1. Jeffrey Vitale Gaspard Vognan

2. Source: ISAAA 2011.

3.  What makes the Burkina Faso story unique?  Demonstrates the feasibility of commercially introducing a GM crop in a less developed country  Persistence and determination in an environment often hostile to biotechnology and GM crops  Collaboration among diverse stakeholders, including smallholder producers, private sector, and public sector

4.  Stagnation  2003-05 Confined Field Trials Ref: Huma et al. 2007;Vitale et al. 2008  2006 Demonstration Plots  2007 On-farm trials  2008 Limited Commercial release  2009-14 Large-Scale Commercial release Testing Legal Framework Biosafety Protocols Monitor & Evaluate Ref: Sustainability paper, Sanders et al., Tom Bassett

5. Summary of Bollgard II® in Burkina Faso: Documented Findings from Surveys Six years of commercial use (2009-2014) – Approaching “full” adoption threshold Higher BGII yields in all years (20.5%) Lower pesticide use (2/3 reduction) Higher economic returns in all years – Consistent with yield increase since no significant change in costs (higher seed cost offset by insecticide cost savings) Health benefits (self-reported) ($1 million annual)

6. BGII Adoption Profile

7. Conventional Cotton = “Gray” – “Red”

8. BGII Adoption Profile Roger’s 80% upper limit Seed Supply Issues Refugia

9. Ave Yield Increase = 20.5% INERA Producer Surveys b a

10. Six years of commercial use (2009-2014) Approaching “full” adoption threshold Higher BGII yields in all years (20.5%) Lower pesticide use (2/3 reduction) Higher economic returns in all years Proportional with yield increase since no significant change in costs: higher seed cost offset by insecticide cost savings → Economic Impact ≈ P cott *∆Yield Significant yield impact → Significant economic impact Health benefits (self-reported) ($1 million annual)

11. Are all farmers benefitting? Does location matter? – Modest regional difference but producers in all zones obtained significantly higher yields growing BGII compared to conventional cotton Does “farm size” matter? – “Larger” farms were found to have higher yields but farms of all size, including smallholder farms, obtained significantly higher yields growing BGII compared to conventional cotton

12. INERA Farm Type Classification Cotton Production Zone Yield ItemSOFITEX (N BT =109)SOCOMA (N BT =73)Faso Coton (N BT =75)All Zone (kg ha -1 ) Large n BT =66 n CV =77 Med n BT =31 n CV =47 Manual n BT =12 n CV =30 Ave Large n BT =23 n CV =21 Med n BT =42 n CV =32 Manual n BT =8 n CV =9 Ave Large n BT =14 n CV =15 Med n BT =61 n CV =56 Manual n BT =0 n CV =0 Ave n BT =257 n CV =287 BG II 1,293A1,169AB1,297AB1,258A1,192AB1,286A1,088ABC1,235A1,173AB954C-995B1,175a Conventional 1,105B1,084BC870C1,053B948BC964BC1,060ABC972B866C825C-834C981b Average Yield 1,199a1,127a1,083b1,155a1,070a1,125a1,074a1,103a1,019ab890b-914b1,078 Yield inc (kg ha -1 ) 1888542720624432227262307129-161193 Advantage (%) 17.07.949.119.525.733.42.627.035.415.6-19.319.7 Inc Rev: $ ha -1 102.4646.44232.38111.88132.58175.4914.84142.69167.0370.15-87.69105.30 Farm Size (ha) BGII 5.833.292.424.734.602.461.533.032.251.39 - 1.553.32 Conventional 4.262.772.003.373.052.071.672.341.571.08 - 1.182.60 Source: Vitale et al. (2010) AgBioforum

13. Production Zone: Sample Distribution

14. Yields by Production Zone b a

15. Why the Concern over Farm Size/Farm Structure? Welfare of the “smallholder farmer” is explicitly mentioned in Burkina Faso’s biosecurity legal framework Welfare of the smallholder farmer overarching theme of CGIAR and many NARS

16. How can Farms be Classified by Size? Biosecurity framework provides no specific definition of “smallholder farm” Our analysis has followed the classification used by INERA based on the # of draft animals owned by the household Given the importance of addressing the welfare of smallholders, we have been investigating whether another classification could provide a more accurate depiction of farm size

17. Farm Size: INERA Classification

18. Farm Size: Yields by INERA Class. A D C B C E R 2 = 0.198

19. Farm Size: Planted Area

20. Farm Size: Yields by Planted Area Small letters: means testing within each land class a b a R 2 = 0.187

21. Farm Size: Household Labor

22. Farm Size: Yields by Household Labor R 2 = 0.167 b a

23. Summary of Initial Findings BGII provided significantly higher yields and economic returns for all types of farmers, in particular smallholder farmers, using three alternative classifications (#animals, land size, HH labor) All three classifications provided about the same level of explanatory power, 17-20% On-going research: Would using all three farm structure variables provide a better farm classification?

