Soft Sawnwood Monthly Price - Russian Ruble per Metric Ton

Data as of March 2026

Range
May 2013 - Jun 2025: 15,284.040 (136.32%)
Chart

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

Unit: Russian Ruble 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
May 201311,212.13-
Jun 201311,457.402.19%
Jul 201311,424.21-0.29%
Aug 201311,409.64-0.13%
Sep 201310,747.50-5.80%
Oct 201310,401.30-3.22%
Nov 201310,855.554.37%
Dec 201311,633.717.17%
Jan 201411,497.07-1.17%
Feb 201412,015.154.51%
Mar 201412,809.626.61%
Apr 201411,914.09-6.99%
May 201411,550.09-3.06%
Jun 201411,420.46-1.12%
Jul 201411,191.70-2.00%
Aug 201411,556.413.26%
Sep 201412,448.837.72%
Oct 201412,962.844.13%
Nov 201415,588.0220.25%
Dec 201419,055.8222.25%
Jan 201523,127.7021.37%
Feb 201521,805.64-5.72%
Mar 201519,379.65-11.13%
Apr 201517,850.84-7.89%
May 201516,715.25-6.36%
Jun 201516,708.95-0.04%
Jul 201517,320.113.66%
Aug 201520,197.6916.61%
Sep 201520,255.840.29%
Oct 201519,453.56-3.96%
Nov 201520,489.385.32%
Dec 201520,652.400.80%
Jan 201624,498.8918.62%
Feb 201625,284.963.21%
Mar 201622,080.72-12.67%
Apr 201621,525.12-2.52%
May 201621,849.691.51%
Jun 201621,553.86-1.35%
Jul 201620,665.90-4.12%
Aug 201620,928.941.27%
Sep 201621,543.452.94%
Oct 201620,711.48-3.86%
Nov 201621,077.271.77%
Dec 201620,045.12-4.90%
Jan 201719,009.06-5.17%
Feb 201718,255.66-3.96%
Mar 201717,025.97-6.74%
Apr 201717,860.364.90%
May 201718,082.971.25%
Jun 201719,140.195.85%
Jul 201719,646.892.65%
Aug 201719,120.46-2.68%
Sep 201718,038.47-5.66%
Oct 201718,751.643.95%
Nov 201719,738.355.26%
Dec 201719,177.23-2.84%
Jan 201819,472.301.54%
Feb 201819,169.16-1.56%
Mar 201819,212.740.23%
Apr 201820,127.604.76%
May 201821,670.407.67%
Jun 201822,386.463.30%
Jul 201822,189.35-0.88%
Aug 201822,384.360.88%
Sep 201823,157.933.46%
Oct 201822,150.90-4.35%
Nov 201822,642.002.22%
Dec 201824,851.569.76%
Jan 201923,785.67-4.29%
Feb 201922,547.09-5.21%
Mar 201922,505.53-0.18%
Apr 201921,641.18-3.84%
May 201923,735.809.68%
Jun 201922,674.63-4.47%
Jul 201922,536.81-0.61%
Aug 201924,192.207.35%
Sep 201923,572.56-2.56%
Oct 201922,430.44-4.85%
Nov 201923,303.013.89%
Dec 201921,706.69-6.85%
Jan 202022,625.334.23%
Feb 202021,631.13-4.39%
Mar 202026,761.2923.72%
Apr 202026,781.280.07%
May 202025,728.71-3.93%
Jun 202024,277.68-5.64%
Jul 202023,919.46-1.48%
Aug 202024,925.484.21%
Sep 202025,196.181.09%
Oct 202027,242.548.12%
Nov 202027,675.221.59%
Dec 202024,469.39-11.58%
Jan 202126,358.607.72%
Feb 202124,818.41-5.84%
Mar 202127,346.7710.19%
Apr 202130,132.6510.19%
May 202131,171.203.45%
Jun 202131,675.181.62%
Jul 202127,302.54-13.80%
Aug 202124,326.35-10.90%
Sep 202121,470.77-11.74%
Oct 202122,173.493.27%
Nov 202122,398.141.01%
Dec 202123,277.233.92%
Jan 202225,112.167.88%
Feb 202226,428.055.24%
Mar 202247,936.7681.39%
Apr 202234,217.46-28.62%
May 202227,272.76-20.30%
Jun 202223,705.88-13.08%
Jul 202223,535.79-0.72%
Aug 202225,975.9210.37%
Sep 202224,159.91-6.99%
Oct 202223,826.54-1.38%
Nov 202223,513.93-1.31%
Dec 202223,915.281.71%
Jan 202321,218.73-11.28%
Feb 202324,198.7814.04%
Mar 202323,614.77-2.41%
Apr 202324,558.324.00%
May 202326,976.039.84%
Jun 202326,285.00-2.56%
Jul 202328,941.7910.11%
Aug 202330,843.766.57%
Sep 202332,421.205.11%
Oct 202330,757.99-5.13%
Nov 202327,521.05-10.52%
Dec 202328,636.074.05%
Jan 202429,711.393.76%
Feb 202430,053.991.15%
Mar 202431,370.984.38%
Apr 202429,401.87-6.28%
May 202429,527.500.43%
Jun 202427,006.78-8.54%
Jul 202427,031.100.09%
Aug 202427,253.120.82%
Sep 202430,169.5210.70%
Oct 202428,116.17-6.81%
Nov 202430,872.839.80%
Dec 202436,535.5018.34%
Jan 202531,410.26-14.03%
Feb 202531,214.05-0.62%
Mar 202528,556.50-8.51%
Apr 202526,527.36-7.11%
May 202526,093.40-1.64%
Jun 202526,496.171.54%

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