Journal of Forest Economics > Vol 40 > Issue 4

Investigating Production Cycles in the U.S. Softwood Lumber Industry: 1965–2017

Kai Ling, Department of Agricultural Economics and Rural Sociology, Auburn University, USA, kzl0095@auburn.edu , Sunjae Won, Department of Agricultural Economics and Rural Sociology, Auburn University, USA, Wenying Li, Department of Agricultural Economics and Rural Sociology, Auburn University, USA
 
Suggested Citation
Kai Ling, Sunjae Won and Wenying Li (2025), "Investigating Production Cycles in the U.S. Softwood Lumber Industry: 1965–2017", Journal of Forest Economics: Vol. 40: No. 4, pp 383-404. http://dx.doi.org/10.1561/112.00000598

Publication Date: 05 Nov 2025
© 2025 K. Ling et al.
 
Subjects
Econometric models,  Latent variable models,  Nonstationary time series,  Time series analysis
 
Keywords
Time series modelingUnobserved components modelStochastic cycleLumber production.
 

Share

Download article
In this article:
1 Introduction 
2 Data and Methodology 
3 Model Calibration 
4 Empirical Results 
5 Discussion and Conclusion 
References 

Abstract

Softwood lumber plays a critical role in U.S. housing construction. This study examines the dynamics of the U.S. softwood lumber industry using an Unobserved Components Model (UCM) applied to annual production data from 1965 to 2017. The model decomposes production into trend, cycle, and irregular components, while also incorporating GDP growth as a key economic driver. Results show a clear cyclical pattern with an average period of 19.6 years. Within the UCM framework, holding the trend and cycle components constant, a one-percentage-point increase in GDP growth will raise softwood lumber production by 0.595%. The stochastic cycle emerges as the primary driver of production variability, while economic shocks exert a secondary but meaningful influence. These findings offer insights into the industry's cyclical nature and inform strategies for enhancing market stability and resilience.

DOI:10.1561/112.00000598