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Deforestation, leakage and avoided deforestation policies: A spatial analysis

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  • Delacote, Philippe
  • Robinson, Elizabeth J.Z.
  • Roussel, Sébastien

Abstract

This paper analyses the impact of several avoided deforestation policies within a patchy forested landscape. Central is the idea that one neighbour's deforestation actions may impact the returns to deforestation in nearby patches. We determine the impact of each policy in terms of avoided deforestation and leakage levels at the landscape scale through modelling and simulations. Avoided deforestation policies at a landscape level are respectively: two Payment for Environmental Services (PES) policies, one focused on deforestation hotspots, the second being equally available to all agents; a conservation area; and, an agglomeration bonus. Because our model accommodates spatial interactions in the absence of a deforestation policy, it is possible that a spatial policy can affect both within-intervention areas and outside-intervention spatial spillovers in terms of leakage across different landowners’ forest patches. These two different elements of the total extent of displacement across the full landscape have not been considered before. Our contribution is twofold. In terms of methodology, we expand the concept of leakage in accounting for direct impacts to adjacent patches and spatial spillovers over the landscape, and we provide a measure of leakage in a dynamic manner for policy assessment. From our analytical model and simulations, we show that leakage is sensitive to the spatial distribution of forest patch types. The two PES policies are the most cost-effective policies regarding avoided deforestation. The agglomeration bonus policy is efficient at the expense of a higher cost, whilst the conservation area policy is efficient when patches with similar characteristics are gathered.

Suggested Citation

  • Delacote, Philippe & Robinson, Elizabeth J.Z. & Roussel, Sébastien, 2016. "Deforestation, leakage and avoided deforestation policies: A spatial analysis," Resource and Energy Economics, Elsevier, vol. 45(C), pages 192-210.
  • Handle: RePEc:eee:resene:v:45:y:2016:i:c:p:192-210
    DOI: 10.1016/j.reseneeco.2016.06.006
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    Cited by:

    1. Gwenolé Le Velly & Alexandre Sauquet & Sergio Cortina-Villar, 2017. "PES Impact and Leakages over Several Cohorts: The Case of the PSA-H in Yucatan, Mexico," Land Economics, University of Wisconsin Press, vol. 93(2), pages 230-257.
    2. Julika Herzberg, 2019. "Protection and Profit: Empirical Evidence of Governmental and Market-based Forest Policies," MAGKS Papers on Economics 201901, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    3. Philippe Delacote & Gwenolé Le Velly & Gabriela Simonet, 2020. "Distinguishing potential and effective additionality to revisit the location bias of REDD+ project," Working Papers hal-01954923, HAL.
    4. Shapiro, Aurélie C. & Bernhard, Katie P. & Zenobi, Stefano & Müller, Daniel & Aguilar-Amuchastegui, Naikoa & d'Annunzio, Rémi, 2021. "Proximate causes of forest degradation in the Democratic Republic of the Congo vary in space and time," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics.
    5. Philippe Delacote & Gwenolé Le Velly & Gabriela Simonet, 2018. "A tale of REDD+ projects. How do location and certification impact additionality?," Working Papers 1808, Chaire Economie du climat.
    6. Yvonne Hargita & Lukas Giessen & Sven Günter, 2020. "Similarities and Differences between International REDD+ and Transnational Deforestation-Free Supply Chain Initiatives—A Review," Sustainability, MDPI, Open Access Journal, vol. 12(3), pages 1-33, January.
    7. García, Jorge H. & Orlov, Anton & Aaheim, Asbjørn, 2018. "Negative leakage: The key role of forest management regimes," Journal of Forest Economics, Elsevier, vol. 33(C), pages 8-13.

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    More about this item

    Keywords

    Avoided deforestation; Leakage; Payments for environmental services; Conservation area; Agglomeration bonus; Spatial analysis;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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