Presentation on theme: "Adoption Impacts and Access to Innovation in Small Resource Poor Countries: Results from a Second Round Survey and Institutional Assessment in HondurasAdoption."— Presentation transcript:
Adoption Impacts and Access to Innovation in Small Resource Poor Countries: Results from a Second Round Survey and Institutional Assessment in HondurasAdoption Impacts and Access to Innovation in Small Resource Poor Countries: Results from a Second Round Survey and Institutional Assessment in Honduras José Falck Zepeda, Denise McLean, Patricia Zambrano, Arie Sanders, Maria Mercedes Roca, Cecilia Chi-Ham Paper presented at the 17 th ICABR meeting, Ravello Italy, June 21 2013
Honduras: High reliance on agriculture Agricultural sector 13% of GDP 1 Agribusiness and related sector 40-45% 2 GDP 1 World Bank, 2011 2 http://www.hondurasopenforbusiness.com/SITEv2/files/pdf/Oportunidades_de_inversion_Agroindustria.pdf
Graphs: WorldBank Development Indicators (2013) Map: National System of Environmental Indicators, SINIA Honduras: Limited resources for agricultural production especially land 87% of territory corresponds to hillsides susceptible to erosion
Honduras: Low productivity of major staple crops Honduras Productivity: 1/3 of world averages and 1/7 of US yields
Corn is an essential part of Honduran diet 1 FAO Statistics Division, 2012, 2 Ministry of Agriculture and Livestock, 2012 Top commodity available for consumption 739 kcal/person/day Basic grains represent up to 60% of Honduran diet 48% of total demand is for human consumption Production Value, Top Commodities (2011) Value [1000 Int$] 1Coffee, green3033578Tomatoes56580 2Cow milk, whole2307239Oranges54126 3Chicken Meat22212210Beans, dry51791 4Bananas20484911Pineapple39416 5Cattle Meat16583012Eggs36661 6Sugar cane16476613Melons33139 7Palm oil13921814Corn32068 Corn in Honduras is grown mostly for food/feed
Corn supply in Honduras increasingly dependent on imports Nearly 40% of corn is imported and thus high concerns for corn price volatility in international markets Honduras Agriculture Ministry Jacobo Regalado: From the million ton we need we are only producing 600 thousands. We are still importing 400 thousands(…) The idea is to accelerate the pace to substitute those 400 thousands with local production. Honduras Agriculture Ministry Jacobo Regalado: From the million ton we need we are only producing 600 thousands. We are still importing 400 thousands(…) The idea is to accelerate the pace to substitute those 400 thousands with local production. Hondudiario, March 19, 2012
Honduras: The problem with production intensification Damage by lepidopteran insects can be as high as 40-70% Increasing issues with other pests and diseases Heavy damage due to aflatoxins / mycotoxins Need to explore new control alternatives amenable to smallholder´s producers Smallholder producers: Little access to technology, pest control alternatives and credit Knowledge limitations: to determine damage and to make correct chemical applications….
