Measurement of economic returns and risks in adoption of RI maize in São Paulo State

• Grant number: 11/08723-6
• Support Opportunities: Regular Research Grants
• Start date: December 01, 2011
• End date: November 30, 2012
• Field of knowledge: Agronomical Sciences - Agronomy
• Principal Investigator: Maura Seiko Tsutsui Esperancini
• Grantee: Maura Seiko Tsutsui Esperancini
• Host Institution: Faculdade de Ciências Agronômicas (FCA). Universidade Estadual Paulista (UNESP). Campus de Botucatu. Botucatu , SP, Brazil

Abstract

One of the reasons for the rapid adoption of transgenic maize in Brazil, particularly the insect-resistant maize (IR) is the economic benefits that this technology can provide to producers, as cost savings in insecticides application as well as the increased income due to increased productivity, by reducing losses attacks lepidopterans. It is further considered that these benefits outweigh the costs of technology, which is the premium paid by producers in using RI maize seed. Considering that both the benefits and gains for producers are subject to the changes in critical variables, it is objective of this study to measure the economic returns of IR maize adopters in two of the main producing regions of São Paulo, introducing the variation in quantities and prices of insecticides, productivity gains and variation in price differences between RI seed maize and conventional hybrids as well as the variation in corn prices. The methodology to be used will be the assessment of net benefits, ie, the economic gains less costs of GM technology, under conditions of risk. Net benefits may vary due three critical variables: 1) increased productivity of GM maize, 2) cost control of plagues, 3) cost of transgenic seeds and 4) Market prices of maize. The probability distribution functions will be estimate for the critical variables, and using Monte Carlo method of simulation, will be estimated the following sets of indicators: measures of central tendency, variability of net benefits (total benefits - total costs), sensitivity analysis of net benefits in relation to critical variables and, so the mapping of risk adopters of GM technology. These indicators will draw economic scenarios associated with its occurrence probability. (AU)