Time series data on forest product prices used in research is frequently the product of temporal, spatial as well as product aggregation. This paper analyzes the implications of the use of composite commodity price indices in cointegration analysis and tests the validity of the assumptions underlying it. It tests for the presence of a common stochastic trend in disaggregated softwood lumber product price series in multiple US markets, a validity condition supported by the Generalized Composite Commodity Theorem (Lewbel, 1996. Aggregation without separability: a generalized composite commodity theorem. The American Economic Review 86(3), 524-543.). The presence of a common stochastic trend in softwood lumber product price series tested is consistently rejected by Johansen's (1988. Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control 12(2-3), 231-254.) multivariate cointegration analysis. Together with rejection of non-stationarity property for a significantly large number of price series tested, the results highlight the significance of the assumptions underlying the use of composite forest commodity price indices for cointegration analysis.

Cyclical patterns in business activity are a common feature of industry in market economies. This study identifies and describes industry cycles in the US softwood lumber industry from 1985 to 2010. Statistical decomposition and filtering procedures are applied to time series data on sales volumes to extract the cyclical component, and nonparametric techniques are used to date the industry cycles. The study identifies four softwood lumber industry cycles: three coincident with business cycles and one attributable to developments in the US–Canada softwood lumber trade dispute. Softwood lumber industry cycle durations ranged between 5 and 6 years. Decline in seasonally adjusted softwood lumber industry business activity caused by cyclic contractions averaged 13 percent for the period under study, with the most recent contraction (January 2006 to March 2009) contributing a 22 percent decline in business activity.

We test the forecasting power and information content of lumber futures prices traded on the Chicago Mercantile Exchange, from 1995 to 2013, at four forecast horizons. A Mincer-Zarnowitz regression finds evidence of statistically significant forecasting power at all forecast horizons. The results also support the presence of a time-varying risk premium for the shorter forecast horizons. A Granger causality test provides evidence that lumber futures prices lag spot prices in information assimilation over longer forecast horizons, while neither lagging nor leading over shorter forecast horizons.

growth in multiunit housing starts has been exceptionally strong and sustained. In this study, we examine empirical evidence for three possible explanations, namely, the passage of Baby Boomers into senior years, the depressed economic conditions, and rising preference of recent birth cohorts for residing in urban cores. Applying Age-PeriodCohort analysis to census data on multiunit housing occupancy from 1970 to 2010, we find evidence to support the explanations that a sharp increase in demand from Millennials drawn to urban cores and retiring Baby Boomers are contributing to the growth in multiunit housing starts. The results provide weak evidence of a negative relationship between depressed economic conditions and demand for multiunit housing starts. Over the long term, demand for multiunit housing can be expected to moderate as a result of the projected aging of the population.