If left entirely to free market forces, all investment decisions would be made by comparisons of national competitive and comparative advantages. These, in turn, would be consistent with the relative returns on capital (at a given rate of time preference) of different investment projects. In the real world, however, investment decisions are significantly more complex and are affected by a number of intangible factors. These factors (generally referred to as "imperfect" market conditions) include imperfections in (or often the complete absence of) crucial market information, the presence of non-financial costs and benefits and the effects of government intervention. Nonetheless, despite these imperfections, financial criteria are generally the main quantitative tools that are used to assess the relative merits of different investments.
Discounted Cash Flow (DCF) techniques provide the analytical basis for many forestry investment decisions. For forest plantation investments, the comparative financial tool that is probably most commonly used, is Internal Rate of Return23 (IRR) analysis. An IRR is the level of profit expected from an investment project, expressed as an equivalent annual percentage rate of interest on all the money invested in that project (see Box 4).
Box 4 Calculating Discounted Cash Flows and Internal Rates of Return
Discounted cash flow analysis is based on the theory of compound interest. It essentially allows an investor to calculate the total value of all future costs and revenues associated with a project as though they were all incurred immediately (referred to as the Net Present Value or NPV of the project). This is done by projecting net income (i.e. revenues - costs) for each period of the investment and then converting each of these figures into a present value. This present value is the amount that would, after taking into account interest costs/income for the requisite number of years, result in the same amount as the future value identified above. The NPV is the sum of these adjusted values over the whole life of the project. The rate at which future values are reduced to take into account how far into the future they occur is called the discount rate (rather than the interest rate, although the two concepts are basically the same). The formula used to calculate NPV is:
Net Present Value = ___ C0 + C1/(1 + r) + C2/(1 + r)2 +....Cn/(1 + r)n]
Where: C = the projected net income in a period;
r = the discount rate; and
n = the total duration of the project
Internal rate of return analysis uses a similar process to calculate the expected rate of return on capital invested in a project. In this instance, rather than selecting a discount rate, the analysis calculates the discount rate at which NPV equals zero. This, in effect, gives the rate of interest earned on all money invested in the project.
The IRR formula for n periods is very similar to that for NPV except that, in this case, the discount rate is adjusted until NPV equals zero:
i.e. find r, such that NPV [i.e. C0 + C1 /(1+r) + C2/(1 + r)2 +....Cn/(1 + r)n] = 0
Almost all cross-country analyses of forest plantation investments present comparisons in terms of Internal Rates of Return. Usually, even when the calculations have all been done by a single agency, these analyses should be treated with caution. For example, in many instances it is unclear whether returns are cited in nominal (inclusive of inflation) or real (inflation-exclusive) terms or even whether returns are pre- or post- taxation. Similarly, questions arise as to how initial land-values are treated in the analysis, how complex taxation regimes have been applied and how different and variable government incentives have been taken into account. Added to these uncertainties, the usual questions relating to the quality of data used in the analysis, the quality of cost and price forecasting assumptions and the assumptions made about silvicultural, management and biological factors, can all conspire to make comparisons difficult. These difficulties are multiplied even further, when forest plantation investments are compared with investments in other sectors of the economy or with other financial instruments.
A robust analysis of alternative forest plantation investment projects requires an in-depth assessment of the costs and revenues associated with each alternative. Table 9 lists a number of factors that should be considered in any such analysis. Important decision values include: the total duration of the investment (i.e. the rotation length); the timing of silvicultural investments; and the timing and projected value of future roundwood production from the forest plantation (thinnings and final clear fellings).
Information available in the public domain about comparative plantation costs in different countries is scattered and very difficult to standardise. Consequently, this analysis uses a number of surrogate measures to establish indicative levels of comparative costs in different countries.