GMOs in Honduras 8 th Latin American country adopting GMOs since 2002 1 1 ISAAA, 2012 Only country in Central America cultivating GMOs for food -USA * -Brazil * -Argentina * -South Africa * -Canada * -Uruguay x1.5 -Philippines x3 -Spain x5 -Chile x7 -Honduras -Portugal x.8 -Czech Republic x.7 -Poland x3 -Egypt x9 -Slovakia x0.4 -Romania x2 By 2011, 72 thousand ha with hybrids and GM 15% area planted 1 GM estimated around 25-30 thousand ha BT (MON810), RR (NK603), Herculex 1, YGVTPro (MON89034) traits approved for commercialization
Honduras: promotional environment favoring biotechnology adoption Favorable policy, economic and social conditions facilitated adoption UN Statistics Division, 2011. WTO Statistics, Trade Profiles, 2012 Strategic interest in aligning agricultural policies with the major economic and trade partners Honduras trade is essentially tied to the United States Historically strong presence of agricultural multinationals interested in increased agricultural productivity
Established Biosafety Framework and Regulations Incorporated biotechnology in National Food Self Sufficiency Strategy Coordinated a joint agricultural and environmental political agenda To facilitate the process to incorporate hybrids and transgenic seeds in 25% of the area planted at the national level by 2014 Honduras Agricultural and Livestock Ministry goal Public Agricultural and Food Sector Strategy To facilitate the process to incorporate hybrids and transgenic seeds in 25% of the area planted at the national level by 2014 Honduras Agricultural and Livestock Ministry goal Public Agricultural and Food Sector Strategy 1996/98: Biosecurity Regulation with Emphasis in Transgenic Plants 1998: National Committee of Biotechnology and Biosecurity (NCBB) 2006: CAFTA-DR Phytozoosanitary Law modification 2008: Cartagena Protocol Ratification 2001/12: Law for the Protection of New Varieties of Plants USAID GAIN Report 2012. Honduran government specific policy support for easing a transition towards biotechnologies Honduras: A case study to understand biotechnology adoption in small resource poor developing countries
Honduras in the Latin American innovation sphere Small markets Medium markets Large markets Non-selective importers of technology El Salvador, Guatemala, Honduras, Nicaragua, Panamá Bolivia, Ecuador Selective importers of technology Costa Rica, Uruguay Paraguay, PeruVenezuela Tool users -Colombia, ChileArgentina, Mexico Innovators Brazil Notes: 1) Source: Trigo, Falck-Zepeda and Falconi (2010), 2) Non-adopters are listed in italic text.
Which policies are important? Public sector investments in biotechnology applications Intellectual property management Biosafety regulations Food/feed safety and consumer protection Support for public sector participation and tech transfer including seed systems Non-adopters Bolivia00--0 Ecuador00--0 Guatemala0-00- Perú0--00 Venezuela+--00 Adopters Argentina+00++ Brazil+-00+ Costa Rica+-00+ Honduras0-00- Mexico+000+ Uruguay+000+ Notes: 1) Source: selected countries from Trigo, Falck Zepeda and Falconi (2010), 2) + signifies promotional policies, 0 denotes neutral policies, - reflects preventive policies, 3) Brazil was categorized as having a preventive biosafety policy in the Trigo et al. paper, but is reclassified here as neutral based on recent developments in the country.
The 2013 (second) survey to observe experiences of conventional & GM corn farmers Economic, social and agronomic impacts We chose a representative sample of corn farmers from the main corn producing state in Honduras
Olancho: The main corn producing state in Honduras - 180,000 metric tons - 35,000 planted hectares >30 % national corn production - 12,000 hectares with GM >40% GM corn production - 10,000 farmers - A range of different corn production systems We captured diversity within the commercial corn production chain
Number of applications ConventionalGM Both types, conventional plot Both types, GM plot < 7 ha> 7 ha< 7 ha> 7 ha< 7 ha> 7 ha< 7 ha> 7 ha Insecticides 188.8.131.52.31.92.01.01.1 S Herbicides 184.108.40.206.220.127.116.11.6 S Fungicides 1.01.51.21.51.01.31.0 NS Fertilizers 18.104.22.168.22.214.171.124.6 NS S: Significant, NS: Not significant Our findings: In average GM corn farmer seem to be using less pesticides GM corn producers from sample made one insecticide and herbicide application less
Environmental Impact Quotient ConventionalGM Both types, conventional plot Both types, GM plot < 7 ha> 7 ha< 7 ha> 7 ha< 7 ha> 7 ha< 7 ha> 7 ha Insecticides 126.96.36.1991.04.68.23.16.1 NS Herbicides 24.329.627.128.642.612.524.616.0 NS Fungicides 3.03.714.510.47.1 9.4 NS Fertilizers 23.727.436.641.636.216.925.522.6 NS S: Significant, NS: Not significant GM and conventional corn farmers seem to have a similar environmental impact measured by the EIQ EIQ: J. Kovach et al, IPM Program, Cornell University, New York State Agricultural Experiment Station Geneva, New York 14456
1 At small scale GM corn farmers seem to be obtaining higher yields & profits
Of Cooks D, the issue of outliers and sampling biases Observation IDYieldCooks D 426.5000.053 845.2000.385 997.4750.033 116 4.5430.039 120 9.1000.020 121 2.5070.022 129 2.8390.021 131 6.5000.688 132 3.2500.054 143 1.8170.028 152 5.2001.230 155 7.8000.036 169 1.0830.020 170 6.0452.381 173 0.9750.030 174 8.0600.032 182 0.1950.060 200 5.2000.033 212 7.8000.032 217 1.3000.020 222 9.1000.022 230 6.5000.026 The classical instrumental variables (IV) estimator is extremely sensitive to the presence of outliers in the sample. This is a concern as outliers can strongly dis- tort the estimated effect of a given regressor on the dependent variable. Although outlier diagnostics exist, they frequently fail to detect atypical observations since they are themselves based on non-robust (to outliers) estimators. Furthermore, they do not take into account the combined influence of outliers in the first and second stages of the IV estimator Desbordes and Verardi, Stata Journal 2012
Production function approach Robust Regression (MM-Regression 85% efficiency, ROBREG)Robust Regression ( MSREGRESS)Instrumental Variables ( IVREG2) VariableCoef.Robust SECoef.Robust SECoef.SE GM corn user (1=Yes)1.2540.319***1.1570.387***1.4530.329*** Located in Juticalpa/Catacamas (1=Yes)0.3460.414n.s.1.3030.199***0.3360.304n.s. Proportion of income from non-ag sources (%)-0.0110.005**-0.0060.007n.s.-0.0090.004** Number of members in the household-0.0660.068n.s.-0.1020.061*-0.0960.051* Time cultivating GM maize-0.0140.007**-0.0260.005***-0.0100.006n.s. Total income0.2510.105**0.1890.075**0.2160.078*** Total area in production (ha)0.0020.001*-0.0020.002n.s.0.0020.001n.s. Total area cultivated with maize (ha)-0.0040.006n.s.0.0040.002*-0.0040.004n.s. EIQ index-0.0390.019**0.0130.016n.s.-0.0200.014n.s. Seed quantity planted (kg/ha)-0.0020.016n.s.0.1170.020***-0.0050.015n.s. AI insecticide (Kg/ha)1.0300.593*2.1561.139*0.7180.561n.s. AI herbicide (Kg/ha)0.0700.064n.s.0.0840.114n.s.0.1580.070** AI fertilizer used (Kg/ha)0.0090.004**0.0170.002***0.0050.002** AI other pesticides(Kg/ha)3.2681.758*1.7360.555***1.5160.883* Cost labor per day ($/ha)-0.0080.006n.s.-0.0060.006n.s.-0.0040.006n.s. Seed planted squared0.000 n.s.-0.0020.000***0.000 n.s. AI insecticide squared-0.2610.133**-2.0900.736***-0.1670.143n.s. AI herbicide squared-0.0030.002n.s.0.0160.009*-0.0060.003** AI fertilizer squared0.000 **0.000 ***0.000 n.s. AI other pesticides squared-3.9782.040*-1.2070.290***-0.9260.654n.s. Irrigation (1=Yes)-0.4630.387n.s.-0.2170.180n.s.0.1960.305n.s. Finance (1=Yes)0.1500.227n.s.-0.0690.131n.s.-0.1870.198n.s. Technical assistance (1=Yes)-0.1700.480n.s.-0.4040.238*-0.1740.262n.s. Constant4.8221.365***3.5920.846***2.6650.603***
