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Bioenergy and Land Use Change

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  • Ciaian, Pavel
  • Kancs, d'Artis
  • Rajcaniova, Miroslava

Abstract

This is the first article that econometrically estimates the global land-use change impact of bioenergy. Applying time-series analytical mechanisms to fuel, biofuel and agricultural commodity prices and production, we estimate the long-run relationship between energy prices, bioenergy production and the global land-use change. Our results suggest that rising energy prices and bioenergy production significantly contribute to the global land-use change both through the direct and indirect land-use change impact. Globally, the total agricultural area yearly increases by 35 578.1 thousand ha due to increasing oil price, and by 12 125.1 thousand ha due to increasing biofuel production, which corresponds to 0.73% and 0.25% of the total worldwide agricultural area, respectively. Soya land-use change and wheat land-use change have the highest elasticities with respect to both oil price and biofuel production. In contrast, nonbiomass crops (grassland and rice) have negative land-use change elasticities. Region-specific results suggest that South America faces the largest yearly total land-use change associated with oil price increase (+10 600.7 thousand ha), whereas Asia (+8918.6 thousand ha), South America (+4024.9 thousand ha) and North America (+1311.5 thousand ha) have the largest yearly total land-use change associated with increase in biofuel production.
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  • Ciaian, Pavel & Kancs, d'Artis & Rajcaniova, Miroslava, 2012. "Bioenergy and Land Use Change," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126379, International Association of Agricultural Economists.
    • Handle: RePEc:ags:iaae12:126379
    DOI: 10.22004/ag.econ.126379
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    Cited by:

    1. Piroli, Giuseppe & Rajcaniova, Miroslava & Ciaian, Pavel & Kancs, d׳Artis, 2015. "From a rise in B to a fall in C? SVAR analysis of environmental impact of biofuels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 921-930.
    2. Yongxi Ma & Lu Zhang & Shixiong Song & Shuao Yu, 2022. "Impacts of Energy Price on Agricultural Production, Energy Consumption, and Carbon Emission in China: A Price Endogenous Partial Equilibrium Model Analysis," Sustainability, MDPI, vol. 14(5), pages 1-14, March.
    3. Carpio, Lucio Guido Tapia, 2019. "The effects of oil price volatility on ethanol, gasoline, and sugar price forecasts," Energy, Elsevier, vol. 181(C), pages 1012-1022.
    4. Ladislav Kristoufek & Karel Janda & David Zilberman, 2015. "Co-movements of Ethanol Related Prices: Evidence from Brazil and the USA," CAMA Working Papers 2015-11, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. repec:lic:licosd:37115 is not listed on IDEAS
    6. Bilgili, Faik & Koçak, Emrah & Bulut, Ümit & Kuşkaya, Sevda, 2017. "Can biomass energy be an efficient policy tool for sustainable development?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 830-845.
    7. Amigues, Jean-Pierre & Moreaux, Michel, 2018. "Competing Land Uses and Fossil Fuel, Optimal Energy Conversion Rates During the Transition Toward a Green Economy Under a Pollution Stock Constraint," TSE Working Papers 18-981, Toulouse School of Economics (TSE).
    8. Mirzabaev, Alisher & Guta, Dawit & Goedecke, Jann & Gaur, Varun & Börner, Jan & Virchow, Detlef & Denich, Manfred & von Braun, Joachim, 2014. "Bioenergy, Food Security and Poverty Reduction: Mitigating tradeoffs and promoting synergies along the Water- Energy-Food Security Nexus," Working Papers 180421, University of Bonn, Center for Development Research (ZEF).
    9. Stolarski, Mariusz Jerzy & Warmiński, Kazimierz & Krzyżaniak, Michał & Olba–Zięty, Ewelina & Akincza, Marta, 2020. "Bioenergy technologies and biomass potential vary in Northern European countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    10. Lászlók, Annet, 2012. "The impact of energy crop production on land use in Hungary," Problems of World Agriculture / Problemy Rolnictwa Światowego, Warsaw University of Life Sciences, vol. 12(27), pages 1-9, September.
    11. Karel Janda & Ladislav Krištoufek, 2019. "The Relationship Between Fuel and Food Prices: Methods and Outcomes," Annual Review of Resource Economics, Annual Reviews, vol. 11(1), pages 195-216, October.
    12. Piroli, Giuseppe & Ciaian, Pavel & Kancs, d'Artis, 2012. "Land use change impacts of biofuels: Near-VAR evidence from the US," Ecological Economics, Elsevier, vol. 84(C), pages 98-109.
    13. Karel Janda & Ladislav Kristoufek, 2019. "The relationship between fuel and food prices: Methods, outcomes, and lessons for commodity price risk management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    14. Karel Janda & Ladislav Krištoufek & Barbora Schererová & David Zilberman, 2021. "Price transmission in biofuel-related global agricultural networks," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 67(10), pages 399-408.
    15. Cuppari, Rosa I. & Higgins, Chad W. & Characklis, Gregory W., 2021. "Agrivoltaics and weather risk: A diversification strategy for landowners," Applied Energy, Elsevier, vol. 291(C).

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    More about this item

    Keywords

    Environmental Economics and Policy; Food Consumption/Nutrition/Food Safety; Food Security and Poverty; Land Economics/Use;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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