conclusions and recommendations

This report has described an accounting framework that can be used to collect cost information about roundwood production in Suriname and a model that can be used to convert this raw data into unit roundwood production costs. It has also shown how total roundwood production cost might be affected by changes in certain key cost variables and assumptions about productivity. In order to calculate economic rent and, consequently, set forest levies, it is important that this information is updated regularly and that these calculations are carried-out for a range of situations in Suriname.

Given current roundwood prices in Suriname, this level of production cost would imply that the economic rent from roundwood production might be in the region of US$ 18.50/m³ to US$ 33.50/m³, in the case of export quality roundwood, or up to Sf 7,750/m³, in the case of roundwood sold to domestic forest processors (see Table 5). Very few roundwood producers are currently producing low grade roundwood for the domestic market (indeed, as the table shows, there would be little or no profit from this at all), which suggests that the economic rent from roundwood sold on the domestic market may be near the top of this range.

Table 5 Current costs of contracting-out various forest operations compared with the costs estimated by the roundwood production cost model

Source: Model results and Whiteman (1999)

The analysis has shown that the total production cost is distributed fairly evenly between expenditure on labour, consumables, capital and profit. However, it has also shown that costs are most sensitive to changes in capital and labour costs and the foreign exchange rate. In terms of the individual forestry activities, it has shown that skidding and transport costs account for the majority of production costs. Therefore, most attention must be given to these items of expenditure in further analysis.

Recommendation 1: In order to update the above figures, it is recommended that new data about individual items of expenditure should be collected periodically. Given the sensitivity of the results to changes in the underlying variables and the likelihood of them changing over time, it is suggested that this should be done once a year, with priority being given to collecting information about the costs of capital machinery, spare parts, fuel, oils and greases and labour costs. The figures should also be immediately revised if there is a sudden change in any of these variables or in the exchange rate. Priority: HIGH.

Recommendation 2: The above analysis has only examined a "typical" forest concession, which is believed to represent average conditions in Suriname. However, the analysis has also shown that the total production cost is sensitive to variables such as transport distance and forest stocking levels. In order to refine the analysis, it is recommended that this analysis should be repeated for a range of different stocking rates and transport distances. This should also include an analysis of production costs, in situations where water transport is used. It would be useful to present these results in the form of a map showing how production cost varies with distance from the main processing centres in Suriname. Priority: HIGH.

Recommendation 3: In order to examine the efficiency of forest operations, it is also suggested that the methodology and model described above should be used to examine the production cost under a range of different production techniques. Key variables that should be examined, include: the product recovery rate in logging operations; the roading density and skid trail layout; and the use of better harvesting and transport machinery. Priority: MEDIUM.

In order to carry-out the above analyses, it is also recommended that the relevant staff of LBB and SBB should be trained in data collection techniques and the use of the model, specifically:

Recommendation 4: Staff should receive training in the following areas: project and policy appraisal (specifically with reference to stumpage value or economic rent calculation and the setting of forest levies); economic modelling using the harvesting cost model (and more general training in spreadsheet modelling if possible); and techniques for data collection, interpretation, validation and data management. Priority: HIGH.