Table 9 Major factors affecting the costs and revenues of forest plantation projects
Type of cost or revenue |
Commentary |
Capital costs - Land purchase/lease - Land preparation - Plants - Planting - Fencing - Access roading and permanent pre-harvest roading |
Capital costs are generally incurred at the beginning of the project and are, consequently, of major importance. This is because they have to be "carried" throughout the length of the rotation (i.e. they are immediate and often account for the largest part of the total investment). |
Silvicultural costs - Fertiliser - Spraying - Pruning - Thinning |
Silvicultural costs will vary according to location, species and the management regime of a plantation. Silvicultural costs may be considered variable costs because, once a plantation is established, various treatments can be omitted or included, thereby varying the returns and risks involved in the project. |
Overhead costs - Insurance - Rates and levies - Management costs - Financing costs |
Overhead costs are generally stable, but are also largely beyond the control of the forest manager. Costs of insurance can, for example, be ignored (and often are in developing countries) but this increases the risk associated with the project. |
Harvesting costs - Roading costs - Logging costs - Transportation |
Harvesting costs are incurred at the end of the project and, while high, are not "carried" in the project for any significant period. On difficult sites, roading and hauling costs can be extremely high. |
Revenues - Production thinning - Final harvest - Other revenues - Land resale |
Revenues are based on forecasts of future prices and are consequently subject to considerable uncertainty. It is very difficult to make meaningful estimates of roundwood prices in the distant future and assessments will reflect a particular view of the future, rather than a definitive analysis (regardless of scientific methodologies). Other revenues might include, for example, those from grazing rights. |
Taxes and incentives - Income taxation - Depreciation regimes - Investment incentives |
Taxation regimes are highly variable between countries and between individual agents in countries. Post-tax IRRs (and, sometimes, qualification for incentives) are, consequently, likely to be case-sensitive. |
Land costs are fundamentally dependent on location and, consequently, very high variations in land costs are both possible and likely within individual countries. Land costs will, for example, depend on topography and a range of other geographic and economic factors, such as: soil productivity; potential yields of alternative crops; and relative proximity to infrastructure and markets. (See Box 5 for an example of one way of calculating the value of land based on its productive capacity). National estimates of land costs are, therefore, very crude averages of a cost that can vary widely.
The Land Expectation Value (LEV) approach to calculating land value recognises that the price of a piece of land is directly related to the value of the future net income stream that will be generated from productive activities taking place on that piece of land. The approach comes largely from a paper written by the 19th century German forest economist Martin Faustmann. The Faustmann formula is basically a Discounted Cash Formula that can be used to calculate the maximum amount that could be paid for a piece of land, such that a forestry project could earn a predetermined rate of return. Indeed the Faustmann formula provides the basis for much of modern forest economics and capital theory and was the precursor to the development of NPV and IRR analysis.
The LEV is, in essence, the NPV of a continuous stream of repeated investment projects of the same type and duration. This can be calculated because of the asymptotic nature of the NPV formula presented earlier. Assuming that the value of a piece of land is basically derived from the profitability of the most profitable activity on that piece of land, the LEV of that activity should, in theory, determine the land price if there is a prevailing consensus about the appropriate rate of return to use in this calculation.
The development of an international index of comparative land costs would be very difficult and beyond the scope of this study. Indeed, the literature search undertaken as part of this analysis discovered only one study that has attempted to estimate average land prices in the past. This study - the World Bank Global Approach to Environmental Analyses or GAEA (World Bank, 1999) - attempts to build on earlier World Bank work that suggested that national land prices would be roughly equal to a multiple of per capita income. Estimates of land value calculated in this way were then adjusted to incorporate broader factors, such as proportions of pasture, cropland, forestland and arid land in the total land area, to arrive at indicative national land prices.24 The figures presented in the GAEA are reproduced here in Table 10 below.25
