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How green is sugarcane ethanol?

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  • Sant'Anna, Marcelo Castello Branco

Abstract

Biofuels offer one approach for reducing carbon emissions in transportation. However, the agricultural expansion needed to produce biofuels may endanger tropical forests. I use a dynamic model of land use to disentangle the roles played by agricultural expansion and yield increases in the supply of sugarcane ethanol in Brazil. The model is estimated using remote sensing (satellite) information of sugarcane activities. Estimates imply that, at the margin, 92% of new ethanol comes from increases in area and only 8% from increases in yield. Direct deforestation accounts for 12% of area expansion. I further assess carbon emissions and deforestation implications from ethanol policies.

Suggested Citation

  • Sant'Anna, Marcelo Castello Branco, 2019. "How green is sugarcane ethanol?," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 807, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
  • Handle: RePEc:fgv:epgewp:807
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    References listed on IDEAS

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    1. Victor Aguirregabiria & Pedro Mira, 2002. "Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models," Econometrica, Econometric Society, vol. 70(4), pages 1519-1543, July.
    2. V. Joseph Hotz & Robert A. Miller, 1993. "Conditional Choice Probabilities and the Estimation of Dynamic Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 497-529.
    3. Treb Allen & Costas Arkolakis, 2014. "Trade and the Topography of the Spatial Economy," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(3), pages 1085-1140.
    4. Ruiqing Miao & Madhu Khanna & Haixiao Huang, 2016. "Responsiveness of Crop Yield and Acreage to Prices and Climate," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(1), pages 191-211.
    5. Ryan Kellogg, 2014. "The Effect of Uncertainty on Investment: Evidence from Texas Oil Drilling," American Economic Review, American Economic Association, vol. 104(6), pages 1698-1734, June.
    6. Amani Elobeid & Simla Tokgoz, 2008. "Removing Distortions in the U.S. Ethanol Market: What Does It Imply for the United States and Brazil?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 918-932.
    7. Angus Deaton & Guy Laroque, 1992. "On the Behaviour of Commodity Prices," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 59(1), pages 1-23.
    8. Andrade de Sá, Saraly & Palmer, Charles & di Falco, Salvatore, 2013. "Dynamics of indirect land-use change: Empirical evidence from Brazil," Journal of Environmental Economics and Management, Elsevier, vol. 65(3), pages 377-393.
    9. Michael J. Roberts & Wolfram Schlenker, 2013. "Identifying Supply and Demand Elasticities of Agricultural Commodities: Implications for the US Ethanol Mandate," American Economic Review, American Economic Association, vol. 103(6), pages 2265-2295, October.
    10. Soren T. Anderson & Ryan Kellogg & Stephen W. Salant, 2018. "Hotelling under Pressure," Journal of Political Economy, University of Chicago Press, vol. 126(3), pages 984-1026.
    11. Crago, Christine L. & Khanna, Madhu & Barton, Jason & Giuliani, Eduardo & Amaral, Weber, 2010. "Competitiveness of Brazilian sugarcane ethanol compared to US corn ethanol," Energy Policy, Elsevier, vol. 38(11), pages 7404-7415, November.
    12. Christine Lasco & Madhu Khanna, 2010. "US–Brazil Trade in Biofuels: Determinants, Constraints, and Implications for Trade Policy," Natural Resource Management and Policy, in: Madhu Khanna & Jürgen Scheffran & David Zilberman (ed.), Handbook of Bioenergy Economics and Policy, chapter 0, pages 251-266, Springer.
    13. P. M. F. Elshout & R. van Zelm & J. Balkovic & M. Obersteiner & E. Schmid & R. Skalsky & M. van der Velde & M. A. J. Huijbregts, 2015. "Greenhouse-gas payback times for crop-based biofuels," Nature Climate Change, Nature, vol. 5(6), pages 604-610, June.
    14. Peter Arcidiacono & Robert A. Miller, 2011. "Conditional Choice Probability Estimation of Dynamic Discrete Choice Models With Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 79(6), pages 1823-1867, November.
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