SSA - SSA MTP 2010-2012 - 2010-12

					Sub-Saharan Africa Challenge Program

Medium-Term Plan 2010-12

Submitted to the Science Council of the Consultative Group on International Agricultural Research (CGIAR)

June 15, 2009

Sub-Saharan Africa Challenge Program Medium-Term Plan 2010-12

Table of Contents

MTP Overview .............................................................................................. 3 Introduction .............................................................................................. 3 Evolution of the SSA CP's Research Design ................................................... 3 Summary of the Changes from the Previous MTP ........................................... 4 The SSA CP's Revised Research Design ........................................................ 5 Expected Outputs, Outcomes and Impact of the SSA CP ................................. 5 Integrated Agricultural Research for Development (IAR4D) ............................. 6 IAR4D Impact Pathway .............................................................................. 7 Research Hypotheses ................................................................................. 8 Highlights of Project Portfolio ...................................................................... 9 New and Terminated Research .................................................................. 10 Slower than Expected Progress in Previous MTP .......................................... 11 Changes in Collaborative Arrangements ..................................................... 11 Alignment with System Priorities ............................................................... 12 Non-System Priority Activities ................................................................... 13 Project Portfolio ....................................................................................... 13 Long term adequacies of reserves.............................................................. 14 Short term liquidity .................................................................................. 14 Project Portfolio .......................................................................................... 15 SSA-01: Meta-Analysis of the IAR4D Concept ............................................ 15 SSA-02: KKM Pilot Learning Site............................................................... 23 SSA-03: ZMM Pilot Learning Site .............................................................. 33 SSA-04: Lake Kivu Pilot Learning Site ....................................................... 43 Annexes .................................................................................................... 52 Implementation of EPMR/CPER Recommendations ....................................... 52 Annex 1: IAR4D Proof of Concept Research Methodology .............................. 62 Annex 2: Innovation and Learning Process ................................................. 71 Financing Plan ............................................................................................ 72

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MTP Overview
Introduction
Sub-Saharan Africa is on course to become the only developing region that may fail, by a significant margin, to attain the Millennium Development Goal targets of halving the proportion of the poor people and those suffering from hunger by 2015. This margin could be trimmed through agriculture, since livelihoods of most Africans are agriculture-based. Efforts towards realizing the aforementioned targets will necessarily entail marked and sustained improvement in the productivity of agriculture and associated enterprises. The World Bank‘s 2008 World Development Report proposes a productivity revolution in smallholder farming as the measure required for agriculture-based countries to realize the potential of agriculture in increasing economic growth, poverty reduction, food security and environmental sustainability. The Asian green revolution epitomizes the role of agricultural research in boosting agricultural productivity. It also highlights that, on their own, research outputs are not sufficient to deliver a green revolution; they need to be complemented by appropriate agricultural policies, markets, rural infrastructure, and institutions. The Sub-Saharan Africa Challenge Program (SSA CP) was initiated in 2004 following extensive consultations with numerous agricultural stakeholders (researchers, extension and development agents, policy makers, farmers, and the private sector) to diagnose the main reasons behind the underperformance of agricultural research in Africa. These consultations established that, besides inadequate funding, the main impediment to the contribution of African agricultural research to development impact lies in the way the research is organized and conducted. Research, technology transfer, and technology use have been treated as independent activities whereby research-derived knowledge consisting of large prescriptive technology packages flows linearly from researchers to farmers through extension agents. The consultations proposed an alternative approach that aims to appropriately embed agricultural research within a larger system of innovation whereby knowledge from numerous sources (comprising all the various actors and stakeholders) is integrated and effectively put into use. This approach to agricultural research is termed Integrated Agricultural Research for Development (IAR4D) and has been adopted by the SSA CP. Therefore, the challenge of the SSA CP is to test the hypothesis that IAR4D performs better than the conventional agricultural research and development (ARD) approach currently used in SSA. This task involves: i. Defining IAR4D and deriving principles on how it should be implemented; and.

ii. Conducting an experiment to empirically establish whether IAR4D is feasible, more costbenefit effective than conventional ARD approaches, and replicable on a large scale.

Evolution of the SSA CP's Research Design
Since its inception in January 2005, the SSA CP has undergone several design changes. It was initially conceived as a large-scale action research and capacity building initiative aimed at testing (identifying the most appropriate practices) and scaling out IAR4D. The testing was to be carried out in three carefully delineated Pilot Learning Sites (PLSs) – one in each of SSA‘s three subregions (i.e., East and Central Africa, West Africa, and Southern Africa). It was designed to start with an 18-month inception phase during which it would establish governance and management structures; draw up a strategy, develop a research plan, and, through a competitive process,
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identify the teams that would implement the plan. At the end of the SSA CP‘s inception phase, in June 2006, the CGIAR science council (SC) evaluated its achievements and in particular its research plan. This evaluation concluded that the SSA CP had registered sufficient progress. On this basis the SC recommended the SSA CP‘s continuation for a three-year research phase during which it would focus on proof of the IAR4D concept in a ―scientific, statistically-based manner‖. The SC outlined three research questions the program would seek to answer in establishing proof of the IAR4D concept, namely: i. Does the IAR4D concept work and can it generate deliverable international and regional public goods for end users? ii. Does the IAR4D framework deliver more benefits to end users than conventional approaches (assuming the conventional research, development and extension approaches have access to the same resources)? iii. How sustainable and usable is the IAR4D approach outside the test environment?

The SC further recommended that in establishing the proof of concept, the CP‘s research should focus on the interfaces of processes driving (a) productivity gains, (b) efficient use of resources, and the care of the environment, (c) agricultural policies, and (d) markets; as the problem and opportunity spaces within which IAR4D will be implemented and evaluated. In response, the SSA CP developed a new research plan articulating the methodology it proposed to follow in answering the above research questions and submitted it for evaluation by the SC in May 2007. The SC‘s commentary on this plan highlighted its lack of specificity and targets by which progress towards establishing the proof of concept could be monitored as a major shortcoming. It also characterized the program‘s proposed impact pathway as too generic. The SC concluded by observing that the SSA CP‘s research design did not sufficiently address the key requirement of identifying the effects of the IAR4D approach in a scientifically robust and statistically-based manner. The SSA CP‘s response to SC‘s commentary is the foundation of the June 2008 and current MTP. The research design (Annex 1) firmly aligns the CP‘s research with the SC‘s recommendations, which emphasized the need for strengthening the rigor that the program proposed to use in generating evidence for proof of the IAR4D concept. The revised research design is summarized in the following section (A2). It forms the framework around which the program‘s ongoing and future research over this MTP‘s period are based.

Summary of the Changes from the Previous MTP
The MTP has remained largely the same, but for minor review of the PLS project narratives and logframes to reflect an adjustment in the time line for deliverables. The introduced Meta-analysis project draws on data and outputs generated by the three PLS projects to test SSA CP‘s hypotheses, make a proof of the IAR4D concept, and derive general principles for the effective implementation of IAR4D. By doing this, the other three PLS projects are now focused on the development and introduction of technological and institutional innovations. Their success in terms of delivering innovations will be crucially important in proving whether IAR4D works. At the same time, however, the three PLS projects will be closely involved in monitoring and evaluating their implementation of IAR4D (in particular, the creation and sustenance of innovation platforms and their influence on the conduct of research and creation of innovations); and on the impact attributed to IAR4D in the specific contexts of these projects. This helps to clarify the operational pathway of the Challenge Program considerably.
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The main advantage of organizing cross-site research as a separate project is that the outputs and output targets arising from this work are now articulated in a separate logical framework with a description of how this research contributes to livelihood impact and the CGIAR system priorities provided.

The SSA CP's Revised Research Design
The description of the SSA CP‘s research design presented herein starts by outlining the program‘s outputs and outcomes. We then characterize IAR4D, in particular by describing its structure, process principles, and impact pathway. Finally, we discuss the hypotheses the research sets out to test in establishing a proof of the IAR4D concept. Details of the methodology that the program proposes to employ in testing the aforementioned hypotheses are set out in Annex 1.

Expected Outputs, Outcomes and Impact of the SSA CP
The principal outputs from the SSA CP include: i. Empirical evidence of whether IAR4D works, the extra benefits it delivers compared to those delivered by traditional approaches given the same resources and whether it is replicable beyond the SSA CP‘s test sites; ii. Guidelines and principles for implementing IAR4D.

iii. Methods and tools for designing, implementing and analyzing social experiments in Sub Saharan Africa iv. Technological, institutional and policy innovations focusing in particular on the interface of processes driving productivity gains, efficient use of resources, the care of the environment, and policies and markets; v. 36 functional innovation platforms (IPs) across the three Pilot Learning Sites and a comprehensive database of process and impact indicator variables about the 36 innovation platforms and their associated research communities and households (540 villages and 5,400 households across the three PLS). The above outputs, except: iv.) (technical, institutional, and policy innovations) and v.) (the innovation platforms and comprehensive database), represent the sets of international public goods that will be generated by the SSA CP. The evidence about the cost-benefit effectiveness of IAR4D relative to conventional approaches, if favorable, together with the guidelines for implementing the approach are expected to support the rapid uptake of this approach across subSaharan Africa (= outcome) and as a result will accelerate agricultural growth, increase food security, reduce poverty, and mitigate environmental degradation (= impact). The local, national and regional innovations (technical, institutional and policy) that will ensue from action research sanctioned by the 36 innovation platforms constitute the main local and regional public goods that will be generated by the SSA CP. In due course, some of these innovations may eventually take the form of ―an international public good‖ depending on the degree of adoption outside the zone where they will be created. The direct impact of the SSA CP, however, should be measurable in the fields and wallets of the farmers and other ARD actors in areas targeted by the innovation platforms. This will constitute the best proof of whether IAR4D approach indeed works.

