Lumber Prices Research Articles

Determinants of Softwood Lumber Prices in the US Northwest

Abstract Lumber prices can be volatile and hard to predict from month to month yet are important for many sectors of the economy, ranging from forestry and construction. An economic model of lumber prices was developed and applied to data representing multiple supply and demand determinants of lumber. Using a suite of econometric models, monthly lumber prices were related back to variables including construction permits, US reserve bank credit, tariffs with Canada, exchange rates with Canada, and variables representing shocks associated with the COVID-19 pandemic. Preferred models use relatively small amounts of publicly available information, making them more accessible to industry participants who want to make their own price predictions. Such information can help guide decisions about whether to expand or scale back an operation in preparation for likely future price movements.

Price Volatility Modeling for the Lumber Futures Market: A Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling Approach

Abstract Lumber is one of the most essential forest products in the United States. During the first year of the COVID-19 pandemic, lumber prices almost quadrupled, and fluctuations reached record levels. Although market experts have pointed to various drivers of such high price volatility, no firm conclusions have been drawn yet. Using the generalized autoregressive conditional heteroskedasticity-mixed data sampling (GARCH-MIDAS) framework, this study assesses the potential drivers of lumber price volatility, with predictors including the Google Trends Web Search Index, housing starts, US lumber production quantity, and VIX index, representing public attention, housing demand, lumber supply, and macroeconomic concerns, respectively. We have found that housing demand is the key driver of lumber price volatility, followed by public attention. It is worth noting that US lumber supply and macroeconomic concerns have played a modest role in explaining lumber price volatility. Also, forecasting lumber price by using the housing demand variable substantially outperforms others. Market participants, including lumber mills, wholesalers, and home builders can get valuable information from the housing market to manage lumber price risk.

COVID-19 and the Mystery of Lumber Price Movements

The COVID-19 pandemic led to unprecedented changes in the U.S. price of softwood lumber by more than 300% between 2020 and 2022. The increased volatility of lumber prices after the COVID-19 outbreak remains unexplained. In this paper, we examine how a calibrated random walk can induce similar price volatility through the development of a stochastic process. As a preferred approach, we employ an event model to estimate the impact of COVID-19 and other key events on the price of softwood lumber. The econometric model serves to provide evidence that the price volatility of softwood lumber is not completely random, and we can instead attribute part of the variation to recent regional and global events. We found that, while COVID-19 did result in a price jump, it was smaller than a rainfall event that restricted imports from Canada, while import duties and other trade actions had no discernible impact on U.S. lumber prices.

Explaining Post-Pandemic Lumber Price Volatility and its Welfare Effects

Abstract The COVID-19 pandemic led to an unprecedented increase in the U.S. price of softwood lumber by more than 300%. The price increase has been attributed to constraints on supply and increased demand for lumber caused by a pandemic-induced boom in domestic housing construction and, more so, home improvements. However, the volatility in lumber prices after the COVID-19 outbreak remains unexplained. In this paper, we employ a theoretical model to explain the cause of price volatility. We examine why demand and supply functions for lumber might be quite inelastic over the period from March 2020 to April 2022, despite very small shifts in demand. This implies that slight movements in interest rates or changes in the prices of substitutes, for example, can lead to large jumps in prices. Price volatility harms consumers while greatly benefitting lumber producers. Overall, as a result of the pandemic, U.S. producers gained some $5.3 billion, while U.S. consumers lost $7.3 billion per quarter.

