Targeting sustainable interventions

An Notenbaert, Tim Robinson, Mark Van Wijk

Impact Pathways and Planning Meeting - Dual Purpose Cattle Value Chain Managua, 5-9 August

Targeting Outputs

Sustainable interventions• Identified & targeted• In promising VCs (and sites)

+ tools and approaches

Environmental impact

Global context

Prioritisation of interventions .

Economically, socially & environmentally

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

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

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

EXTRAPOLATE1. EXTRAPOLATE

EXTRAPOLATE: Current situation1. EXTRAPOLATE

EXTRAPOLATE: Policy changes1. EXTRAPOLATE

EXTRAPOLATE1. EXTRAPOLATE

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

EXTRAPOLATE – analysis tools

Small-medium producers

Pastoralists and agro-pastoralistsSmall processors & traders

Poor consumers

Wealthy producers/processors/consumers

1. EXTRAPOLATE

Promote genetic improvement

Small-medium producers

Pastoralists and agro-pastoralists

1. EXTRAPOLATE

Enforce quality control

Small-medium producers

Pastoralists and agro-pastoralists

1. EXTRAPOLATE

Optimal combination of policies1. EXTRAPOLATE

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

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

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

• 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

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 … … … … …

… … … … … …

Indicator 2

Indicator 1

Indicator 3

Indicator 2

Indicator 1

Indicator 3

Model Intervention 1

Intervention 1

Intervention 2

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.

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

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!

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

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