The objective of the study was to identify and analyze long−term trends as well as cyclic, seasonal, and irregular effects in timber volume and prices by means of time series decomposition. The adopted multiplicative model was the product of all the time series components identified using the Census X11 method. The study material consisted of quarterly data on the volume and prices of timber sold by the Marcule Forest District (central Poland) in the years 2006−2018. Analysis was performed for the overall timber production volume, as well as separately for pine timber (constituting 86% of the total) and oak timber (5%), taking into account large−diameter saw timber (WC0) and medium−diameter industrial and general purpose timber (pulpwood, S2A). Over the analyzed period, the nominal prices of timber rose on average by 39% from 165 to 229 PLN/m. The greatest price increase was recorded for large−diameter oak timber (by 100%), while the prices of WC0 pine timber, which accounted for the greatest proportion of the production volume, increased by 23% on average. Production characterized marked seasonality throughout the year, depending on the species. Pine timber sales were the lowest in 1supst/sup quarter and the highest in 3suprd/sup one, while oak timber sales were the lowest in 3suprd/sup quarter and the highest in 4supth/sup one. The seasonal effect accounted for the largest proportion of variation in timber production volume. The seasonality of timber prices was negatively correlated with production. The highest prices for pine and oak timber were obtained in 1supst/sup and 2supnd/sup quarters respectively, when the production volume of those timber species was the lowest. Conversely, the lowest prices were recorded in seasons characterized by the greatest production volume, i.e., in 3suprd/sup quarter for pine and in 4supth/sup quarter for oak. The decomposition of overall variation in timber prices into its components, which can be predicted (cyclic and seasonal fluctuations as well as long−term trend), and those that are difficult to forecast (irregular effect) is of great significance for timber sales management as the results can be used to improve timber price forecasting.

Sylwan 163 (10): 820-829