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Cointegration analysis in the Central European spruce timber market

Kożuch Anna

Drewno : prace naukowe, doniesienia, komunikaty

2021

vol. 64, nr 208

119--133

The oversupply of spruce timber in Central Europe reduces softwood prices, compromising the profitability of forest holdings. To date, relationships between Central European timber markets have been relatively little studied; the same is true of the factors affecting roundwood price variability and fluctuations in that region. An understanding of changes in those markets and linkages between them is important not only for forest owners and managers, but also for companies in the wood sector. The present work describes market analysis in terms of long-term correlations between the Austrian, Czech, Polish, and Slovak markets (cointegration analysis). Cause-and-effect relationships between the analyzed markets were verified using the Granger causality test. The Engle-Granger and Johansen cointegration tests revealed a long-term equilibrium between the analyzed spruce sawlog markets, except for Slovakia. Bidirectional causality was found between the Austrian, Czech, and Polish markets. However, there was no evidence for the integration of pulpwood markets, which indicates their independence.

The application of trend estimation model in predicting the average selling price of timber

Adamowicz Krzysztof, Górna Aleksandra

Drewno : prace naukowe, doniesienia, komunikaty

2020

vol. 63, nr 206

147--159

The article analyzes the possibility of adopting trend estimation model to predict the average selling price of timber (CGUS). The study used information about the average selling prices of timber in chosen periods (2006-2017). The data concerning the actual CGUS was used to create a trend estimation model. The models and CGUS predictions were conducted based on three different time series encompassing 5-year periods. The predicted (CGUS) trend estimation in particular years was requested based on extrapolation, which exceeded the accepted set of information used in the study to create a trend estimation model. On the basis of the conducted study it was ascertained that the method of modeling linear trend estimation should be adopted in the price prediction process. The error assessment with which the linear function formulas are burdened, it was noticed that the value of the coefficient of residual variation was between 4.40% and 7.82%. It was also noticed that the linear modeling of CGUS trend estimation, despite unfavorable values of coefficient of determination and convergence, to some extent, can be viewed as an assistance tool in the decisionmaking process in the scope of predicting the height of the analyzed price. This view was supported by the achieved predictions which were verified with the actual prices of timber. The price difference between the actual and the predicted one was between -1.59 PLN to 2.27 PLN, and in relative terms the predictive error was between 0.83 to 1.15%. In our opinion the presented research process can constitute a reference point as a comparative element to verify the results for other, new price prediction models. The process of modeling timber prices should be extended by other predicators which are connected with forest market chain.