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A spatial dependence approach to assessing the impacts of Sustainable Forestry Initiative’s Fiber Sourcing certification on forestry Best Management Practices in Georgia, United States

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  • Kadam, Parag
  • Magnan, Nicholas
  • Dwivedi, Puneet

Abstract

Understanding the effectiveness of the Sustainable Forestry Initiative Fiber Sourcing (SFI-FS) standard in increasing/sustaining a high forestry Best Management Practices (BMP) implementation rate is critical for the overall sustainability of southern forestlands. We analyze the impacts of SFI-FS standard on the forestry BMP implementation rate in Georgia, United States, by considering the locations of certified and non-certified mills between 2002 and 2019. The results show each increasing non-certified sourcing area overlap reduces BMP rates by 0.15%, while the same rate goes up by 0.08% overall with each increasing certified sourcing overlap. Moreover, the results of the spatial analyses indicate that neighbors' certified overlaps have a negative effect on average forestry BMP rates associated with a sourcing mill, even though the overall effect is positive. An increase in own harvesting area and mill size reduces BMP rates by 0.056%, but an increase for neighboring sourcing mills increases them by 0.063%, showing an overall positive effect of these two variables. These findings reflect the supply chain inefficiency brought on by concurrent contracting behavior between small mills and their larger certified neighbors. BMP rates are higher in the mill sourcing area by 0.023%, with each increase in the presence of perennial streams, further indicating that loggers are adequately following BMPs in areas that have perennial streams. Our overall results show that spatial dependence is an essential mechanism for ascertaining the effectiveness of SFI-FS standard at large spatial scales.

Suggested Citation

  • Kadam, Parag & Magnan, Nicholas & Dwivedi, Puneet, 2023. "A spatial dependence approach to assessing the impacts of Sustainable Forestry Initiative’s Fiber Sourcing certification on forestry Best Management Practices in Georgia, United States," Forest Policy and Economics, Elsevier, vol. 157(C).
    • Handle: RePEc:eee:forpol:v:157:y:2023:i:c:s1389934123001661
    DOI: 10.1016/j.forpol.2023.103071
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    References listed on IDEAS

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    1. R. Kelley Pace & James P. LeSage, 2010. "Omitted Variable Biases of OLS and Spatial Lag Models," Advances in Spatial Science, in: Antonio Páez & Julie Gallo & Ron N. Buliung & Sandy Dall'erba (ed.), Progress in Spatial Analysis, pages 17-28, Springer.
    2. James P. LeSage, 2014. "What Regional Scientists Need to Know about Spatial Econometrics," The Review of Regional Studies, Southern Regional Science Association, vol. 44(1), pages 13-32, Spring.
    3. Kadam, Parag & Dwivedi, Puneet & Karnatz, Caroline, 2021. "Mapping convergence of sustainable forest management systems: Comparing three protocols and two certification schemes for ascertaining the trends in global forest governance," Forest Policy and Economics, Elsevier, vol. 133(C).
    4. Dwivedi, Puneet & Tumpach, Chantal & Cook, Chase & Izlar, Bob, 2018. "Effects of the sustainable forestry initiative fiber sourcing standard on the average implementation rate of forestry best management practices in Georgia, United States," Forest Policy and Economics, Elsevier, vol. 97(C), pages 51-58.
    5. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
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