VALUING A TIMBER HARVEST CONTRACT AS A HIGH‐DIMENSIONAL AMERICAN CALL OPTION VIA LEAST‐SQUARES MONTE CARLO SIMULATION

Abstract Industrial timberland ownership in the United States has shifted substantially in the last 20 years. Having sold their fee‐owned timberlands, forest products companies relied heavily on the open market for raw timber. To reduce their exposure to market risks, however, forest products companies have been using a number of supply chain instruments, such as timber harvest contracts. As these vehicles become increasingly important to the forest industry, it is necessary and important to determine their economic values. In this study, we treated a 3‐year timber harvest contract on a 30‐year‐old loblolly pine plantation as a high‐dimensional American call option and calculated its value by the least‐squares Monte Carlo simulation technique. The estimated values of such a contract ranged from $1,693/ac to $1,984/ac under two timber price assumptions. With reasonable starting timber prices and strike price in the simulation, random timber prices led to higher contract values. Results from this study can help private landowners, timber brokers, and forest products companies better manage their business risks.     

THE ROLE OF STOCHASTIC MONOTONICITY IN THE DECISION TO CONSERVE OR HARVEST OLD-GROWTH FOREST

The problem of when, if ever, a stand of old-growth forest should be harvested is formulated as an optimal stopping problem, and a decision rule to maximize the expected present value of amenity services plus timber benefits is found analytically. This solution can be thought of as providing the “correct” way in which cost-benefit analysis should be carried out. Future values of amenity services provided by the standing forest and or timber are considered to be uncertain and are modeled by Geometric Poisson Jump (GPJ) processes. This specification avoids the ambiguity which arises with Geometric Brownian Motion (GBM) models, as to which form of stochastic integral (Itô or Stratonovich) should be employed, but more importantly allows for monotonic (yet stochastic) processes. It is shown that monotonicity (or lack of it) in the value of amenity services relative to timber values plays an important part in the solution. If amenity values never go down (or never go up) relative to timber values, then the certain-equivalence cost-benefit procedure provides the optimal solution, and there is no option value. It is only to the extent that the relative valuations can change direction that the certainty-equivalence procedure becomes sub-optimal and option value arises.     

ENVIRONMENTAL AND FINANCIAL SUSTAINABILITY OF FOREST MANAGEMENT PRACTICES

One of the guiding themes for forest management policy throughout much of North America is sustained yield. The basic premise behind this theme is that a constant or nondeclining flow of services from the forest is socially desirable. Unfortunately, the act of capturing the benefits of this service (timber harvesting) often has detrimental effects on the timber-productive capacity of a forest site. This paper presents a dynamic program that is used to determine the optimal harvest system choice for a timber stand described by average piece size, stand density, a measure of site quality, and stumpage value. The harvest systems are defined by logging costs, reforestation and rehabilitation costs, and the impact of the system on the productivity of the site. An application of the model is presented for lodgepole pine in Alberta. We conclude that, at high discount rates, soil conservation is not economically rational. At lower discount rates, some degree of soil conservation is desirable on the more productive sites. At lower discount rates, there also appears to be an incentive for more intensive forest management. Limitations on acceptable harvest practices can have a large impact on optimal rotation age and the volume harvested. There is a large opportunity cost resulting from a requirement for sustainable volume production because of the impact of harvesting on soil productivity.     

PUBLIC AND PRIVATE FOREST DISTURBANCE REGIMES IN THE SOUTHERN APPALACHIANS

The choice to harvest timber depends on, among other things, the accessibility and location of the forest. This paper examines observed harvest choices derived from satellite imagery and tests for relationships between harvest probability and location, quality, and ownership attributes of the site. Results indicate that the overall probability of harvesting for public lands is significantly lower than for private lands. Substantially different disturbance patterns relative to location attributes are also established for these groups. Results suggest a way to include spatially explicit information regarding private land management in public land management plans. An example demonstrates how alternative uses of public lands might be considered in the broader context of a multiple ownership landscape.     

