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Evaluating multi-step system forecasts with relatively few forecast-error observations

Listed author(s):
  • Hendry, David F.
  • Martinez, Andrew B.

This paper develops a new approach for evaluating multi-step system forecasts with relatively few forecast-error observations. It extends the work of Clements and Hendry (1993) by using that of Abadir et al. (2014) to generate “design-free” estimates of the general matrix of the forecast-error second-moment when there are relatively few forecast-error observations. Simulations show that the usefulness of alternative methods deteriorates when their assumptions are violated. The new approach compares well with these methods and provides correct forecast rankings.

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File URL: http://www.sciencedirect.com/science/article/pii/S0169207016300991
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Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 33 (2017)
Issue (Month): 2 ()
Pages: 359-372

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Handle: RePEc:eee:intfor:v:33:y:2017:i:2:p:359-372
DOI: 10.1016/j.ijforecast.2016.08.007
Contact details of provider: Web page: http://www.elsevier.com/locate/ijforecast

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  1. Athanasopoulos, George & de Carvalho Guillén, Osmani Teixeira & Issler, João Victor & Vahid, Farshid, 2011. "Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions," Journal of Econometrics, Elsevier, vol. 164(1), pages 116-129, September.
  2. De Gooijer, Jan G. & Vidiella-i-Anguera, Antoni, 2004. "Forecasting threshold cointegrated systems," International Journal of Forecasting, Elsevier, vol. 20(2), pages 237-253.
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  22. Hoffman, Dennis L & Rasche, Robert H, 1996. "Assessing Forecast Performance in a Cointegrated System," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 495-517, Sept.-Oct.
  23. Paap, Richard & Franses, Philip Hans & Hoek, Henk, 1997. "Mean shifts, unit roots and forecasting seasonal time series," International Journal of Forecasting, Elsevier, vol. 13(3), pages 357-368, September.
  24. Vahid, Farshid & Issler, Joao Victor, 2002. "The importance of common cyclical features in VAR analysis: a Monte-Carlo study," Journal of Econometrics, Elsevier, vol. 109(2), pages 341-363, August.
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