seasonal fluctuations assessment of log and lumber prices using multipleregression analysis: case study of azarood forest, mazandaran

knowledge of seasonal fluctuations is of great importance for sale management. the aim of this research is to assess the impact of sale season on the log and lumber prices. hence, after evaluation of sale documents in azarood forestry plan, the data of 410 timber sale lots at roadside of four seasons from 1992 to 2008 were extracted and incorporated into a dataset. calculating the average selling price for each species group and products per season and year, four time series of seasonal price for two species group and products (log and lumber) were obtained. then, all prices were deflated to the base year of 2007.the augmented dicky-fuller test were then employed to evaluate stationarity of time series. impact of season sale variables (independent dummy variable) on timber price was analyzed using multiple regression analysis, mra, and stepwise method of spss 14.0 software. the impact of sale season on log and lumber prices was appeared to be significant for first species group while insignificant impact was found for second species group (at 5% level). the results revealed that selling lumbers and logs of first species group in summer and autumn caused a price raise of 13 and 11 percent (i.e., 120409 and 150798 rial/m3 at constant prices of 2007) compared to other seasons, respectively. wood trade and building boom in summer and autumn seems to contribute to timber prices raise in these seasons. implications of such analysis seem to be of interest both for forest managers and wood industries.