THE ECONOMICS OF TIMBER SUPPLY: AN ANALYTICAL SYNTHESIS OF MODELING APPROACHES

The joint supply of timber and other services from forest environments plays a central role in most forest land debates. This paper defines a general conceptual model of timber supply that provides the context for discussing both individual harvest choice and aggregate supply models. While the structure and breadth of these models has developed considerably over the last twenty years, unresolved issues remain. Supply formulations that account for the quality and vintage distribution of forest capital will be necessary for improving medium- and long-run forecasts. This will be especially important for examining the potential impacts of structural changes in forest production and timber markets. In addition, consistent aggregation of individual owners to total supply will be required to address changing forest land ownership patterns.     

AN OPTIMIZATION APPROACH TO IDENTIFYING TIMBER SUPPLY FUNCTION COEFFICIENTS

This paper examines an optimization approach to identifying short-run timber supply function coefficients when the form of the supply function is known. By definition, a short-run timber supply function is a functional relationship between the optimal harvest level in each period (e.g., each year) and the actual forest-market state in the same period. The short-run timber supply function represents the optimal harvest decision policy, and therefore, the problem of optimal harvesting can be formulated as a problem of determining this function. When the form of the supply function is known, the problem becomes one of identifying the coefficients of the supply function. If the management objective is to maximize the expected present value of net revenues from timber harvesting over an infinite time horizon, and the timber price process is, in a sense, stationary, the supply function coefficients correspond to the optimal solution to an anticipative optimization problem. In this case, the supply function coefficients can be determined by maximizing the expected present value of the net revenues from timber harvesting, where periodic harvest levels are determined using the supply function. Numerical results show that the short-run supply functions determined using this approach gives good approximations of the true supply function.     

Optimal harvest strategy for even‐aged stands with price uncertainty and risk of natural disturbances

We present a reservation price model to examine the joint impacts of natural disturbances and stumpage price uncertainty on the optimal harvesting decision for even‐aged forest stands. We consider a landowner who manages a loblolly pine stand to produce timber and amenities, under age‐dependent risk of wildfires and uncertainty in future timber prices. We show that the incorporation of risk of wildfires decreases the optimal reservation prices. The inclusion of risk of wildfires leads to lower land values and reduces the mean harvest age compared with the case of no‐risk of wildfires. Higher economic gains are obtained with the reservation price strategy compared with the deterministic rotation age model—a difference in the land value of $2,326 ha^?1 (21%) between the two approaches. Recommendations for Resource Managers

• Our adaptive harvest strategy shows that the incorporation of risk of wildfires decreases the optimal reservation prices compared with the case of no‐risk of wildfires.
• Low reservation prices—a price that makes the landowner indifferent between harvesting or waiting longer—result in lower economic benefits for landowners and potential conversions of lands to nonforest use.
• Forest management practices oriented to reduce the effects of catastrophic disturbances, for example, creating a more complex forest structure with different stand densities, become imperative to ensure the sustainability of forestlands in the US South.
• Our analysis also suggests that the valuation of forestry investments should consider not only the risk of catastrophic events but also uncertainty in future timber prices. Higher appraisals of land value are obtained when timber price uncertainty is explicitly recognized, providing financial incentives for landowners to invest in forestry.

     

Forestry management under uncertainty

The forest harvest and road construction planning problem consists fundamentally of managing land designated for timber production and divided into harvest cells. For each time period the planner must decide which cells to cut and what access roads to build in order to maximize expected net profit. We have previously developed deterministic mixed integer linear programming models for this problem. The main contribution of the present work is the introduction of a multistage Stochastic Integer Programming model. This enables the planner to make more robust decisions based on a range of timber price scenarios over time, maximizing the expected value instead of merely analyzing a single average scenario. We use a specialization of the Branch-and-Fix Coordination algorithmic approach. Different price and associated probability scenarios are considered, allowing us to compare expected profits when uncertainties are taken into account and when only average prices are used. The stochastic approach as formulated in this work generates solutions that were always feasible and better than the average solution, while the latter in many scenarios proved to be infeasible.     