Value of land (per ha) |
Countries |
less than US$100 |
Ethiopia, Nepal, Uganda, Vietnam, Sierra Leone, Niger, Mali, Chad, Sudan, Bhutan, Mauritania, Guyana, Egypt, Tanzania, Mozambique |
US$101-200 |
Burundi, Malawi, Guinea-Bissau, Cambodia, Burkina Faso, Kenya, Nigeria, Madagascar, Somalia, People's Republic of China, Lao PDR, Equatorial Guinea, Yemen, Maldives, Zambia |
US$201-300 |
Rwanda, Bangladesh, Gambia, Haiti, San Tome and Principe, Benin, Pakistan, Ghana, Nicaragua, Liberia, Central African Republic, Jordan |
US$301-500 |
Honduras, Cote d'Ivoire, Armenia, India, Togo, Afghanistan, Tajikistan, Lesotho, Zaire, Zimbabwe, Cape Verde, Algeria, Guinea, Mongolia, Libya |
US$501-1000 |
Morocco, Oman, Angola, Jamaica, Senegal, Guatemala, Congo, Kiribati, Cameroon, Myanmar, Philippines, Uzbekistan, Georgia, Peru, Papua New Guinea, Iraq, Indonesia, Azerbaijan, Kyrgyz Republic, Solomon Islands, Swaziland, Comoros, Djibouti, Sri Lanka, Bolivia |
US$1,001-2,000 |
Democratic Republic of Korea, Cuba, South Africa, Chile, Yugoslavia, Albania, Latvia, Slovak Republic, Micronesia, Marshall Islands, Ukraine, Kazakhstan, Belize, Bulgaria, Colombia, Tunisia, Turkmenistan, Vanuatu, Western Samoa, Romania, El Salvador, Lebanon, Lithuania, Paraguay, Ecuador, Dominican Republic, Syrian Arab Republic, Moldova, Islamic Republic of Iran |
US$2,001-3,000 |
Poland, Estonia, Brazil, Belarus, St Lucia, Dominica, Thailand, Panama, Turkey, Russian Federation, Tonga, Fiji, Granada, Venezuela, Bahrain, Namibia, Botswana, Costa Rica, St. Vincent and the Grenadines |
US$3,001-5,000 |
Guam, Macao, New Caledonia, Martinique, Aruba, Netherlands Antilles, Hungary, Qatar, Seychelles, Kuwait, Mauritius, Antigua and Barbuda, Malaysia, Trinidad and Tobago, Reunion, St Kitts and Nevis, Czech Republic, Mexico, Saudi Arabia, Uruguay |
US$5,001-10,000 |
Barbados, Portugal, Israel, Ireland, New Zealand, Republic of Korea, Greece, French Polynesia, Channel Islands, Virgin Islands (US), Iceland, Argentina, Bahamas, Malta, Suriname, Cyprus, Puerto Rico, Slovenia, Brunei, Gabon, Singapore, Guadeloupe, United Arab Emirates |
US$10,001-15,000 |
Canada, Australia |
US$15,001-20,000 |
Belgium, United Kingdom, Spain, Norway |
US$20,001-30,000 |
Switzerland, Germany, Sweden, France, Italy, Austria, USA, Netherlands Finland |
Greater than US$30,000 |
Denmark, Luxembourg, Japan |
Source: World Bank (1999).
It should be noted that the values presented in Table 10 are likely to bear little relationship to current commercial market prices for land in any particular year. Rather, the values are presented mainly for comparative purposes. Countries shown to have very high land values in GAEA would also be expected to have very high commercial land values. Similarly, countries estimated to have mid-range and low land values in GAEA would also be expected to have lower commercial land values.
The GAEA study estimates that, on average, Denmark has the most expensive land in the World, with an average valuation of US$38,100 per hectare. The cheapest average land value can be found in Mozambique, with a valuation of only US$30 per hectare. Land in Denmark is thus estimated to be 1,270 times more expensive than land in Mozambique. Despite this seemingly overwhelming competitive disadvantage, however, Denmark is reported to have 410,000 hectares of forest plantations, while Mozambique has only 32,000 hectares!
An important component of many forestry activities is the cost of labour. In general, forest management activities such as planting, pruning and thinning are very labour intensive although, in some (generally developed) countries, broadcast seeding is routinely practised and some of these operations may be mechanised. Harvesting operations are generally mechanised, with varying degrees of labour inputs, ranging from relatively high labour and low capital use in many developing countries to high levels of mechanisation (e.g. using, for example, feller-bunchers as opposed to chain-saws) in some developed countries. Labour costs vary markedly across countries, but are generally relatively uniform within countries.
There are two central aspects to labour costs that should be considered in an evaluation of forest plantation costs - the wage rate and productivity. Wage rates are generally highest in the most developed countries, where technology and training also tend to make productivity highest. Consequently, high wage rates tend to go hand-in-hand with high capital costs. Internationally, wage rates are distributed along a continuum, whereas technological and systemic advances mean that distinct leaps are possible in productivity. Competitive advantage in labour costs accrues, consequently, to countries with the lowest wage costs within a distinct productivity bracket.
Average levels of national income (i.e. GDP per capita) provide a useful, though far from perfect, surrogate for comparing wage rates between countries and the average GDP per capita for every country and territory in the World is shown in Table 11 opposite.
