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Impacts of agent information assumptions in forest sector modeling

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  • Sjølie, Hanne K.
  • Latta, Gregory S.
  • Adams, Darius M.
  • Solberg, Birger

Abstract

The forest sector faces changing political paradigms and volatile policy measures. Policy makers rely on economic and biological models to inform them of the impacts and risks associated with both anticipated and unforeseen policies or shocks to the system. Assumptions about agents' knowledge of future events are fundamental in all forms of models suggesting that the degree of information of future events may have large behavioral impacts. Despite the importance of this assumption, few studies have looked into what this difference in information may imply, and few studies have analyzed the importance of varying the degree of a priori information on the impacts of policy measures. This paper attempts to elucidate some of these impacts by comparing how an exogenous shock affects the Norwegian forest sector if the agents are assumed to have: (i) perfect information, (ii) information about the market shift only a limited time before its implementation or (iii) no a priori information. The shock analyzed is an import ban on all coniferous wood into Norway, which is possible if the Pinewood nematode (PWN) becomes more widespread in Europe. To examine this question, we adapt the Norwegian forest sector model NorFor to reflect perfect, limited and no prior information. The results indicate that if the agents anticipate the shock, they will begin to adjust harvest and production levels before it occurs. Due to high opportunity costs, harvest is reduced in the first periods to allow increases later. Bioenergy, with much lower profit than pulp and paper on the margin, is the hardest hit by the ban, while paper production is little affected. This may also be due to high capital costs in the paper industry and a perfectly elastic wood demand curve for bioenergy use. Substantial price increases for both raw materials and final products are suggested under either limited or perfect foresight. The analysis may provide useful insight about how agents react to sudden changes depending on their a priori information.

Suggested Citation

  • Sjølie, Hanne K. & Latta, Gregory S. & Adams, Darius M. & Solberg, Birger, 2011. "Impacts of agent information assumptions in forest sector modeling," Journal of Forest Economics, Elsevier, vol. 17(2), pages 169-184, April.
    • Handle: RePEc:eee:foreco:v:17:y:2011:i:2:p:169-184
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    References listed on IDEAS

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    Cited by:

    1. Miguel Riviere & Sylvain Caurla & Philippe Delacote, 2020. "Evolving Integrated Models From Narrower Economic Tools : the Example of Forest Sector Models," Post-Print hal-02512330, HAL.
    2. Hurmekoski, Elias & Sjølie, Hanne K., 2018. "Comparing forest sector modelling and qualitative foresight analysis: Cases on wood products industry," Journal of Forest Economics, Elsevier, vol. 31(C), pages 11-16.
    3. Moiseyev, Alexander & Solberg, Birger & Kallio, A. Maarit I., 2013. "Wood biomass use for energy in Europe under different assumptions of coal, gas and CO2 emission prices and market conditions," Journal of Forest Economics, Elsevier, vol. 19(4), pages 432-449.
    4. Miguel Riviere & Sylvain Caurla, 2020. "Representations of the Forest Sector in Economic Models [Les représentations du secteur forestier dans les modèles économiques]," Post-Print hal-03088084, HAL.
    5. Latta, Gregory S. & Sjølie, Hanne K. & Solberg, Birger, 2013. "A review of recent developments and applications of partial equilibrium models of the forest sector," Journal of Forest Economics, Elsevier, vol. 19(4), pages 350-360.
    6. Kallio, A.M.I. & Salminen, O. & Sievänen, R., 2013. "Sequester or substitute—Consequences of increased production of wood based energy on the carbon balance in Finland," Journal of Forest Economics, Elsevier, vol. 19(4), pages 402-415.
    7. Hurmekoski, Elias & Hetemäki, Lauri, 2013. "Studying the future of the forest sector: Review and implications for long-term outlook studies," Forest Policy and Economics, Elsevier, vol. 34(C), pages 17-29.
    8. Sotirov, Metodi & Sallnäs, Ola & Eriksson, Ljusk Ola, 2019. "Forest owner behavioral models, policy changes, and forest management. An agent-based framework for studying the provision of forest ecosystem goods and services at the landscape level," Forest Policy and Economics, Elsevier, vol. 103(C), pages 79-89.
    9. Lauri, Pekka & Havlík, Petr & Kindermann, Georg & Forsell, Nicklas & Böttcher, Hannes & Obersteiner, Michael, 2014. "Woody biomass energy potential in 2050," Energy Policy, Elsevier, vol. 66(C), pages 19-31.

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