The existence and direction of causal relationships between the time series for the Finnish roundwood market for the period 1960–1994 is tested. Using simple bivariate analysis, we found evidence that for both logs and pulpwood, the lagged prices are helpful in forecasting quantity for the next year, but not vice versa. Saw log stumpage prices have significantly Granger-caused pulpwood prices over the business cycles, but the effect has diminished towards the present time. For quantities traded, the direction of causality was rather from pulpwood to saw logs. The consistency of bivariate test results was checked by the Granger-causality tests within trivariate VAR-models for both markets, and the results were found to be fairly similar to bivariate tests. The price fluctuations in the international markets for forest products have been found to be carried to domestic wood markets dominantly via the pulpwood part of the market.
The first aim of this study was to develop a simulation model describing the flow of different timber qualities to different firms. The second aim was to study preliminary the factors which affect timber distributions. In addition, we tested the hypothesis that in a small sawmill firm the traditional way of organizing timber procurement does not direct effectively good quality logs to the special production. The game theoretic approaching and the principles of Monte-Carlo simulation were applied in development of the simulation model. The most important factors of the model were tried to find for further studies with sensitive analysis. Empirical validation brought forth promising results in the area of one municipality. The buyer’s awareness of a marked stand, the seller’s willingness to sell a marked stand, the buyer’s ability to pay for wood and the proportion of first quality pine logs in a marked stand affected the distribution of pine logs. The results also supported the hypothesis that the traditional system, in which sawmills or their own forest departments procure themselves all timber needed, is not the most effective way to direct enough good quality timber to the special production.
Tree height data from 33 progeny trials of Scots pine (Pinus sylvestris L.) were used to determine the effect of within-plot subsampling on the magnitude of statistically detectable differences between families, family heritability and correlation of family means based on different sample sizes. The results indicated that in trials established with a standard plot configuration of 25 trees per plot, measuring only 10–15 trees gives nearly the same precision as with assessment of all the plot trees. Even as few as 4–6 trees assessed per plot may constitute a sufficient sample if families or parental trees of extreme performance are being selected. Trials established with non-contiguous plots were found to be more efficient than those established using multiple-tree contiguous plots.