The Impact of Crypto Currencies on the Economy and The Financial Industry

This paper is based on the discussion about the cryptocurrencies and its impact on the financial industry. However, the adoption of cryptocurrencies is a different matter because right now the Bitcoins is considered as for wealthy, developed and tech-savvy cultures. Based on the analysis about the points of differences of the currency a countries profile can be developed who are more likely to adopt the Bitcoin. The cryptocurrencies are considered a potential solution against the accessibility, exchange, fraud, and inflation. Moreover, the prices are considerably increasing because the demand for core good is growing rapidly relative to supply. As per the analysis the fiat currency system is considered as the main reason for the future inflation however it will not cause any significant problem in the overall financial industry. The growing demand for housing is also increasing the price of lumber that also increased in the prices of wood. Consequently, all the related goodwill becomes more expensive following the trickle through the economy. Moreover, the asset market also contributes considerably to the inflation. An increase in the price of certain commodity incentivizes the people who are producing those commodities. In this regard, the producers withhold the supply of those commodities that eventually results in increased prices. Furthermore, the inflation can also be caused by the supply shock like the interruption in oil supply to Southern US caused by Katrina devastated. It caused fluctuation dramatically in the real exchange rates instead of producing desired results. The fluctuation also triggers the development of three asymmetries in the exchange market. The first factors that come into play is the loss aversion which means that the losing side will suffer more loss vocally and acutely as compare to the less vocal winning side during the time of depreciation or appreciation. Hence, the fiscal policy will experience more disturbances.

The Wind and the Rain, and: Conservation Theory, and: Vespers, and: Shutdown, and: The "I Want" Song

The Wind and the Rain, and: Conservation Theory, and: Vespers, and: Shutdown, and: The "I Want" Song Rachel Richardson (bio) The Wind and the Rain In those first weeks—first because she was newly arrived, and so the scene had resetas unfamiliar, a blank line, even though for others it was the middle of a project at the office or a round of bloodwork or simply another February—in those days, weeks, her first of feeling windon her face and her mother's (my) hand at her forehead, shielding the skin from rain, the neighbors had mostly taken down the lit balls that blazed in trees from Thanksgiving through the darkest days, and wet yellow leaves clogged the gutters, slicking sidewalks. Someone had given us a fish hat,bit of whimsy, a chartreuse knit whose softness seemed right for someone so newly born, that jarring color and the fin swaying atop her head. She was bunched to my chest, so it swayed at my heart. Little fish, swept along the sidewalks of a pallid college town, raining and between rains. [End Page 119] Then bursts of sun from breaches in the pillowed clouds. Her mouth opened in an asymmetrical yawn because of a paralyzed lip— fairly common, the doctor said, and after she learns your expressions you'll only see it when she cries. Open, shut. Cry, be calmed. She wriggles into spring, the days get longer, andprobably it is here in the story that, down the street, a cluster of Nina's cellsbegin to mutate, though it will be another year before she feels the lump. Shakespeare's fools always let us in on the truth of the scene when the dramatic figures are too busy, caught in their morning plans, suiting up in the handmaid's skirts,writing a love note in a disguised hand. The way Feste, under clear skiesafter the royals' double wedding, skips offstage singing and the rain, it raineth every day. [End Page 120] Conservation Theory Turns out, if you love a forest, you're supposed to live in a small house.You're supposed to accept your grandmother's hand-me-down sewingrocker instead of snatching up the sectional at the liquidation sale.Turns out the forest is a family, so you don't cut down the elders. You need to learn about soil and beetles, heart rot, and the price of lumber in China. Turns out the world is not the silence under a crown of redwoods, not mostly. If you want a forest you should buy the trees. If you want a forestyou should deed them to the conservationists to keep from yourdescendants' desires. Zillow hungers for a listing. Treed lots photograph so beautifully,framing the dappled light. Turns out the price of lumber in China is going up up up. You're notsupposed to love a thing that costs so much to keep in the ground. The loggers are waiting. The local economy is counting on you. It's not your fault you loved to run your hand along smooth floorboardsas a child; it's not your fault you took the sweet air for granted. You grew tall in the shadows of great houses. [End Page 121] Vespers Lord, let me never start a forest fire.May my birth not herald the deathof a thousand doves.Lord, in this time of uncertainty, may I milkclear liquid from my breast, may themicroparticles of plastics not enterthe placenta. Lord, let them not enterthe blood. I will do better, Lord, atthy bidding, I will walk where'er I travel.In my body, Lord, is thy feast,I will preserve it as I preserve the habitatof the monarch butterfly in milkweedplanted up the length of my driveway.Lord, let me turn off notifications,turn away from membership pointsand free gifts with purchase.Let the electric grid cut me off.Lord, your endings are always in sighteven as you overcome us with abundance.Let me reach inbox zero, let me proceedas I wish to have begun. Let not my creakingbody distract you from...

