Quantifying the consequences of disturbances on wood revenues with Impulse Response Functions

Abstract

Forest disturbances in Europe are very likely to increase in frequency and intensity. Assessing their economic consequences is required to identify feasible adaptation strategies. Such economic calculations depend on estimates for the reduction in revenues after disturbance events. These losses can be caused by both a lower wood quality as well as an oversupply on the wood markets. Despite its importance, data-driven approaches to quantify the consequences of disturbances on wood revenues in Central Europe are rare. We applied econometric time series analysis with Structural Vector Autoregressive (SVAR) models to harvest and sales data from Hesse, Germany. Additionally, we derived estimates for reductions in wood revenues for integration in bioeconomic simulation models. Our analyses indicate that the observed losses in wood revenues for spruce after disturbances are mainly due to an oversupply on the wood markets, rather than a loss in wood quality. In addition, the results suggest that calamities of transregional extent or multiple disturbances in subsequent years are likely to reduce wood revenues beyond the assumptions often used in bioeconomic simulation models. Although our results for beech were more ambiguous, they indicate that losses in revenues for beech after disturbances in the past were mainly due to a reduced wood quality. Our study highlights the importance of taking a differentiated view on the consequences of disturbances on wood revenues, considering their spatial extent and species-specific mechanisms.