Content Horizons For Forecasts Of Economic Time Series
AbstractWe consider the problem of determining the horizon beyond which forecasts from time series models of stationary processes add nothing to the forecast implicit in the conditional mean. We refer to this as the content horizon for forecasts, and define a forecast content function at horizons s = 1,... S as the proportionate reduction in mean squared forecast error available from a time series forecast relative to the unconditional mean. This function depends upon parameter estimation uncertainty as well as on autocorrelation structure of the process under investigation. We give an approximate expression (to o(1/T)) for the forecast content function at s for a general autoregressive process, and show by simulation that the expression gives a good approximation even at modest sample sizes. Finally we consider parametric and non-parametric (kernel) estimators of the empirical forecast content function, and apply the results to forecast horizons for inflation and the growth rate of GDP, in U.S. and Canadian data.
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Bibliographic InfoPaper provided by McGill University, Department of Economics in its series Departmental Working Papers with number 1999-01.
Length: 21 pages
Date of creation: Apr 1999
Date of revision:
Other versions of this item:
- John Galbraith, 1999. "Content Horizons for Forecasts of Economic Time Series," CIRANO Working Papers 99s-17, CIRANO.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
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.:
- Hardle, W., 1992.
"Applied Nonparametric Methods,"
9204, Catholique de Louvain - Institut de statistique.
- Hardle, W., 1992. "Applied Nonparametric Methods," Discussion Paper 1992-6, Tilburg University, Center for Economic Research.
- Hardle, W., 1992. "Applied Nonparametric Methods," Papers 9206, Tilburg - Center for Economic Research.
- HÄRDLE, Wolfgang, 1992. "Applied nonparametric methods," CORE Discussion Papers 1992003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Wolfgang Hardle & Oliver Linton, 1994. "Applied Nonparametric Methods," Cowles Foundation Discussion Papers 1069, Cowles Foundation for Research in Economics, Yale University.
- 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.
- Francis X. Diebold & Lutz Kilian, 1997. "Measuring predictability: theory and macroeconomic applications," Working Papers 97-23, Federal Reserve Bank of Philadelphia.
- 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, 1998. "Measuring Predictability: Theory and Macroeconomic Applications," Working Papers 98-16, New York University, Leonard N. Stern School of Business, Department of Economics.
- Francis X. Diebold & Lutz Kilian, 1997. "Measuring Predictability: Theory and Macroeconomic Applications," NBER Technical Working Papers 0213, National Bureau of Economic Research, Inc.
- Neil R. Ericsson & Jaime Marquez, 1998.
"A framework for economic forecasting,"
Royal Economic Society, vol. 1(Conferenc), pages C228-C266.
- Eric Ghysels & Denise R. Osborn & Paulo M. M. Rodrigues, 1999. "Seasonal Nonstationarity and Near-Nonstationarity," CIRANO Working Papers 99s-05, CIRANO.
- Marcel Boyer, 1999. "Les Expos, l'OSM, les universités, les hôpitaux : Le coût d'un déficit de 400 000 emplois au Québec = Expos, Montreal Symphony Orchestra, Universities, Hospitals: The Cost of a 400,000-Job Shortf," CIRANO Papers 99c-01, CIRANO.
- James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc.
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