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Profitability prospects, risk aversion and time preferences of soybean producers in the region of Santarém, Brazilian Amazon: perspectives for an ecological transition

Published online by Cambridge University Press:  18 November 2020

Gabriel Leblanc ,
Marc Lucotte ,
Frédéric Mertens  and
Charles Séguin Open the ORCID record for Charles Séguin [Opens in a new window]
Gabriel Leblanc
Affiliation:
Institut des sciences de l'environnement, Faculté des sciences, Université du Québec à Montréal, Montréal (Québec), Canada
Marc Lucotte
Affiliation:
Institut des sciences de l'environnement, Faculté des sciences, Université du Québec à Montréal, Montréal (Québec), Canada GEOTOP and Département des sciences de la Terre et de l'atmosphère, Faculté des sciences, Université du Québec à Montréal, Montréal (Québec), Canada
Frédéric Mertens
Affiliation:
Universidade de Brasília - UnB, Centro de Desenvolvimento Sustentável, Brasilia, Federal District, Brazil
Charles Séguin*
Affiliation:
Institut des sciences de l'environnement, Faculté des sciences, Université du Québec à Montréal, Montréal (Québec), Canada Département des sciences économiques, École des sciences de la gestion, Université du Québec à Montréal, Case postale 8888, succursale Centre-ville, Montréal, (Québec) H3C 3P8, Canada
*
Author for correspondence: Charles Séguin, E-mail: [email protected]
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Abstract

Reducing adverse environmental consequences of modern industrial agriculture requires an ecological transition of agricultural practices. An important determinant of adoption of new agricultural practices by producers is the perceived profitability of these practices. The profitability of ecological agricultural practices tends to rely on improved crop prices and reduced input use. Transition to such practices often entails increased profit volatility (risk) and long-term returns (temporal profile). Ideal candidates for transition would therefore be aware of the output price and input costs dimensions of their profitability, as well as willing to assume some risks and show patience to value long-term returns. We assessed the potential for such a transition along these three dimensions (profitability, risk aversion and time preferences) in a group of soybean producers in the agricultural frontier of the Brazilian Amazon. Primary data were collected using a questionnaire and economic tests in the region of Santarém (State of Pará, Brazil). We found that, while these producers have a low-risk aversion that could favor the adoption of new ecological practices, their focus on increasing yields to enhance profits and their high discount rates considerably reduces their propensity to adopt these practices.

Keywords

Agricultural profitabilityecological transitionrisk aversiontime preferences
Type
Research Paper
Information
Renewable Agriculture and Food Systems , Volume 36 , Issue 3 , June 2021 , pp. 290 - 298
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Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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References

