of a forestry investment
Forestry projects are a form of capital investment with a particularly long time horizon, and as such present an interesting case of capital budgeting. In many countries, plantation forestry has traditionally been the domain of government agencies, e.g. the national Forestry Commission in the UK and the various state forestry services in Australia. Timber was considered to be a critical economic resource but the long production period meant that only governments had the long-term perspective and capacity to enter into forestry investments. This situation has changed markedly in the past fifty years, with probably the bulk of forestry investment in most countries being undertaken by private companies and individuals. The need for the establishment of plantations has been stimulated by decreasing supplies of timber from native forests through unsustainable logging practices, and the withdrawal of large areas from logging because of their being set aside as protected areas, particularly in tropical counties.
An integral component of investment in forestry is the need for financial information about the likely cash flows associated with the establishment, management and final harvest of a plantation. This chapter uses the development of a financial model for forestry investment as a case study of financial modelling. The financial evaluation of forestry projects poses many challenges and this chapter examines the key parameters for forestry appraisal and some of the problems faced by developers of financial models. The development of a model for the evaluation of forestry projects is outlined, following the step-by-step approach which was actually used by the model developers. This basic model framework is then used to illustrate how to undertake a sensitivity analysis and risk simulation.
Study objectives
After studying this chapter the reader should be able to: r appreciate the need for estimates of forestry returns
r identify the problems encountered in developing a forestry financial model
r appreciate the difficulty in establishing cash flow estimates for long-lived forestry projects r discuss the methods of allowing for risk in the evaluation of forestry projects
r develop a simple forestry model
r apply sensitivity and risk simulation to forestry projects.
Key parameters for forestry models
The most common cash outflows associated with forestry operations include establishment costs (e.g. land and site preparation such as clearing, fencing and preparing the soil; purchase of planting stock; planting, mulching and watering), weed control, fertilization, pruning and thinning to waste, and commercial harvesting. The major cash inflows come from the sale of commercial thinnings and the final harvest, and perhaps tree residues such as firewood. In some situations, revenues are also derived from non-wood forest products such as wild berries, mushrooms, honey and hunted game, all of which are made possible by the environment created by the forest.
Cash flow estimates of growing native timbers as a business enterprise will vary depending on a variety of factors, some of the more important of which are:
r Site characteristics (e.g. climate, soil, aspect) r Species mixture
r Silvicultural system (e.g. planting density, weed control and pruning) r Harvest age and harvest scheduling
r Final yield or mean annual increment of individual species r Interactions between species in mixed-species plantations
r Stumpage price (affected by a number of supply and demand factors)
r Costs (land preparation, planting and establishment, maintenance, harvesting) r Amount of government assistance
r Harvest rights (buffer zones, harvest on steep land, roading permission) r Taxation regime (deductions allowable, treatment of harvest revenue) r Allowance for non-wood benefits
r Discount rate
In principle, a spreadsheet could be devised which incorporates each of these factors. One factor that can have a major impact on eventual cash flows is timber yield from plantations. Yield is commonly expressed as ‘mean annual increment’ (MAI) which is the aggregate volume of harvestable timber produced in a year from the growth of trees in a plantation. It is usually expressed as cubic metres of timber produced per hectare per year. Other factors, such as site productivity, species mixture, harvest ages and timber prices (usually expressed as $ per cubic metre) may also strongly affect eventual cash flows.
As well as direct and measurable financial benefits, forests provide a variety of non- market services that are more difficult to quantify in terms of cash flows. These include: crop benefits (e.g. windbreaks, insect control); visual amenity, including wildlife viewing; environmental products and services (e.g. carbon sequestration, erosion control, wildlife habitats, biodiversity); soil protection and stream bank stability; improvements in water quality; and acting as a store of wealth for the owner. In some cases, forestry activities may
impose non-wood costs such as the opportunity cost associated with conversion of cropland to forest, increased fire risk for adjacent properties, and crop damage from feral or native animals using the forest as a habitat. Non-wood benefits and costs may be private (i.e. borne by the company or individual) or social (public). Private non-wood benefits and costs are relevant to the private capital budgeting process and investment decision and hence should be included in a financial model for a forest company, though their estimation often presents considerable difficulty.
In general, social (or public) non-wood benefits and costs are not included in forestry financial analysis. However, they are sometimes included in more extended economic anal- ysis, such as a governmental economic cost/benefit analysis. The importance of these non- market benefits is apparent when it is realized that trees are often grown to obtain these benefits with no intention of logging. Furthermore, in some cases the multiple uses of forests have a direct impact on management or harvesting practices and need to be incorporated in the financial analysis.
