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Small Sample Properties of Forecasts From Autoregressive Models Under Structural Breaks

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Author Info
Pesaran, M Hashem
Timmermann, Allan G

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Abstract

This Paper develops a theoretical framework for the analysis of small sample properties of forecasts from general autoregressive models under structural breaks. Finite-sample results for the mean-squared forecast error of one-step-ahead forecasts are derived, both conditionally and unconditionally, and numerical results for different types of break specifications are presented. It is established that forecast errors are unconditionally unbiased even in the presence of breaks in the autoregressive coefficients and/or error variances so long as the unconditional mean of the process remains unchanged. Insights from the theoretical analysis are demonstrated in Monte Carlo simulations and on a range of macroeconomic time series from G7 countries. The results are used to draw practical recommendations for the choice of estimation window when forecasting from autoregressive models subject to breaks.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 4401.

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Date of creation: Jun 2004
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Handle: RePEc:cpr:ceprdp:4401

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Related research
Keywords: autoregression; msfe; rolling window estimator; small sample properties of forecasts; structural breaks;

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Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications

References listed on IDEAS
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Full references

Cited by:
(explanations, 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.)

  1. Guillaume Chevillon, 2006. "Multi-step Forecasting in Unstable Economies: Robustness Issues in the Presence of Location Shifts," Economics Series Working Papers 257, University of Oxford, Department of Economics. [Downloadable!]
  2. Junsoo Lee & John A. List & Mark Strazicich, 2005. "Nonrenewable Resource Prices: Deterministic or Stochastic Trends?," NBER Working Papers 11487, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  3. Pesaran, M. Hashem, 2004. "General Diagnostic Tests for Cross Section Dependence in Panels," IZA Discussion Papers 1240, Institute for the Study of Labor (IZA). [Downloadable!]
    Other versions:
  4. M. Hashem Pesaran & Andreas Pick & Allan Timmermann, 2009. "Variable Selection and Inference for Multi-period Forecasting Problems," CESifo Working Paper Series CESifo Working Paper No. , CESifo Group Munich. [Downloadable!]
    Other versions:
  5. Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2004. "‘Forecasting Time Series Subject to Multiple Structural Breaks’," Cambridge Working Papers in Economics 0433, Faculty of Economics, University of Cambridge. [Downloadable!]
    Other versions:
  6. Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2009. "Forecasting Large Datasets with Bayesian Reduced Rank Multivariate Models," Economics Working Papers ECO2009/31, European University Institute. [Downloadable!]
  7. A. Carriero & G. Kapetanios & M. Marcellino, 2008. "Forecasting Exchange Rates with a Large Bayesian VAR," Economics Working Papers ECO2008/33, European University Institute. [Downloadable!]
    Other versions:
  8. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90. [Downloadable!]
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