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Integrated Agricultural Research for Development (IAR4D)
The point of departure of IAR4D from conventional ARD is that whereas the latter treats researchdevelopment-production-consumption as a linear process (Figure 1) in which research is by far the predominant source of knowledge, IAR4D embeds research within an innovation system comprising relevant actors who interact within a network to develop, test and promote technological and institutional innovations along agricultural value chains (Figure 2). Unlike the linear configuration, the network (systemic) approach facilitates timely feedback to researchers and aims at promoting knowledge sharing and interactions leading to innovations (rather than research products per se). Here, innovation refers to the activities and processes associated with putting into use of new technical and institutional or organizational knowledge. It therefore adds value to products of research thus catalyzing the achievement of development impact.

IAR4D is characterized by a structure and several process principles, which will be discussed below. Structure of IAR4D The core of the IAR4D structure is an Innovation Platform (IP) — an informal coalition, collaboration, partnership and alliance of ARD actors, that is, public and private scientists, extension workers, representatives of farmers, farmers‘ associations, private firms and nongovernmental organizations, and government policy makers who communicate, cooperate and interact to set priorities, develop concepts and plans to promote agricultural productivity and profitability. The core competencies brought to bear by the IP are greater than the sum of the IP‘s constituents acting independently. Process principles of IAR4D The key process principles that characterize IAR4D include: i. Existence of an IP, which serves as the platform for diagnosing problems of common interest, exploring opportunities and investigating solutions. The actors in the IP: · · are organized in partnerships or teams to bring about mutually desirable change; should be competent and have incentives to jointly innovate; and
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· are constituted to include sources of the key competences and knowledge required to address the problems, opportunities and entry points that prompt its establishment ii. Non-linear (network) collective and collaborative interaction among IP actors (rather than linear researcher-extension-farmer transfer of technology model. This enhances: · direct and continuous interaction, communication and knowledge sharing among the IP actors; · quick and continuous feedback from end users (farmers) at all stages of research for development; and · timely integration of new knowledge into the innovation process using experiential learning, monitoring and evaluation and the continual feedback. iii. Research that addresses key constraints and opportunities agreed to by IP actors in the context of entire value chains (from input supply through production to consumption) and sustainable livelihood systems. iv. A research process that is multidisciplinary and participatory.

v. Institutional and human capacity building for IAR4D actors to effectively participate, whereby: · · the capacity building needs are identified by IP actors; and training (formal and non-formal) is provided by the appropriate partners.

IAR4D Impact Pathway
Figure 4 summarizes the basic IAR4D‘s impact pathway. As stated above in A.2.3, the first stage is the establishment of the IP where the priorities that would determine the objectives of the research are agreed upon, a concept and plan of action developed and the roles of each actor or groups of actors on the platform clearly defined. The research process would then involve the use of inputs (such as information, research staff, research collaborators and financial resources). The processes leading to impact may be broken into three phases (see Annex 2 for graphic illustration of this process): · Identification of a common challenge (through the IP) and using inputs through an action research process to generate outputs in accordance with the project‘s priorities and objectives. · Development of processes to deliver the outputs to beneficiaries (putting research into use — sometimes referred to as the innovation process). This involves putting into use the outputs generated by the research process. This process is facilitated by the IP and leads to incremental changes in relationships and behavior of stakeholders in particular the users of the research outputs. These incremental changes in relationships and behavior are the outcomes which could include: (a) increased awareness and knowledge; (b) behavioral outcomes (such as adoption of relevant innovations, more effective supply of inputs to satisfy demand, increased and better expressed demand for inputs, and increased volume of input sales); (c) market outcomes (increased and more effective supply of outputs, increased demand by consumers); and (d) efficiency outcomes (increased yields, technical plus allocative efficiency and profit).

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· Out-scaling, by using agricultural development processes leading to improved food security, income, livelihood assets, the natural resource base and resilience to shocks; i.e., impact. The mandate of IP actors ordinarily stretches beyond the IAR4D site. Accordingly, these actors serve as agents for out scaling the research approach and its outputs beyond the initial site. Several factors such as favorable weather, macroeconomic conditions, transportation and communication systems, institutional structures, policy regimes, socioeconomic and political stability condition the agricultural development process. Factors exogenous at the household level but endogenous at the community level include infrastructure (public and privately supplied), institutions (governance and market structures), policies (macroeconomic, sectoral, pricing or social, among other), technologies, and information. Factors exogenous at the community level include agro- climatic conditions and external market conditions (world prices and access to foreign markets). The IP enables the team to internalize as much of the conditioning factors as possible so that impact can be achieved.

Figure 4: The basic IAR4D impact pathway

Research Hypotheses
The SSA CP will test three hypotheses that flow from its three research questions (see section A1.2), namely:
Research Question 1. Does the IAR4D concept work and can it generate international public goods (IPGs) and regional public goods (RPGs) to end users? Hypothesis H1: If an innovation platform is created and is functional with the five components characterizing IAR4D, then it will lead to increased interactions and better outcomes among partners in the IP compared to where there is no IP and among farm households in communities where IAR4D is in operation compared to communities where IAR4D is not in operation. H2: IAR4D delivers more benefits to end users compared to conventional approaches (if the conventional ARD approaches have access to the same resources).

2. Does the IAR4D framework deliver more benefits to end users than conventional approaches (assuming conventional research, development and extension approaches have access to the same resources)? SSA Challenge Program

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Research Question 3. How sustainable and usable is the IAR4D approach outside its test environment, that is, concerning its scaling out for broader impact?

Hypothesis H3: If the design and estimation show that IAR4D works in different contexts then it can be extrapolated outside the test environments.

Highlights of Project Portfolio
The SSA CP‘s research is organized around four projects: one Meta-Analysis project and three PLS projects in different regions of sub-Saharan Africa (i.e., Lake Kivu [LK] in Eastern and Central Africa, Kano-Katsina-Maradi [KKM] in West Africa, and Zimbabwe-Malawi-Mozambique [ZMM] in Southern Africa). Each PLS project comprises three sub-projects, each implemented by a separate taskforce. The PLS sub-projects are designed to generate outputs that will result in similar outcomes, though the activities for each sub-project are aimed at addressing problems that are specific to the circumstances of the very different environments and production chains. The nine sub-project taskforces are supported by a cross-site research support team (CRST) that provides backstopping in selected key areas and facilitates the use of common research methods in order to enable integration of data, which in turn, allows for cross-site analysis and comparisons. The key areas for which cross-site expertise has been mobilized include impact assessment, participatory monitoring and evaluation, research methods and data management. The CRST will play a lead role in implementing the Meta-Analysis project. The Meta Analysis project has been introduced since last year to organize all the cross-PLS research work to generate general inferences. As a result, the other three PLS MTP projects are now more clearly focused on the establishment of the innovation platforms and the subsequent development, testing and promotion of technological and institutional innovations. The adoption of a more rigorous research method (to prove that the IAR4D approach is more successful than the traditional research-extension approach) has also led to some important changes (see Annex 1). The three PLS projects and their subprojects are briefly described below. KKM PLS project: The three sub-projects that constitute the KKM project are distinguished by the agro-ecological zone (AEZs) where their research is based and focused. The relevant AEZs are the Sahel, the Sudan Savanna, and the Northern Guinea Savanna. Each of the three sub-projects aims to evaluate the effectiveness of IAR4D in its respective AEZ by establishing IPs and conducting action research aimed at intensifying crop and livestock systems, improving access to markets and promoting sustainable management of the natural resource base. The titles and lead institutions of the three KKM sub-projects are: 1. Improving livelihoods of rural population through intensification, access to markets, and sustainable management of natural resources in the Sahelian AEZ. The taskforce implementing this sub-project is led by the national agricultural research institute of Niger (INRAN). 2. Sustainable agricultural intensification and integrated natural resource management to improve rural livelihoods in the Sudan Savanna. This taskforce implementing this sub-project is led by the International Institute of Tropical Agriculture (IITA). 3. Developing a multi-stakeholder approach to linking technical options, policy, and market access for improved land productivity in the Northern Guinea Savanna. The taskforce implementing this sub project is led by the International Fertilizer Development Center (IFDC).

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ZMM PLS Project: The ZMM PLS is composed of a mosaic of landscapes ranging from high potential highland commercial agriculture with high population density and small landholdings, to low potential areas characterized by extensification through slash and burn, degraded soils, low rainfall and poor market access. Overall, the PLS is vulnerable to both drought and flooding (effects of global climate changes). The principal challenge the ZMM PLS project proposes to address in evaluating the effectiveness of IAR4D hinges around the need to reduce vulnerability through improved soil nutrient and water use, intensification, diversification and improved functioning of markets and value chains. The sub-projects of the ZMM project are organized around value chains, namely irrigated and rain-fed vegetables value chain (1 sub-project) and staple food cereal grains (2 sub-projects). The titles and lead institutions of the three ZMM PLS sub-projects are: 1. Improving human nutrition and income through integrated agricultural research on production and marketing of vegetables in Malawi and Mozambique. The taskforce implementing this sub-project is led by Bioversity International. 2. Integrating sustainable soil fertility management innovations in staple cereal systems and other value chains to enhance livelihoods and environmental systems in Southern Africa. The taskforce implementing this sub-project is led by the Soil Fertility Consortium for Southern Africa (SOFECSA), which is hosted by the International Institute for Maize and Wheat Improvement (CIMMYT). 3. Efficient water and nutrient use in cereal grains systems in market-based conservation agriculture systems. The taskforce implementing this sub-project is led by the Tropical Soil Biology Fertility Institute (TSBF) of the International Center for Tropical Agriculture (CIAT). LK PLS Project: The LK PLS is characterized by steep slopes, a bimodal rainfall pattern, high population density, and fragmented smallholder plots that are intensively cultivated. The principal challenge the LK project proposes to address in evaluating the effectiveness of IAR4D concerns increasing returns to land use in a sustainable way (e.g., through shorter season, higher yielding crops) and increasing the production and value addition of high value, low volume products. The project‘s action research approach integrates watershed management and landscape analysis to identify market-driven technological and institutional innovations for sustainable productivity enhancement to address livelihood improvements. The titles and lead institutions of the three Lake Kivu PLS sub-projects are: 1. More food products and better nutrition at reduced cost and minimal degradation of the natural resource base. The taskforce implementing this sub-project is led by the national agricultural research institute of Rwanda (ISAR) 2. Beneficial conservation and sustainable use of natural resources. The taskforce implementing this sub-project is led by Makerere University, Uganda 3. Wealth creation through agro enterprise diversification and improved market access. The taskforce implementing this sub-project is led by CIAT.

