Some forecasting principles from the M4 competition

Jennifer Castle, Jurgen Doornik and David Hendry

No 2019-W01, Economics Papers from Economics Group, Nuffield College, University of Oxford

Abstract: Economic forecasting is difficult, largely because of the many sources of nonstationarity. The M4 competition aims to improve the practice of economic forecasting by providing a large data set on which the efficacy of forecasting methods can be evaluated. We consider the general principles that seem to be the foundation for successful forecasting, and show how these are relevant for methods that do well in M4. We establish some general properties of the M4 data set, which we use to improve the basic benchmark methods, as well as the Card method that we created for our submission to the M4 competition. A data generation process is proposed that captures the salient features of the annual data in M4.

Keywords: Automatic forecasting; Calibration; Prediction intervals; Regression; M4; Seasonality; Software; Time series; Unit roots (search for similar items in EconPapers)
Pages: 27 pages
Date: 2019-01-09
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:nuf:econwp:1901

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