24. Does Farm Size Affect BGII Impact? BG II is a scale neutral technology: – Control effectiveness of BGII independent of field size (~95%) – No new equipment needed (or that could be sold) – Seed cost on a per ha basis (no scale effect) – Insecticide costs on a per ha basis (no scale effect) Farm size and farm structure can affect yield performance …

25. Empirical Evidence Investigate the effect of farm size and farm structure on BG II yield performance using six years of cotton producer survey data Test whether farm size/farm structure related variables have a significant effect on cotton yield: – Farm size (area) – Household labor – Number of bullocks

26. Empirical Model Structure Y = α 0 + α 1 Year + α 2 Type + α 3 Zone + α 4 Sprays + β 1 Animals + β 2 Area + β 3 Labor + interactions Variables: – Type BGII or conventional – Year 2009-2014 – Zone SOFITEX,SOCOMA, or Faso Coton – Sprays Late season sprays (secondary pests) – Animals # of working animals (bullocks) – Area # hectares of cotton planted by household – Labor # of household members working on-farm

27. Model Results SourceEstimatePr>FEstimatePr>FEstimatePr>F Intercept853.7<.0001854.9 Year…<.0001 Type_Coton (BT=1)139.62<.0001146.41<.0001 Year*Type_Coton…0.00180.0020.0048 Zone…<.0001 Type_Coton*Zone…0.01020.01760.0358 Sprays…0.1180.16370.1121 Type_Coto*Sprays…0.00140.00150.0465 Labor0.0816430.9423-1.534640.4694-0.333580.8609 Land18.65116<.000116.788850.00815.93261<.0001 Animals26.68308<.000129.64985<.000132.24178<.0001 Labor*Land0.6748730.0141 Land*Animals-0.594330.6084 Labor*Animals-0.323120.5855 Labor/Land0.3109340.9114 Animals/Land-11.54530.0777 R2R2 Model 1 Model 2 Model 3 0.212 0.215 0.229

28. Model Results: Estimated BGII Yield Function: Land, Labor, and Animals 3 animals 4 laborers 1,100 kg yield 4 animals 8 laborers 1,250 kg yield

29. Practical Implication Research findings suggests that the prior definition used to define farm types, based only on # bullocks, is as good as alternative classifications using land and labor. Provide policy makers, and the on-going legal framework, with an alternative approach to define what a “smallholder” producer is, i.e. include a “3-D” definition.

30. The End

31. Does Farm Size Affect BGII Impact? BG II is a scale neutral technology: – Control effectiveness of BGII independent of field size (~95%) – No new equipment needed (or that could be sold) – Seed cost on a per ha basis (no scale effect) – Insecticide costs on a per ha basis (no scale effect) Farm size and farm structure can affect yield performance …

32. How Farm Size Can Matter: Stylized Facts Economy of scale: larger farms can more easily cover fixed costs compared to smaller ones – Higher profits earned by larger farms Wealth Effect: Higher profits enable larger (& better managed) farms to make more investments in equipment (e.g. animal traction) and resources – Bigger farms are wealthier & better equipped than smallholders who remain resource constrained – Greater efficiency, risk mgmt easier, access to capital

33. How Farm Size Can Matter: Stylized Facts “Rich get richer” while smallholders remain trapped in subsistence farming – Increase land holdings, access to quality lands, and political power while smaller producers are pushed to the margins

34. Empirical Evidence Investigate the effect of farm size and farm structure on BG II yield performance using six years of cotton producer survey data Test whether farm size/farm structure related variables have a significant effect on cotton yield: – Farm size (area) – Household labor – Number of bullocks

35. Scale Effects in Cotton Production Farm equipment (+) – Manual farms vs. animal powered vs. mechanized Deeper plowing, increased speed of operation for bigger farms Household farm labor (+/-) – Big farms likely to have larger workforce but also larger field size – Small farms could have more labor per ha but likely have greater labor demand since they are less well equipped – So this variable is difficult to predict a priori and likely to depend on other variables (interaction terms) Farm Size (+/-) – Larger farms are more difficult to manage since they are more complex and have larger area, e.g. pest scouting and nutrient management – Larger farms likely better equipped and more efficient – So this variable is difficult to predict a priori and likely to depend on other variables (interaction terms)

36. Model Structure Test alternative regression models and identify which variables are significant and which model best fits the data Include interaction terms and create new variables to place farm structure variables on a unit basis, e.g. labor per ha Include other variables to explain cotton yield: – Year – Zone – Insecticide sprays