Synchronized movement between US lumber futures and southern pine sawtimber prices and COVID-19 impacts

We analyzed the synchronized movements of lumber futures and southern pine sawtimber stumpage prices in the United States since 2011 and their response to COVID-19 events using wavelet analysis and event study. We found that the sawtimber and lumber prices have followed complex comovement patterns in the time–frequency domain and both reacted to COVID-19 events with a higher response intensity of the lumber price. Although they reacted differently to the early COVID-19 episodes and vaccine news, the sawtimber and lumber prices responded similarly to the COVID-19 pandemic declarations by the World Health Organization and US president, the US Food and Drug Administration panel’s recommendation of the first COVID-19 vaccine, and economic stimulus legislation. The patterns of synchronized movements between the sawtimber and lumber prices varied with time and frequency, but their comovement at low frequencies (>64 weeks) has strengthened since 2014 and been led by the lumber futures price; COVID-19 episodes have not changed this trend. The different magnitude of response of the two prices to the COVID-19-related events, as well as the long-term dominance of the lumber price in the comovement, reveals asymmetric price negotiation power and benefit distributions among the agents of the lumber value chain.

Understanding the Impacts of Plant Capacities and Uncertainties on the Techno-Economic Analysis of Cross-Laminated Timber Production in the Southern U.S.

Understanding the economic feasibility of cross-laminated timber (CLT), an emerging and sustainable alternative to concrete and steel, is critical for the rapid expansion of the mass timber industry. However, previous studies on economic performance of CLT have not fully considered the variations in the feedstock, plant capacities, manufacturing parameters, and capital and operating costs. This study fills this gap by developing a techno-economic analysis of producing CLT panels in the Southern United States. The effects of those variations on minimum selling price (MSP) of CLT panels are explored by Monte Carlo simulation. The results show that, across all the plant capacities from 30,000 to 150,000 m3/year, the MSP ranges from $345 to $609/m3 with a ±6%–9% range caused by the variations in feedstocks, key manufacturing parameters, capital and operating cost. The MSP decreases significantly along the increasing capacities. A sensitivity analysis exhibits that the lumber price, lumber preparing loss, plant capacity, and the installed costs of layering and gluing, finishing, and miscellaneous, are the top driving factors to CLT MSP. Supported by Geographic Information System, this study also studies the transportation cost of delivering CLT to customers under three CLT demanding levels (1%, 5%, 15%). The results show that the transportation cost is 1%–8% of the MSP. Lower demanding level or higher plant capacity can increase the transportation cost due to average longer delivering distance. When considering the delivered cost that sums MSP and transportation cost, larger plant capacity does not necessarily generate lower delivered cost.

Nowcasting of Lumber Futures Price with Google Trends Index Using Machine Learning and Deep Learning Models

Abstract Firms engaged in producing, processing, marketing, or using lumber and lumber products always invest in futures markets to reduce the risk of lumber price volatility. The accurate prediction of real-time prices can help companies and investors hedge risks and make correct market decisions. This paper explores whether Internet browsing habits can accurately nowcast the lumber futures price. The predictors are Google Trends index data related to lumber prices. This study offers a fresh perspective on nowcasting the lumber price accurately. The novel outlook of employing both machine learning and deep learning methods shows that despite the high predictive power of both the methods, on average, deep learning models can better capture trends and provide more accurate predictions than machine learning models. The artificial neural network model is the most competitive, followed by the recurrent neural network model.

Effects on Global Forests and Wood Product Markets of Increased Demand for Mass Timber

This study evaluated the effects on forest resources and forest product markets of three contrasting mass timber demand scenarios (Conservative, Optimistic, and Extreme), up to 2060, in twelve selected countries in Asia, Europe, North America, and South America. Analyses were carried out by utilizing the FOrest Resource Outlook Model, a partial market equilibrium model of the global forest sector. The findings suggest increases in global softwood lumber production of 8, 23, and 53 million m3 per year by 2060, under the Conservative, Optimistic, and Extreme scenarios, respectively, leading to world price increases of 2%, 7%, and 23%, respectively. This projected price increase is relative to the projected price in the reference scenario, altering prices, production, consumption, trade of forest products, timber harvest, forest growth, and forest stock in individual countries. An increase in softwood lumber prices due to increased mass timber demand would lead to the reduced consumption of softwood lumber for traditional end-use (e.g., light-frame construction), suggesting a likely strong market competition for softwood lumber between the mass timber and traditional construction industries. In contrast, the projected effect on global forest stock was relatively small based on the relatively fast projected biomass growth in stands assumed to be regenerated after harvest.

COVID-19 impacts on U.S. lumber markets

The Covid-19 pandemic led to an unprecedented increase in the U.S. price of softwood lumber by more than 300%. The reasons for this increase have been attributed to constraints on supply caused by pandemic-induced labor shortages, and increased demand for lumber caused by a Covid-19 related boom in domestic real estate and home improvements. In this paper, we examine the effect that these factors might have had on the increase in prices and the related changes in the welfare of U.S. lumber manufacturers and downstream users of lumber. We examine three cases where the demand function shifts outwards: (1) the lumber supply function remains unchanged; (2) the U.S. lumber supply function and that of its trading partners shifts inwards; and (3) U.S. lumber producers restrict output at its pre-Covid level. Overall, we find that U.S. producers gained between $0.7 and $8.0 billion per quarter as a result of the pandemic, while downstream processors gained $639 million. We argue, however, that the ultimate consumer of the downstream products that require lumber as an input (housing construction, furniture) might well be worse off as surplus lost as a result of reduced expenditures on commodities and services restricted by Covid-19 are not quite recovered when spending switches to lumber-related commodities.

The ecological and economic values of a 50 years old secondary forest in East Kalimantan, Indonesia

Abstract. Karmini, Karyati, Widiati KY. 2021. The ecological and economic values of a 50 years old secondary forest in East Kalimantan, Indonesia. Biodiversitas 22: 4597-4607. Secondary forests in the tropics are often ignored since they are assumed to have low ecological functions while on the other hand the economic values have been reduced. This study aimed to analyze the ecological and economic values of a 50-year secondary forest in East Kalimantan that experienced several various land-use changes. The ecological aspects analyzed were stand structure, floristic composition, and species diversity. Economic aspects include log prices, logging costs, profit margins, and stumpage values. A vegetation survey of woody trees with a diameter at breast height of more than 5 cm was carried out on ten plots measuring 20 m × 20 m each. A total of 437 trees belonging to 38 species, 30 genera, and 19 families were recorded with Moraceae and Euphorbiaceae were the most dominant families with Family Important Value (FIV) of 86.79. The three most dominant species were Macaranga motleyana (IVi of 50.95), Artocarpus elasticus (IVi of 34.41), and Symplocos fasciculata (IVi of 31.46). The trees in the study plot have a diversity index of 1.33, dominance index of 0.07, evenness index of 0.37, and species richness of 6.09. The average logging cost, logs price, lumber price, profit margin, and stumpage value at secondary forest were USD69.43 m-3, USD44.63 m-3, USD100.03 m-3, USD10.30 m-3, and USD28.73 ha-1, respectively. The 50 years old secondary forests in East Kalimantan have biodiversity, especially trees that have economic value, therefore their existence needs to be preserved and their use is carried out by maintaining and increasing biodiversity.

COVID-19 and Forests in Canada and the United States: Initial Assessment and Beyond

Information on the initial effects of a novel coronavirus, COVID-19, during 2020 on forests in Canada and the United States was derived from existing published studies and reports, news items, and policy briefs, amplified by information from interviews with key informants. Actions taken by governments and individuals to control the spread of the virus and mitigate economic impacts caused short-term disruptions in forest products supply chains and accelerated recent trends in consumer behavior. The COVID-19 containment measures delayed or postponed forest management and research; a surge in visitation of forests near urban areas increased vandalism, garbage accumulation, and the danger of fire ignitions. Forests and parks in remote rural areas experienced lower use, particularly those favored by international visitors, negatively affecting nearby communities dependent upon tourism. Physical distancing and isolation increased on-line shopping, remote working and learning; rather than emerging as novel drivers of change, these actions largely accelerated existing trends. On-line shopping sales had a positive effect on the packaging sector and remote working had a negative effect on graphic paper manufacturing. More time at home and low interest rates increased home construction and remodeling, causing historically high lumber prices and localized material shortages. The response to the pandemic has shown that rapid social change is possible; COVID-19 presents a once in-a-lifetime opportunity to shift the global development paradigm toward greater sustainability and a greener, more inclusive economy, in which forests can play a key role. In both Canada and the United States, the notion of directing stimulus and recovery spending beyond meeting immediate needs toward targeting infrastructure development has momentum.

