Estimating Regional Softwood Lumber Supply in the United States Using Seemingly Unrelated Regression

Abstract

In this article, we present estimates of regional softwood lumber supply functions in the United States using annual time series data for 1959 to 2009. Seemingly unrelated regression is used in a profit maximization framework to model softwood lumber supply as a function of lumber and stumpage prices, lagged supply, wage rate, and interest rate for the eastern and western United States. The effects of listing the northern spotted owl (Strix occidentalis caurina) as a threatened species and the US–Canada softwood lumber trade dispute are controlled for in empirical estimation. Results show that regional lumber supply is quite inelastic to lumber price and that stumpage price and bank prime rate negatively influence regional lumber supply. Results also suggest that present market supplies of softwood lumber have potential expansionary influence on future supplies, that listing of the northern spotted owl in 1990 reduced the lumber supply in the western region during subsequent years, that the US–Canada softwood lumber trade dispute/agreements favored regional lumber production in the United States during the period from 1996 to 2005, and that supply has declined during the recent period of economic recession.