TIMBER SUPPLY UNDER DEMAND UNCERTAINTY: WELFARE GAINS FROM PERFECT COMPETITION WITH RATIONAL EXPECTATIONS

ABSTRACT. This paper presents a noneconometric approach to estimating the short‐run timber supply function based on optimal harvest decisions. Determination of optimal harvest levels and estimation of supply function coefficients are integrated into one step by incorporating a parametric short‐run timber supply function into the harvest decision model. In this manner we convert the original harvest decision model into a new optimization problem with the supply function coefficients functioning as “decision variables.” Optimal solution to the new decision model gives the coefficients of the short‐run supply function and, indirectly, the optimal harvest levels. This approach enables us to develop stochastic models of the timber market that are particularly useful for forest sector analysis involving comparison of alternative institutional regimes or policy proposals and when the timber market is affected by stochastic variables. For demonstration purposes, we apply this method to compare the performances of two timber market regimes (perfect competition and monopoly) under demand uncertainty, using the Swedish data. The results show that the expected timber price is 22 percent lower and the expected annual timber supply is 43 percent higher in the competitive market than in the monopoly market. This confirms the theoretical result that monopoly reduces supply and increases price. The expected social welfare gain from perfect competition over monopoly is about 24 percent.     

OPTIMAL FOREST STAND MANAGEMENT WHEN BENEFITS ARE DERIVED FROM CARBON

The management of second-growth and old-growth forest stands has important implications for the global carbon cycle. This paper considers the optimal forest rotation when flows of CO₂ to carbon have positive value. If benefits are derived only from carbon, then typically it will never be optimal to harvest any forest stands. This result is a formalization and extension of Harmon et al. [1990]. Private forest owners will often maximize net returns to timber, ignoring benefits from carbon sequestration. Thus, the privately and socially optimal rotations will not generally coincide. We show that the socially optimal rotation is always greater than the privately optimal rotation and less than or equal to the rotation when only carbon is valued.     

Modeling target volume flows in forest harvest scheduling subject to maximum area restrictions

In forest harvest scheduling problems, one must decide which stands to harvest in each period during a planning horizon. A typical requirement in these problems is a steady flow of harvested timber, mainly to ensure that the industry is able to continue operating with similar levels of machine and labor utilizations. The integer programming approaches described use the so-called volume constraints to impose such a steady yield. These constraints do not directly impose a limit on the global deviation of the volume harvested over the planning horizon or use pre-defined target harvest levels. Addressing volume constraints generally increases the difficulty of solving the integer programming formulations, in particular those proposed for the area restriction model approach. In this paper, we present a new type of volume constraint as well as a multi-objective programming approach to achieve an even flow of timber. We compare the main basic approaches from a computational perspective. The new volume constraints seem to more explicitly control the global deviation of the harvested volume, while the multi-objective approach tends to provide the best profits for a given dispersion of the timber flow. Neither approach substantially changed the computational times involved.     

TEMPORAL AGGREGATION AND TESTING FOR TIMBER PRICE BEHAVIOR

ABSTRACT. Different harvest timing models make different assumptions about timber price behavior. Those seeking to optimize harvest timing are thus first faced with a decision regarding which assumption of price behavior is appropriate for their market, particularly regarding the presence of a unit root in the timber price time series. Unfortunately for landowners and investors, the literature provides conflicting guidance on this subject. One source for the ambiguous results of unit root tests of timber prices may involve data problems. We used Monte Carlo simulations to show that aggregating observations below their observed rate resulted in similar power reductions and empirical size distortions across three classes of unit root tests. Moving‐average error structures can also affect power and sizes of tests on period‐averaged data. Such error structures can also be created by the kind of temporal averaging common in reported timber prices. If we take timber prices at their face value and therefore ignore these sampling error and temporal aggregation complications, we find that unit root tests on southern timber prices support a unit root in 158 out of 208 product‐deflation combinations tested, random walks in 38 of the series found to be nonsta‐tionary, and stationarity in none. However, if we recognize temporal aggregation errors, unit root tests more commonly favor stationarity, especially for pulpwood stumpage. Because price trends for sawtimber and pulpwood products may behave differently even in the same region, stochastic harvest timing models must be developed that allow their multiple products to follow different price paths.     

Long-range timber supply planning for a vertically integrated paper mill

We consider a vertically integrated papermaking operation composed of an integrated pulp and paper mill with its regional supply network. Considering land procurement and harvest rotation as strategic decision variables, we construct a model to establish a long-range timber supply plan that minimizes the total discounted cost of meeting annual virgin wood fiber demand over an infinite horizon. Under appropriate assumptions on costs and storage, the land procurement and harvest rotation decisions are separable with harvest rotation being determined via a forest economics-type equation and land procurement being determined by a newsvendor-type equation.     

ECONOMIC EVALUATION OF BIOTECHNOLOGICAL PROGRESS: THE EFFECT OF CHANGING MANAGEMENT BEHAVIOR

Abstract The paper assesses the welfare effects of biotechnological progress, as exemplified by tree improvements, using a partial equilibrium model. Timber demand is assumed to be stochastic and the distributions of its coefficients known. The coefficients of a log‐linear supply function are determined by maximizing the expected present value of the total surplus of timber production, both in the presence and in the absence of genetically improved regeneration materials. The supply functions are then used to estimate the expected present values of the total surplus in different cases through simulation. These estimates enable us to assess the direct effect and the effect of changing harvest behavior on the expected present value of the total surplus. The main results of the study are (i) the presence of genetically improved regeneration materials has significant impacts on the aggregate timber supply function; (ii) the application of genetically improved regeneration materials leads to a significant increase in the expected present value of the total surplus; and (iii) a considerable proportion of the welfare gain results from the change in harvest behavior. A conclusion we draw from this study is that ignoring the influences of technological and policy changes on behavior can lead to significantly biased welfare estimates. We view the model as a potential approach to conducting counterfactual policy comparisons in economics without forward‐looking data.     

Carbon sequestration and land management under uncertainty

Uncertainty about the role of forestry and land-use change in mitigating global warming is addressed using a possibilistic linear programming model of forest and agricultural land management. The objective is to maximize the cumulative net discounted returns in the two sectors, while meeting specific carbon-uptake goals and maintaining stable flows of timber over the planning horizon. Because of ambiguity related to timber yield and carbon parameters, and vagueness of policy targets (economic returns, timber production and carbon-uptake), ordinal measures of uncertainty are applied. While ordinality entails loss of precision, it makes it possible to solve complex problems. This paper compares land-use policies in the boreal forest zone of Northeastern British Columbia under uncertainty with those from a more typical scenario that applies best-guess parameter values. Including uncertainty explicitly into the possibility analysis changes optimal land-use and forest management, and leads to different levels of projected timber supply, economic performance and carbon sequestration. The amount of carbon dioxide (CO₂) removed from the atmosphere and the economic cost of carbon uptake are sensitive to how the decision-maker tackles uncertainty.     

MULTIPLE USE VALUES AND OPTIMAL STEADY STATE AGE DISTRIBUTIONS

Forest management today, generally, focuses not only on wood values but also on the many other amenities and services provided by growing forests. The significance of these multiple use values was recognized by Hartman [1976] who derived a formula for the optimal rotation for a single stand when the services provided by the stand throughout its life are considered in addition to the value of the final harvest. Some more recent work has focused on the case of multiple stands where the amenity values at a point in time depend on the age distribution of the stands at that time. One approach to harvesting multiple stands for wood values alone is the forestry maximum principle developed by Heaps [1984] and Wan [1985]. It will be shown here how the forestry maximum principle can be modified to incorporate the amenity services provided by the growing forest. The optimal steady state age distributions for the multiple stand forest can then be identified and described with the help of Hartman's rotation formula.     

