Soft Sawnwood Monthly Price - Singapore Dollar per Metric Ton

Data as of March 2026

Range
Mar 2006 - Mar 2026: -126.383 (-24.52%)
Chart

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

Unit: Singapore Dollar 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 2006515.33-
Apr 2006495.04-3.94%
May 2006516.814.40%
Jun 2006556.447.67%
Jul 2006566.721.85%
Aug 2006581.172.55%
Sep 2006560.88-3.49%
Oct 2006588.264.88%
Nov 2006544.99-7.36%
Dec 2006565.403.75%
Jan 2007546.06-3.42%
Feb 2007567.043.84%
Mar 2007523.89-7.61%
Apr 2007535.872.29%
May 2007551.322.88%
Jun 2007521.73-5.37%
Jul 2007468.52-10.20%
Aug 2007379.15-19.07%
Sep 2007478.5926.23%
Oct 2007432.99-9.53%
Nov 2007443.722.48%
Dec 2007450.531.53%
Jan 2008462.172.58%
Feb 2008440.07-4.78%
Mar 2008413.24-6.10%
Apr 2008397.97-3.69%
May 2008417.664.95%
Jun 2008402.10-3.73%
Jul 2008451.4912.29%
Aug 2008441.99-2.11%
Sep 2008446.541.03%
Oct 2008479.667.42%
Nov 2008502.024.66%
Dec 2008466.66-7.04%
Jan 2009518.0311.01%
Feb 2009483.04-6.75%
Mar 2009471.46-2.40%
Apr 2009473.420.42%
May 2009482.651.95%
Jun 2009472.94-2.01%
Jul 2009456.36-3.51%
Aug 2009452.33-0.88%
Sep 2009415.54-8.13%
Oct 2009403.02-3.01%
Nov 2009430.376.79%
Dec 2009449.274.39%
Jan 2010439.22-2.24%
Feb 2010432.66-1.49%
Mar 2010441.762.10%
Apr 2010419.54-5.03%
May 2010427.521.90%
Jun 2010429.500.46%
Jul 2010432.300.65%
Aug 2010434.210.44%
Sep 2010429.70-1.04%
Oct 2010410.03-4.58%
Nov 2010358.69-12.52%
Dec 2010412.5215.01%
Jan 2011395.23-4.19%
Feb 2011373.67-5.46%
Mar 2011360.17-3.61%
Apr 2011342.16-5.00%
May 2011354.223.52%
Jun 2011361.241.98%
Jul 2011373.893.50%
Aug 2011385.203.02%
Sep 2011381.91-0.85%
Oct 2011399.784.68%
Nov 2011405.821.51%
Dec 2011384.39-5.28%
Jan 2012398.923.78%
Feb 2012397.28-0.41%
Mar 2012379.77-4.41%
Apr 2012401.075.61%
May 2012418.274.29%
Jun 2012407.21-2.64%
Jul 2012395.14-2.96%
Aug 2012403.822.20%
Sep 2012398.28-1.37%
Oct 2012385.80-3.13%
Nov 2012399.463.54%
Dec 2012365.26-8.56%
Jan 2013371.021.58%
Feb 2013377.641.78%
Mar 2013388.782.95%
Apr 2013401.213.20%
May 2013446.4511.28%
Jun 2013446.690.05%
Jul 2013442.65-0.90%
Aug 2013440.14-0.57%
Sep 2013416.95-5.27%
Oct 2013403.51-3.23%
Nov 2013414.472.72%
Dec 2013445.217.42%
Jan 2014430.67-3.27%
Feb 2014431.800.26%
Mar 2014449.514.10%
Apr 2014419.43-6.69%
May 2014414.49-1.18%
Jun 2014415.290.19%
Jul 2014400.60-3.54%
Aug 2014399.34-0.31%
Sep 2014413.893.64%
Oct 2014403.39-2.54%
Nov 2014436.988.33%
Dec 2014446.592.20%
Jan 2015470.445.34%
Feb 2015456.25-3.01%
Mar 2015443.12-2.88%
Apr 2015455.352.76%
May 2015442.03-2.93%
Jun 2015412.46-6.69%
Jul 2015410.36-0.51%
Aug 2015430.204.83%
Sep 2015429.68-0.12%