New and Terminated Research
The research proposed in this MTP was formulated in response to the commentary made by the SC on the MTP that was submitted in 2007. The main change to the research proposed in that MTP was the increased emphasis placed on quantitative evaluation in seeking to establish the proof of concept for IAR4D (Annex 1). This change was reflected in the reformulation and
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sharpening of the research hypotheses. It also implies that the scope of the process-related research previously proposed has been trimmed down. Nevertheless, since the research concerns testing the effects of ARD processes, the research retains a substantial quantum of processrelated research. In the first year of the work on the proof of the IAR4D concept, not research was terminated at the PLS.

Slower than Expected Progress in Previous MTP
The previous MTP is being implemented across the TFs and the PLS. Although Innovation Platforms have been established in all the PLSs, research activities are lagging behind in some PLSs. The following reasons have been observed as the main cause of the slower than expected progress in the implementation of the previous MTP. · Some field activities were delayed due to social disturbances and war in Zimbabwe and Democratic Republic of Congo respectively. · The take-off of the activities of the CRST team was delayed due to the time spent in identifying scientists with desired expertise in the areas of interest to SSA CP and in eventually finalizing contracts with different institutions for the engagements of the identified people. This delayed the take-off of some activities of CRST members till the last quarter of 2008 and even 2009 in some other cases. · Livestock components of most research activities in KKM PLS did not commence in 2008, due to non- availability of relevant staff within ILRI, the partner organization that was depended upon for capacity support on livestock research matters. · Formation of IP was slowed down in some cases due to re-mobilization of the nonresearcher partners. This became necessary as part of the grand measure to bring most of the partners who had deserted due to the protracted delay back into the teams. · Some TF activities were adversely affected by high rate of staff movement from one institution to another. The slower than expected progress is reflected in the SSA CP‘s under-spending during 2008. The total expenditures for the year amounted to US$ 4.56 million (46.01%) of the US$ 9.91 million budgeted for the year. In the light of the quantum of activities carried forward, it is envisaged that the activities of the SSA CP will require to be extended to 2010.

Changes in Collaborative Arrangements
The changes in collaborative arrangements proposed in this MTP relate to: · FARA‘s proposition to engage Obafemi Awolowo University, Ile-Ife (OAU-Ife), Nigeria and Institute of Learning and Change Initiative (ILAC) in a collaborative arrangement to provide extra support in specific areas of impact assessment. OAU-Ife will provide expert support to conduct exante analysis across the TFs, PLSs and program wide levels. ILAC will support the facilitation monitoring and evaluation of complex institutional arrangements among the IP actors. It will also facilitate learning and change among actors, and assess progress towards the realization of the output. It is envisaged that ILAC will complement the efforts of the CRST member who provided support for Monitoring and Evaluation in 2008 but had to change her institution at the end of the 2008 and is therefore unable to provide same level of service this year from her new institution.

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· FARA proposes to renew its collaborative arrangements with WARDA and IFPRI to provide expertise to strengthen the program‘s impact evaluation capacity. · FARA also proposes to renew the agreements with CIAT and ICRAF/ILRI‘s research methods group for backstopping in participatory monitoring and evaluation, and in research data management respectively. · FARA proposes to transfer the management of post doctoral fellow to the partner NARI, CG centers or the PLS coordinating institution. This is different from the previous arrangement where the post doctoral fellows were hosted by NARI partners, while the management of their activities and payment were coordinated by FARA. · FARA proposes, with the agreement from SADC/FANR to stand in for SADC/FANR in coordinating the activities of the ZMM PLS until a suitable institution has been identified to undertake the responsibility.

Alignment with System Priorities
The alignment of the SSA CP‘s Project Portfolio with the CGIAR System Priorities (SPs) is outlined in Table 1. This CP contributes to nine SPs, namely 3a, 3b, 4a, 4c, 4d, 5a, 5b, 5c and 5d. Approximately 50% of the program‘s investment is directed to activities that contribute to Priority Area 5 (Improving Policies and Facilitating Institutional Innovation to Support Sustainable Reduction of Poverty and Hunger). The Meta-Analysis project and outputs 1 and 3 of each PLS project are all concerned with the proof of concept of IAR4D and elaboration of its principles. Hence they contribute to SPs 5a (Improving science and technology policies and institutions), 5c (Improving rural institutions and their governance) and 5d (Improving policies and facilitating institutional innovation to support sustainable reduction of poverty and hunger). This CP contributes to the remaining six SPs through Output 2 of the three PLS projects. This output embodies all the potential technological, market, policy and institutional innovations that will be generated by the sub-projects as part of the process of establishing the proof of the IAR4D concept. Table 1: Alignment of the SSA CP’s research to System Priorities
MTP projects 1. Meta-Analysis Project Outputs Output 1 Output 2 Output 3 Output 4 2. KKM PLS Project Output 1 Output 2 Output 3 3. ZMM PLS Project Output 1 Output 2 CGIAR System Priorities 5a, 5c, 5d 5a, 5c, 5d 5a, 5d 5a, 5d 5a, 5c, 5d 3a, 3b, 4a, 4c, 4d, 5b 5a, 5c, 5d 5a, 5c, 5d 3a, 4c, 4d, 5b

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Output 3 4. Lake Kivu PLS Project Output 1 Output 2 Output 3

5a, 5c, 5d 5a, 5c, 5d 3a, 3b, 4a, 4c, 4d, 5b 5a, 5c, 5d

Non-System Priority Activities
All research activities proposed in this MTP contribute directly to the CGIAR‘s System Priorities.

Project Portfolio
The SSA CP project portfolio comprises four projects: one Meta-Analysis project and three Pilot Learning Site (PLS) projects (each representing a particular region of sub-Saharan Africa) (see Table 3). The Meta-Analysis project draws on the data and outputs generated by the three PLS projects to test the SSA CP‘s hypotheses (which center around proof of concept of IAR4D) and to derive general principles for the effective implementation of IAR4D. The three PLS projects contribute to establishing proof of the IAR4D concept and deriving principles for its implementation by: (a) establishing and facilitating and monitoring the operation of innovation platforms (12 platforms per project); (b) developing and introducing technological, market, policy and other institutional innovations; and (c) evaluating whether IAR4D works in their specific contexts and whether it delivers more benefits than the traditional research-extension approach. The four projects complement one another. Table 3: Project Portfolio
Three PLS projects: Objective: Derive process guidelines for implementing IAR4D and generate data for evaluating its feasibility and impacts by: (i) creating functioning innovation platforms; and (ii) generating innovations in farmers‘ fields, and (iii) evaluating IAR4D impacts in specific contexts and for specific objectives. LK PLS (Eastern & Central Africa) Specific objective: More food production and agricultural productivity through diversification and improved market access while improving the use of natural resources. The LK PLS comprises the following subprojects: 1. More food products and better nutrition at reduced cost and minimal degradation of the natural resource base (sub-project lead institution: ISAR); KKM PLS (West Africa) Specific objective: Improve the productivity of farming systems and ensure an efficient use of resources through technical, administrative, marketing and management improvements. The KKM PLS comprises the following subprojects: 1.Improving livelihoods of rural population in the Sahel through intensification, access to markets, and sustainable management of natural resources (sub-project lead institution: INRAN); ZMM PLS (Southern Africa) Specific objective: Improve the performance of the agricultural value chains through intensification and other technical innovations in high & low potential farming systems. The ZMM PLS comprises the following subprojects: 1. Improving human nutrition and income through integrated agricultural research on production and marketing of vegetables in Malawi and Mozambique (sub-project lead institution: Bioversity International); 2. Integrating sustainable soil fertility management innovations in staple cereal systems and other value chains to 13

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2. Beneficial conservation and sustainable use of natural resources (sub-project lead institution: Makerere University); and 3. Wealth creation through agro enterprise diversification and improved market access (sub-project lead institution: CIAT)

2. Sustainable agricultural intensification and integrated natural resource management to improve rural livelihoods in the Sudan Savanna (sub-project lead institution: IITA); and 3. Developing a multistakeholder approach to linking technical options, policy, and market access for improved land productivity in the Northern Guinea Savanna (subproject lead institution: IFDC).

enhance livelihoods and environmental systems in Southern Africa (sub-project lead institution: SOFECSA/CIMMYT); and 3. Efficient water and nutrient use in cereal grains systems in market-based conservation agriculture systems (subproject lead institution: TSBF-CIAT).

