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Sugarcane industry's socioeconomic impact in São Paulo, Brazil: A spatial dynamic panel approach

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  • Gilio, Leandro
  • Azanha Ferraz Dias de Moraes, Márcia

Abstract

This study assesses the socioeconomic development impacts of the recent sugarcane industry expansion on municipalities in the Brazilian state of São Paulo over seven years, from 2005 through 2011. It was used as socioeconomic development indicator the Index of Municipal Development (IFDM), provided by the Federation of the State of Rio de Janeiro Industries (FIRJAN). A dynamic spatial panel model was built using the System Generalized Method of Moments (GMM-SYS) to assess the impacts of the sugarcane industry, caused by the expansion of both the cultivated area and the presence of ethanol and sugar processing plants. We found that the presence of a processing plant has a positive effect in the socioeconomic development of the municipality where the plant is located and in neighboring municipalities. Besides, we found a small negative relationship between increases in the amount of area devoted to sugarcane cultivation in a municipality and the IFDM value for that municipality, which can be explained by job losses in the farming sector, most likely by the recent mechanization process of sugarcane harvesting.

Suggested Citation

  • Gilio, Leandro & Azanha Ferraz Dias de Moraes, Márcia, 2016. "Sugarcane industry's socioeconomic impact in São Paulo, Brazil: A spatial dynamic panel approach," Energy Economics, Elsevier, vol. 58(C), pages 27-37.
    • Handle: RePEc:eee:eneeco:v:58:y:2016:i:c:p:27-37
    DOI: 10.1016/j.eneco.2016.06.005
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    References listed on IDEAS

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    Cited by:

    1. Huang, Junbing & Xiang, Shiqi & Wu, Panling & Chen, Xiang, 2022. "How to control China's energy consumption through technological progress: A spatial heterogeneous investigation," Energy, Elsevier, vol. 238(PC).
    2. 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.
    3. 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.
    4. Huang, Junbing & Chen, Xiang & Cai, Xiaochen & Zou, Hong, 2021. "Assessing the impact of energy-saving R&D on China’s energy consumption: Evidence from dynamic spatial panel model," Energy, Elsevier, vol. 218(C).
    5. Martinez-Valencia, Lina & Garcia-Perez, Manuel & Wolcott, Michael P., 2021. "Supply chain configuration of sustainable aviation fuel: Review, challenges, and pathways for including environmental and social benefits," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    6. Caldarelli, Carlos Eduardo & Gilio, Leandro, 2018. "Expansion of the sugarcane industry and its effects on land use in São Paulo: Analysis from 2000 through 2015," Land Use Policy, Elsevier, vol. 76(C), pages 264-274.
    7. Brinkman, Marnix L.J. & da Cunha, Marcelo P. & Heijnen, Sanne & Wicke, Birka & Guilhoto, Joaquim J.M. & Walter, Arnaldo & Faaij, André P.C. & van der Hilst, Floor, 2018. "Interregional assessment of socio-economic effects of sugarcane ethanol production in Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 347-362.

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    More about this item

    Keywords

    Bioenergy; Sugarcane; Ethanol; Social impacts; Spatial dynamic panel;
    All these keywords.

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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