Ranking the importance of quality variables for the price of high quality beech timber (Fagus sylvatica L.)

Based on the linear regression method this paper uses two econometric models to explain timber prices achieved for high quality beech timber ( Fagus sylvatica L.). The modelling starts with the assumption that among other variables, the buyers' preference determines the level of the demand curve and therefore the price paid for specific goods of a given quantity. In a first step the buyers' preference was used as the central independent variable in an econometric model ("Price-preference-model"). The variable was derived through 4 026 written buyers' bids for 980 high quality beech logs offered by the Bavarian State Forest Service in autumn 2001. The logs represented a total quantity of 2 032 cubic meters ( m(3)). The number of bids for a specific timber log multiplied by its volume served as a proxy for the buyers' preferences, while indicating the potentially marketable amount of timber for a particular log. As a covariate the quantity of timber offered of a particular type, defined by timber diameter, length and quality grade was employed. Both variables, the buyers' preference and the timber quantity, accounted for 67% of the variation of the timber prices ( RMSE +/- 38.4 Euro/m(3)). The buyers' preference absolutely dominated the model, alone accounting for 66% of the variation. The subsequently derived second econometric model ("Preference-quality-model") was utilised to explain the buyers' preference by means of relevant log size and quality variables. Among the set of independent quality variables, only the "red heartwood", the "stem curvature", the "spiral grain", the "growth stresses" and the "roughness of the bark" contributed significantly to explain the buyers' preference. The "Preference-quality-model" was able to explain 58% of the variation of the actual buyers' preferences observed. Both models, the "Price-preference-model" and the "Preference-quality-model" were eventually combined in order to rank the timber quality variables according to their importance regarding the timber price. When combining both models an overall r(2) of 0.66 was achieved. Tests with independent data were successful. The ranking showed that the "red heartwood" is the most important timber quality variable, followed by "spiral grain", "stem curvature", "roughness of the bark" and "growth stresses". Moreover, an analysis of separate "Price-preference-models" and "Preference-quality-models" revealed clear differences between European and Asian buyers. While the Asian buyers were more interested in large logs (in terms of the diameter), the European buyers were more differentiated in their preferences with regard to the timber quality. If the "red heartwood" already covered 30% of the stem's diameter, for example, it was not important for to Asian buyers, whether the red heartwood comprised of more or less than 50%. "Growth stresses" and "Signs of old felling damage" played no quantifiable role in the "Preference-quality-model, Asia" while they did in the "Preference-quality-model, Europe". Where the "Roughness of the bark" was important for the Asian buyers, it was not relevant for the European market. Whereas the European buyers would prefer to buy stems with "red heartwood" comprising of less than 30% of the stem's diameter, the Asian buyers would accept a higher amount of " red heartwood".