Acs, S, Berentsen, PBM and Huirne, RBM (2007) Conversion to organic arable farming in The Netherlands: a dynamic linear programming analysis. Agricultural Systems 94, 405–415.CrossRefGoogle Scholar
Acs, S, Berentsen, P, Huirne, R and Van Asseldonk, M (2009) Effect of yield and price risk on conversion from conventional to organic farming. Australian Journal of Agricultural and Resource Economics, 53, 393–411.CrossRefGoogle Scholar
Andersen, S, Harrison, GW, Lau, MI and Rutström, EE (2006) Elicitation using multiple price list formats. Experimental Economics 9, 383–405.CrossRefGoogle Scholar
Andersen, S, Harrison, GW, Lau, MI and Rutström, EE (2008) Eliciting risk and time preferences. Econometrica 76, 583–618.CrossRefGoogle Scholar
Barr, A (2003) Risk Pooling, Commitment, and Information: An experimental test of two fundamental assumptions. Centre for the Study of African Economies Working Paper, 187.Google Scholar
Benbrook, CM (2016) Trends in glyphosate herbicide use in the United States and globally. Environmental Sciences Europe 28, 3.CrossRefGoogle ScholarPubMed
Binswanger, HP (1980) Attitudes toward risk: experimental measurement in rural India. American Journal of Agricultural Economics 62, 395–407.CrossRefGoogle Scholar
CAR (2020) Cadastro Ambiental Rural Modulo de Cadastro Manual do Úsario v2.0, p. 141.Google Scholar
Cavigelli, MA, Hima, BL, Hanson, JC, Teasdale, JR, Conklin, AE and Lu, YC (2009) Long-term economic performance of organic and conventional field crops in the mid-Atlantic region. Renewable Agriculture and Food Systems 24, 102–119.CrossRefGoogle Scholar
Clark, S, Klonsky, K, Livingston, P and Temple, S (1999) Crop-yield and economic comparisons of organic, low-input, and conventional farming systems in California's Sacramento Valley. American Journal of Alternative Agriculture 14, 109–121.CrossRefGoogle Scholar
CONAB (2017) Séries historicas. Available at http://www.conab.gov.br/conteudos.php?a=1252.Google Scholar
Dabbert, S and Madden, P (1986) The transition to organic agriculture: a multi-year simulation model of a Pennsylvania farm. American Journal of Alternative Agriculture 1, 99–107.CrossRefGoogle Scholar
Delbridge, TA, Coulter, JA, King, RP, Sheaffer, CC and Wyse, DL (2011) Economic performance of long-term organic and conventional cropping systems in Minnesota. Agronomy Journal 103, 1372–1382.CrossRefGoogle Scholar
De Ponti, T, Rijk, B and Van Ittersum, MK (2012) The crop yield gap between organic and conventional agriculture. Agricultural Systems 108, 1–9.CrossRefGoogle Scholar
Duke, SO (2015) Perspectives on transgenic, herbicide-resistant crops in the United States almost 20 years after introduction. Pest Management Science 71, 652–657.CrossRefGoogle ScholarPubMed
Duquette, E, Higgins, N and Horowitz, J (2013) Time Preference and Technology Adoption: A Single-Choice Experiment with US Farmers.Google Scholar
Duru, M, Therond, O and Fares, M (2015) Designing agroecological transitions; a review. Agronomy for Sustainable Development 35, 1237–1257.CrossRefGoogle Scholar
FAO (2009) Available at http://www.fao.org/wsfs/forum2050/wsfs-forum/en/.Google Scholar
Ferguson, RS and Lovell, ST (2014) Permaculture for agroecology: design, movement, practice and worldview. A review. Agronomy for Sustainable Development 34, 251–274.CrossRefGoogle Scholar
Galor, O and Özak, Ö (2016) The agricultural origins of time preference. American Economic Review 106, 3064–3103.CrossRefGoogle ScholarPubMed
Garrett, RD, Lambin, EF and Naylor, RL (2013) The new economic geography of land use change: supply chain configurations and land use in the Brazilian Amazon. Land Use Policy 34, 265–275.CrossRefGoogle Scholar
Ghadim, AKA, Pannell, DJ and Burton, MP (2005) Risk, uncertainty, and learning in adoption of a crop innovation. Agricultural Economics 33, 1–9.CrossRefGoogle Scholar
Gibbs, HK, Rausch, L, Munger, J, Schelly, I, Morton, DC, Noojipady, P, Soares-Filho, B, Barreto, P, Micol, L, Walker, NF and Walker, NF (2015) Brazil's soy moratorium. Science (New York, N.Y.) 347, 377–378.CrossRefGoogle ScholarPubMed
Grisley, W and Kellog, E (1987) Risk-taking preferences of farmers in northern Thailand: measurements and implications. Agricultural Economics: The Journal of the International Association of Agricultural Economists, 1(968-2016-75379), 127–142.Google Scholar
Hardaker, JB, Lien, G, Anderson, JR and Huirne, RB (2015) Coping with Risk in Agriculture: Applied Decision Analysis. Boston, MA: CABI.CrossRefGoogle Scholar
Harrison, GW, Humphrey, SJ and Verschoor, A (2010) Choice under uncertainty: evidence from Ethiopia, India and Uganda. The Economic Journal 120, 80–104.CrossRefGoogle Scholar
Hepperly, PR, Douds, D and Seidel, R (2006) The Rodale Institute Farming Systems trial 1981 to 2005: Long-term analysis of organic and conventional maize and soybean cropping systems. In Long-Term Field Experiments in Organic Farming. ISOFAR Scientific Series, Berlin: Verlag Dr. H. J. Köster, pp. 15–32.Google Scholar
Horrigan, L, Lawrence, RS and Walker, P (2002) How sustainable agriculture can address the environmental and human health harms of industrial agriculture. Environmental Health Perspectives 110, 445–456.CrossRefGoogle ScholarPubMed
