targeting sustainable interventions (eng)
DESCRIPTION
TRANSCRIPT
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Targeting sustainable interventions
An Notenbaert, Tim Robinson, Mark Van Wijk
Impact Pathways and Planning Meeting - Dual Purpose Cattle Value Chain Managua, 5-9 August
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Targeting Outputs
Sustainable interventions• Identified & targeted• In promising VCs (and sites)
+ tools and approaches
Environmental impact
Global context
Prioritisation of interventions .
Economically, socially & environmentally
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Providing a global context
- For action in the VCs- For identifying promising VCs
What we’re aiming for- with CCAFS/CRP2:
- projections of demand, supply, environmental indicators- Global dialogue around ASF nutrition security- Prioritisation framework
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Prioritization of interventions
A few approaches we’d like to test:- Extrapolate (contact: Tim Robinson)- Optimisation modeling (contact: Mark Van Wijk)- System Dynamic Modeling (lead by VCD theme)
Slow track: systems analysis of detailed household data; systems optimizationFast track: PRA approaches; ex-ante analysis
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Ex-ante tool for ranking (policy) alternatives• Designed for policy interventions (PPLPI) but equally applicable to
technical and systems interventions• Simple PC-based programme• Promotes a participatory approach• Easy to use, well documented
• User Guide• Reference Manual
• Not data-intensive• Simple graphic output• Can evaluate combinations of interventions• Can be used at a range of levels
1. EXTRAPOLATE
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EXTRAPOLATE1. EXTRAPOLATE
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EXTRAPOLATE: Current situation1. EXTRAPOLATE
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EXTRAPOLATE: Policy changes1. EXTRAPOLATE
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EXTRAPOLATE1. EXTRAPOLATE
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Dairy development policy: Uganda
• Promote genetic improvement• Strengthen delivery of veterinary services• Provide appropriate extension services• Improved market infrastructure and information• Ensure quality control along the chain• Increase local consumption to build a strong domestic market• Promote efficiency in the input supply system• Increased access to credit facilities
Proposed components of policy:
1. EXTRAPOLATE
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EXTRAPOLATE – analysis tools
Small-medium producers
Pastoralists and agro-pastoralistsSmall processors & traders
Poor consumers
Wealthy producers/processors/consumers
1. EXTRAPOLATE
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Promote genetic improvement
Small-medium producers
Pastoralists and agro-pastoralists
1. EXTRAPOLATE
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Enforce quality control
Small-medium producers
Pastoralists and agro-pastoralists
1. EXTRAPOLATE
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Optimal combination of policies1. EXTRAPOLATE
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Key elements of a pro-poor policy
• Promote genetic improvement• Strengthen delivery of veterinary services• Provide appropriate extension services• Improved market infrastructure and information• Ensure quality control along the chain• Increase local consumption to build a strong domestic market• Promote efficiency in the input supply system• Increased access to credit facilities
1. EXTRAPOLATE
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Key elements of a pro-poor policy
• This does NOT mean that genetic improvement and standards/regulation should be discouraged or dropped from the policy document• Rather that when these broad policy outcomes are disaggregated
into their component parts (laws, strategies, institutions etc.) care needs to be taken to ensure that the poorer producers are not disadvantaged, and that their needs are also addressed
1. EXTRAPOLATE
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2. OPTIMISATION
• Optimization of effect sizes through LP is a standard approach to do that
• Trade offs between different indicators can be quantified• Drawbacks:– All effect sizes need to be quantified accurately– LP results in single solutions
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• Therefore: take into account UNCERTAINTY of effects of interventions on system performance indicators
• By sampling these uncertainty intervals you get – packages of interventions, rather than single optimal solutions– Insight in the robustness of the intervention you are proposing– Insight in key factors that need more accurate quantification
2. OPTIMISATION
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Construct effect size table: based on literature values and expert knowledge
Interventions Livestock Production(short term)
Labour hours costs
GHG emissions
Short term Investment costs
…
1 + 10% (stdev 8)
+20% (stdev 15)
+10% (stdev 5)
+30% (stdev 10)
2 + 20% (stdev 5)
+40% (stdev 15)
+20% (stdev 7)
+50% (stdev 20)
…
3 … … … … …
4 … … … … …
… … … … … …
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Indicator 2
Indicator 1
Indicator 3
Indicator 2
Indicator 1
Indicator 3
Model Intervention 1
Intervention 1
Intervention 2
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Indicator 2
Indicator 1
Indicator 3
Indicator 2
Indicator 1
Indicator 3
Model Intervention 2
Intervention 1
Intervention 2
And this you do very often (e.g. 1000s of times) to know the probability of choosing certain interventions 1. under which conditions;2. with which objectives.
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Model
Climate
Prices
Farm characteristics
Model parameters
Uncertainty / Variation in
Probabilities of decisions
Probabilities of indicator outcomes
Trade offs betweenindicators
Thereby it is a simple and rough way of prioritizing
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Prioritization of interventions
All these approaches :- Based on constraints analysis and best-bet identification in
VCs- Need for good data and knowledge from the VCs
Short term: identify resource person
Longer term: joint proposal development!
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Environmental impact assessment
Working on a framework for ex-ante environmental impact assessment of livestock and fish value chains:
- Pilot study in Dairy VC in East-Africa (BMGF-funded)
- Key dimensions: water, GHG, nutrients
Need for bigger proposal development!…Flagship in phase 2
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CGIAR is a global partnership that unites organizations engaged in research for a food secure future. The CGIAR Research Program on Livestock and Fish aims to increase the productivity of small-scale livestock and fish systems in sustainable ways, making meat, milk and fish more available and affordable across the developing world.
CGIAR Research Program on Livestock and Fish
livestockfish.cgiar.org