Oct 2015431.350.39%
Nov 2015445.273.23%
Dec 2015415.79-6.62%
Jan 2016450.838.43%
Feb 2016460.782.21%
Mar 2016433.80-5.85%
Apr 2016436.180.55%
May 2016455.264.37%
Jun 2016448.35-1.52%
Jul 2016433.57-3.29%
Aug 2016434.180.14%
Sep 2016454.184.61%
Oct 2016457.530.74%
Nov 2016460.860.73%
Dec 2016464.420.77%
Jan 2017455.77-1.86%
Feb 2017442.16-2.99%
Mar 2017413.57-6.47%
Apr 2017442.266.94%
May 2017442.990.16%
Jun 2017456.573.07%
Jul 2017450.99-1.22%
Aug 2017436.95-3.11%
Sep 2017421.81-3.46%
Oct 2017442.304.86%
Nov 2017454.002.65%
Dec 2017440.77-2.91%
Jan 2018455.943.44%
Feb 2018445.24-2.35%
Mar 2018442.52-0.61%
Apr 2018435.51-1.59%
May 2018466.287.07%
Jun 2018480.092.96%
Jul 2018481.540.30%
Aug 2018462.02-4.05%
Sep 2018469.541.63%
Oct 2018464.26-1.12%
Nov 2018468.550.92%
Dec 2018507.338.28%
Jan 2019485.48-4.31%
Feb 2019463.74-4.48%
Mar 2019468.451.01%
Apr 2019454.27-3.03%
May 2019501.4010.38%
Jun 2019482.10-3.85%
Jul 2019485.180.64%
Aug 2019510.115.14%
Sep 2019501.45-1.70%
Oct 2019478.15-4.65%
Nov 2019496.813.90%
Dec 2019466.67-6.07%
Jan 2020493.735.80%
Feb 2020469.22-4.96%
Mar 2020512.849.30%
Apr 2020509.97-0.56%
May 2020502.95-1.38%
Jun 2020488.72-2.83%
Jul 2020464.44-4.97%
Aug 2020462.51-0.42%
Sep 2020452.68-2.13%
Oct 2020477.155.41%
Nov 2020485.191.69%
Dec 2020440.14-9.28%
Jan 2021469.216.60%
Feb 2021442.92-5.60%
Mar 2021493.0611.32%
Apr 2021528.197.13%
May 2021560.916.19%
Jun 2021581.693.70%
Jul 2021499.99-14.04%
Aug 2021448.00-10.40%
Sep 2021397.16-11.35%
Oct 2021419.655.66%
Nov 2021420.190.13%
Dec 2021431.182.62%
Jan 2022442.292.58%
Feb 2022455.723.04%
Mar 2022633.4238.99%
Apr 2022603.82-4.67%
May 2022596.25-1.25%
Jun 2022577.75-3.10%
Jul 2022558.99-3.25%
Aug 2022595.496.53%
Sep 2022572.81-3.81%
Oct 2022553.12-3.44%
Nov 2022537.26-2.87%
Dec 2022496.35-7.61%
Jan 2023407.79-17.84%
Feb 2023441.658.30%
Mar 2023416.22-5.76%
Apr 2023402.94-3.19%
May 2023455.6113.07%
Jun 2023422.18-7.34%
Jul 2023425.100.69%
Aug 2023436.222.62%
Sep 2023457.634.91%
Oct 2023435.58-4.82%
Nov 2023410.25-5.82%
Dec 2023420.822.58%
Jan 2024446.896.20%
Feb 2024441.47-1.21%
Mar 2024458.003.74%
Apr 2024429.20-6.29%
May 2024439.982.51%
Jun 2024415.60-5.54%
Jul 2024416.400.19%
Aug 2024401.59-3.56%
Sep 2024427.376.42%
Oct 2024382.22-10.57%
Nov 2024411.297.61%
Dec 2024478.4116.32%
Jan 2025427.79-10.58%
Feb 2025455.596.50%
Mar 2025444.26-2.49%
Apr 2025422.32-4.94%
May 2025420.82-0.35%
Jun 2025432.512.78%
Jul 2025432.530.00%
Aug 2025404.65-6.45%
Sep 2025385.87-4.64%
Oct 2025358.72-7.04%
Nov 2025377.985.37%
Dec 2025378.140.04%
Jan 2026390.763.34%
Feb 2026385.37-1.38%
Mar 2026388.950.93%

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