Search

Forest sector models are widely used for policy and economic analyses. Basic assumptions vary considerably between models, but little attention has been paid to the impacts these differences may have on model results. Norway provides a great opportunity to fill this void as it has two forest sector models currently in use based on different modeling assumptions, but sharing the same data source. In one model, agents are assumed to be myopic in the meaning that they rely only on the current market conditions. Harvest behavior is in this model based on econometric relations and exogenous forest growth rates. The second model approach employs extensive forest data and assumes that agents have perfect information over the model time horizon. We discuss the differences between the two modeling approaches and compare quantitatively the model results of two case studies. However, both types of models are rather sensitive to changes in assumptions and data. The strengths and weaknesses of the two model approaches and their appropriateness for responding to the study questions should be considered when choosing modeling methodology. Using both models in parallel removes the uncertainty caused by the foresight assumption/optimization routine and thus provides in total more information. [ABSTRACT FROM PUBLISHER]

The forest sector in Norway is very transport intensive, accounting for approximately 14% of total domestic freight transport traffic on Norwegian roads. This paper presents an analysis linking a general equilibrium freight transport modelling tool with a partial equilibrium model of the forest sector. The freight transport model predicts transport costs, modal split and transport patterns, and the results are treated as inputs to the forest sector model. The objective of the paper is to analyse the modelling effect of taking forest sector model effects back into the freight transport model and treated as new demand. Compared to a base scenario for the year 2020, we compare analyses with and without this new demand from the forest sector model back into the freight transport modelling tool. [ABSTRACT FROM AUTHOR]

Forestry and forest industries are transport-intensive sectors. In Norway, the forest sector (forestry and forest industries) represents less than 1% of gross domestic product, but 14% of the total road transport work. Road transport represents 19% of the greenhouse gas (GHG) emissions in Norway. This article is an analysis of the economic and GHG emission impacts of the following three transport policy scenarios targeting the forest sector in Norway: (1) increased fuel prices, (2) increased allowable total weight for log trucks, and (3) accelerated infrastructure development. Three different models were combined in the analyses: a national full equilibrium model, a national transport logistics model and a regionalized partial equilibrium forest sector model. The results showed that increased maximum total weight had a greater economic impact on transport costs for roundwood than for forest industry products. Elimination of bottlenecks, such as bridges with limited allowable weight, is needed if the full potential of increased total weight is to be utilized. General infrastructure measures in the main road network had greater economic impacts on forest industries than on forestry. The short-run regional effects of changes in transport costs on production and trade-flows were, however limited, mostly in the range of 1-2%. Increased total weight brought increased emissions of GHGs, owing to transfer from rail to road, whereas accelerated infrastructure investment and increased fuel prices yielded reduced emissions, although the effects were relatively small, in the range of 0.5-1%. [ABSTRACT FROM AUTHOR]

A partial equilibrium forest sector model which is augmented to include bioenergy was applied to project the use of bioenergy based on forest fuels and forest industry by-products in Norway for three different scenarios of the future prices of electricity and oil. The impacts on forestry and forest industries of the different energy price scenarios were also studied. The advantage of the suggested methodology is that it allows for assessments of the economic potential of bioenergy, taking into account the competition for raw materials, the specific heat demand of various regions, and interregional and international trade. Bioenergy will, according to this study, be fairly competitive in some market segments with the current price levels of electricity and oil, and only a minor increase (decrease) in energy (roundwood) prices would release substantially increased bioenergy production levels. Pulpwood prices of pine and non-coniferous species are projected to increase substantially when assuming increasing energy prices. Except for particleboard mills, production levels of forest industries appeared relatively insensitive to the energy price changes. [ABSTRACT FROM AUTHOR]