IBGE (2016) Pará. Santarém. Infográficos: despesas e receitas orçamentárias e pib. Available at http://cidades.ibge.gov.br/painel/economia.php?lang=&codmun=150680&search=para|santarem|infogr%E1ficos:-despesas-e-receitas-or%E7ament%E1rias-e-pib.Google Scholar
IBGE (2017 a) Conheça Cidades E Estados Do Brasil. Available at http://cidades.ibge.gov.br.Google Scholar
IBGE (2017 b) Censo Agro 2017. Available at https://censoagro2017.ibge.gov.br/templates/censo_agro/resultadosagro/produtores.html?localidade=15.Google Scholar
INPE (2019) Available at http://terrabrasilis.dpi.inpe.br/app/dashboard/alerts/legal/amazon/aggregated/.Google Scholar
IPCC (2019) Climate Change and Land. Available at https://www.ipcc.ch/srccl/.Google Scholar
IPEADATA (2010) Instituto de Pesquisa Economica Aplicada. Área colhida – soja. http://www.ipeadata.gov.br/.Google Scholar
Knapp, S and van der Heijden, MG (2018) A global meta-analysis of yield stability in organic and conservation agriculture. Nature communications, 9, 3632.CrossRefGoogle ScholarPubMed
Kurosaki, T and Fafchamps, M (2002) Insurance market efficiency and crop choices in Pakistan. Journal of Development Economics 67, 419–453.CrossRefGoogle Scholar
Langley, JA, Heady, EO and Olson, KD (1983) The macro implications of a complete transformation of US agricultural production to organic farming practices. Agriculture, Ecosystems & Environment 10, 323–333.CrossRefGoogle Scholar
Liu, T, Bruins, RJ and Heberling, MT (2018) Factors influencing farmers’ adoption of best management practices: a review and synthesis. Sustainability 10, 432.CrossRefGoogle ScholarPubMed
Malézieux, E (2012) Designing cropping systems from nature. Agronomy for Sustainable Development 32, 15–29.CrossRefGoogle Scholar
Miyata, S (2003) Household's risk attitudes in Indonesian villages. Applied Economics 35, 573–583.CrossRefGoogle Scholar
Moscardi, E and De Janvry, A (1977) Attitudes toward risk among peasants: an econometric approach. American Journal of Agricultural Economics, 59, 710–716.CrossRefGoogle Scholar
Ollivier, G, Magda, D, Mazé, A, Plumecocq, G and Lamine, C (2018) Agroecological transitions: what can sustainability transition frameworks teach us? An ontological and empirical analysis. Ecology and Society 23, 5.CrossRefGoogle Scholar
Rodriguez, J, Molnar, J, Fazio, R, Sydnor, E and Lowe, M (2009) Barriers to adoption of sustainable agriculture practices: change agent perspectives. Renewable Agriculture and Food Systems 24, 60–71.CrossRefGoogle Scholar
Rosenzweig, MR and Wolpin, KI (1993) Credit market constraints, consumption smoothing, and the accumulation of durable production assets in low-income countries: investments in bullocks in India. Journal of Political Economy 101, 223–244.CrossRefGoogle Scholar
Schnitkey, G (2019) Expected Corn Versus Soybean Returns in 2019. Farmdoc Daily (9): 29. Urbana, IL: Department of Agricultural and Consumer Economics, University of Illinois at Urbana-Champaign.Google Scholar
Seufert, V, Ramankutty, N and Foley, JA (2012) Comparing the yields of organic and conventional agriculture. Nature 485, 229–232.CrossRefGoogle ScholarPubMed
Soares-Filho, B, Rajão, R, Merry, F, Rodrigues, H, Davis, J, Lima, L, Macedo, M, Coe, M, Carneiro, A and Santiago, L (2016) Brazil's market for trading forest certificates. PLoS One 11, 4.CrossRefGoogle ScholarPubMed
Tanaka, T, Camerer, CF and Nguyen, Q (2010) Risk and time preferences: linking experimental and household survey data from Vietnam. American Economic Review 100, 557–571.CrossRefGoogle Scholar
Trading Economics (2020a) Brazil Inflation Rate 1980–2020. https://tradingeconomics.com/brazil/inflation-cpi.Google Scholar
Trading Economics (2020b) Denmark Inflation Rate 1981–2020. https://tradingeconomics.com/denmark/inflation-cpi.Google Scholar
Van Bruggen, AHC, He, MM, Shin, K, Mai, V, Jeong, KC, Finckh, MR and Morris, JG Jr (2018) Environmental and health effects of the herbicide glyphosate. Science of the Total Environment, 616, 255–268.CrossRefGoogle ScholarPubMed
Vincent-Caboud, L, Peigné, J, Casagrande, M and Silva, EM (2017) Overview of organic cover crop-based no-tillage technique in Europe: farmers’ practices and research challenges. Agriculture 7, 42.CrossRefGoogle Scholar
Walker, R, Defries, R, del Carmen Vera-Diaz, M, Shimabukuro, Y and Venturieri, A (2009) The expansion of intensive agriculture and ranching in Brazilian Amazonia. Washington DC American Geophysical Union Geophysical Monograph Series, 186, 61–81. Washington, DC: AGU.Google Scholar
Weiner, J (2003) Ecology–the science of agriculture in the 21st century. The Journal of Agricultural Science 141, 371–377.CrossRefGoogle Scholar
Wik, M, Aragie Kebede, T, Bergland, O and Holden, ST (2004) On the measurement of risk aversion from experimental data. Applied Economics, 36, 2443–2451.CrossRefGoogle Scholar
XE (2017) XE: BRL/USD Currency Chart. https://www.xe.com/fr/currencycharts/?from=BRL&to=USD.Google Scholar
Yesuf, M and Bluffstone, RA (2009) Poverty, risk aversion, and path dependence in low-income countries: experimental evidence from Ethiopia. American Journal of Agricultural Economics 91, 1022–1037.CrossRefGoogle Scholar