Analysis of Lumber Prices Time Series Using Long Short-Term Memory Artificial Neural Networks

This manuscript confirms the feasibility of using a long short-term memory (LSTM) recurrent neural network (RNN) to forecast lumber stock prices during the great and Coronavirus disease 2019 (COVID-19) pandemic recessions in the USA. The database was composed of 5012 data entries divided into recession periods. We applied a timeseries cross-validation that divided the dataset into an 80:20 training/validation ratio. The network contained five LSTM layers with 50 units each followed by a dense output layer. We evaluated the performance of the network via mean squared error (MSE), root mean squared error (RMSE), and mean absolute error (MAE) for 30, 60, and 120 timesteps and the recession periods. The metrics results indicated that the network was able to capture the trend for both recession periods with a remarkably low degree of error. Timeseries forecasting may help the forest and forest product industries to manage their inventory, transportation costs, and response readiness to critical economic events.

The Forestry Investment Total Return (FITR) Index

There is an emerging global trend toward more responsible and sustainable investment practices that is creating an increased appetite for forestry investments. This is against a backdrop of a dearth of forestry investment performance data of the kind suitable to aid econometrically significant investment projections. This article uses historical roundwood timber and lumber price data combined with a forestry discount rate to synthetically create historical forestry investment returns for the last two centuries. A Forestry Investment Total Return (FITR) Index is created from these data. A key advantage of the index is not relying on smoothed timber prices, making returns more representative of their reporting period. The FITR Index shows forestry investment outperforming equities over long durations, with a lower standard deviation of returns and a positive, rather than negative, skew of returns. The article suggests that responsible and sustainable investments can produce strong investment performance. <b>TOPICS:</b>Other real assets, mutual funds/passive investing/indexing, performance measurement, ESG investing <b>Key Findings</b> ▪ The study estimates US forestry investment returns averaged 9.24% per annum from 1871 to 2018 with a standard deviation of returns of 12.3% and a positive skew of 88%. Comparable returns on US equities were 8.95% per annum with a higher standard deviation of 17.9% and a negative skew of 13%. ▪ Estimated forestry returns are based on an assumed forestry discount rate and changes in US timber prices over the period. The article shows that changes in timber prices relative to consumer prices have a consistent pattern going back to 1269. ▪ Forestry investment is likely to be a win–win for investors seeking sustainable investments and for policymakers by providing the potential for strong investment returns while also tackling environmental and climate change.

Regional Economic Impacts from Timber Check Dam Construction—A Comparison with Concrete Check Dam Construction

Recently, many mountain disasters caused by natural phenomena, such as typhoons and heavy rains, have struck Japan, where check dams are used as important disaster prevention structures. Meanwhile, increased timber use in Japan is expected to revitalize regional economies, thus drawing attention to the use of timber in check dams. However, comparisons between timber and concrete check dams, in terms of their impact on the regional economy, have been overlooked in previous studies. Therefore, targeting Akita Prefecture in Japan, we evaluated quantitatively the respective regional economic impact of timber and concrete check dam construction through an input–output analysis. An extended input–output table was developed based on the revenue and expenditure data obtained from interviews with check dam construction companies. The construction cost and amount of sediment runoff prevention of a concrete check dam was unified with those of a timber check dam to evaluate their respective economic impact. In both cases, the impact of timber check dam construction was about 12 to 13% larger. In brief, timber check dam construction was found to have a more positive impact on the regional economy than concrete check dam construction. However, with the regional self-sufficiency ratio of the lumber and wood products sector at less than 20%, or the lumber price at 60% of its current price, the economic impact of constructing a timber check dam becomes smaller than that of a concrete check dam. In other words, it is important to harvest, process, and use timber regionally to contribute to the regional economy. Specifically, using timber that is processed, rather than simply harvested, in the region has a larger economic impact on the region. Additionally, in timber check dam construction, procuring inexpensive timber and reducing construction costs may be a trade-off for revitalizing the regional economy.

