Skip to main content

Advertisement

SpringerLink
Log in

Potential impacts on local quality of life due to sugarcane expansion: a case study based on panel data analysis

  • Case Study
  • Published:
Environment, Development and Sustainability Aims and scope Submit manuscript

Abstract

Agribusiness participation in Brazil generates investments in rural infrastructure and employment, with direct effects on local quality of life. In this sense, government policies to support the production of ethanol from sugarcane and to promote bioelectricity from bagasse production have made Brazil a country of world leadership in this field. This paper reports an assessment of socioeconomic impacts due to sugarcane production in three regions in Brazil (Piracicaba, Presidente Prudente and Southwest Goiás). Local quality of life is defined as five dimensions: income and inequality, education, infrastructure, health and general development, analysed using panel data modelling, with variables that could explain differences in development due to local characteristics, including sugarcane activity. Presidente Prudente has the highest levels of progress in education, poverty, infrastructure and general development indicators. The models indicate that participation of sugarcane has positive impacts on the indicators of the microregion. In case of Piracicaba microregion, in two models (“L-Theil” and “Illiteracy rate”) indicators related with sugarcane sector are significant explanatory variables, contributing for better indicators. Finally, Southwest Goias—where sugarcane activity develops later—is the single microregion in which the adjusted models have no significant explanatory variables related to sugarcane sector.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  • Albouy, D. (2008). Are big cities bad places to live? Estimating quality of life across metropolitan areas. Cambridge: National Bureau of Economic Research.

    Book  Google Scholar 

  • Anríquez, G., & Stamoulis, K. (2007). Rural development and poverty reduction: Is agriculture still the key? Journal of Agricultural and Development Economics, 4(1), 5–46.

    Google Scholar 

  • Anyaehie, M., & Areji, A. (2015). Economic diversification for sustainable development in Nigeria. OJPS, 05(02), 87–94.

    Article  Google Scholar 

  • Binder, M., & Georgiadis, G. (2010). Determinants of human development: Insights from state-dependent panel models. Human Development reports. United Nations.

  • Birthal, P., Roy, D., & Negi, D. (2015). Assessing the impact of crop diversification on farm poverty in India. World Development, 72, 70–92.

    Article  Google Scholar 

  • Camargo, A., & Toneto, R. (2008). Indicadores socioeconomicos e a cana-de-açúcar no estado de São Paulo. In 1º Workshop do Observatório do Setor Sucroalcooleiro. Piracicaba.

  • Campeão, P., Sauer, L., Sproesser, R., & de Paulo, N. (2009). Influência do setor sucroalcooleiro no Índice de Desenvolvimento Humano Municipal (IDH-M). In 47º SOBER (pp. 1–15). Porto Alegre: SOBER. Available at: http://www.sober.org.br/palestra/13/1329.pdf. Accessed 8 Feb 2016.

  • Castro, N., Brandão, R., & Dantas, G. (2010). A bioeletricidade sucroenergética na matriz elétrica. In E. Souza & I. Macedo (Eds.), Etanol e bioeletricidade (1st ed., pp. 140–153). São Paulo: Luc Projetos de Comunicação.

    Google Scholar 

  • Caumo, A. et al. (2011). O corte manual da cana-de-açúcar sob uma perspectiva de gênero: um estudo de caso no município de Mirandópolis—SP. In Congresso sociedade brasileira de economia, administração e sociologia rural (pp. 1–19). Belo Horizonte: Grupo de Pesquisa 9: Políticas Sociais para o Campo.

  • Chagas, A. (2010). mpacto da Produção de Cana-de-Açúcar sobre as Condições Sociais das Regiões Canavieiras. Informações Fipe. pp. 10–15. http://downloads.fipe.org.br/publicacoes/bif/2010/4_bif355a.pdf. Accessed May 4, 2016.

  • Clements, E. (2012). Agrarian reform, food sovereignty and the MST: socioenvironmental impacts of agrofuels production in the Pontal do Paranapanema region of São Paulo state, Brazil. NERA, 21, 08–32.

    Google Scholar 

  • Cook, P. (2011). Infrastructure, rural electrification and development. Energy for Sustainable Development, 15(3), 304–313. 10.1016/j.esd.2011.07.008. Accessed Sept 19, 2014.

  • De Janvry, A., & Sadoulet, E. (2000). Rural poverty in Latin America: Determinants and exit paths. Food Policy, 25(4), 389–409.

    Article  Google Scholar 

  • Diener, E., & Suh, E. (1997). Measuring quality of life: Economic, social and subjective indicators. Social Indicators Research, 40, 189–216.

    Article  Google Scholar 

  • Epley, D., & Menon, M. (2007). A method of assembling cross-sectional indicators into a community quality of life. Social Indicators Research, 88(2), 281–296.

    Article  Google Scholar 

  • European Commission. (2008). Poverty and social exclusion in rural areas. Directorate-General for Employment, Social Affairs and Equal Opportunities.

  • Feliciano, C. (2013). O conflito como elemento chave na construção da região do Pontal do Paranapanema. Acta Geográfica, 1, 167–186.

    Article  Google Scholar 

  • Fernandes, C. et al. (2011). O mercado de trabalho formal no setor sucroalcooleiro no Brasil. In Congresso sociedade brasileira de economia, administração e sociologia rural. Belo Horizonte: Grupo de Pesquisa 10: Desenvolvimento Rural, Territorial e Regional.

  • Guedes, P. L., Sparovek, G., & Bernardes, M. (2015). Feasibility of cultivation of sugarcane in agroforestry systems. Scientia agrícola, 60(3), 489–493.

    Google Scholar 

  • Hart, M. (1999). Guide to sustainable community indicators. North Andover, MA: Hart Environmental Data.

    Google Scholar 

  • Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46, 1251–1271.

    Article  Google Scholar 

  • Hoffmann, R. (2008). Income of people engaged in Brazil’s sugar cane agribusiness. In M. A. de Almeida (Eds.), Sugarcane (1st ed., pp. 199–236). São Paulo: Berlendis.

    Google Scholar 

  • IRENA. (2014). Supply and demand projections. Global bioenergy. Bonn: IRENA.

    Google Scholar 

  • Jannuzzi, P. (2001). Indicadores sociais no Brasil. Campinas, SP: Alínea Editora.

    Google Scholar 

  • Kanagawa, M., &; Nakata, T. (2008). Assessment of access to electricity and the socio-economic impacts in rural areas of developing countries. Energy Policy, 36(6), 2016–2029. 10.1016/j.enpol.2008.01.041. Accessed Sept 19, 2014.

  • Leknes, S. (2015). The more the merrier? Evidence on quality of life and population size using historical mines. Regional Science and Urban Economics, 54, 1–17.

    Article  Google Scholar 

  • Machado, P. (2012). Análise de Indicadores Socioeconômicos em Municípios Canavieiros: estudos de caso em São Paulo e Alagoas. Master. State University of Campinas.

  • Machado, P., Picoli, M., Torres, L., Oliveira, J., & Walter, A. (2015). The use of socioeconomic indicators to assess the impacts of sugarcane production in Brazil. Renewable and Sustainable Energy Reviews, 52, 1519–1526.

    Article  Google Scholar 

  • Martinelli, L., Garrett, R., Ferraz, S., & Naylor, R. (2011). Sugar and ethanol production as a rural development strategy in Brazil: Evidence from the state of São Paulo. Agricultural Systems, 104(5), 419–428.

    Article  Google Scholar 

  • Matarrita-Cascante, D. (2009). Changing communities, community satisfaction, and quality of life: A view of multiple perceived indicators. Social Indicators Research, 98(1), 105–127.

    Article  Google Scholar 

  • Mendonça, M. (2006). A OMC e os Efeitos Destrutivos da Indústria da Cana no Brasil. http://www.social.org.br/relatorio2005/relatorio033.htm. Accessed May 4, 2016.

  • Molina, G., & Purser, M. (2010). Human development trends since 1970: A social convergence story. Human Development Reports. United Nations.

  • Moraes, M. (2007). Indicadores do mercado de trabalho do sistema agroindustrial da cana-de-açúcar do Brasil no período 1992–2005. Estudos Econômicos, 37(4), 875–902.

    Article  Google Scholar 

  • Moraes, M. et al. (2010). Externalidades sociais dos combustíveis. In E. L.L. de Sousa & I. de Carvalho Macedo (Eds.), Etanol e Bioeletricidade: A cana-de-açúcar no futuro da matriz energética (1st ed., pp. 48–74). São Paulo: Luc Projetos de Comunicação.

    Google Scholar 

  • Nassar, A., Rudorff, B., Antoniazzi, L., Alves de Aguiar, D., Piedade Bacchi, M., & Adani, M. (2008). Sugarcane ethanol (1st ed.). Wageningen: Wageningen Academic Publishers.

    Google Scholar 

  • Neves, M., Trombin, V., & Consoli, M. (2010). O mapa sucroenergético do Brasil. In E. Souza & I. Macedo (Eds.), Etanol e bioeletricidade (1st ed.). São Paulo: Luc Projetos de Comunicação.

    Google Scholar 

  • Park, H. (2011). Practical guides to panel data modeling: A step-by-step analysis using stata. Tutorial working paper. Graduate School of International Relations, International University of Japan.

  • Petrini, M., & Rocha, J. (2014). Identification of grain areas replaced by sugarcane and analysis of the relationship with family farming production in the state of Goiás. Engenharia Agrícola, 34(6), 1296–1306.

    Article  Google Scholar 

  • PNUD. (2014). PNUD Brasil—Programa das Nações Unidas para o Desenvolvimento. http://www.pnud.org.br/Noticia.aspx?id=3909. Accessed Sept 23, 2014.

