Soft Sawnwood Monthly Price - Norwegian Krone per Metric Ton

Data as of March 2026

Range
Mar 2016 - Mar 2026: 256.109 (9.55%)
Chart

Description: Soft Sawnwood, average export price of Douglas Fir, U.S. Price, Norwegian Krone per Metric Ton

Unit: Norwegian Krone per Metric Ton



Source: International Monetary Fund

See also: Agricultural production statistics

See also: Top commodity suppliers

See also: Commodities glossary - Definitions of terms used in commodity trading

Overview

Soft sawnwood is dimension lumber cut from softwood species such as pine, spruce, fir, and spruce-pine-fir mixes. It is typically priced by volume, with market quotations commonly expressed in US dollars per cubic meter. In commodity references, a widely used benchmark is the average export price from the United States, which reflects tradeable grades rather than retail lumber sold to end users. Soft sawnwood is a standardized industrial material used in structural framing, roof trusses, flooring substructures, pallets, packaging, and general construction. It is distinct from hardwood lumber because it is generally lighter, easier to machine, and more closely tied to mass housing and repair-and-remodel activity. Pricing is influenced by grade, moisture content, dimensions, and whether the product is kiln-dried or green. Because lumber is bulky and costly to transport relative to value, regional supply chains and freight access play an important role in market formation.

Supply Drivers

Soft sawnwood supply is shaped by forest biology, harvesting cycles, and mill capacity. Major producing regions include Canada, the United States, Scandinavia, and parts of Russia and Central Europe, where conifer forests are extensive and suited to mechanized harvesting. Unlike annual crops, timber supply depends on long growth cycles, so output responds slowly to changes in planting, thinning, and final harvest decisions. Weather affects both forest growth and logging access: drought, storms, wildfire, insect outbreaks, and freeze-thaw conditions can disrupt standing timber availability and transport. Insect and disease pressure can also alter the quality mix of logs available to mills.

Processing capacity is another constraint. Sawmills require steady log flows, energy, labor, and capital-intensive equipment, so outages or maintenance can tighten supply even when timber is available. Transport bottlenecks matter because logs and lumber are heavy and low-value relative to freight cost; rail, truck, and port access shape export competitiveness. Regional housing cycles can also affect sawmill utilization, since mills often adjust output to match construction demand and inventory conditions. Because lumber can be stored only for limited periods without quality loss, producers manage production around seasonal logging conditions and downstream demand.

Demand Drivers

Demand for soft sawnwood is driven primarily by residential construction, renovation, and light industrial uses. Structural framing in houses and low-rise buildings is the largest end use in many markets, especially where wood-frame construction is common. Demand also comes from pallets, crates, packaging, and temporary works, which link lumber consumption to manufacturing, logistics, and trade flows. In colder climates, seasonal building patterns often create stronger demand during construction seasons, while repair-and-remodel activity provides a steadier baseline.

Substitution plays an important role. Soft sawnwood competes with steel, concrete, engineered wood products, and in some applications plastic or composite materials. Wood-frame construction is favored where labor practices, building codes, and material costs support it, while engineered products can replace some dimensional lumber in structural applications. Demand is also influenced by population growth, household formation, and income conditions because housing starts and home improvement spending respond to broader economic cycles. In packaging and pallets, demand is tied to goods movement and manufacturing output rather than housing alone. Building codes, fire standards, and efficiency requirements shape the mix of wood products used, but the basic role of soft sawnwood as a versatile structural material remains persistent.

Macro and Financial Drivers

Soft sawnwood prices are sensitive to general economic activity because construction and industrial packaging are cyclical. A stronger US dollar can affect export competitiveness by making US lumber more expensive in foreign-currency terms, while a weaker dollar can support export demand. Interest rates matter because housing and construction are credit-sensitive; higher borrowing costs typically reduce building activity and lumber consumption through the financing channel. Storage and financing costs also influence market structure: lumber is bulky, degrades if poorly stored, and ties up working capital, so inventories are costly to carry. This can produce periods of backwardation when nearby supply is tight or contango when inventories are ample. Lumber prices may also correlate with broader cyclical assets through their link to construction, manufacturing, and freight conditions, though the relationship is driven by physical demand rather than financial speculation alone.

