A model to estimate regional softwood sawmill conversion efficiency

This study develops a model to estimate U.S. softwood sawmill conversion efficiency by region. Data from 650 softwood sawmills in all geographic regions of the United States were analyzed. A three-stage least squares method was used to estimate an initial model. Removal of insignificant variables reduced the model to a simple recursive, which was estimated by an ordinary least squares method. Signs of estimated coefficients of the simple recursive model were as expected. All coefficients of explanatory variables were statistically significant. The resultant model provides a tool for estimating lumber recovery factor (LRF) as a result of known or predicted changes in variable values. Mean, standard deviation, and range values of explanatory variables are given by region. These values can be used in the model to provide estimates of LRF by region. Examples are shown to demonstrate how the developed model should be used to estimate LRF based on changes in variables.

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