Second stage (2SLS net income)First stage, dependent variables is GM corn user) VariableCoef.Std. Err.Coef.Std. Err. GM corn user (1=Yes)279.1131.7** Located in Juticalpa/Catacamas (1=Yes)166.3123.9n.s.0.2090.067** Proportion of income from non-ag (%)1.7n.s.0.001 n.s. Number of members in the household-32.518.7*-0.0020.012n.s. Time cultivating GM maize-7.12.7***0.0030.001* Total income96.734.4***0.0020.018n.s. Total production area (ha)1.10.3***0.000 n.s. Total maize area (ha)0.01.2n.s.0.0020.001** EIQ index-6.37.6n.s.-0.0030.003n.s. Seed planted (kg/ha)-4.54.7n.s.0.0020.004n.s. AI insecticide (Kg/ha)98.7209.2n.s.-0.1830.130n.s. AI herbicide used (Kg/ha)46.526.4*0.0010.017n.s. AI fertilizer used (Kg/ha)1.1n.s.0.0000.001n.s. AI other pesticides (Kg/ha)201.1402.1n.s.0.0020.209n.s. Cost labor per day ($/ha)-8.52.8***0.0000.001n.s. Seed planted squared0.0 n.s.0.000 n.s. AI insecticide squared-60.149.4n.s.0.0350.033n.s. AI herbicide squared-1.70.9*0.0000.001n.s. AI fertilizer squared0.0 n.s.0.000 n.s. AI other pesticides/fungicides used squared-205.6240.3n.s.0.0710.155n.s. Irrigation (1=Yes)-102.9181.1n.s.-0.0440.072n.s. Finance (1=Yes)-74.397.5n.s.-0.0510.047n.s. Technical assistance (1=Yes)56.3122.4n.s.0.0460.062n.s. Price GM seed0.0330.005** Year cultivating GM seed-0.2750.032** Constant659.2214.6***0.2520.161n.s. Net income
THEN…WHY HAVE WE NOT OBSERVED FULL ADOPTION BY HONDURAN PRODUCERS?
Characteristic Monthly income >500 US$ Access to technical assistance Access to credit Farmers applying fungicides Insecticide costs Fertilizer costs Cost of the use of machinery GM 82 to 98% of farmers 16 to 30% of farmers 24 to 56% of farmers 58 to 50% of farmers 28 to 62 US$/ha 328 to 373 US$/ha 192 to 275 US$/ha Conventional 40 to 64% of farmers 11 to 0% of farmers 19 to 28% of farmers 4 to 8% of farmers 11 to 16 US$/ha 213 to 237 US$/ha 106 to 104 US$/ha Access to inputs may restrict adoption Farmers without information, credit or other inputs are less likely to adopt GM crops Depending on plot size
Access to markets may limit profitability Farmers with smaller plots or in remote areas are less likely to adopt biotechnology Characteristic Closer to urban areas Sell directly to industry Transportation costs Selling price Agronomic cycle GM 92 to 93% of farmers 45 to 80% of farmers 134 to 152 US$/ha 352 to 395 US$/ton 3-4 months Conventional 12 to 16% of farmers 2 to 4% of farmers 17 to 40 US$/ha 274 to 294 US$/ton 4-5 months Depending on plot size
Gender/seed type Preferred for productionPreferred for consumption ConventionalGMConventionalGM Male/Conventional01300 Male/GM01851 Female/Conventional200180 Female/GM01280 All2043311 Farmers may prefer other traits Local corn varieties make better tortillas Preliminary data from exploratory panel, 2013. Unpublished. Preferred traits for production by production size & location Large/valleyLarge/hillsSmall/valleySmall/hills Black spot resistance High yield Heavy grain BT RR Price Drought resistance % germination Full cob Farmers have greater preference for protection against risk
Conclusions GM maize continues to perform as expected compared to a conventional Positive yield advantage Higher net income Reduction in pesticide applications Unclear environmental impact (need more work) For expansion of area with GM maize in Honduras, issue is not a technical issue but seems to be an institutional Additional work needed to examine Production and financial risk Distribution of impact by size Impacts of institutional issues
Arie Sanders Maria Mercedes Roca Miljian Villalta Alan B. Bennett Cecilia Chi-Ham Denisse McLean Jose Falck-Zepeda Patricia Zambrano Sandra Mendoza. Participatory research consultant Research funded by: