Time Series Analysis for Short-Term Forest Sector Market Forecasting

Among the various functions of the forest its special significance as a source of raw materials for the timber industry can be emphasized. Wood is an environmentally friendly and a renewable resource. By the growing and simultaneously competing use of the natural resource wood, its commercial role becomes increasingly important. To bring economic potentials into conformity with social and environmental requirements for the performance of the ecosystem forest, wise management of the use of the natural product wood is necessary, also with respect to a successful, sustainable-oriented and bio-based economy. Reliable predictions about possible short-term changes in the timber market are scarce although they play a key role in supporting decision making. Forecasts help to recognize and minimize risks in the supply chain management e.g. initiating the adjustment of timber harvesting to fast changing market conditions. In this context, the relevance of the statistical technique of time series methods in forest sector research is highlighted in this paper. The main purpose of this research method is to extract important information out of the time series itself as well as possible causal relationships between the time series and to use this information to identify future economic developments. The fact that time series methods provide strong results combined with only modest data requirements underlines their unique usefulness for the analysis of forest economic issues. To some extent, they can serve as an alternative for the often very complex models of the forest sector. Therefore, this work aims at sensitizing to the advantages of time series for forest sector short-term modelling. Based on this, a breeding ground is provided for progressive research in the forest sector through the application of time series analysis.