Sampling Distributions of Post‐Sample Forecasting Errors

Spyros Makridakis and Robert L. Winkler

Journal of the Royal Statistical Society Series C, 1989, vol. 38, issue 2, 331-342

Abstract: Forecasting errors fall in two clearly different categories: (a) the residual errors from fitting a model to the available data and (b) the post‐sample forecasting errors. The emphasis of statistical theory and forecasting methodology has been on model fitting errors, even though the greatest concern in applied work should be with post‐sample errors. The purpose of this paper is to investigate empirically sampling distributions of post‐sample forecasting errors. The characteristics of such distributions are studied and compared with characteristics of distributions of model fitting errors. The discrepancies between characteristics of model fitting and post‐sample errors are quite large and somewhat variable.

Date: 1989
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