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An empirical analysis of forest transition and land-use change in developing countries

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  • Julien Wolfersberger

    (Laboratoire d'Economie Forestière, INRA - AgroParisTech)

  • Philippe Delacote

    (Laboratoire d'Economie Forestière, INRA - AgroParisTech)

  • Serge Garcia

    (Laboratoire d'Economie Forestière, INRA - AgroParisTech)

Abstract

Deforestation is a major environmental issue in developing countries, and agricultural land expansion is one of its main causes. The objective of this paper is twofold:(1) to identify the macroeconomic determinants of ending deforestation; and (2) to explain cumulative deforestation and other land uses. To do this, we first study the probability of a turning point for deforestation (i.e., the switch from decreasing to expanding forest areas), based on the Forest Transition (FT) theory. Second, we adapt a land-use model to explain the trade-off between forest and agriculture during development. To take the link between both phenomena into account, we estimate a dynamic panel seemingly unrelated regression (SUR) model along with a switching regression model, applied to a dataset of 57 developing countries observed over four time periods. The estimation results reveal that economic development and institutions play a significant role in long-term deforestation. Our results also suggest that after the first development stage, agriculture and forest are not always competing land uses. Thus, these results give us new insights into public policies such as REDD+.

Suggested Citation

  • Julien Wolfersberger & Philippe Delacote & Serge Garcia, 2015. "An empirical analysis of forest transition and land-use change in developing countries," Working Papers - Cahiers du LEF 2015-05, Laboratoire d'Economie Forestiere, AgroParisTech-INRA, revised May 2015.
  • Handle: RePEc:lef:wpaper:2015-05
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    References listed on IDEAS

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    Cited by:

    1. de Jong, Wil & Liu, Jinlong & Youn, Yeo-Chang, 2017. "Land and forests in the Anthropocene: Trends and outlooks in Asia," Forest Policy and Economics, Elsevier, vol. 79(C), pages 17-25.
    2. Barbier, Edward B. & Tesfaw, Anteneh, 2015. "Explaining forest transitions: The role of governance," Ecological Economics, Elsevier, vol. 119(C), pages 252-261.
    3. Kazungu, Moses & Ferrer Velasco, Rubén & Zhunusova, Eliza & Lippe, Melvin & Kabwe, Gillian & Gumbo, Davison J. & Günter, Sven, 2021. "Effects of household-level attributes and agricultural land-use on deforestation patterns along a forest transition gradient in the Miombo landscapes, Zambia," Ecological Economics, Elsevier, vol. 186(C).
    4. Afawubo, Komivi & Noglo, Yawo Agbényégan, 2019. "Remittances and deforestation in developing countries: Is institutional quality paramount?," Research in Economics, Elsevier, vol. 73(4), pages 304-320.
    5. Wang, Haoluan & Qiu, Feng, 2017. "Investigating the Impact of Agricultural Land Losses on Deforestation: Evidence From a Peri-urban Area in Canada," Ecological Economics, Elsevier, vol. 139(C), pages 9-18.
    6. Edward B. Barbier, 2019. "Institutional Constraints and the Forest Transition in Tropical Developing Countries," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 25(1), pages 1-18, February.
    7. Leblois, Antoine & Damette, Olivier & Wolfersberger, Julien, 2017. "What has Driven Deforestation in Developing Countries Since the 2000s? Evidence from New Remote-Sensing Data," World Development, Elsevier, vol. 92(C), pages 82-102.
    8. Heagney, E.C. & Falster, D.S. & Kovač, M., 2021. "Land clearing in south-eastern Australia: Drivers, policy effects and implications for the future," Land Use Policy, Elsevier, vol. 102(C).
    9. John Rand & Paula Castro Rodriguez & Finn Tarp & Neda Trifković, 2019. "The governance of global value chains, the state, and small businesses: The case of timber in Myanmar," WIDER Working Paper Series wp-2019-78, World Institute for Development Economic Research (UNU-WIDER).
    10. Wehkamp, Johanna & Koch, Nicolas & Lübbers, Sebastian & Fuss, Sabine, 2018. "Governance and deforestation — a meta-analysis in economics," Ecological Economics, Elsevier, vol. 144(C), pages 214-227.
    11. Li, Lingchao & Chhatre, Ashwini & Liu, Jinlong, 2019. "Multiple drivers and pathways to China's forest transition," Forest Policy and Economics, Elsevier, vol. 106(C), pages 1-1.
    12. Kazungu, Moses & Zhunusova, Eliza & Yang, Anastasia Lucy & Kabwe, Gillian & Gumbo, Davison J. & Günter, Sven, 2020. "Forest use strategies and their determinants among rural households in the Miombo woodlands of the Copperbelt Province, Zambia," Forest Policy and Economics, Elsevier, vol. 111(C).
    13. Longhui Lu & An Huang & Yueqing Xu & Raymundo Marcos-Martinez & Yaming Duan & Zhengxin Ji, 2020. "The Influences of Livelihood and Land Use on the Variation of Forest Transition in a Typical Mountainous Area of China," Sustainability, MDPI, vol. 12(22), pages 1-23, November.
    14. Qianwen Duan & Minghong Tan, 2019. "Spatial and Temporal Variations of Forest Cover in Developing Countries," Sustainability, MDPI, vol. 11(6), pages 1-15, March.
    15. Edward Barbier & Philippe Delacote & Julien Wolfersberger, 2016. "The economic analysis of the forest transition," Working Papers 1605, Chaire Economie du climat.

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    More about this item

    Keywords

    Forest Transition; Switching regression model; Dynamic panel SUR;
    All these keywords.

    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • 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

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