The study reported in this document comprises a comparative financial and economic analysis of two management alternatives:
The study considers two different time frames:
(1) 1-year calculation period
The financial costs and revenues of the CL and RIL systems were calculated for harvesting in primary forest. Costs were based on data for the year 2000. For the one-year calculation period, costs and revenues were neither projected nor discounted, although some activities are realised at different points in time; thus the actual costs were compared with actual revenues.
(2) 40-year calculation period
For this analysis it was assumed that the harvesting operations are carried out after a rotation period of 40 years in a logged over-forest. In this situation costs and benefits occur at different points in time. The economic benefit of the forest management options depends not only on the total amount of money disbursed and received but also on the time at which the amount is paid (e.g., harvesting costs) or received (e.g., timber revenues). In order to compare the costs and benefits occurring at different time scales, discounting has to be applied since humans commonly value benefits available today more highly than benefits scheduled to occur in the future. Discounting corrects for the differences in time and enables the calculation of the Present Value (PV) of an amount to be received or paid in the future.
The method applied in this analysis is the classical approach of a Cost-Benefit-Analysis (CBA) involving the calculation of Net Present Value (NPV). CBA is a tool for evaluating the financial and economic value of an investment, considering the point in time as well as the amount of cash flows. This method allows the comparison of the alternative management options.
The analysis is separated into two aspects:
1. Financial analysis:
This analysis deals with actual cash flows. Only traded goods and services are considered and valued by applying market prices. Such an analysis is appropriate from a forest manager's perspective.
In contrast, the economic analysis takes the viewpoint of the society as a whole. Although the analysis determines the amount of the benefit stream generated through the costs of inputs, it does not specify who actually receives the benefits. Economic analyses consider costs and benefits accruing to the total economy, regardless of whether or not the goods and services are actually traded.
The analysis omits transfer payments. In case market prices are poor estimates of the economic value, costs and benefits are valued with shadow prices. For intermediate goods and services the shadow price is the value in use, whereas for intermediate goods and services it reflects the opportunity costs (Gittinger, 1996, p. 499).
A conversion factor is used to adjust financial costs and benefits to reflect economic values. In order to simplify the calculation of shadow prices, a standard conversion factor of 1.2 (i.e., plus 20%) on traded financial prices was applied. The percentage of the tradable good component relative to the total costs or benefits was estimated.
The methodology used in comparing costs and benefits is the same for financial or economic assessments of project worth, but the entities defined as costs and benefits are different (Gittinger, 1996, p. 19).
The valuation in this study uses year 2000 prices, costs and interest rates for comparing the management options. Thus it is assumed that, in the long term, inflation will affect prices and costs in the same direction and magnitude.
The results of the analysis are all given in Malaysian Ringgit (RM). The exchange rate was RM 3.79 per US dollar as of 15 October 2000.
Study Blocks:
Between 1998 and 2000 the FDS and FOMISS, in cooperation with Samling, established RIL trial blocks in the FSPA. Altogether 13 blocks stocked with primary Mixed Hill Dipterocarp Forests were harvested in accordance with the standards developed by FDS/FOMISS (Jonathan et al., 1999). An additional data source was the information obtained from the first 1996 FOMISS RIL trial in the Model Forest Management Area (MFMA). General information with regard to CL was obtained as average data from the entire FSPA.
Costs:
The RIL trial blocks were initialised especially with regard to the practical implementation of RIL as a part of the SFMS. This is why data on productivity and costs were only available for rough steps of the RIL operation. A more detailed breakdown of some cost centers was not possible. Figures on harvesting costs (skidtrail preparation, winching, skidding, tree felling) were provided by the concessionaire (Samling, 2001). The data were available for six RIL trial blocks that were harvested between February and July 2000.
Costs under CL were derived from the data provided by Samling for five blocks for the period from June to August 2000 (Samling, 2001). These harvesting costs from Samling consider four cost centers: (1) fuel, oil and lubricants (FOL); (2) repairs and maintenance (R&M); (3) salary and wages (S&M); and (4) capital costs (CC). The data include both total costs and costs per m³. However, no detailed information was available on harvesting productivity such as the number of working days, the number of rain days, harvested volume per day, etc.
The harvesting costs supplied by the company display some irregularities. To give an example for skidding machine R352R in RIL Block 36, the following data were provided for the month of May 2000: Volume harvested = 18 m³; SMU = 219; FOL = RM 4,450; R&M = RM 64; S&W = RM 162; CC = RM 7,757 (Total = RM 12,652). Thus the total unit cost according to these data was RM 703/m³, with RM 247/m³ for fuel, oil and lubricants.
These data should be reviewed as soon as possible. Nevertheless, since these were the only available costs of harvesting operations under CL and RIL in the FSPA it was decided to incorporate them into the actual CBA.
Non-timber forest values:
The main source for the evaluation of non-timber forest values was a study by Sander (2000a), who focused on the financial and economic efficiency of forest management options in the FSPA. The data used in his CBA were obtained from external studies. Nevertheless, it seemed useful to use the same data, especially due to the possibility that the results of the CBA of timber harvesting operations will be incorporated into an overall economic assessment of SFMS.
Damage assessment:
A post-harvesting damage assessment was conducted in six RIL blocks and six conventionally logged blocks. The following tree damage classes were recorded: (1) uprooted; (2) broken trunk; (3) severe bark damage; (4) severe crown damage; (5) combination of (3) & (4); (6) minor bark damage; (7) minor crown damage; (8) combination of (6) & (7); (9) bent tree; (10) felled but not extracted (normally due to hollowness or severe defect); (11) no damage. Only severely damaged trees, i.e., damage classes (1) to (5) and (10) were used in the calculation of tree damage to the residual stand.