Meta-Analysis (of the IAR4D Concept) Project Objective: Derive generalizable principles for implementing IAR4D and evaluate its feasibility and impact across sub Saharan Africa Implementation of the meta analysis project will be led by the cross-site research support team which will work in collaboration with the PLS project teams.

Long term adequacies of reserves
The Sub-Saharan Africa Challenge Program does not accumulate annual surpluses or deficits, so this indicator is not applicable. Nevertheless, it is noteworthy that FARA Secretariat has entered into a memorandum of understanding with its donors through which the donors are jointly committed to harmonizing their funding for the Secretariat‘s core functions as well as FARA‘s programs, including the SSA CP, over five years (from 2008 to 2012). Through this arrangement, the Secretariat will be able to ascertain in advance the resources available to finance its core functions and program activities each year. The implementation of this arrangement is certainly delayed but there are recent indications that it may take off within 2009. The overall indications from current donors of SSA CP show that while the program would have enough finances to undertake planned activities for 2009, it does not have guarantee of having enough financial resources for the activities of 2010 which serve as the concluding part of the proof of the concept of IAR4D

Short term liquidity
TheSSA CP secured full financial support for thefunding of the budget for 2007 which wassupposed to be the first year of the researchphase (US$ 9.9 million). However, fullresearch activities did not commence that year because an acceptable researchmethodology was still being developed. Consequently,unspent money was ploughed into 2008. Thiscarry-over money made the Program‘s funding outlook for 2008 to look good inspite of the fact that only 42% of the Program‘s budget was secured (i.e. $ 4.18million from a budget of $ 9.91million) in the year. Based on current pledges from the Program‘sfunders and the carry-over fund from 2008, the funding outlook for 2009 looksbright but 2010 is not as bright. FARAis now faced with the challenge of mobilizing funds to ensurecontinuity and completion of field operations in 2010..

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Project Portfolio
SSA-01: Meta-Analysis of the IAR4D Concept
Project Overview and Rationale
Meta-Analysis (of the IAR4D Concept) Project Objective: Derive generalizable principles for implementing IAR4D and evaluate its feasibility and impact across sub Saharan Africa Implementation of the meta analysis project will be led by the cross-site research support team which will work in collaboration with the PLS project teams.

The increasingly popular hypothesis that adopting a systemic approach to agricultural research delivers substantially higher benefits than the conventional research-to-extension approach has not been subjected to a rigorous test. Moreover, scientifically robust evidence of whether this approach is feasible under Sub-Saharan Africa circumstances is yet to be established. In order for the various ARD actors to mobilise the investment and political support necessary to reform agricultural research towards a systems approach thereby increasing its development impact, the aforementioned knowledge gap must be bridged, that is, the proof that IAR4D indeed measures up to what it is hailed to be capable of delivering needs to be established. The Meta-Analysis project is the avenue through which the outputs of the SSA CP for the current research phase will be generated. It aims to deliver outputs that will bridge the said knowledge gap by pooling and analysing data from the PLS projects. It pursues this aim by addressing the following three research questions:    Does the IAR4D concept work and can it generate deliverable international and regional public goods for the end users? Does the IAR4D framework deliver more benefits to end users than conventional approaches (if the conventional ARD approach had access to the same resources)? How sustainable and usable is the IAR4D approach outside its test environment (i.e., issues of scaling out for broader impact)?

The Meta-Analysis project is being implemented by the Cross-Site Research Support Team (CRST)—experts in natural and social sciences drawn from CGIAR centers and advanced research institutes—in close collaboration with the PLS project teams (which comprise the sub-project taskforces).

Outputs Description
Changes from Previous MTP Changes from previous MTP by output are described in this box Output 1: Empirical evidence of whether IAR4D works, the extra benefits it delivers compared to those delivered by traditional approaches given the same resources and whether it is replicable beyond the SSA CP’s test sites Description: principal research products expected from SSA CP‘s research.

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Alignment to CGIAR Priorities : 5A: Improving science and technology policies and institutions; 5C: Improving rural institutions and their governance; 5D: Improving research and development options to reduce rural poverty and vulnerability; Output 2: General principles for implementing IAR4D Description: principal research products expected from SSA CP‘s research. Alignment to CGIAR Priorities : 5A: Improving science and technology policies and institutions; 5C: Improving rural institutions and their governance; 5D: Improving research and development options to reduce rural poverty and vulnerability; Output 3: A database of process and impact indicator variables for 36 innovation platforms and their associated research communities and households (540 villages and 5,400 households across the three PLS) which will be made available as a public good for long term monitoring of the sustainability and impact of the platforms. Description: Principal research product expected from SSA CP's reasearch. Alignment to CGIAR Priorities : 5A: Improving science and technology policies and institutions; 5D: Improving research and development options to reduce rural poverty and vulnerability; Output 4: Methods and tools for designing, implementing and analyzing social experiments in Sub-Saharan Africa Description: Important research product expected from the SSA CP's research. Alignment to CGIAR Priorities : 5A: Improving science and technology policies and institutions; 5D: Improving research and development options to reduce rural poverty and vulnerability;

Alignment to CGIAR Priorities
MTP Project Outputs i. Empirical evidence of whether IAR4D works, the extra benefits it delivers compared to those delivered by traditional approaches given the same resources and whether it is replicable beyond the SSA CP‘s test sites; CGIAR system priorities 5a, 5c, 5d

ii.

Guidelines/principles for implementing IAR4D.

5a, 5c, 5d 5a, 5d

iii. A database of process and impact indicator variables for 36 innovation platforms and their associated research communities and households (540 villages and 5,400 households across the three PLS).

iv. Methods and tools for designing, implementing and analyzing social experiments in Sub-Saharan Africa

5a, 5d

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The Meta-Analysis project contributes to CGIAR system priority area 5 (Improving policies and facilitating institutional innovation to support sustainable reduction of poverty and hunger. It is expected to test and validate institutional innovations that will improve the generation, access and use of technology and market options. The knowledge created by the project will be used as an input in the formulation of policies to support the reform of how ARD institutions discharge their mandates. Outputs 1 and 2 contribute to system priorities 5a (science and technology policies and institutions), 5c (rural institutions and their governance), and 5d (improving research and development options to reduce rural poverty and vulnerability): Outputs 3 and 4 contribute to system priorities 5a and 5d.

Description of Impact Pathway
The Meta-Analysis project largely involves pooling data from the PLs projects and analyzing it. Consequently its outputs are specifically in the form of data and knowledge. The knowledge will include (a) evidence of whether IAR4D works and delivers more benefits than conventional ARD approaches and (b) principles for implementing IAR4D. If the evidence confirms that IAR4D is indeed feasible and delivers more benefits than conventional approaches, the project will have produced justification for increased investments and policy support in favor of IAR4D processes. The evidence that IAR4D works along with principles and guidelines about how it works are the key requirements for ARD organizations (SROs and NARS) to adopt the approach thereby increasing the impact of agricultural research. The evidence is expected to include a validation of the impact pathway for IAR4D. It is hypothesized that IAR4D delivers benefits by facilitating exchange of knowledge among relevant ARD, which enables the research process to focus on generating the most relevant outputs. Further, the network mode of interaction characteristic of IAR4D enhances the translation of research outputs into outcomes (putting research into use) thereby improving the resultant impact. In the event that the evidence is not in favor of IAR4D, it will serve a crucial role in sparing ARD the opportunity cost of investing in IAR4D. The conditioning factors include (1) dissemination of the evidence generated by the project to SROs, NARS and their collaborating partners; (2) political will and buy-in from government and SRO decision-makers and political leaders in support of the institutional reforms and investments necessary for IAR4D to work; (3) capacity of ARD partners to adopt IAR4D and engage in innovation; (4) investments to support the necessary institutional reforms in agricultural organizations.

International Public Goods
Most of the outputs of the Meta-Analysis project are expected to become IPGs. The evidence about whether IAR4D works and delivers more benefits than the traditional ARD approach will be generated from analysis of process monitoring and impact evaluation conducted over 36 innovation platforms, 540 villages and 5,400 households spread across the SSA CP‘s three pilot learning sites (further details about the research approach are presented in Annex 1). The principles for implementing IAR4D will be derived from an analysis of processes entailed in the establishment and operation of innovation platforms and the conduct of action research to generate technological, market and policy innovations by the three PLS projects. For each subproject, these processes will be associated with the starting conditions, adoption of the innovations and impact of the research. The general principles for implementing IAR4D will emerge from analysis of the data generated by the sub-projects.

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The three projects will generate a rich data set that FARA proposes to maintain as a public good, available for use by other researchers. The database is expected to be updated as appropriate to monitor the sustainability and performance of institutional and technological innovations long after the current SSA CP phase. The methods and tools for designing, implementing and analyzing social experiments include novel adaptations to existing field techniques and analysis methods, and custom tools that will be developed and used in implementing the three PLS projects and the meta-analysis project.

Elaboration of Partners Roles
The Meta-Analysis project is jointly implemented by the SSA CP‘s cross-site research support team (CRST) and the PLS project teams (PLS lead institutions and sub project taskforces). The CRST comprises experts drawn from CGIAR centers (CIAT, WARDA, ICRAF, ILRI and IFPRI), advanced research institutes (ECART, United Nations University-MERIT, Maastricht) and University of Development Studies (UDS) in Tamale, Ghana. The PLS lead institutions include IITA and CIAT. The subproject taskforces are mostly led by CGIAR centers (IITA, CIAT, CIMMYT, Bioversity International), NARS (INRAN, ISAR, Makerere University) and IFDC, an IARC. IWMI and ICRISAT contribute specialized watershed management competencies to the LK PLS project.

Table 4: Partners and their Roles in the Meta-Analysis Project
Type CGIAR centers Partner organization CIAT Role Lead institute for the LK PLS project; lead institution for two sub projects (one in ZMM PLS and one in LK PLS); hosts the CRST expert responsible for participatory monitoring and evaluation. Lead institution for one of the three KKM PLS sub projects.

IITA

WARDA, ILRI and IFPRI

Hosts the CRST experts responsible for research design and econometric methods of evaluation of social programs and PM&E Hosts the CRST experts for PM&E Hosts the CRST experts responsible for data management. Responsible for developing methods for trade off analysis, ecosystem valuation, and decision support systems for integrated watershed management in LK PLS. Lead institution for one of the ZMM PLS sub projects Lead institution for one of the KKM PLS sub projects

Bioversity (ILAC) ICRAF/ILRI IWMI and ICRISAT

Bioversity IFDC

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Type NARS

Partner organization ISAR (Rwanda) INRAN (Niger) Makerere University (Uganda) Obafemi Awolowo University, Ile Ife, Nigeria UDS

Role Lead institution for one of the LK PLS sub projects Lead institution for one of the KKM PLS sub projects Lead institution for one of the LK PLS sub projects Hosts the CRST experts responsible for ex-ante analysis Hosts CRST expert responsible for research methods and biometry Lead Institution Coordinating KKM PLS Technical assistance Technical assistance

SRO ARIs

CORAF/WECARD ECART UNU-MERIT

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Logical Framework
Outputs Output 1 Empirical evidence of whether IAR4D works, the extra benefits it delivers compared to those delivered by traditional approaches given the same resources and whether it is replicable beyond the SSA CP’s test sites Intended Users SROs, NARS, IARCs, national, regional and international policy makers, agribusiness actors, NGOs, farmer organizations, donors Outcome Increased adoption and reliance on IAR4D (increased involvement of non-traditional actors in ARD) Increased investment towards supporting IAR4D processes Increased human and institutional capacity for innovation among ARD actors Target 2010: Policy strategies Target 2010: Policy strategies Feasibility of IAR4D evaluated Cost-benefit effectiveness of IAR4D compared with traditional approaches established Replicability of IAR4D established. Impact Improved returns from agricultural research and development contributing to improved food security, increased household incomes, reduced poverty, and sustainable natural resource management

Target 2010: Policy strategies

Output 2

General principles for implementing IAR4D

Researchers (NARS, SROs, IARCs), national policy makers, agribusiness actors, NGOs, farmer organizations,

Increased adoption and reliance on IAR4D (increased involvement of non-traditional actors in ARD) Increased investment towards supporting IAR4D processes

Improved returns from agricultural research and development contributing to improved food security, increased household incomes, reduced poverty, and sustainable natural resource management

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Outputs

Intended Users

Outcome Increased human and institutional capacity for innovation among ARD actors

Impact

Target 2009: Practices

Guidelines for establishing innovation platforms tested Principles for implementing IAR4D identified

Target 2010: Practices

Output 3

A database of process and impact indicator variables for 36 innovation platforms and their associated research communities and households (540 villages and 5,400 households across the three PLS) which will be made available as a public good for long term monitoring of the sustainability and impact of the platforms. Time series database of process and indicators variables for 540 villages and 5400 households established and made accessible to the public

Researchers (NARS, SROs, IARCs), national, regional and international policy makers, agribusiness actors, NGOs, farmer organizations, donors

Increased adoption and reliance on IAR4D (increased involvement of non-traditional actors in ARD) Increased investment towards supporting IAR4D processes Increased human and institutional capacity for innovation among ARD actors

Improved returns from agricultural research and development contributing to improved food security, increased household incomes, reduced poverty, and sustainable natural resource management

Target 2010: Materials

Output 4

Methods and tools for designing, implementing and analyzing social experiments in Sub-

Researchers (NARS, SROs, IARCs)

Increased adoption and reliance on IAR4D (increased involvement of non-traditional actors in

Improved returns from agricultural research and development contributing to improved food security, 21

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Outputs Saharan Africa

Intended Users

Outcome ARD) Increased investment towards supporting IAR4D processes Increased human and institutional capacity for innovation among ARD actors

Impact increased household incomes, reduced poverty, and sustainable natural resource management

Target 2009: Practices

Good practices and tools for tracking learning and institutional change Tool and methods for impact evaluation in social experiments

Target 2010: Practices

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SSA-02: KKM Pilot Learning Site
Project Overview and Rationale
The KKM pilot learning site is located on the border between south central Niger and north central Nigeria, and encompasses three different agroecological zones (AEZs) that cross all of West and Central Africa at this latitude: (1) The Sahelian zone (Sahel); (2) The Sudan Savanna (SS); and (3) The Northern Guinea Savanna (NGS). As one moves from the northern to the southern parts of this PLS, average temperatures decline, and annual rainfall and the length of the growing period increase. Principal crops in the PLS include: (i) cereals (pearl millet, sorghum, maize, upland rice, and wheat), (ii) legumes (groundnut, cowpea, soybeans), (iii) roots and tubers (cassava, sweet potato); and (iv) cotton. Other emerging crops include tiger nuts (Cyperus esculentus) and sesame (Sesamum indicum). Vegetable crops (pepper, onion, tomatoes, cabbage or water melon) are mainly grown under irrigation. In all three agroecological zones, livestock is an essential part of the production systems. Each AEZ, however, faces some major constraints to agricultural development that were identified through validation exercises undertaken during the SSA CP‘s inception phase. The KKM PLS project comprises three sub-projects each focusing its research in one of the three AEZs. The Sahel Sub-Project: The major constraints to sustainable agricultural production in the Sahel are: (i) natural resource degradation (due primarily to inherent poor soil fertility, erosion, deforestation, and overgrazing), (ii) desertification, (iii) insect pests and diseases, and (iv) parasitic weeds (in particular Striga). Socio-economics constraints identified include poor access to inputs, and high cost and low quality of inputs, poorly developed agricultural produce markets; poor access to credit; increasing conflicts between pastoralists and crop farmers; inadequate policy incentives to encourage private sector investment; and low uptake of technologies by producers. The Sahel sub-project is led by INRAN (Institut National de la Recherche Agronomique du Niger) and will work in the areas of Katsina (Nigeria) and Maradi (Niger) on the value chains (including policy issues) related to livestock feed issues, irrigated vegetable, legume crop production and soil fertility management. These production/consumption value chains were chosen based on the comparative advantages of the Sahel region and the main constraints as identified through the validation exercise. The Sudan Savanna sub-project: The main constraints to agricultural production in the Sudan Savannah include limited adoption of improved technologies, land degradation, diseases, insect pests, Striga infestation, and lack of labor-saving technologies for field operations and processing. These constraints are compounded by market-related and policy related ones such as limited access to credit; low farm-gate prices; inadequate supply, high cost and low quality of inputs; poor access to output markets, and weak linkages between producers, agro-industry and markets on the market side and, on the policy side, by conflicts arising from access to community resources and utilization especially between farmers and pastoralists. Ineffective extension systems and lack of policy incentives also constrain agricultural intensification. The Sudan Savanna sub- project is led by IITA (International Institute for Tropical Agriculture). Its areas of intervention include the Sudan Savanna zones of Katsina and Kano States in Nigeria. This subproject will work on cereal-legume-livestock issues in the two States with special focus on the production to consumption value chains. The actual choice of cereal and legume depends on the comparative advantages of each of the regions due to a rainfall north-south gradient. The Northern Guinea Savannah (NGS) sub-project: The NGS AEZ is characterized by inherently poor soils compounded by farmers‘ poor access to financing, relevant technologies, and markets. The main biophysical constraints to increased production of both crops and livestock are the inadequate availability of metabolizable energy, protein, and phosphorus for livestock production; and nitrogen, phosphorus, and organic matter for crop production. Long-term trends
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of agricultural commodity prices were downward since the 1960s with profound implication for producer confidence. Furthermore, ad hoc and inconsistent policy pronouncements and proclamations have left the private sector leery of government intentions, and this resulted in reduced production/and importation of agro-inputs. The NGS sub-project is led by IFDC (International Fertilizer Development Center). It will have activities in the NGS zones of Katsina and Kano States as well. The value chains that this taskforce will focus on include maize–legumes systems, livestock feeding, vegetables and rice production and marketing. Livestock feeding has been a recurrent problem in the NGS while vegetable marketing and rice field fertility are the other two entry points identified for this AEZ. Objective of KKM PLS project Overall, crop and livestock productivity in the KKM PLS is quite low partly owing to high prevalence of pests and diseases, very limited use of productivity enhancing inputs, limited use of improved technologies, poor linkages between production and markets, and lack of productivity enhancing policies. The per capita farm input-use across this PLS has sharply fallen because of high prices of inputs (fertilizer, feed), lack of credits, and volatile agriculture product prices. Previous ARD activities in the KKM site have identified technologies that can potentially overcome some of the above constraints. Some of these technologies are ready for uptake by stakeholders but need more exposure to farmers while others require further research and development work. The KKM Pilot Learning Site project seeks to address these challenges concerning low agricultural productivity, rural poverty, food insecurity and widespread degradation of natural resources in the KKM PLS, within the overall research framework of the SSA-CP. The constraints identification study and subsequent constraint validation exercises conducted in the KKM have summarized and prioritized the main constraints and defined the activities to tackle those constraints. The identified priority research areas were then used as entry points in defining the three sub-projects that comprise the KKM PLS project. The main objective of the KKM PLS project is to test the effectiveness of innovation systems (IAR4D) in supporting the development and adoption of market-driven, crop/livestock productivity-enhancing innovations. Each of the three sub-projects that constitute the KKM PLS project has the same types of outputs but activities differ based on the entry points and the specific context of each AEZ. The specificity of each sub-project comes from the actual content of the field research work planned based on the identified entry points. The taskforce responsible for implementing each sub-project comprises scientists, extension services, NGOs, private sector actors, policymakers (especially at the local level). This group constitutes the nucleus of the innovation platform. Each sub-project will establish four innovation platforms that will deal with issues related to value chains that are most important for the given AEZ (Table 5). Table 5: Theme and Number of Innovation Platforms per KKM PLS Taskforce
Value chain Livestock-feed Cereal/legumes livestock* Groundnut Fadama rice Fadama vegetables Total Sahel Taskforce 1 1 1 0 1 4 NGS Taskforce 1 1 0 1 1 4 Sudan Savannah Taskforce 0 4 0 0 0 4 Total 2 6 1 1 2 12

Note: * In the Sudan Savanna, 2 IPs will deal with the sorghum/cowpea production systems in the north of the Sudan Savanna and 2 IPs with maize/cowpea production systems in the south.

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Outputs Description
Changes from Previous MTP Output 1: Innovation platforms introduced and functioning Description: The activities resulting in this output are those leading to the formation of the Innovation Platforms (IPs). Initial steps involve the bringing together of the core members and stakeholders to prioritize and determine the objective of the project and the actions to be undertaken. It is to be noted that the comparative advantage of this approach is that it enables various actors or stakeholders to come together to interact and prioritize challenges, exchange knowledge and guide the development of technological and institutional innovations to resolve the challenges. They also support the ―putting into use‖ of the innovations in order to achieve the desired impact. Alignment to CGIAR Priorities : 5A: Improving science and technology policies and institutions; 5C: Improving rural institutions and their governance; 5D: Improving research and development options to reduce rural poverty and vulnerability; Output 2: Potential technological, market, policy and institutional innovations identified, developed and mechanisms for putting them into use analyzed Description: Depending on the specific production-consumption value chain selected for each subproject, activities have been designed to identify, develop and test technological, market, policy and institutional innovations; and establish mechanisms for putting them into use to realize the desired impact. Alignment to CGIAR Priorities : 3A: Increasing income from fruit and vegetables; 3B: Increasing income from livestock; 4A: Promoting integrated land, water and forest management at landscape level; 4C: Improving water productivity; 4D: Promoting sustainable agro-ecological intensification in low- and high-potential areas; 5B: Making international and domestic markets work for the poor; Output 3: Lessons learned from the innovation platforms evaluated and documented Description: The KKM PLS project will contribute to the SSA-CP proof of concept of IAR4D through its three stated outputs. The evaluation and documentation of this social experiment, from the establishment of IPs to delivery of technological and institutional innovations, and the evaluation of the whole process will demonstrate the effectiveness of the IAR4D approach in delivering benefits to farmers, which is the MTP project‘s contribution to the proof of concept work of the SSA-CP. Alignment to CGIAR Priorities : 5A: Improving science and technology policies and institutions; 5C: Improving rural institutions and their governance; 5D: Improving research and development options to reduce rural poverty and vulnerability;

Alignment to CGIAR Priorities
Table 6 summarizes how the three subprojects that constitute the MTP project contribute to the CGIAR system priorities.

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Table 6: CGIAR System Priorities Targeted by KKM PLS Project
Project Outputs 1. Functioning innovation platforms created CGIAR system priorities 5a, 5c, 5d

2. Potential technological, market, policy and institutional innovations identified, developed and mechanisms for putting them into use analyzed 3. Lessons learned from the innovation platforms evaluated and documented

3a, 3b, 4a, 4c, 4d, 5b

5a, 5c, 5d

Description of Impact Pathway
The impact pathway for this project is tied to the pathway for the Meta-Analysis project because this project, like the other PLS projects, generates the data and knowledge the Meta-Analysis project will draw upon to deliver its impact (see B.1.4). The project will also have direct impacts within in the communities where it will be implemented. Given the major conditioning factors in the KKM PLS (major drought affecting crop and livestock production, major market price collapse for crops and or livestock), the research plan aims to improve the productivity of farming systems and ensure an efficient use of resources through development, testing and promoting of technical, marketing and management innovations in the three AEZs of the KKM PLS. The outputs listed in B2.2 will be generated by the research process as described in Figure 3 (see overview). The role of the extension workers, NGOs, the private sector and the policy makers is to ensure that the innovations are put into use so that all actors including the farmers derive expected benefits from the project. Output 1 will generate knowledge about how to set up and make IPs functional. This will be documented to become an IPG. Capacity building will be carried out to promote institutional change, knowledge management, and information sharing among actors on the IP. It will level the playing field among the different TF members and between them and other stakeholders and enhance their ability to collectively apply IAR4D as an effective tool. It is expected that a wellfunctioning IP will lead to more awareness and understanding of the technical and institutional innovations coming out from output 2 thus helping stakeholders‘ adoption of them (Output 3). Output 2 deals with the technological (crop and livestock productivity enhancing technologies) and institutional (linking farmers to input and output markets, dialogue with policy makers, and involvement of non traditional partners) innovations which can be transformed into outcomes and impact. Activities that transform output 2 into outcomes and impact will be led by the extension services (ADPs in Nigeria and ‗Directions Régionales‘ in Niger), CBOs, and NGOs. The mechanisms by which innovations are successfully put into use will also be identified. These are expected to inform strategies aimed at increasing the adoption of existing research outputs as well as organizing research to generate outputs that are readily adoptable. Lessons learned from the IPs will be evaluated and documented to result in Output 3.

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International Public Goods
In addition to the approaches adopted by the SSA-CP as a whole, the KKM PLS will adopt several context- and site-specific approaches for carrying out the research and generating public goods. Using an innovation systems approach, existing technologies will be screened and adapted and recommendations made for various farmer typologies. Strategies for accelerating the putting of research outputs into use will also be investigated The IPGs derived from this project will therefore include: (i) a set of methods, (for setting up IPs, and their functionality, the framework for tracking and evaluating IPs, ―putting research into use‖) (ii) technological, institutional, policy and market innovations at the interface of productivity, sustainable natural resource management, markets and policies. Furthermore, data from this project along with data from other PLS project will be pooled by the Meta-Analysis project to generate the SSA CP‘s principal IPGs (see B1.5). In this way, this project will contribute to the proof of the IAR4D concept and the definition of guidelines for implementing IAR4D.

Elaboration of Partners Roles
In addition to the CGIAR centers (IITA, ILRI, ICRISAT, CIAT-TSBF) and ARI centers (IFDC, ICRA) involved in this program, three categories of partners can be distinguished: (1) Farmers‘ organizations, NGOs, and CBOs; (2) National agricultural research and extension services (NARES) and universities; and (3) Private sector actors. Each category has its own role to play in producing the desired outputs. Within each category, several partners are identified due to geographical spread and interest of the partners (see Table 7). Table 7: Partners and their Roles in the KKM PLS Project
Partner Type Farmers‘ organizations including CBOs Partner organization FUMA-Gaskia, FCMN, AREN, Meyetti Allah Role Involved in community-based seed production and scaling up/out; knowledge and information management; participatory action research and learning Provide on-farm research land; involvement in participatory adaptive research and learning, policy advocacy for farmers; community seed production; advocacy role in the taskforce as well as promote use of quality inputs. Perform similar roles as AFAN but with focus on women farmers KAFA will participate in action research and learning on crop, soil and livestock management including value addition while DMDA will participate in action 27

All Farmers‘ Association of Nigeria (AFAN)

Women Farmers‘ Association of Nigeria (WOFAN) Kahutu Apex Farmers‘ Association (KAFA) and Dawano Market Development Association (DMDA), IRNS, SG2000

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Partner Type

Partner organization

Role research and learning on markets development. They will both contribute to policy analysis and formulation and will engage in advocacy for policy and institutional change. They will both play key role in information sharing and PM&E.

Agricultural research organizations, universities, and extension services

IARCS (IITA, ILRI, ICRISAT, CIATTSBF, IFDC, ICRA)

Provide technologies, research leadership (coordination), action research on soil and crop and livestock production management and marketing; analysis, synthesis and international dissemination of research results Adaptive trials using participatory action research and learning; scaling-up/out technologies; participatory training of stakeholders; facilitate market development IAR will participate in capacity building, action research on soil and crop and livestock production management and marketing. Involved in Capacity building, knowledge and information management and participatory action research and learning

Research organizations: INRAN, IAR, LCRI, NAPRI, NAERLS,

Universities: University. of Niamey; Bayero University of Kano; Ahmadu Bello University;,and University of Agriculture, Makurdi Extension services: ADPs (KATARDA, KNARDA, DRDA, DRE)

Others include: National Seed Service (NSS), Nigerian Institute for Horticultural Research and Training (NIHORT), KUST, and Cooperative Extension Center (CEC). Private Sector, agribusiness, entrepreneurs Fertilizer Producers and Suppliers Association of Nigeria (FEPSAN), Manufacturers Association of Nigeria, Agrochemicals Group of Manufacturers Association of Nigeria, Grand Cereals and Oils Mills, Premier Seed Ltd, Kano state input dealers association. All of them will participate in policy analysis and formulation, and advocacy for policy change, markets analysis and development, information sharing, and PM&E. FEPSAN will participate to action research on fertilizer formulation and will develop the capacity of fertilizer retailers and their networks. Premier Seed will participate on the participatory screening germplasm and the development of contract-farming for seed production. Participatory input and output market development; scalingup/out; value addition; provision of farm implements; provide market outlets for seed from communitybased seed production schemes. Members of the IP who purchase 28

Olga-Oil, FAHL, MANOMA, Katsina Oil Mill, Extrata Foods; Premier Seeds, Jubali, Nagoma Seeds Kano, Grand Cereals Company, Jos, Northern Flour limited‘ Modern Universal Foods Kano, Convenient Foods Jubaili Agrotec Ltd, Africa SSA Challenge Program MTP 2010-12

Partner Type

Partner organization Agro Ltd Kano, Golden Fertilizer, Musa Baba and Sons Nig Ltd.

Role farmers produce for their industrial activities.

Policy makers

4 LGAs in Kano (Bunkure and Shanono)and Katsina (Musawa and Safana)

Members of the IP, who provide policy support for the activities of the IP.

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Logical Framework
Outputs Output 1 Innovation platforms introduced and functioning Intended Users Innovation platform members such as farmers, farmer organizations, input suppliers, traders, processors, agricultural research and extension agencies, credit institutions, NGOs, CBOs, Ministry of Agriculture, local government, etc., IARCs Researchers in national and international institutions Outcome 1. Knowledge and information sharing among IP members improved; 2. Awareness among IP members about potential technical and institutional innovations and market opportunities increased; 3. Awareness of IP members about sustainable NRM increased; 4. Technological and institutional innovations adopted by farmers and other stakeholders in the production chain. Target 2009: Practices Approaches for strengthening the innovation capacity of IPs documented Impact Improved food and nutrition security, increased household incomes, reduced poverty, and sustainable natural resource management.

Output 2

Potential technological, market, policy and institutional innovations identified, developed and mechanisms for putting them into use analyzed

Farmers and other actors along the value chain. Researchers in national and international institutions Advisory service providers

1. Knowledge and information sharing among IP members improved; 2. Awareness among IP members about potential technical and institutional innovations and market opportunities increased; 3. Awareness of IP

Improved food and nutrition security, increased household incomes, reduced poverty, and sustainable natural resource management.

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Outputs

Intended Users

Outcome members about sustainable NRM increased; 4. Technological and institutional innovations adopted by farmers and other stakeholders in the production chain.

Impact

Target 2009: Policy strategies

At least one technological and one institutional innovation identified and tested by each of the IPs. The mechanisms through which at least one technological or institutional innovations developed by each IP can be successfully ―put into use‖ identified and documented

Target 2010: Practices

Output 3

Lessons learned from the innovation platforms evaluated and documented

1. Knowledge and information sharing among IP members improved; 2. Awareness among IP members about potential technical and institutional innovations and market opportunities increased; 3. Awareness of IP members about sustainable NRM increased; 4. Technological and institutional innovations adopted by farmers and

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Outputs

Intended Users

Outcome other stakeholders in the production chain.

Impact

Target 2008: Materials

Baseline database on project area conditions established; Frameworks for tracking and evaluating IP dynamics developed; Lessons learned on setting up and sustaining the functioning of IPs documented Model for assessing the efficiency and benefits of IAR4D developed

Target 2008: Practices

Target 2008: Practices

Target 2009: Unassigned

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SSA-03: ZMM Pilot Learning Site
Project Overview and Rationale
The Zimbabwe-Mozambique-Malawi Pilot Learning Site (ZZM PLS) is a corridor through northeast Zimbabwe, central Mozambique and southern Malawi. The ZMM PLS is dominated by the maizemixed farming system. Principal livelihoods are based on maize, tobacco, cotton, grain legumes, small ruminants, and poultry and off-farm work activities. The maize-mixed system is currently in crisis because smallholder farmers have reduced levels of use of science-based inputs due to shortages of seed of improved varieties, fertilizers and agro-chemicals and the high input to output price ratios. There are also problems of declining farm sizes and draught animal ownership; reduced labor supply due to HIV/AIDS; and falling migrant remittances. Soil fertility is declining, yields are falling and smallholder farmers are reverting to extensive production practices. This is creating a self-reinforcing cycle of increasing land degradation which worsens poverty and food insecurity that in turn exacerbate the land degradation. Drought and market volatility result in vulnerability, thereby reinforcing the vicious cycles. Despite the current crisis, there exist significant opportunities for long term agricultural growth and high potential for poverty reduction. In the more densely populated areas with better services, strategies include intensification and diversification out of maize into higher value cash crops such as vegetables and livestock combined with increasing off-farm income activities with strong linkages to agriculture. Implementation of these strategies depends on productive and profitable technologies for improved soil fertility management, conservation agriculture, integrated pest management (IPM), private sector investment for the development of viable input and output markets and farmers‘ collective action (bulk buying, rotational savings, joint marketing, and rural micro-finance institutions). Diversification could also involve development of low-lying areas for irrigated or rain-fed vegetable production. In the low population density areas priorities include area expansion and intensification through zero tillage, conservation farming, grain legumes integration, farmer-based multiplication of seeds and planting materials, and community-based land tenure reform. The ZMM PLS inception workshop held in April 2005 in Malawi and the validation exercise conducted from July to August 2005, diagnosed constraints and priorities for change that need to be addressed to break the poverty trap. These were consistent with those identified through the FARA stakeholder consultative process conducted earlier, in 2003.. Constraints included inefficient input and output markets, lack of agricultural credit and financial services, low profitability and limited market access, low investment, nutrient mining and soil degradation, low crop yields, severe household resource constraints, poverty and low purchasing power, weak scientific capacity in national agricultural research and extension services and universities, and dysfunctional local institutions. The Validation Team found that the incidence and severity of the constraints and opportunities for resolving them vary by farming systems, agro-ecology, population density and market access. To break the poverty trap, multiple interventions are needed at multiple scales: more efficient input and output markets, credit providers, integrated soil fertility and water management, and improved crop varieties, improved technical support services, and more efficient and effective institutions and policies. The FARA led consultations and the Validation Team hypothesized that the key to effectively addressing the challenges faced in this PLS lay in institutional arrangements that would mobilize the knowledge, skills and other resources held by the numerous actors with a stake in the development of the PLS‘ communities. They proposed the testing of how IAR4D could be employed to address the challenges enumerated above by providing a framework for organizing the actors, building farmers‘ skills and organizations, creating incentives and partnerships and mobilizing financial support for other components of innovation systems. To undertake the task of
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testing IAR4D, taskforces were formed by matching individuals and organizations in the private sector, higher learning institutions, public sector/NARS (research and extension), NGOs, and civil society, e.g. farmers‘ organizations in response to the call for concept notes prioritizing research issues identified through the validation exercise. Three taskforces with winning research proposals were selected and their proposals consolidated to create the ZMM PLS project which however comprises three sub-projects aligned to the winning research proposals. Objective of the ZMM PLS Project The main objective of the ZMM PLS project is to test the effectiveness of IAR4D (proof of concept) in improving the performances of priority agricultural value chains through intensification and other technical and institutional innovations in high and low potential farming systems. Each of the three sub-projects that constitute the ZMM PLS project focuses on a specific value chain and is expected to deliver similar outputs. However, the activities of the sub project differ based on the entry points and the specific context of each value chain. The three sub-projects are outlined below (also see Table 8). Staple cereal value chain sub-project: This sub project is led by the Soil Fertility Consortium for Southern Africa SOFECSA hosted by CIMMYT). It aims to contribute to the proof of the IAR4D concept by identifying the effectiveness of innovation platforms for addressing major constraints on the development, dissemination and uptake of soil fertility management research results in order to increase agricultural productivity, competitiveness, profitability, and employment, while improving livelihoods outcomes. This is linked to improving efficiency of agricultural input and output markets, farmers‘ and marketing participants skills development, development of farmers‘ and marketing participant‘ organizations, public agricultural research and extension organizations and private sector firms‘ capabilities to supply technology linked to market demand, micro-credit and taking interventions to scale. Cereal-grains value chain sub-project: This sub-project is led by the Tropical Soil Biology and Fertility Institute of CIAT (TSBF-CIAT). It aims to contribute towards establishing proof of the IAR4D concept by identifying the effectiveness of IAR4D platforms for resolving constraints on the development, dissemination and uptake of new conservation agriculture interventions linked to improved agricultural input and output markets, improved social capital that allows farmers to tap both internal and external community networks thereby promoting access to sources of information, support and resources (e.g. links to traders, financiers, extension agents, and NGOs). The sub-project also examines the effectiveness of the IAR4D process in building the capacity of farming communities with relevant skills for rural development, for increasing access to markets, for improved post harvest handling and grain storage and diversification of production systems with high value crops. The vegetables value chain sub-project: This sub-project is led by Bioversity International. It aims to contribute to establishing proof of the IAR4D concept by identifying the effectiveness of IAR4D innovation platforms for resolving constraints on the development, dissemination and uptake of science-based practices in vegetable growing, harvesting, preservation, storage, transporting, packaging, processing and marketing. The sub-project investigates the impact of multiple scale integration of interventions to strengthen capacity of public and private sector organizations to undertake vegetable research and work with farmers to produce vegetables under improved soil and water management conditions, building capacity of farmers to produce vegetables ‗as a business‘, developing linkages with agricultural input and output markets, and stimulating vegetables demand through promotions.

