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4. Elicitation process and information sources

Home Knowledge toolkit 4. Elicitation process and information sources
This section provides a brief account of the parameter elicitation process and the information sources used. The following table gives an overview of the parameters used in the priority assessment, their respective sources and some more detailed information about the respective elicitation process and criteria. The ‘Taskforce’ refers to the group of economists and scientists from all participating RTB Centers (Bioversity International, International Center of Tropical Agriculture CIAT, International Potato Center CIP, and International Institute for Tropical Agriculture IITA), with the help of the regional research for development banana networks (BAPNET, BARNESA, Innovate Plantain, and MUSALAC), who worked on the assessment for the five crops included. The group agreed on model and methodology intrinsic parameters to ensure the assessment is carried out in a comparable way across crops.

Expert working groups formed at the Kampala workshop started estimating the model parameters which were then completed/refined by the resource persons for each research option (see table below). The economist conducting the assessment worked closely with those resource persons through meetings, email and calls to fill the developed templates containing all parameter estimates required for the assessment.

 

Parameters Information source Remarks
1 Target countries Resource person(s)* working on the parametrization of the respective research option Criteria for inclusion of a country:

  1. The constraint was currently present or would be present over the next 25 years (the assessment period)
  2. A large area in absolute terms is affected by the constraint, i.e. larger banana production area and/or large‐scale spread of the constraint
  3. RTB will likely be working in (collaboration with) the respective country to make adoptable innovations addressing the constraint available to farmers.

Thus the list of countries included in the assessment varies for the different research options, though there naturally is some overlap

2 Banana production FruiTrop FruiTrop (2010) uses FAO crop production statistics (which show banana and plantain as separate commodities, but somewhat arbitrarily allocate cultivar groups) but includes other additional references, surveys, and professional sources.

Production information is disaggregated by cultivar group within each country.

Since cultivar groups used by FruiTrop differ slightly from those decided on for the RTB banana priority assessment, expert assessment was used to allocate production from cultivar categories used by FruiTrop to cultivar groups of the priority setting exercise.

3 Banana yield FAOSTAT Banana yield expressed as average crop yield of last three years available.

FAO data do not separate production from large-scale, commercial plantations from (semi-) subsistence production under smallholder conditions. Yield figures especially for countries with sizable banana export industry seemed too high for the RTB target group of poor (small‐scale) producers. Expert judgement was used to cap some of the yield figures to reflect smallholder conditions.

4 Banana production area FAOSTAT, FruiTrop Computed by authors using the FAOSTAT yield information and FruiTrop production figures
5 Crop price FAOSTAT Average farm gate banana price from 2010-2012. If available the weighted average price for banana/plantain was used.

Default price if no data: $300/MT

6 Target domain, current and future spread of the constraint Expert estimates Estimates first derived from the group work during the Kampala workshop and then adjusted by respective resource person to reflect country and/or cultivar group specific conditions.
7 Changes in yields, production costs, and postharvest losses after adopting technology Expert estimates Estimates first derived from the group work during the Kampala workshop and then adjusted by respective resource person to reflect country and/or cultivar group specific conditions.
8 Adoption ceiling, adoption start and pace Expert estimates Estimates first derived from the group work during the Kampala workshop and then adjusted by respective resource person to reflect country and/or cultivar group specific conditions.
9 Research and Development costs Expert estimates Estimates first derived from the group work during the Kampala workshop and then adjusted by respective resource person to reflect country and/or cultivar group specific conditions.
10 Dissemination costs Taskforce agreement Two levels: $80 for each new hectare of adoption for knowledge intensive technologies, $50 per new hectare of adoption of all other technologies
11 Probability of research success Expert estimates Probability of research being successful and delivering an adoptable technology at the country level; max value of 0.8 for quick wins and lower values if uncertainty of research success is higher; technology and if necessary country specific resource person estimates
12 Demand and supply elasticities Taskforce agreement Supply elasticity: 1.0; Demand elasticity: 0.5
13 Discount rate Taskforce agreement 10% discount rate
14 Depreciation rate Taskforce agreement Use 1 across all technologies/crops
15 Population, poverty rate, %-GDP from agriculture World Bank World Development Indicators
16 Poverty elasticities Taskforce agreement based on: Thirtle, C., L. Beyers, Y. Ismael, and J. Piesse. 2003. Can GM-Technologies Help the Poor? The Impact of Bt-Cotton in Makhathini Flats, KwaZulu-Natal. World Development 31(4): 717–732. Elasticities adjust based on geographic location for each country: 0.72 for Africa, 0.48 for Asia, and 0.15 for LAC; Poverty reduction reported is reached at highest adoption level;
17 Household (HH) size and crop area per HH CGIAR RTB estimate of beneficiaries (CGIAR, 2011)
18 Assessment period Taskforce agreement 25 years (starting in 2014 and running to 2039)

*Resource persons for the different research options are as follows:
Recovery from BBTV: Charles Staver, Guy Blomme, Lava Kumar, Celestin Niyongere
BXW management: GM-resistant varieties: Guy Blomme, Eldad Karamura, Charles Staver
BXW management: cultural practices: Leena Tripathi, Guy Blomme
Cropping system intensification: Charles Staver, Piet van Asten, Thierry Lescot
Conventional breeding for improved disease resistance: Rony Swennen (East African Highland Bananas, plantain); Frédéric Bakry (plantain, sweet acid), Edson Perito Amorim (sweet acid)
Sustainable Fusarium wilt management: Charles Staver, Miguel Dita, Luis Perez Vicente, Marcia Barquero

Knowledge toolkit

  • 1. Identification of major constraints and opportunities
    • 1.1. Summary of expert survey process
    • 1.2. Kampala workshop outcome
  • 2. Formulation of research options
  • 3. Methodology for assessment
    • 3.1. Cost-Benefit Analysis
    • 3.2. Poverty effects model
    • 3.3. Estimation of the number of potential beneficiares
  • 4. Elicitation process and information sources
  • 5. Parameter estimates and underlying assumptions
  • 6. Results
  • 7. Limitations and lessons learned
  • 8. Survey
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