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Unlocking Emerging Economies: Exploring the Influence of International Trade on Strategic Options Through Logistic Regression Approach

Author

Listed:
  • Rizwan Akhtar

    (Karakoram International University
    University of Religions and Denominations)

  • Jamal Hussain

    (Karakoram International University
    University of Religions and Denominations)

  • Lingchao Li

    (Beijing Forestry University)

  • Baodong Cheng

    (Beijing Forestry University)

  • Tran Cuong

    (Hanoi University of Industry)

  • Sajjad Haider

    (Karakoram International University)

  • Abdul Razaq

    (Karakoram International University)

  • Iftikhar Ali

    (Karakoram International University)

  • Chenlu Tao

    (North China Electric Power University)

Abstract

This study delves into the dynamic interplay between emerging economies’ international trade and strategic options (forest transition or not). We seek to unlock the intricate connection between international trade and trade structure adjustments on forest cover dynamics through a rigorous analysis using a logistic regression model. The findings of our study exhibit a clear link between the total exports of manufactured goods and services (TEXP) and strategic options, indicating a significant and negative effect on strategic options. On the other hand, the percentage of non-primary goods exports (PNPEXP) does not significantly affect strategic options. The study recommends that policymakers promote the growth of manufacturing and services industries to protect and increase forest cover in emerging economies. It also contributes to the broader discussion on international trade and offers practical insights for policymakers and stakeholders leading the challenges of emerging economies.

Suggested Citation

  • Rizwan Akhtar & Jamal Hussain & Lingchao Li & Baodong Cheng & Tran Cuong & Sajjad Haider & Abdul Razaq & Iftikhar Ali & Chenlu Tao, 2025. "Unlocking Emerging Economies: Exploring the Influence of International Trade on Strategic Options Through Logistic Regression Approach," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(2), pages 7845-7873, June.
    • Handle: RePEc:spr:jknowl:v:16:y:2025:i:2:d:10.1007_s13132-024-02072-y
    DOI: 10.1007/s13132-024-02072-y
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