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Confronting the Food–Energy–Environment Trilemma: Global Land Use in the Long Run

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  • Jevgenijs Steinbuks
  • Thomas Hertel

Abstract

Economic, agronomic, and biophysical drivers affect global land use, so all three influences need to be considered in evaluating economically optimal allocations of the world’s land resources. A dynamic, forward-looking optimization framework applied over the course of the coming century shows that although some deforestation is optimal in the near term, in the absence of climate change regulation, the desirability of further deforestation is eliminated by mid-century. Although adverse productivity shocks from climate change have a modest effect on global land use, such shocks combined with rapid growth in energy prices lead to significant deforestation and higher greenhouse gas emissions than in the baseline. Imposition of a global greenhouse gas emissions constraint further heightens the competition for land, as fertilizer use declines and land-based mitigation strategies expand. However, anticipation of the constraint largely dilutes its environmental effectiveness, as deforestation accelerates prior to imposition of the target. Copyright Springer Science+Business Media Dordrecht 2016

Suggested Citation

  • Jevgenijs Steinbuks & Thomas Hertel, 2016. "Confronting the Food–Energy–Environment Trilemma: Global Land Use in the Long Run," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 63(3), pages 545-570, March.
  • Handle: RePEc:kap:enreec:v:63:y:2016:i:3:p:545-570
    DOI: 10.1007/s10640-014-9848-y
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    Cited by:

    1. Thomas W. Hertel, 2017. "Land Use in the 21st Century: Contributing to the Global Public Good," Review of Development Economics, Wiley Blackwell, vol. 21(2), pages 213-236, May.
    2. Peter Midmore, 2017. "The Science of Impact and the Impact of Agricultural Science," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(3), pages 611-631, September.
    3. Thomas W. Hertel & Jevgenijs Steinbuks & Wallace E. Tyner, 2016. "What Is the Social Value of Second Generation Biofuels?," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 38(4), pages 599-617.
    4. Vik, Jostein, 2020. "The agricultural policy trilemma: On the wicked nature of agricultural policy making," Land Use Policy, Elsevier, vol. 99(C).
    5. Midmore, Peter, 2017. "The Science of Impact and the Impact of Agricultural Science," 91st Annual Conference, April 24-26, 2017, Royal Dublin Society, Dublin, Ireland 258614, Agricultural Economics Society.
    6. Naso, Pedro & Lanz, Bruno & Swanson, Tim, 2020. "The return of Malthus? Resource constraints in an era of declining population growth," European Economic Review, Elsevier, vol. 128(C).
    7. Yongyang Cai & Kenneth Judd & Jevgenijs Steinbuks, 2017. "A nonlinear certainty equivalent approximation method for dynamic stochastic problems," Quantitative Economics, Econometric Society, vol. 8(1), pages 117-147, March.
    8. Naso, Pedro & Haznedar, Ozgun & Lanz, Bruno & Swanson, Tim, 2022. "A macroeconomic approach to global land use policy," Resource and Energy Economics, Elsevier, vol. 69(C).
    9. Pedro Naso; Ozgun Haznedar; Bruno Lanz; Timothy Swanson, 2021. "Food Security in the Long-Run:A Macroeconomic Approach to Land Use Policy," CIES Research Paper series 71-2021, Centre for International Environmental Studies, The Graduate Institute.
    10. Cai,Yongyang & Steinbuks,Jevgenijs & Judd,Kenneth L. & Jaegermeyr,Jonas & Hertel,Thomas W., 2020. "Modeling Uncertainty in Large Natural Resource Allocation Problems," Policy Research Working Paper Series 9159, The World Bank.

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    More about this item

    Keywords

    Biofuels; Climate change; Deforestation; Energy; Environment; Food; Forestry; GHG emissions; Global land use; C61; Q15; Q23; Q26; Q40; Q54;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment
    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry
    • Q26 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Recreational Aspects of Natural Resources
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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