37. Empirical Model Structure Y = α0 + α0Zone + α0Zone + α0Sprays + β1Area + β1 + α0Year Variables: – Type (BGII or conventional) – Year – Zone – Insecticide sprays – Village

38. Model Results SourceEstimatePr>FEstimatePr>FEstimatePr>F Intercept853.7<.0001854.9 Year…<.0001 Type_Coton (BT=1)139.62<.0001146.41<.0001 Year*Type_Coton…0.00180.0020.0048 Zone…<.0001 Type_Coton*Zone…0.01020.01760.0358 Late_spray_Cat…0.1180.16370.1121 Type_Coto*Late_spray…0.00140.00150.0465 Actifs_agricole0.0816430.9423-1.534640.4694-0.333580.8609 Surface_parcelle18.65116<.000116.788850.00815.93261<.0001 Nombre_animaux_trait26.68308<.000129.64985<.000132.24178<.0001 Actifs_ag*Surface_pa0.6748730.0141 Surface_p*Nombre_ani-0.594330.6084 Actifs_ag*Nombre_ani-0.323120.5855 Actifs_ha0.3109340.9114 Animals_ha-11.54530.0777 R2

39. Results

40. Two-Dimensional View of Smallholder Farms Lighter colors represent larger residuals

41. Practical Implication Research findings suggests that the prior definition used to define farm types, based only on # bullocks, is not the best one, but is still consistent with our more general findings. Provide policy makers, and the on-going legal framework, with an alternative approach to define what a “smallholder” producer is, i.e. include a “3-D” defintion.

42. Conclusions/Policy Implications Smallholder farmers benefit the same as larger, better equipped farms on a proportional basis no matter how “smallholder” is defined Larger, better equipped farms have higher yields and do achieve higher overall yield and economic benefits ALL farm types and size perform significantly better with BGII than conventional cotton Policy makers need to focus assisting farmers to become better equipped and to utilize increased profitability of BGII cotton to invest in farm equipment More efficient farms are expected to improve yields as suggested by the survey results. – Larger farm sizes will be an outcome of the increased farm capital but increasing farm size just for the sake of larger farms will not increase yields.

43. Farm Type YearManualSmallLargeMotoriseAve 2009-2011BGII1012aC1064aC1207aB(1555A)1094a CONV915aA909bA973bA-933b Diff97155234-128 % Diff10.617.124.017.2 2012-2013BGII978aB1028aB1162aA-1056a CONV882aB863bB947bA-897b Diff96165215158 % Diff 10.919.122.717.7 2014BGII782aD962aC1144aB(1310aA)962a CONV760aC872bB979bA(1000bA)870b Diff2290165(310)92 % Diff2.910.316.9(13.1)10.5 Ave 2009-2014 BGII953aD1021aC1174aB(1352aA)1049a CONV860bB887bB979bA(1000bA)908b Diff92135196(352)141 % Diff10.815.119.9(13.5)15.5 2009/2010 - 2014/2015 – Yields*old farm type (animals)*type of cotton Sofitex + Socoma + Faso Coton Notes statistical analyses Mean separation indicated by letters a,b,c is comparing cotton types within same farm type Mean separation indicated by letters A,B,C is comparing farm types within same cotton type ALL FARM TYPES BENEFIT FROM GROWING BOLLGARD II®

44. 2009/2010 – 2013/2014 BGII yield benefit for all field sizes Higher yields More consistent yield

45. 2009/2010 – 2013/2014 BGII yield benefit for all HH Labor Higher yields More consistent yield

46. Better Way to Classify Farms

47. Monsanto Company Confidential This presentation focused on cotton yield impact of BGII The close proximity of the average production costs of BGII cotton and conventional cotton indicates that the primary source of the increase in cotton profit from growing Bollgard II across years (2009/2010 – 2011/2012) was from a combination of the yield increase and the higher cotton price that placed a greater value on output compared to the previous two years. Other socio-economic benefits directly linked to yield are available but not discussed in this presentation - Economic return ($/ha) Cotton income – Cotton Production cost - Household income (related to hectares of BGII) - Return to labor ($/day) - more consistent production => this will become visible in presentation (less variable, target pest control) Consistent benefits not directly linked to yield are available but not discussed in this presentation - improved human health (and related reduced health care cost) reduced insecticide exposure (2 treatments vs 6 treatments) chemical storage, preparations spray solutions, exposure during applications waste handling - Reduced environmental impact from reduced insecticide usage - labor saving and the related time spending

48. Further Research Is there more land available in all villages? Is additional training needed for increasing animal traction