Timber harvest scheduling with price uncertainty using Markowitz portfolio optimization

Harvest scheduling models need to account for uncertain revenue predictions when minimizing risk of financial loss is an important management objective. In this paper, we present methods for estimating the means and covariances of stumpage prices and incorporating them in harvest scheduling models. We approached the estimation problem by fitting time-series models to loblolly pine sawtimber and pulpwood stumpage prices in Georgia, USA, and deriving formulas for means and covariances of price predictions. Statistical evidence supported integrated autoregressive models, which caused covariances of price predictions to increase with time. The means and covariances of price predictions were combined with timber yield and land value predictions to give exact formulas for the revenue means and covariances of timber management activities. Sawtimber regimes dominated pulpwood regimes by providing higher mean revenues across a wide range of revenue variances. Harvest scheduling results for a hypothetical forest of pine plantations showed that the forest plan that maximized mean income without concern for risk (expressed as the standard deviation of income) involved sawtimber production with a 35-year rotation age. Risk was reduced 30% with little effect on mean income by using shorter-rotation sawtimber regimes. Risk was reduced 80% by using a mix of short-rotation sawtimber and pulpwood regimes because pulpwood price was only weakly correlated with sawtimber price. The latter risk-reduction came at the expense of mean income, which was reduced by as much as 50%. The risks and compositions of optimal forest plans were extremely sensitive to assumptions about the range of future prices that were inherent in different prediction models. This sensitivity emphasizes the importance of carefully determining the decision makers beliefs about stumpage price behavior.     

Introducing cost-plus-loss analysis into a hierarchical forestry planning environment

Cost-plus-loss analysis of data for forestry planning has often been carried out for highly simplified planning situations. In this study, we suggest an advance in the cost-plus-loss methodology that aims to capture the hierarchical structure and iterative nature of planning by the large forest owner. The simulation system that is developed to simulate the planning process of the forest owner includes the tactical and operational levels of a continuous planning process. The system is characterized by annual re-planning of the tactical plan with a planning horizon of ten year and with the option to reassess data for selected stands before operational planning. Operational planning is done with a planning horizon of two years and the first year of the plan is considered to have been executed before moving the planning process one year forward. The annual cycle is repeated 10 times, simulating decisions made over a ten-year time horizon. The optimizing planning models of the system consider wood flow requirements, available harvest resources, seasonal variation of ground conditions and spatiality. The data used are evaluated according to standard procedures in cost-plus-loss analysis. Results from a test case indicate high decision losses when planning at both levels is based on the type of data prevalent in the stand databases of Swedish companies. The losses can be reduced substantially if higher-quality data are introduced before operational planning. In summary, the results indicate that the method makes it possible to analyze where in the planning process one needs better data and their value.     

A cutting plane method for solving harvest scheduling models with area restrictions

We describe a cutting plane algorithm for an integer programming problem that arises in forest harvest scheduling. Spatial harvest scheduling models optimize the binary decisions of cutting or not cutting forest management units in different time period subject to logistical, economic and environmental restrictions. One of the most common constraints requires that the contiguous size of harvest openings (i.e., clear-cuts) cannot exceed an area threshold in any given time period or over a set of periods called green-up. These so-called adjacency or green-up constraints make the harvest scheduling problem combinatorial in nature and very hard to solve. Our proposed cutting plane algorithm starts with a model without area restrictions and adds constraints only if a violation occurs during optimization. Since violations are less likely if the threshold area is large, the number of constraints is kept to a minimum. The utility of the approach is illustrated by an application, where the landowner needs to assess the cost of forest certification that involves clear-cut size restrictions stricter than what is required by law. We run empirical tests and find that the new method performs best when existing models fail: when the number of units is high or the allowable clear-cut size is large relative to average unit size. Since this scenario is the norm rather than the exception in forestry, we suggest that timber industries would greatly benefit from the method. In conclusion, we describe a series of potential applications beyond forestry.