Sawmills need to manage the arrival amounts, inventory, and prices of sawlogs to maintain the operating profit and sustainable management of the sawmill. This study examines Akita Prefecture, which has a high harvest volume of sugi logs and a high proportion of sugi sawlogs in sawmills. Autoregressive distributed lag (ARDL) models were applied to clarify the affecting factors of arrival amounts, inventory, and sawlog prices. Citing research findings that the existence of missing variables (lag values), rather than the existence of a unit root, is the cause of the spurious regression relationship, we used the ARDL models to analyze the long-term relationships and the error correction models (ECM). The period of analysis was from January 2005 to December 2020. The findings revealed that the price of sawlogs (sugi, 24-28 cm in diameter) and the lumber price (sugi nuki, special grade) were associated in the long term. Additionally, the amount of sawlogs arriving and consumed were also associated in Akita Prefecture. However, while deciding the amount of inventory and arrival, priority was placed on the consumption of sawlogs or the lumber shipped, and sawlog price had only a weak influence in these processes. Finally, ECM for arrival amounts revealed a faster error correction speed than the price and inventory ECM models.
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