Analysis and modeling of timber storage accumulation after severe storm events in Germany
In this study, we explore the determinants of forest enterprises’ timber storage accumulation after severe storm events. The explanatory power of variables reflecting economic, institutional and tree species-related factors is tested via econometric analyses. Timber storage accumulation is assessed conducting a weighted multiple linear regression analysis. In addition, the moderating effect of timber price alterations on timber storage accumulation is tested employing timber price alterations as a moderator variable in a hierarchical regression analysis. The results show a linear positive relation between forest enterprises’ damaged and stored timber quantities. It was found that coniferous timber was stored to a greater extent than non-coniferous timber which can be explained by higher storm damage as well as better suitability for multiyear storage. State forestry stored the highest shares of damaged timber, followed by municipal and private forest enterprises, which can be explained as a countervailing measure. A further central finding of our study is that the timber price drops after storm events act as a moderator variable on the relation between damaged and stored timber quantities. Hence, empirical timber price reactions help to improve estimation accuracy regarding the shares of damaged timber which are stored. Derived from our results, we find timber storage accumulation to be a common practice by forest companies to mitigate revenue losses caused by extreme storm events. As coefficients vary strongly among the analyzed variables’ categories, we consider case-specific storage accumulation estimations to be crucial for improving the accuracy of national wood and timber accounting, but also for a full view on storm-related economic damage in the forest sector. In addition, it is likely that capturing the proportions of timber storage in forests will gain relevance in the future, since forest damage from natural disturbances is expected to increase as a consequence of climate change.