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Negative incentives and sustainability in the amazonian logging industry [Negative incentives and sustainability in the amazonian logging industry]

Author

Listed:
  • Hilder André Bezerra Farias

    (UFPA)

  • Sérgio Luiz de Medeiros Rivero

    (UFPA)

  • Márcia Jucá Teixeira Diniz

    (UFPA)

Abstract

This paper investigates the existence of lock-in of low technology and high environmental impact on Brazilian Amazon logging industry. The research employed evolutionary economics as a theoretical basis, especially the concept of technological trajectories. The duality of decisions involving logging - conventional logging (CL) versus reduced-impact logging (RIL) - was studied. An agent-based simulation model - in which decision-making under bounded rationality is based on a genetic algorithm - was implemented in Java programming language. Results demonstrate the existence of lock-in, producers aversion to risks, greater operational efficiency of sustainable logging, and benefits derived from a policy of environmental bonuses, both in economic and ecological terms.

Suggested Citation

  • Hilder André Bezerra Farias & Sérgio Luiz de Medeiros Rivero & Márcia Jucá Teixeira Diniz, 2017. "Negative incentives and sustainability in the amazonian logging industry [Negative incentives and sustainability in the amazonian logging industry]," Nova Economia, Economics Department, Universidade Federal de Minas Gerais (Brazil), vol. 27(3), pages 363-391, September.
    • Handle: RePEc:nov:artigo:v:27:y:2017:i:3:p:363-391
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    References listed on IDEAS

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    More about this item

    Keywords

    logging industry; bounded rationality; agent-based simulation; reduced-impact logging; evolutionary economics;
    All these keywords.

    JEL classification:

    • B52 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Historical; Institutional; Evolutionary; Modern Monetary Theory;
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry

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