Asymmetric Price Transmission of Hardwood Lumber Imported by China after Imposition of the Comprehensive Commercial Logging Ban in All Natural Forests

The Comprehensive Commercial Logging Ban in All Natural Forests (CCLB) policy, introduced in April 2015, aims to protect all natural forests in China. It has impacted both China’s domestic timber supply and imports. We investigated price transmission in China’s hardwood lumber imports resulting from the implementation of this policy. We selected three hardwood lumber species, i.e., Sapelli (Entandrophragma), Mandshurica (Fraxinus), and Laurel (Terminalia), and used their daily prices from 30 April 2015 to 30 November 2017. Threshold co-integration and threshold error correction models are employed for this analysis. We identified a structural breakpoint on 30 November 2016, and consequently partitioned the data series into two parts for the two subperiods separated by the breakpoint. The empirical results indicated that there was asymmetric price transmission (APT) for both subperiods. Adjustment of positive price deviations to the long-term equilibrium levels was slower than that of negative price deviations. In the short term, the price of high-quality lumber evolved independently, whereas the price of lower-quality lumber tended to return to the equilibrium. The APT reflects a redistribution of welfare, benefiting the exporters more than the importers. We find that positive discrepancies in each price pair were inclined to be more persistent in the first subperiod than in the second subperiod. This could attribute to the fact that the degree of CCLB intervention in the former one was higher than in the latter one.

Quantifying the Announcement Effects in the U.S. Lumber Futures Market

The impact of information release from public report announcements has been widely investigated in many commodity markets, but little attention has been paid to the lumber market. In this paper, we use generalized autoregressive conditional heteroskedasticity (GARCH) models to examine the effect of two housing market reports, namely the New Residential Construction (Housing Starts) and the New Residential Sales reports, on the U.S. lumber futures market from 2000 to 2017. Our results suggest that the housing starts report indeed affects lumber market volatility, while the new home sales report exerts a minor impact. We further find that the effect of the two reports decreases with inventory levels and differs depending on the nature of the news. When the level of inventory is low, larger-than-expected housing starts has a more substantial effect than lower-than-expected housing starts. During periods of abundant stocks, however, lower-than-expected housing starts increase the volatility more than larger-than-expected news. For the new home sales reports, we find that while lower-than-expected sales do not affect lumber price volatility, larger-than-expected sales do increase the volatility.

Techno-economic analysis for manufacturing cross-laminated timber

Cross-laminated timber (CLT) is a bio-based building material that enables rapid construction and buildings with low embodied energy. Despite its comparative maturity in European markets, relatively little information regarding process design and economics for the manufacture of cross-laminated timber is available in the literature. Two techno-economic analyses were conducted to quantify the mill-gate cost of cross-laminated timber. The cross-laminated timber manufacturing process was described, and costs were analyzed for two facility scales. Cross-laminated timber produced at the large-scale facility using lumber priced at an average value for the northwest United States has a minimum selling price of $536/m3. Sensitivity analyses were used to define the impact of plant size, asset utilization, lumber price, plant capital cost, material waste, and other variables on minimum selling price. The cost of cross laminated timber rises quickly when a facility is not fully utilized. The second-ranking cost controlling variable is lumber price, while energy prices have minimal influence. The price of cross laminated timber can be optimized by locating a facility near low-cost lumber. The lowest-price region analyzed was the southeast United States using Southern Pine, which reduced the cost of cross laminated timber to $518/m3.

Dealing with the Housing Crisis: A Study on Softwood Sawmills in the Southern United States

Abstract In this article we discuss the impact of the recent housing crisis and economic recession on the southern US softwood sawmill industry. We use the first difference model to quantify the impact of market conditions on the performance of independent sawmills including their adjustments and responses between 2006 and 2012. Our results show that lumber and log price change, adjustment in product mix and labor input, and export strategy were key factors influencing production and capacity utilization levels during and after the housing crisis. Furthermore, these factors contributed in different magnitudes in the housing crisis and recovery periods.