The choice of an appropriate discount rate is a contentious issue. For example, in Australia, the Queensland state forest agency (Department of Primary Industries), which is required to make a commercial return on plantations under its control, currently uses a rate of 7% when assessing their industrial softwood plantations. It is sometimes argued that a lower rate (such as 3% or 4%) is more appropriate for assessing forestry activities, to allow for the important non-wood benefits produced by growing trees. Whilst some government initiatives can be investigated by adjusting the discount rate in this manner, discount rate adjustment as a method of benefit incorporation is not usual in commercial projects generally. Forestry investments judged not viable at the commercial rate may become acceptable using a lower rate. This is particularly important for forestry investments under consideration by government, which must satisfy multiple objectives when establishing and managing forests.
Sources of variability in forestry investment performance
Plantation forestry is not a risk-free investment. A variety of factors contributes to the uncertainty in revenue generated. Most cash inflows from plantations occur with the final harvest of trees when they reach maturity, although some additional cash inflows may be generated from the sale of trees that are thinned as part of the normal management practices. Typically it is thirty or more years until plantations are ready for final harvest, hence long- term predictions of physical and financial performance have to be made. The main sources of variability in the financial performance of forestry are summarized in Table 10.1.
Most of the costs of establishing forestry are incurred in the first few years of plantation life and are reasonably predictable. Contract rates for the various plantation operations are generally well known. The cost of land preparation can vary to some extent, depending on site characteristics. Seedling costs should be known in advance, as well as initial fertilizer costs. Weed control practices and labour requirements can be predicted within a narrow range. Should unusually dry weather be experienced after planting, there may be additional costs in watering and replanting lost trees.
Table 10.1. Sources of risk in farm forestry
Risk category Major sources
Risk of poor establishment Dry weather, poor weed control Production (timber yield) risk Storm or cyclone
Fire
Pest (insect, disease)
Unsuitable species or mixture for the site Collateral damage at harvest
Timber quality and product type risk Inappropriate pruning and thinning regime Insect damage
Product type and fashion changes in demand
Sovereign risk Regulatory changes concerning machinery use and roading Changes in taxation arrangements
Uncertain harvest rights and compensation
Market risk Uncertain future timber prices
Plantation establishment success and growth rates are less predictable, particularly when species are used for which only limited experience has been gained. Even with the best of intentions, there is no guarantee that thinning and pruning will be carried out at optimal times. The type of product which will be produced is also uncertain: high-quality poles are likely to be more profitable than sawlogs due to earlier harvest and favourable prices.
With mixed-species plantings and differing harvest ages for different species, there is a risk of damaging retained trees at the various harvest stages. This is overcome to some extent by planting whole rows of individual species, but even then it presents problems in that growth within rows will not be uniform and it may be desired to retain some individual trees. Helicopter or balloon lifting at harvest is highly expensive, but financially viable for high-value trees.
Sovereign risk relates to changes by government in the rules relating to farm forestry. Over the life of a plantation, it is probable that there will be numerous changes in taxation arrangements. Also, environmental regulations have a tendency to become more stringent over time, and these could increase management and harvesting costs or even lead to the outlawing of harvest. The extent to which compensation will be provided for such limitations on property rights is quite unpredictable.
In general, these sources of risk do not pose a threat of total crop loss. Even with severe storm damage or fires, it is usually possible to salvage a considerable proportion of the timber.
In summary, a variety of sources of risk arise with respect to timber quantity, quality and price. Superimposed upon the various risk components, landholders often have lit- tle information about likely plantation performance and payoff. This is particularly the case for species which have not been widely used in industrial forestry, and for which little ‘growth curve’ data are available. In Australia, most industrial forestry relies on
exotic conifers, and there is little information available about growth rates of native tree species, even though these species are increasingly being favoured by growers and markets. One native conifer species which is widely grown in plantations is hoop pine (Araucaria cunninghamii), but this is limited to favourable sites in terms of soil fertility and climate.
Some opportunity exists to minimize these risks. While plantation insurance is not nor- mally taken out, the relatively non-perishable nature of the product allows harvesting to be timed for when timber prices are relatively high. Also, forestry may be conducted as a risk-reducing business diversification, with harvesting when other income is low. In fact, forestry is sometimes viewed as a form of superannuation or savings, with harvest when there is a particular need for cash, say to assist in intergenerational property transfer or to buy out the equity shares of siblings.
Methods of allowing for risk in the evaluation of forestry investments
It is typical of projects spanning a number of years into the future that costs and benefits (especially the latter) are estimated subject to a high degree of uncertainty. That is, the cash flow estimates are simply best-guess point values arising from (unknown) probability distributions of random cost and benefit variables. This is certainly the case with forestry investments. Some of the methods used to deal with investment risk in forestry are now outlined.
Taking conservative benefit estimates. This is probably the simplest and most widely adopted method of allowing for risk in forestry projects. However, benefits tend to be adjusted in a rather arbitrary manner, and the approach provides little information to the decision-maker about the extent of risk faced. The emphasis is on protection against ‘downside risk’, and no recognition is given to the possibility of payoffs above the single-point estimates. As a result, projects which are financially sound could easily be rejected.