Per capita GDP (US$) |
Countries |
less than US$100 |
Eritrea, Ethiopia, Mozambique, Sao Tome and Principe, Sudan |
US$101-200 |
Bhutan, Burkina Faso, Cambodia, Chad, Dem. Rep. Congo, Guinea-Bissau, Malawi, Somalia, Tajikstan, Tanzania |
US$201-300 |
Bangladesh, Bosnia-Herzegovina, Burundi, DPR Korea, Madagascar, Mali, Nepal, Niger, Rwanda, Sierra Leone, Vietnam |
US$301-500 |
Angola, Armenia, Azerbaijan, Benin, Central African Republic, Comoros, Equatorial Guinea, Gambia, Georgia, Ghana, Guinea, Haiti, India, Kenya, Kyrgyzstan, Lao PDR, Lesotho, Mauritania, Mongolia, Nicaragua, Moldova, Togo, Turkmenistan, Uganda, Uzbekistan, Zambia |
US$501-1000 |
Albania, Belarus, Bolivia, Cameroon, Cape Verde, China, Cote d'Ivoire, Djibouti, Egypt, Guyana, Honduras, Kazakhstan, Kiribati, Nigeria, Pakistan, Papua New Guinea, Senegal, Solomon Islands, Sri Lanka, Suriname, Ukraine, Yemen, Zimbabwe |
US$1,001-2,000 |
Algeria, Bulgaria, Congo, Cuba, Dominican Rep., Ecuador, El Salvador, Guatemala, Indonesia, Iran, Jamaica, Jordan, Latvia, Liberia, Lithuania, Maldives, Marshall Islands, Morocco, Paraguay, Philippines, Romania, Samoa, Swaziland, Macedonia, Tonga, Vanuatu, Yugoslavia |
US$2,001-3,000 |
Afghanistan, Belize, Colombia, Costa Rica, Dominica, Estonia, Fiji, Grenada, Mexico, Micronesia, Myanmar, Namibia, Panama, Peru, Russian Federation, St Vincent and Grenadines, Thailand, Tunisia, Turkey |
US$3,001-5,000 |
Botswana, Brazil, Chile, Croatia, Czech Republic, Hungary, Lebanon, Malaysia, Mauritius, Poland, St Kitts and Nevis, St Lucia, Slovakia, South Africa, Syria, Trinidad and Tobago, Venezuela |
US$5,001-10,000 |
Antigua and Barbuda, Argentina, Bahrain, Barbados, Cook Islands, Gabon, Greece, Guadeloupe, Republic of Korea, Libya, Malta, Netherlands Antilles, Oman, Palau, Saudi Arabia, Seychelles, Slovenia, Uruguay |
US$10,001-15,000 |
Bahamas, Cyprus, Iraq, Martinique, Portugal, Puerto Rico, Qatar, Reunion, Spain |
US$15,001-20,000 |
Brunei-Darussalam, Canada, Ireland, Israel, Italy, Kuwait, New Caledonia, New Zealand, San Marino, United Arab Emirates, United Kingdom |
US$20,001-30,000 |
Australia, Austria, Belgium, Finland, France, French Guiana, French Polynesia, Germany, Iceland, Monaco, Netherlands, Singapore, Sweden, United States |
Greater than US$30,000 |
Denmark, Japan, Liechtenstein, Luxembourg, Norway, Switzerland |
Source: World Bank.
In terms of productivity, labour inputs per unit of output will vary according to the species planted, terrain, intensity of management and the level of capital utilisation. There are likely to be enormous differences in these factors between countries and even within countries there can be considerable differences in labour productivity in forest plantation operations.
Thompson (1990), for example, produced a survey of forest employment in Great Britain and found a marked difference in labour inputs between the publicly-owned Forestry Commission forests and privately-owned forests. These results are summarised in Table 12.
Table 12 Estimates of labour productivity in forestry in Great Britain in 1988-1989
Function, measurement units and type of forest manager |
Amount |
ESTABLISHMENT (work-years per hectare) Forestry Commission Private owners |
0.057 0.145 |
MAINTENANCE (work-years per 1,000 hectares) Forestry Commission Private owners |
1.507 4.276 |
HARVESTING (work-years per 1,000 cubic metres) Forestry Commission Private owners |
0.961 1.098 |
OFFICE/FOREST EMPLOYEE RATIO Forestry Commission Private owners |
0.249 0.182 |
Source: Thompson (1990).
The difficulty of producing broad estimates of labour productivity for a particular country is further demonstrated by Thompson, who noted that:
"Privately owned woodlands are, on the whole, on better quality land, concentrated in lowland areas and with a higher proportion of broadleaves and, therefore, require a higher level of maintenance."
It could also be speculated that the Forestry Commission uses specialised labour, has greater economies of scale in forest management and is a more capital-intensive forest manager.
23 There are a number of financial tools (of varying complexity) that may be used to assess a forest plantation investment. The relative importance of any particular tool will depend on the role that the forest plantation investment is expected to perform within the investors overall portfolio of investments. Net Present Value (NPV), for instance, belongs (with IRR) to the Discounted Cash Flow family of models. These two models have, however, different decision structures. Other well-known investment analysis tools include: the Capital Asset Pricing Model (CAPM), which assigns importance to diversifying risk within an overall portfolio; and Real Option Analysis, which incorporates an assessment of future management options into the investment appraisal.
"It should be stressed that the land values computed here remain quite insensitive to location. For example, the locational relationship between land and water has an obvious effect on its agricultural potential, while latitude and elevation influence growing seasons. A GIS approach to wealth accounting could begin to recognise such factors. It should be noted, however, that a distinction should still be made between the value of land and "real estate." The latter is often an indirect reflection of where produced assets (transport systems, human settlements, etc.) are located and not an inherent property of the land."
25 A more comprehensive description of the process used to estimate land prices is included in the original report (World Bank, 1999).
