Forecasting Germany's Printing and Writing Paper Imports

Abstract

Abstract Short-term forecasting of forest products demand is one of the key inputs for successful market planning in the forest sector. Currently, this field is dominated by consultants' and industry analysts' forecasts, which are often based on methods and procedures that are not well documented, or are ad hoc. This article seeks to contribute to the scarce literature on this topic by presenting results for short-term forecasts for the import demand for coated printing and writing paper in Germany. A number of univariate time series models, single equation econometric models, and multivariate systems models are estimated using quarterly data from 1991:Q1–2001:Q2, and observations from 2001:Q3–2002:Q4 are used for the out-of-sample forecast performance evaluation. Forecasts are also computed using various weighted combinations of the individual forecasting models. The results indicate that forecast accuracy increases when one moves from univariate time series models to econometric models. The best single forecasting model in terms of the root-mean-squared error criterion is a VARX model in differences. However, by optimally combining individual model forecasts, one is able to produce even more accurate forecasts. FOR. SCI. 51(5):483–497.