MonthPriceChange
Mar 20162,681.63-
Apr 20162,654.61-1.01%
May 20162,735.173.03%
Jun 20162,746.200.40%
Jul 20162,718.71-1.00%
Aug 20162,673.90-1.65%
Sep 20162,742.712.57%
Oct 20162,699.13-1.59%
Nov 20162,747.781.80%
Dec 20162,768.260.75%
Jan 20172,705.51-2.27%
Feb 20172,599.70-3.91%
Mar 20172,501.38-3.78%
Apr 20172,714.338.51%
May 20172,705.62-0.32%
Jun 20172,792.173.20%
Jul 20172,682.68-3.92%
Aug 20172,535.55-5.48%
Sep 20172,447.77-3.46%
Oct 20172,596.626.08%
Nov 20172,740.265.53%
Dec 20172,721.39-0.69%
Jan 20182,731.020.35%
Feb 20182,642.33-3.25%
Mar 20182,614.50-1.05%
Apr 20182,595.69-0.72%
May 20182,820.058.64%
Jun 20182,890.812.51%
Jul 20182,871.12-0.68%
Aug 20182,810.36-2.12%
Sep 20182,823.380.46%
Oct 20182,778.82-1.58%
Nov 20182,881.593.70%
Dec 20183,185.4210.54%
Jan 20193,060.81-3.91%
Feb 20192,940.57-3.93%
Mar 20192,974.711.16%
Apr 20192,869.11-3.55%
May 20193,198.3011.47%
Jun 20193,052.32-4.56%
Jul 20193,069.570.57%
Aug 20193,301.727.56%
Sep 20193,275.07-0.81%
Oct 20193,189.94-2.60%
Nov 20193,336.884.61%
Dec 20193,111.99-6.74%
Jan 20203,272.875.17%
Feb 20203,137.93-4.12%
Mar 20203,700.0017.91%
Apr 20203,741.861.13%
May 20203,578.97-4.35%
Jun 20203,340.10-6.67%
Jul 20203,102.90-7.10%
Aug 20203,020.46-2.66%
Sep 20203,037.060.55%
Oct 20203,256.817.24%
Nov 20203,273.380.51%
Dec 20202,884.51-11.88%
Jan 20213,015.164.53%
Feb 20212,834.30-6.00%
Mar 20213,132.1810.51%
Apr 20213,314.375.82%
May 20213,495.045.45%
Jun 20213,675.005.15%
Jul 20213,245.71-11.68%
Aug 20212,926.79-9.83%
Sep 20212,548.16-12.94%
Oct 20212,628.423.15%
Nov 20212,698.282.66%
Dec 20212,842.535.35%
Jan 20222,898.061.95%
Feb 20223,000.253.53%
Mar 20224,128.4937.60%
Apr 20223,939.77-4.57%
May 20224,138.285.04%
Jun 20224,065.29-1.76%
Jul 20224,016.57-1.20%
Aug 20224,175.593.96%
Sep 20224,166.98-0.21%
Oct 20224,107.50-1.43%
Nov 20223,928.48-4.36%
Dec 20223,619.80-7.86%
Jan 20233,060.11-15.46%
Feb 20233,392.1410.85%
Mar 20233,272.06-3.54%
Apr 20233,178.39-2.86%
May 20233,667.6515.39%
Jun 20233,393.15-7.48%
Jul 20233,259.26-3.95%
Aug 20233,379.513.69%
Sep 20233,596.776.43%
Oct 20233,504.08-2.58%
Nov 20233,327.74-5.03%
Dec 20233,361.811.02%
Jan 20243,483.423.62%
Feb 20243,463.69-0.57%
Mar 20243,617.774.45%
Apr 20243,444.89-4.78%
May 20243,466.280.62%
Jun 20243,267.23-5.74%
Jul 20243,348.182.48%
Aug 20243,267.77-2.40%
Sep 20243,498.567.06%
Oct 20243,153.28-9.87%
Nov 20243,398.877.79%
Dec 20243,965.6016.67%
Jan 20253,561.05-10.20%
Feb 20253,786.206.32%
Mar 20253,553.02-6.16%
Apr 20253,366.43-5.25%
May 20253,350.11-0.48%
Jun 20253,387.651.12%
Jul 20253,428.581.21%
Aug 20253,207.14-6.46%
Sep 20252,986.40-6.88%
Oct 20252,777.34-7.00%
Nov 20252,944.756.03%
Dec 20252,960.260.53%
Jan 20263,057.723.29%
Feb 20262,912.69-4.74%
Mar 20262,937.740.86%

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