Requiring a short payback period. Sometimes projects are favoured because they lead to recovery of expenditure in a relatively short period. The payback period in forestry is usually the number of years from plantation development to clearfell (i.e. when all remaining mature trees are harvested at the same time), since thinnings (even the later commercial thinnings) cannot be expected to recover plantation establishment costs. Favouring a short payback period usually means adopting a short rotation system such as production of pulpwood from eucalypts with harvest after about seven to ten years. A shortened payback period means that there is less uncertainty about whether a market will exist for the timber harvested and, associated with this, the stumpage price which will be achieved.
Including a risk margin in the discount rate. In Chapter 7 we discussed how the discount rate (k) has three components, i.e.:
where r is the risk free rate, u is the average risk premium for the firm and a is an additional risk factor to account for the difference between the average risk faced by the firm and the risk of the proposed project.
Adjusting a to reflect the additional riskiness of forestry would result in an appropriate discount rate commensurate with the risk of the investment project being considered. Sensitivity analysis can be employed to measure the investment risk for forestry projects. Timber yield (progressively calculated through mean annual increment in total cubic metres) at a nominated harvest age and timber price are frequently subjected to sensitivity analysis. These parameters may be defined for a number of product lines from the same plantation, e.g. thinnings and final harvest, or poles, peelers (high-quality logs used to produce veneer) and sawlogs. It is also usual to test sensitivity with respect to the discount rate, or alternatively to plot the NPV profile with respect to discount rate.
Risk or venture analysis. This is sometimes carried out (e.g. Harrison, Herbohn and Emtage, 2001) to provide an overall estimate of project risk (this compares with sensitivity analysis which is usually designed to estimate risk with respect to one variable at a time). Risk analysis provides an estimate of the probability that a plantation will be profitable (positive NPV or required rate of return achieved), which can be particularly useful information for decision-makers. Commonly, Monte Carlo simulations are used here.
Problems faced in developing forestry financial models
There are numerous problems that may be encountered in developing financial models for assessing forestry investments. These problems usually arise from the particular nature of forestry – a long investment period over which world timber prices are likely to fluctuate, combined with the multiple-use nature of forests and the interaction of forestry with other ventures in a diversified firm.
Forestry is a long-term activity. Typically it takes twenty to thirty years for pine plantations to mature in temperate countries such as Australia and New Zealand. In Europe, rotations (the time taken from planting to final harvest of plantations) are typically fifty to eighty years for pines and up to two hundred years for broad-leaf species such as English oak. At the opposite end of the scale are some fast-growing hardwoods that can be harvested after only eight to ten years in some tropical countries. The long investment period typical of forestry projects provides a number of challenges when developing financial models. In particular, timber prices are likely to fluctuate over this period and it is difficult to predict the price that will be obtained for timber when it is harvested. The problems with forecasting timber prices thus pose a challenge in estimating cash inflows as part of the financial modelling process. Timber prices may increase over time in real terms, i.e. the price increase may be greater than the rate of inflation. For example, an annual increase in the real price of timber of 1.3% has been suggested (Russell et al., 1993). Furthermore, there is a risk that technological change or fashion change could result in weak demand for some timber types (e.g. satellite
communications reducing demand for poles for phonelines, consumer preferences for wood colour changing over time). Regulatory change in response to changing community attitudes could increase costs and restrict areas which can be harvested.
The long time required for trees to grow also means that there is sometimes a lack of biological growth data that can be used to predict growth rates (and hence timber yield). Timber yield and harvest timing are critical variables in forestry financial models. The lack of such data is most critical when new (non-traditional) species for which there is no past history of cultivation are being used in plantations. As seen in Chapter 4, the Delphi and other group forecasting methods can be used to develop estimates of growth and harvest ages which can be used in financial models.
The multiple-use nature of forests has also been recognized in the management of large industrial and government plantation estates. These management practices can have direct impact on the financial performance of the investment and thus should be considered in the appraisal process. For example in Finland, when a plantation estate is harvested, a number of habitat trees must be retained. The failure to harvest these trees directly reduces cash inflows to the investor. Similarly in the United Kingdom, there is recognition that native Scots pine and native broad-leaf species provide greater non-timber benefits than the exotic Sitka spruce. The result has been the harvesting of Sitka spruce plantations earlier than their optimal rotation age and their subsequent replacement with plantations of Scots pine and broad-leaf species. In many countries there are also large incentives provided to establish plantations, ranging from tax benefits to direct cash payments. Where they exist, these also need to be incorporated in the appraisal.
As with any appraisal of a capital project, it is necessary to gain an understanding of the social environment in which the project is being undertaken. In the case of a forestry investment, the way in which a forest is managed, and the ultimate quantity of timber which can be harvested, can be greatly affected by the increasing need for forests to be managed for multiple uses.
Developing a financial model: a step-by-step approach
As with any project appraisal, undertaking a financial analysis of a forestry project can be broken down into a number of individual and relatively simple steps:
(1) Identify the forestry system to be adopted – for example, the type of trees to be planted