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Multi-step forecasting in emerging economies: An investigation of the South African GDP

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  • Chevillon, Guillaume

Abstract

To forecast at several, say h, periods into the future, a modeller faces a choice between iterating one-step-ahead forecasts (the IMS technique), or directly modeling the relationship between observations separated by an h-period interval and using it for forecasting (DMS forecasting). It is known that structural breaks, unit-root non-stationarity and residual autocorrelation may improve DMS accuracy in finite samples, all of which occur when modelling the South African GDP over the period 1965-2000. This paper analyzes the forecasting properties of 779 multivariate and univariate models that combine different techniques of robust forecasting. We find strong evidence supporting the use of DMS and intercept correction, and attribute their superior forecasting performance to their robustness in the presence of breaks.

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Bibliographic Info

Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 25 (2009)
Issue (Month): 3 (July)
Pages: 602-628

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Handle: RePEc:eee:intfor:v:25:y:2009:i:3:p:602-628

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Web page: http://www.elsevier.com/locate/ijforecast

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Keywords: Multi-step forecasting Intercept correction Structural breaks;

References

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Cited by:
  1. Guillaume Chevillon, 2007. "Direct Multi-Step Estimation And Forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 746-785, 09.
  2. Lorenzo Pascual & Esther Ruiz & Diego Fresoli, 2011. "Bootstrap forecast of multivariate VAR models without using the backward representation," Statistics and Econometrics Working Papers ws113426, Universidad Carlos III, Departamento de Estadística y Econometría.

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