|GUIDELINES for||. . .|
|Developing Stand Density Management Regimes|
Harvesting costs can be categorized by harvesting phase, such as road and site development costs, tree-to-truck (felling and yarding) costs, log haul (loading, truck haul, towing or barging) costs and administration and overhead costs. The effects of density management on each cost phase must be accounted for in any analysis.
Development, overhead and administrative costs are fixed harvesting costs. Density management treatments which result in changes to the volume of timber produced by a stand will not affect total fixed harvesting costs, but will affect the average fixed costs per cubic metre of timber produced.
Density management treatments have a larger impact on certain components of tree-to-truck and log haul costs, called variable costs. For instance, log haul costs are influenced primarily by changes in loading time resulting from the number of logs required to complete a load. However, the cost of the loading component of log haul costs is relatively small. Density management practices have their greatest impact on tree-to-truck costs, particularly the yarding component.
For further information on more detailed aspects of harvesting costs, refer to the Ministry of Forests Coast and Interior Appraisal Manuals (B.C. Ministry of Forests 1995a, b and Stone 1996a and Stone et al. 1996).
Milling costs need not be accounted for in economic analysis based on log values, since the log prices used in the analysis should already reflect differences in milling costs. However, when the analysis is based on lumber and wood chip end products, the effects of density management treatments on milling costs must be considered. Larger log sizes result in lower milling costs, although other factors, such as log taper, must also be considered. Stone (1996a) and Stone et al. (1996) illustrate a method for predicting changes in milling costs.
The cost of stand density treatments is usually a function of site and stand conditions such as road access and travel distance, the average slope of the site, original stand density and the number of trees removed, and the average height and diameter of the trees removed. Local labour market conditions may also influence treatment prices. For instance, the number of silviculture operators available to bid on a project and the amount of work currently under contract may have a substantial effect on treatment prices. Local market treatment costs should be used to assess density management options. If this information is unavailable, regional average costs may be used.
Silviculture investments are characterized by treatment costs and benefits that occur in different time periods through the rotation. These costs and benefits must be converted to present values in order to assess investment efficiency. The purpose of a discount rate in an economic analysis is to reflect the preference that societies, organizations or individuals have for present versus future consumption.
Income received or costs incurred today are considered to be worth more than income or costs that occur in some future time period. The rate of discount is used to determine how much less future revenues or expenditures represent in today's dollars. Discounting permits a comparison of various flows of benefits and costs occurring over time in a consistent and logical manner.
Choice of a discount rate is influenced by markets for capital, opportunity costs of capital, risk and perceptions of risk, uncertainty, inflation expectations, differences in the rate of borrowing and lending, as well as other factors. Governments and private sectors are both influenced by these factors. However, private sectors of the economy are affected to a greater degree due to uncertainties in future product demand, natural resource conservation policies, and the wider range of alternative investment opportunities available.
Heaps and Pratt (1989), in The Social Discount Rate for Silvicultural Investments, estimated the discount rate using the social opportunity cost of capital for public sector investments in Canada, and found a range of between 3 and 7%, depending on how risk and uncertainty are accounted for. They argued that a risk-free rate should be used for silviculture investments, and recommended a discount rate of between 3 and 5%.
The Ministry of Forests uses a 4% real rate of discount for public sector forestry investment analysis. The discount rate, whether public or private, is a "real" discount rate. This means that it does not include any inflationary expectations. Inflation is "netted out" of a real discount rate since it is assumed to affect both costs and prices equally over time.
Whatever discount rate is selected, it must be used consistently for all silviculture treatments. For example, although a lower discount rate would "improve" the economics of juvenile spacing, it would also reduce the benefits derived from commercial thinning. The discount rate is clearly a two-edged sword.
Sensitivity analysis is an important analytical method used to evaluate the effects of risk and uncertainty in economic analyses. Sensitivity analysis involves re-calculating the site value of a silviculture treatment using a range of values around key factor assumptions. Key factors in an economic analysis include future revenue, harvest cost, milling costs, silviculture costs (regeneration, tending, protection, administration), and investment period (rotation length).
For example, a sensitivity analysis of future harvesting cost would involve repeating the economic analysis using harvesting costs that are slightly higher and slightly lower than the expected value. The usual approach is to test values within plus and minus an arbitrary percentage (e.g., 10%) of the expected value. The sensitivity analysis is performed while keeping all other key factors constant.
The three site values from the sensitivity analysis are then compared; large differences indicate that site value is "sensitive" to small changes in harvesting cost. Sensitivity in one or more key factors suggests that the economic analysis is not robust, and may lead to errors of interpretation. The outcome of the sensitivity analysis will determine whether all input values and assumptions should be re-evaluated.
Copyright 1999 Province of British Columbia