IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i16p6898-d1454342.html
   My bibliography  Save this article

Strategic Analysis of the Forest Carbon Market in Brazil

Author

Listed:
  • Lucas Lamare Moreira Alves

    (Department of Forestry Engineering, University of Brasilia, Brasilia 70910-900, Brazil)

  • Humberto Angelo

    (Department of Forestry Engineering, University of Brasilia, Brasilia 70910-900, Brazil)

  • Alexandre Nascimento Almeida

    (Department of Forestry Engineering, University of Brasilia, Brasilia 70910-900, Brazil
    UnB Planaltina Faculty, University of Brasilia, Planaltina 73300-000, Brazil)

  • Gilson Fernandes Silva

    (Department of Forestry Engineering, Federal University of Espirito Santo, Vitória 29047-110, Brazil)

  • Eraldo Aparecido Trondoli Matricardi

    (Department of Forestry Engineering, University of Brasilia, Brasilia 70910-900, Brazil)

  • André Nunes

    (UnB Planaltina Faculty, University of Brasilia, Planaltina 73300-000, Brazil)

  • Celso Vila Nova Souza Júnior

    (UnB Planaltina Faculty, University of Brasilia, Planaltina 73300-000, Brazil)

Abstract

The forest carbon market in Brazil presents a complex scenario filled with challenges and opportunities. This study employed SWOT analysis to evaluate the dynamics of this market, based on the perceptions of 77 specialists from various professional fields. The analysis revealed that extensive forest cover and biodiversity preservation are significant strengths that position Brazil as a potential leader in the global carbon credit market. However, weaknesses such as illegal deforestation and fragile public policies undermine the effectiveness of conservation efforts. Opportunities include the growing international demand for carbon credits and the recognition of the importance of local communities in forest conservation. Nevertheless, external threats like land conflicts and political instability pose considerable risks. The study concludes that it is crucial to strengthen public policies and regulatory frameworks, promote technological innovation, and ensure the active inclusion of local and indigenous communities to guarantee the sustainability and growth of Brazil’s forest carbon market. The research suggests that despite significant challenges, Brazil can overcome these obstacles with the implementation of effective strategies.

