1. Ravello, June 17 th 2015 Jaim J. da Silva Jr. GM COTTON SEEDS DIFFUSION: IMPACT ASSESSMENT ATBRAZILLIAN AGRIBUSINESS 1

2. Cotton Production in Brazil Total Cotton area 2013/2014- 1.1 million hectares Concetrated in 2 regions: Mato Grosso (57%) and Matopiba (32%) Second season for soybean Yields (ton/ha) Quantity (ton) lack of information

4. Average area of the plots in the sample – 1,296 Hectares Data on cotton production among 2009-2013 seasons at the Mato Grosso State. The data comprises values of 157 farms, separated by plots at farm level.

5. 5 Seed Market Structure and Sample data Where: -WA is the weighted average age of varieties of the sample, - p is the proportion of the area sown to variety i in year t and, - R is the number of years (time t) since the registration (RNC) of variety i.

6. 6 Seed and Trait Market structure National MarketRegisteredFirms SampleRegisteredFirms Total Cultivars18114Total Cultivars6010 GM Cultivars476GM Cultivars254 Traits63 43 Firm Market Share (%)2010/2011 Bayer50% FMT23% MDM14% IMAMT8% EMBRAPA1% Others4% Source: Céleres Consulting

7. 7 Introduction and Outline Demand for agricultural biotechnologies in developing countries are growing fast. Commercial approval of GM cotton seeds in 2003. Nowadays it is widespread in about 50% of the cotton area. Although Brazil holds the 2nd position in the global ranking of GM seeds, research on socioeconomic and environmental impacts assessment at farm level still incipient; Céleres (2014), Alves et al. (2012), Seixas e Silveira (2014). General objective - evaluate profit and yield impacts from using GM cotton seeds in Brazillian agribusiness.

8. 8 Introduction and Outline Research looks the diffusion of GM cotton seeds at the Mato Grosso State. Econometric models based on farm level dataset to assess net profit and yield changes per hectare. Identification strategy: interfarm variation in gross operational margin and productivity per hectare for different seed traits (Conventional, Bt, HT) along of the 2009 - 2013 seasons. Main results: Possible to identify a reduction in the number of insecticides application and insecticide spending per hectare when comparing Bt and conventional seeds Models does not confirm that there are differences in profit and yield between conventional and transgenic cotton seeds (Bt and HT)

9. 9 Dataset and Descriptive Statistics Plot Level Information 2009-2013 ConventionalHt Bt Seed Cost (R$/Hectare) 149.26 260.55 368.83 (71.91) (106.11) (79.84) Insectiticide applications (number/hectare)13.10 12.90 10.07 (3.63) (3.50) (2.10) Herbicide applications (number/hectare) 4.13 4.64 3.82 (1.53) (1.60) (1.51) Insecticide Spending(R$/Hectare) 641.51 606.29 458.57 (223.04) (260.57) (203.76) Herbicide Spending (R$/Hectare) 334.62 286.06 341.08 (149.47) (121.17) (120.80) Yield (Arroba/Hectare) 272.45 263.09 267.05 (31.33) (28.00) (30.25) Direct Costs (R$/Hectare) 4,081 3,721 3,623 (588.74) (498.43) (524.10) Gross Margin (R$/Hectare) 3,047 3,339 3,387 (1,284) (938) (1,261) No.of plots 164 83 56 Source: Research data

10. 10 Dataset and Empirical Strategy Survey on costs, revenues, production and biotech adoption that has been conducted by a private consulting firm during 2009-2013 at the State of Mato Grosso. The sample used in the estimations comprises 303 observations, separated according to the plots on the farm. Thus, each observation corresponds to plot i, in the year t, producing cotton using a determined type of seed (Conventional, Bt, HT).

11. 11 The Model Net impact of Seed type on cotton yield and profit per hectare (Kathage and Qaim, 2012). Pooled data and panel random effects specifications of a cotton yield function and a cotton profit function Log log models with dummies for controling time, region and seed type. Model 1 - Pooled data - Estimated equation: Y = α + βX + δt + е Model 2- Panel data (random effects) – Estimated equation: Y it = β 0 + β 1 X it + w it where w it = c i + e it

12. 12 The Model VMP 1 VMP 0 x $ w Prediction: HT seed increases the amount of pr0duction do to better control of weed. Net environmental effect is ambiguous Scale? Substitution?

13. 13 The Model VMP 0 VMP 1 x $ w Prediction: Bt seed decreases the amount of insecticides and increases the profitability

14. 14 Cotton Yield Model – Dependent Variable: Productivity (Kg of fiber and feather per hectare) *,**,*** indicates that the estimated coefficient is statistically significant to 10%, 5% and 1%, respectively. In both models, the dependant variable is the gross operating margin, measured in R$ per hectare. The values in parenthesis correspond to the standard deviation.

15. 15 Cotton Profit Model – Dependent Variable: Gross margin (R$/Ha) *,**,*** indicates that the estimated coefficient is statistically significant to 10%, 5% and 1%, respectively. In both models, the dependant variable is the gross operating margin, measured in R$ per hectare. The values in parenthesis correspond to the standard deviation.

16. 16 Wrapping Up Econometric models showed non evidence that GM cotton seeds (IR or Bt trait) increases profit or yield. It is possible for cotton farms in Brazil to attain the same level of productivity using either the insect-resistant seeds or using insecticides to manage insects; New and old pleagues not controlled by the insect resistance trait. Grass resistance on herbicide tolerant. Seed price increases and weak substition of pesticides captures most of the positive impacts of GM seed adoption.

17. 17 Wrapping Up In the particular case of Brazil, where farmers have a well-defined cotton production function, the results are in keeping with the reality observed. This is due to the fact that in the growing environment there are different pests against which the insect-resistant trait is not effective in its control; It can therefore be deduced that the delay in diffusion process of transgenic cotton seeds is associated not to a lack of information on the part of the farmers, but to their deep knowledge on pest and weed control methods, therefore the focus on productivity and profit gains changes when they decide to adopt new technologies.

18. 18 ControlModerate controlNo control Alabama argillaceaHelicoverpa zeaAnthonomus grandis SP Chrysodeixis includensHelicoverpa armigeraAphis gossypii Heliothis virescensSpodoptera frugiperdaNezara viridula Pectinophora gossypiellaEuschistos heros Spodoptera eridania Spodoptera cosmioides New Plagues

19. 19 THANK YOU! jaim@eco.unicamp.br