  • Reporter Brasil, (2009). O Brasil dos agrocombustíveis: Impactos das lavouras sobre a terra, o meio e a sociedade. Impacto das lavouras sobre a terra, o meio e a sociedade. http://www.reporterbrasil.org.br/documentos/o_brasil_dos_agrocombustiveis_v5.pdf. Accessed May 4, 2016.

  • Ribeiro de Oliveira, F. (2009). Ocupação, emprego e remuneração na cana-de-açúcar e em outras atividades agropecuárias no Brasil, de 1992 a 2007. Master. Escola Superior de Agricultura Luiz de Queiroz.

  • Rocha, F. (2007). Avaliação do custo, produtividade e geração de emprego no corte de cana-de-açúcar, manual e mecanizado, com e sem queima prévia. Mestrado, UNESP, PhD, USP.

  • Schalock, R., Bonham, G., & Verdugo, M. (2008). The conceptualization and measurement of quality of life: Implications for program planning and evaluation in the field of intellectual disabilities. Evaluation and Program Planning, 31(2), 181–190.

    Article  Google Scholar 

  • Silva, R. (2008). Setor sucroalcooleiro no estado de São Paulo: mensurando impactos socioeconômicos. In 1° Workshop do Observatório do Setor Sucroalcooleiro. Piracicaba, pp. 1–16.

  • Sirgy, M., Michalos, A., Ferriss, A., Easterlin, R., Patrick, D., & Pavot, W. (2006). The qualityity-of-life (QOL) research movement: Past, present, and future. Social Indicators Research, 76(3), 343–466.

    Article  Google Scholar 

  • Sirgy, M., Widgery, R., Lee, D., & Yu, G. (2009). Developing a measure of community well-being based on perceptions of impact in various life domains. Social Indicators Research, 96(2), 295–311.

    Article  Google Scholar 

  • Torres, L. (2013). Análise de Indicadores Socioeconômicos para Avaliação de Impactos da Cana-de-Açúcar nos Principais Estados Produtores. Master. UNICAMP.

  • Vieira, G. (2003). Avaliação do custo, produtividade e geração de emprego no corte de cana-de-açúcar, manual e mecanizado, com e sem queima prévia. Master. UNESP.

  • Walter, A., Dolzan, P., Quilodrán, O., de Oliveira, J., da Silva, C., Piacente, F., & Segerstedt, A. (2011). Sustainability assessment of bio-ethanol production in Brazil considering land use change, GHG emissions and socio-economic aspects. Energy Policy, 39(10), 5703–5716.

    Article  Google Scholar 

  • Weinhold, I., & Gurtner, S. (2014). Understanding shortages of sufficient health care in rural areas. Health Policy. 10.1016/j.healthpol.2014.07.018. Accessed Sept 19, 2014.

  • Wooldridge, J. (2002). Econometric analysis of cross section and panel data (1st ed.). Cambridge, MA: MIT Press.

    Google Scholar 

  • Wu, F., Zhang, D., & Zhang, J. (2008). Unequal education, poverty and low growth—A theoretical framework for rural education of China. Economics of Education Review, 27(3), 308–318. 10.1016/j.econedurev.2006.09.008. Accessed Sept 17, 2014.

  • Yamaguchi, A. (2014). Influences of quality of life on health and well-being. Social Indicators Research, 123(1), 77–102.

    Article  Google Scholar 

Download references

Acknowledgements

This paper reports results of a research developed with the financial support of Fundação do Amparo a Pesquisa do Estado de São Paulo—FAPESP (project 2011/51710-2). The authors would like to thank FAPESP for this support. Pedro Machado is also grateful to the Brazilian agency CNPq for the financial support received as grants.

Author information

Authors and Affiliations

  1. Mechanical Engineering Faculty, UNICAMP, Rua Mendeleyev, 200, Cidade Universitária “Zeferino Vaz” Barão Geraldo, Campinas, SP, CEP 13083-860, Brazil

    Pedro Gerber Machado & Arnaldo Walter

  2. Brazilian Bioethanol Science and Technology Laboratory, Rua Giuseppe Máximo Scalfaro, 10.000, Bairro Guará, Campinas, SP, CEP 13083-100, Brazil

    Michelle Cristina Picoli

  3. “Governance, Biodiversity, Protected Areas and Social Inclusion” Research Group, Av. Pasteur, 250, Instituto de Psicologia da UFRJ - Pavilhão Nilton Campos, Praia Vermelha, Rio de Janeiro, RJ, CEP 22290-240, Brazil

    Cristina Gerber João

Authors
  1. Pedro Gerber Machado
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Arnaldo Walter
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michelle Cristina Picoli
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Cristina Gerber João
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pedro Gerber Machado.

Appendix

Appendix

See Table 8.

Table 8 Three microregions and their municipalities (and the identification of the correspondent dummies)
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Machado, P.G., Walter, A., Picoli, M.C. et al. Potential impacts on local quality of life due to sugarcane expansion: a case study based on panel data analysis. Environ Dev Sustain 19, 2069–2092 (2017). https://doi.org/10.1007/s10668-016-9823-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10668-016-9823-6

Keywords

Search

Navigation