany.
- John Galbraith & Simon van Norden, 2008.
"The Calibration Of Probabilistic Economic Forecasts,"
Departmental Working Papers
2008-05, McGill University, Department of Economics.
- John Galbraith & Simon van Norden, 2008. "The Calibration of Probabilistic Economic Forecasts," CIRANO Working Papers 2008s-28, CIRANO.
- Bruijn, B. de & Franses, Ph.H.B.F., 2011. "Evaluating the Rationality of Managers' Sales Forecasts," Econometric Institute Report EI 2011-36, Erasmus University Rotterdam, Econometric Institute.
- John Galbraith & Simon van Norden, 2009. "Calibration and Resolution Diagnostics for Bank of England Density Forecasts," CIRANO Working Papers 2009s-36, CIRANO.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Shama Rangwala) The email address of this maintainer does not seem to be valid anymore. Please ask Shama Rangwala to update the entry or send us the correct address.
If references are entirely missing, you can add them using this form.