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A comparison of prediction efficiency for timber prices in Poland in times of economic crisis with the application of the linear approximation method and brown’s exponential smoothing model

Górna Aleksandra, Adamowicz Krzysztof

Drewno : prace naukowe, doniesienia, komunikaty

2021

vol. 64, nr 208

135--147

An analysis was made of two prediction methods: the Linear Approximation Method (LAM) and Brown’s Exponential Smoothing Model (BESM). These two methods were investigated and compared in terms of their efficiency in timber price prediction. Models and price predictions were prepared based on three time series (5-, 7- and 9-year) for three years: 2015, 2016 and 2017. The analyses were conducted using data on mean annual timber prices from the period 2006-2017. This meant that the time series included the years of the 2007-2008 economic crisis. Prediction efficiency was evaluated by comparing the results obtained with actual timber prices in the years 2015-2017. It was found that the predictions generated by LAM were better than those produced by BESM. The smallest relative and absolute errors of prediction were obtained applying the linear function: Υt^ = 5.277t + 161.70. This function was constructed based on a 5-year time series. Absolute error amounted to 1.59 PLN (€0.35). Relative error was below 1%. The results of this work suggest that further studies are desirable to investigate the applicability of trend analysis to the prediction of timber prices with the inclusion of analyses of nonlinear trends. The present results of timber price modelling may provide a basis to search for a homogeneous model of timber price prediction adapted to specific conditions of timber sales.

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.