DIGITALNA ARHIVA ŠUMARSKOG LISTA
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ŠUMARSKI LIST 9-10/2018 str. 54     <-- 54 -->        PDF

(m3 u.b. × ha-1) were excluded as they were strongly correlated, with their pairs expressed in over bark cubic meters. As shown in Eq. 1, in the case of prediction of initial tendering price (ITP) by the harvesting technical parameters, the common variability of all of the studied harvesting variables explained the variability of the former in a proportion of 20% (Adj. R2 = 0,20). All of the variables taken into account, as well as the developed model were significant (α = 0.05, p < 0.01).
ITP = 39.604 + 13.823 × FT + 14.087 × HS + 0.148 × TA – 0.007 × LS + 0.028 × RI + 5.637 × TS + 35.351 × PC – 0.443 × S – 0.004 × ED  (Eq. 1)
For the final tendering price (FTP) model (Eq. 2), however, the volume sold per cut-block and removal intensity failed to become significant. In the developed model, the common variability of the remaining variables explained the variability of the final tendering price in a proportion of 17% (adj. R2 = 0.17). All of the variables taken into account, as well as the developed model were significant (α = 0.05, p < 0.01).
Regression analysis of the difference in tendering price (DP), did not returned an accurate model, as the adjusted coefficient of determination was very low (adj. R2 = 0.03). However, the model was significant and included the felling type, harvesting system, cut-block area and terrain slope as relevant predictors.
FTP = 54.051 + 16.773 × FT + 21.148 × HS + 0.213 × TA + 7.216 × TS + 42.712 × PC – 0.872 × S – 0.003 × ED                           (Eq. 2)
3.3. Analysis of tendering prices – Analiza natječajnih cijena
We have made numerous attempts to describe the market and the factors influencing certain features of the supply and demand, but most them have not succeeded. Still, some interesting results were found when analyzing the transactions. Due to the described system for standing wood selling, the volumes that are tendered can give an indication regarding the timber demand: the smaller the negotiated volume the bigger the demand. Fig. 3 is presenting the ratio between the tendered and the untendered standing wood volumes for conifers and beech. Just looking at the tendered volumes for the three years (Fig. 3 and 4) one can see that the prices for conifers (89%) were bigger when compared with beech (67%), this probably indicating a bigger market demand for conifers species.
For the analyzed set of transactions, the auction price increased every year especially for both conifers and beech. Also, for both species the biggest increase in auction price was between 2013 and 2014: 39% for beech and 46% for conifers. Despite the auction price increase, the average price difference (average difference between selling price and auction price) did not decrease: it remained rather constant for conifers and even increased for beech, e.g. trend lines in Fig. 5 would confirm this statement. These numbers also indicate that the stumpage market demand increased during the analyzed years.