Proportion of compacted area:
For the RIL system, data on skidtrail length were obtained from the Final Harvesting Map. The average skidtrail width in the RIL blocks was estimated based on spot checks made by FOMISS staff (Hahn-Schilling, 2000, personal communication). From this it was possible to calculate the average area in which soil was disturbed (compacted) during the harvesting operation. Results from a study by Richter (2000) focusing on forest rehabilitation in the FSPA were used to estimate the proportion of compacted area under the CL system.
Utilisation factor (UF):
During the harvesting operation, felled and trimmed logs were measured by FDS/FOMISS field staff. By comparing these data with the gross volume of the standing harvestable tree, the volume of merchantable timber wasted due to poor felling and trimming techniques (= poor utilisation) could be estimated. Thus, UF is defined as the commercial wood volume felled and trimmed, measured as a percentage of the gross bole volume of the standing tree. However, since comparable measurements were not carried out in the CL blocks it was necessary to apply professional estimates for the CL system.
Log waste:
Timber was also wasted in the form of logs that were left behind on the log landing, and through second trimmings at the log landing or royalty assessment point. This log waste was estimated by comparing the commercial log volume measured after first trimming at the felling site with the official commercial volume as recorded at the royalty assessment point.
Growth simulation:
Figures on forest growth of the residual trees and the recruitment of new trees after harvesting were estimated with the Dipterocarp Forest Growth Simulation Model, DIPSIM (Ong & Kleine, 1995). The model is based on permanent growth and yield plots from various localities in Sarawak. Input data for the FSPA were obtained from a large data set from 275 sample plots of 0.25 ha, which are systematically distributed within the FSPA, covering primary forests as well as logged over forests. The simulation was carried out on the basis of 21 Harvesting Units. The total net production area of the Harvesting Units amounts to 39,103 ha. The area is stocked with primary forests. The basic parameters used for the DIPSIM calculation are summarised in Appendix 1.
Calculation of forest biomass and carbon storage:
The economic analysis compares the value of carbon storage of the two harvesting systems. Therefore it was necessary to get a rough estimate on stocks of carbon storage. As a first step the biomass density was calculated (Brown, 1997):
Formula (1) ABD = VOB * WD * BEF
Formula (2) BEF = exp [3.213 – 0.506 * ln (BV)] for BV < 190 t/ha
BEF = 1.74 for BV > 190 t/ha
Explanation:
ABD = Aboveground biomass density [t/ha]
VOB =
Inventory volume over bark of tree boles [m³/ha]
WD = Volume-weighted average
wood density [t/m³]
BEF = Biomass expansion factor; ratio of aboveground
oven-dry biomass of trees to oven-dry biomass of inventory volume
BV =
Biomass of inventory volume [t/ha]; calculated as the product of VOB/ha and
WD
exp [x] =The exponential function as applied to object x
ln(y) =The natural logarithm of y
The inventory volume (VOB) used in the calculation was obtained from the DIPSIM simulation. Based on figures given by Brown (1997) an arithmetic mean wood density (WD) of 0.57 t/m³ was applied for the calculation. Following the estimation of the stand biomass a conversion factor of 0.5 was used to express biomass in terms of carbon (Moura Costa, 1996; Brown, 1997).
Formula (3) C = ABD * 0.5
Explanation:
C = Carbon stored in aboveground biomass [t/ha]
ABD= Aboveground biomass density [t/ha]
Carbon stocks per ha were calculated for 5-year intervals. The average of these figures was used for the economic analysis of the carbon stock value.
The economic indicators applied in this analysis are as follows:
(1) Net Present Value:
The NPV is derived by subtracting the sum of the Present Value (PV) of a cash flow of costs from the sum of the PV of a cash flow of revenues. The PV of the costs is represented by the following formula:
Formula (4)
(Hanusch, 1994, p. 98)
Explanation:
PV (C) = Present Value of costs
C1...T = Value of costs for a period of years
r= Discount rate
The PV of revenues is calculated in the same way. The difference between discounted revenues and discounted costs gives the NPV:
Formula (5) NPV = PV(R) – PV(C)
Explanation:
NPV = Net Present Value
PC(R) = Present Value of
revenues
PV(C) = PresentValue of costs
Generally, an investment is accepted if the NPV is positive at a pre-selected discount rate. If a number of mutually exclusive options are being evaluated, the option with the highest NPV at a given discount rate is chosen.
(2) Internal rate of return:
The IRR is the discount rate at which the NPV is zero, or the rate at which the discounted costs equal discounted revenues.
Formula (6) NPV = PV(R) – PV(C) = 0
The selection criterion is to accept projects having an IRR higher than the pre-selected discount rate. In the case of mutually exclusive options the one with the highest IRR is the most attractive option.
(3) Benefit Cost Ratio:
The BCR is calculated by dividing the PV of revenues by the PV of costs:
Formula (7) BCR = PV(R) / PV(C) (Hanusch, 1994, p. 116)
Generally, a project with a BCR > 1 is accepted. Where several alternative options are being assessed the one with the highest BCR is chosen.
A sensitivity analysis was carried out in order to estimate how changes in key technical and economic parameters subject to uncertainty would alter the economic performance or decision-making criteria of the two management options. To work out the effect of a selected element on the measure of project worth only one element was changed whereas the others remained unchanged. Finally, several elements were simultaneously altered to produce a realistic combination of changes and to assess their impact on the NPV. The sensitivity analysis was undertaken for the following parameters: