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The Role of Technical Efficiency Gains on Greenhouse Gas Emissions: An Analysis of Brazilian Sugarcane Production

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  • Pedro Soares
  • Humberto Francisco Silva Spolador

Abstract

This article aimed to investigate the contribution of technical efficiency gains to reducing the emission of greenhouse gases in Brazilian sugarcane production and to estimate the monetary compensation that producers should receive to reduce pollution. Using an output distance function and its duality with the revenue function, we estimated the technical efficiency of sugarcane production in Brazilian municipalities and the shadow price of reducing carbon dioxide (CO2) emissions from the production of this crop. The main result was an overall technical efficiency average of 81%, which indicates that if producers adopt better management practices, the sugarcane production could be expanded by 19% with a contraction by the same magnitude in CO2 emissions. We also estimated a mean shadow price of R$9.18 per ton of carbon dioxide, with the highest estimated values in the states of Mato Grosso do Sul, Paraná, Mato Grosso, and Bahia. However, in the state of São Paulo, the most representative national producer, the estimated shadow price is R$6.34 per ton of carbon dioxide. In this sense, public policies, especially through public financing and public technical assistance, could potentially mitigate the producers' losses in the short run since pollution decline usually requires more mechanization.

Suggested Citation

  • Pedro Soares & Humberto Francisco Silva Spolador, 2025. "The Role of Technical Efficiency Gains on Greenhouse Gas Emissions: An Analysis of Brazilian Sugarcane Production," Agribusiness, John Wiley & Sons, Ltd., vol. 41(4), pages 956-968, October.
    • Handle: RePEc:wly:agribz:v:41:y:2025:i:4:p:956-968
    DOI: 10.1002/agr.22018
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    References listed on IDEAS

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    1. Spolador, Humberto Francisco Silva & Danelon, André Felipe, 2024. "New evidence of the driving forces behind Brazil's agricultural TFP growth—A stochastic frontier analysis with climatic variables and land suitability index," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 68(02), January.
    2. Capaz, Rafael Silva & Carvalho, Vanessa Silveira Barreto & Nogueira, Luiz Augusto Horta, 2013. "Impact of mechanization and previous burning reduction on GHG emissions of sugarcane harvesting operations in Brazil," Applied Energy, Elsevier, vol. 102(C), pages 220-228.
    3. Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107609464, Enero-Abr.
    4. Rezek, Jon P. & Perrin, Richard K., 2004. "Environmentally Adjusted Agricultural Productivity in the Great Plains," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(2), pages 1-24, August.
    5. Fare, Rolf & Grosskopf, Shawna & Weber, William L., 2006. "Shadow prices and pollution costs in U.S. agriculture," Ecological Economics, Elsevier, vol. 56(1), pages 89-103, January.
    6. Fare, Rolf & Grosskopf, Shawna & Noh, Dong-Woon & Weber, William, 2005. "Characteristics of a polluting technology: theory and practice," Journal of Econometrics, Elsevier, vol. 126(2), pages 469-492, June.
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    Cited by:

    1. Su Liu & Bingjie Huang & Zhiyang Shen, 2026. "Climate Risk and Green Productivity in African Agriculture: Challenges, Opportunities, and Policy Implications," Agribusiness, John Wiley & Sons, Ltd., vol. 42(2), pages 733-747, April.

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