Suggested Citation

  • Lucas Lamare Moreira Alves & Humberto Angelo & Alexandre Nascimento Almeida & Gilson Fernandes Silva & Eraldo Aparecido Trondoli Matricardi & André Nunes & Celso Vila Nova Souza Júnior, 2024. "Strategic Analysis of the Forest Carbon Market in Brazil," Sustainability, MDPI, vol. 16(16), pages 1-13, August.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:16:p:6898-:d:1454342
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/16/6898/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/16/6898/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xie, Qiwei & Hao, Jingjing & Li, Jingyu & Zheng, Xiaolong, 2022. "Carbon price prediction considering climate change: A text-based framework," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 382-401.
    2. Liang, Chao & Goodell, John W. & Li, Xiafei, 2024. "Impacts of carbon market and climate policy uncertainties on financial and economic stability: Evidence from connectedness network analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 92(C).
    3. Wu, Yizhong & Liu, Xiaoxing & Tang, Chun, 2024. "Carbon Market and corporate financing behavior-From the perspective of constraints and demand," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 873-889.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cao, Jin-Hui & Xie, Chi & Zhou, Yang & Wang, Gang-Jin & Zhu, You, 2025. "Forecasting carbon price: A novel multi-factor spatial-temporal GNN framework integrating Graph WaveNet and self-attention mechanism," Energy Economics, Elsevier, vol. 144(C).
    2. Tabak, Benjamin M. & Fulber, Ives Cezar & Froner, Matheus B., 2025. "The nexus between carbon, energy and agrifood—A contemporaneous and lagged spillover analysis," Finance Research Letters, Elsevier, vol. 75(C).
    3. Zhang, Xincheng & Wu, Shaojiang, 2024. "Natural resources and sustainable development: Evidence from the dynamic correlation between crude oil and gold market," International Review of Economics & Finance, Elsevier, vol. 96(PB).
    4. Yan, Xiang & Xin, Boqing & Cheng, Changgao & Han, Zhiyong, 2024. "Unpacking energy consumption in China's urbanization: Industry development, population growth, and spatial expansion," Research in International Business and Finance, Elsevier, vol. 70(PA).
    5. Xu, Yingying & Dai, Yifan & Guo, Lingling & Chen, Jingjing, 2024. "Leveraging machine learning to forecast carbon returns: Factors from energy markets," Applied Energy, Elsevier, vol. 357(C).
    6. Wang, Zhengzhong & Wei, Yunjie & Wang, Shouyang, 2025. "Forecasting the carbon price of China's national carbon market: A novel dynamic interval-valued framework," Energy Economics, Elsevier, vol. 141(C).
    7. Li, Zheng-Zheng & Li, Yameng & Huang, Chia-Yun & Peculea, Adelina Dumitrescu, 2023. "Volatility spillover across Chinese carbon markets: Evidence from quantile connectedness method," Energy Economics, Elsevier, vol. 119(C).
    8. Huo, Dongxia & Bagadeem, Salim & Elsherazy, Tarek Abbas & Nasnodkar, Siddhesh Prabhu & Kalra, Akash, 2023. "Renewable energy consumption and the rising effect of climate policy uncertainty: Fresh policy analysis from China," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 1459-1474.
    9. Beibei Hu & Yunhe Cheng, 2023. "Prediction of Regional Carbon Price in China Based on Secondary Decomposition and Nonlinear Error Correction," Energies, MDPI, vol. 16(11), pages 1-22, May.
    10. Wenwen Liu & Miaomiao Tang & Peng Zhao, 2025. "The dynamic impact of investor climate sentiment on the crude oil futures market: Evidence from the Chinese market," PLOS ONE, Public Library of Science, vol. 20(2), pages 1-29, February.
    11. Tommaso, Caterina Di & Foglia, Matteo & Pacelli, Vincenzo, 2024. "The impact of climate policy uncertainty on the Italian financial market," Finance Research Letters, Elsevier, vol. 69(PA).
    12. Yumei Guan & Chiwei Su & Tao Guan, 2025. "The Dynamic Bidirectional Causality Between Carbon Pricing and Green Technology Innovation in China: A Sub-Sample Time-Varying Approach," Sustainability, MDPI, vol. 17(12), pages 1-23, June.
    13. Gong, Xue & Lai, Ping & He, Mengxi & Wen, Danyan, 2024. "Climate risk and energy futures high frequency volatility prediction," Energy, Elsevier, vol. 307(C).
    14. Jujie Wang & Maolin He, 2025. "Extended decomposition ensemble framework based on full data analysis and optimized combination with relaxed boundary for carbon price forecasting," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(1), pages 909-942, January.
    15. Li, Xiafei & Yang, Shuangpeng & Luo, Keyu & Liang, Chao, 2024. "Spillover relationships between international crude oil markets and global energy stock markets under the influence of geopolitical risks: New evidence," International Review of Financial Analysis, Elsevier, vol. 96(PA).
    16. Chishti, Muhammad Zubair & Salam, Muhammad & Xaisongkham, Sorphasith & Du, Anna Min, 2025. "Influence of green ICT and socioeconomic factors on sustainable development: Evidence from Chinese provinces," Research in International Business and Finance, Elsevier, vol. 73(PA).
    17. Wei, Yu & Wang, Zhuo & Zhou, Xiaorui & Shang, Yue & Ren, Lin, 2024. "Are the leading indicators really leading? Evidence from mixed-frequency spillover approach," Finance Research Letters, Elsevier, vol. 69(PB).
    18. Wang, Xing & Li, Pengyu & Yuan, Yangguang & Zhang, Qianxiang, 2025. "The impact of the carbon trading market on corporate employment: Theoretical and empirical evidence," Energy, Elsevier, vol. 320(C).
    19. Wan, Yu-fan & Wang, Ming-hui & Wu, Feng-lin, 2025. "Greater fragility, greater exposure: A network-based analysis of climate policy uncertainty shocks and G20 stock markets stability," The North American Journal of Economics and Finance, Elsevier, vol. 76(C).
    20. Zhang, Jun & Chen, Donghui, 2024. "Time-frequency cross-country spillovers of climate policy uncertainty: Does it matter for financial risk?," Energy, Elsevier, vol. 312(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:16:p:6898-:d:1454342. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.