An assessment of forest sector modeling approaches: conceptual differences and quantitative comparison

Abstract

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.

Keywords:

• forest economics
• forest sector models
• partial equilibrium
• dynamic recursive models
• intertemporal optimization models
• myopic models

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

Funding for this work was in part supported by the Research Council of Norway, the Norwegian Forest Owner Association, and the Norwegian forest industries [grant number 415764 (“Klimatre”)], [grant number 415735 (“ClimPol”)], [grant number 415758 (“CenBio”)].