ABSTRACT
Lumber prices can be volatile and hard to predict from month to month yet are important for many sectors of the economy, ranging from forestry and construction. An economic model of lumber prices was developed and applied to data representing multiple supply and demand determinants of lumber. Using a suite of econometric models, monthly lumber prices were related back to variables including construction permits, US reserve bank credit, tariffs with Canada, exchange rates with Canada, and variables representing shocks associated with the COVID-19 pandemic. Preferred models use relatively small amounts of publicly available information, making them more accessible to industry participants who want to make their own price predictions. Such information can help guide decisions about whether to expand or scale back an operation in preparation for likely future price movements. Study Implications: This study shows that Douglas-fir lumber prices in the US Northwest can be predicted quite accurately with selected macro-economic variables that are commonly reported in the public domain. Using statistical techniques, monthly lumber prices in the United States were related back to variables including new home construction permits, US reserve bank credit, tariffs, and exchange rates. With suitable assumptions about future economic conditions, the models could be used by researchers as well as professionals at lumber mills, wholesales, and retailers to make near term predictions.