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Table 8: Targeted Value Chains by the ZMM PLS sub-projects
Sub project and Value chains targeted Staple cereal systems and other value chains Staple cereal-grain legumes Vegetables No of Innovation Platforms 4 4 4 Sub project lead institution SOFECSA/CIMMYT TSBF-CIAT Bioversity International

Outputs Description
Changes from Previous MTP Output 1: Innovation platforms introduced and functioning Description: The main research activities that lead to this output include establishing Innovation Platforms as part of the process of finding solutions to problems that have been identified; putting in place a Participatory Learning and Action Research (PLAR) methodology and using it to facilitate IP meetings; establishing a Participatory Monitoring and Evaluation (PM&E) system and communication, information and knowledge management systems for interaction within IP and between IP members and their constituents; and capacity building for IAR4D actors to effectively participate. Alignment to CGIAR Priorities : 5A: Improving science and technology policies and institutions; 5C: Improving rural institutions and their governance; 5D: Improving research and development options to reduce rural poverty and vulnerability; Output 2: Potential technological, market, policy and institutional innovations identified, developed and mechanisms for putting them into use analyzed Description: By definition partners have an interest and a share in bringing about outcomes that lead to the attainment of their objectives. The IPs determine the research objectives which the sub-project taskforce will pursue by developing relevant technological, market, policy or institutional innovations. The successful putting into use of these innovations is expected to lead to their wider adoption. Mechanisms and approaches for successfully putting into use the innovations generated through the IPs in order to realize the desired outcomes such as increased adoption of the innovations and their subsequent effects, constitute an important dimension of this output. Alignment to CGIAR Priorities : 3A: Increasing income from fruit and vegetables; 4C: Improving water productivity; 4D: Promoting sustainable agro-ecological intensification in low- and highpotential areas; 5B: Making international and domestic markets work for the poor; Output 3: Lessons learned from the innovation platforms evaluated and documented Description: The principal elements of this output are: (i) procedures for setting up and sustaining the functioning of an IP, (ii) establishing the effectiveness of the IP in bringing together a broader group of players to jointly address challenges and opportunities and (iii) establishing the impact of IAR4D in the specific value chain contexts. Alignment to CGIAR Priorities : 5A: Improving science and technology policies and institutions; 5C: Improving rural institutions and their governance; 5D: Improving research and development options to reduce rural poverty and vulnerability;
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Alignment to CGIAR Priorities
Table 9 summarizes how the three subprojects that constitute the ZMM PLS project contribute to the CGIAR‘s system priorities. Table 9: CGIAR System Priorities Targeted by the ZMM PLS Project
MTP project outputs 1. Functioning innovation platforms created 2. Potential technological, market, policy and institutional innovations identified, developed and mechanisms for putting them into use analyzed 3. Lessons learned from the innovation platforms evaluated and documented CGIAR system priorities 5a, 5c, 5d 3a, 4c, 4d, 5b

5a, 5c, 5d

Description of Impact Pathway
The conditioning factors include (1) resource availability, skills levels, staff time and human and institutional capacity; (2) partnership commitment, NARS staff turnover, research facilities and vehicles, and NGOs investments; (3) favorable weather, macroeconomic conditions, transportation and communications systems, institutional structures, policy regimes and socioeconomic and political stability; and (4) political will and buy-in from strategic government decision-makers and political leaders. Some of these will be internalized in forming the Innovation Platforms. Given the conditioning factors, the research will generate impact through both direct and indirect pathways. The direct pathway involves members of the innovation platforms including representatives of farmers‘ organizations, NGOs, NARS extension organizations, agribusiness firms, and policy makers transforming the technological and institutional innovations into outcomes by carrying information to other stakeholders. This will result in uptake of technological and institutional innovations for sustainable intensification and diversification of staple cerealsgrain legumes and vegetable production systems. The indirect pathway comprises two paths: (i) by contributing to the impact pathway of the Meta-Analysis project since it (the MetaAnalysis project) draws on the data generated by the ZMM PLS project to produce its IPGs and create impact (ii) through the participating CGIAR research organizations, NARS research and extension organizations, NGOs, agribusiness organizations learning lessons and adopting IAR4D to improve the efficiency of staple food cereals-grain legumes value chains, thereby increasing impact through spillovers. This path also includes other voluntary organizations and NGOs more directly involved in development seeing the benefits of IAR4D, adopting and scaling out the approach, especially the elements concerning putting research into use.

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International Public Goods
The research approach to develop IPGs from the ZMM PLS project is similar to the approach for the KKM PLS project outlined in B2.5. Using an innovation systems approach, existing technologies will be screened and adapted and recommendations made for various farmer typologies. The IP will be leveraged as a key action research instrument for developing and testing policy, market and institutional innovations. Strategies for accelerating the putting of research outputs into use will also be investigated The principal IPGs that this project will generate include: (iii) a set of methods, (for setting up IPs, and their functionality, the framework for tracking and evaluating IPs, ―putting research into use‖) (iv) technological, institutional, policy and market innovations at the interface of productivity, sustainable natural resource management, markets and policies. Furthermore, data from this project along with data from other PLS project will be pooled by the Meta-Analysis project to generate the SSA CP‘s principal IPGs (see B1.5). In this way, this project will contribute to establishing proof of the IAR4D concept and the definition of guidelines for implementing IAR4D.

Elaboration of Partners Roles
Table 10 gives an overview of the various partners involved in the ZMM PLS project and their roles. Table 10: Partners and their Roles in the ZMM PLS Project
Partner type CGIAR Centers Name SOFECSA-CIMMYT, CIAT, Bioversity International, IFPRI, and AVRDC – World Vegetable Center Role Taskforce leadership, coordination, project management and reporting. Also contribute to methodology development, action research, data analysis and new knowledge, information and technology generation and evaluation Facilitate development of maize and other cereal and vegetable seed market and supply chains to improve target farmers‘ access to a range of context specific varieties (drought-, Low Ntolerant, OPVs, Hybrids, indigenous vegetables), technical backstopping on process research; communication and sharing of project outputs beyond the PLS; capacity SSA Challenge Program MTP 2010-12 37

Partner type

Name

Farmer organizations, farmer groups and community- based organizations

Malawi: National Farmers‘ Association of Malawi; Mozambique: FOS-Chitima; Zimbabwe: Zimbabwe Farmers‘ Union

Agricultural research organizations

Malawi: Department of Agricultural Research Services; Mozambique: Instituto de Investigação Agraria de Moçambique; Zimbabwe: Department of Agricultural Research for Development

Role building of partners in policy and institutional analysis, and monitoring, evaluation and impact assessment system Participatory experimentation with varieties and crop management practices, communication and information and knowledge management, farmer collective action, scaling out through peerto-peer adoption and spreading of innovations and influencing of policy and advocacy Adaptive trials, action research and learning; scaling-up/out technologies; systems analysis, training of NGOs and farmer groups; facilitation of information exchange. Organizing farmer participatory technology experimentation and learning, training; managing focal points of the national agricultural knowledge and information management. Adaptive trials, action research and learning; scaling-up/out technologies; training of stakeholders; facilitate market development, provide extension methodologies and guides. Scaling out and scaling up promising innovations and processes Adaptive trials, action research and learning; scaling-up/out technologies; training of stakeholders; facilitate market development and linking farmers to markets Translating integrated soil fertility management (ISFM) research and development research findings on mineral 38

Agricultural extension services

Malawi: Department of Agricultural Extension Mozambique: Department of Agricultural Extension Zimbabwe: Department of Agricultural Technical and Extension Services

NGOs

Malawi: World Vision and CARE International; Mozambique: Africare; Zimbabwe: DAPP.

Private agribusiness companies

Windmill (Pvt) Ltd (Fertilizer manufacturers); HASST (machinery manufacturers); Freshmark (Shoprite); Fresh Produce Section, People‘s supermarket

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Partner type

Name

Role fertilizer formulations and supply chain development into business plans; turning research ideas into experimental and new fertilizer products Market information, agroenterprise training and support, training of stakeholders; facilitate market development Capacity building (research students and higher-degree supervision, action research and learning and training of trainers‘ courses), adaptive research, and linking knowledge and information management among different stakeholders Provide mandate for policy coordination, implementation and support of public institutions for scaling out and scaling up innovations and good practices Brings complementary advanced skills and tools in database management and modeling necessary for capacity building and scaling up

Universities and agricultural institutes of higher learning

Malawi: Bunda College; Mozambique: University of Eduardo Mondlane; Zimbabwe: University of Zimbabwe.

Ministry government departments responsible for agriculture and policy planning

Malawi Agricultural Sector Investment Policy Planning Unit

ARI

University of Wageningen

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Logical Framework
Outputs Output 1 Innovation platforms introduced and functioning Intended Users Innovation platform members such as farmers, farmer organizations, input suppliers, traders, processors, agricultural research and extension agencies, credit institutions, NGOs, CBOs, Ministry of Agriculture, local government, etc. Outcome 1. Knowledge and information flows among IP members and between IP members and community improved; 2. Awareness among IP members and between IP members and communities about potential technological and institutional innovations increased; 3. Awareness about sustainable NRM among farmers increased; 4. Adoption of technological and institutional innovations by farmers, agribusiness and other players in the value chains increased; and 5. Efficiency along the targeted value chains increased... Target 2009: Practices Approaches for strengthening the innovation capacity of IPs documented Impact Improved food and nutrition security, increased household incomes, reduced poverty, and sustainable natural resource management.

Output 2

Potential technological, market, policy and institutional innovations

Farmers and other actors along the value chain.

1. Knowledge and information flows among IP members and between IP

Improved food and nutrition security, increased household incomes, 40

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Outputs identified, developed and mechanisms for putting them into use analyzed

Intended Users

Outcome members and community improved; 2. Awareness among IP members and between IP members and communities about potential technological and institutional innovations increased; 3. Awareness about sustainable NRM among farmers increased; 4. Adoption of technological and institutional innovations by farmers, agribusiness and other players in the value chains increased; and 5. Efficiency along the targeted value chains increased...

Impact reduced poverty, and sustainable natural resource management.

Target 2009: Policy strategies

At least 3 institutional innovations for targeting alternative NRM technologies and supporting agribusiness, post harvest storage and input/output support services developed; Mechanisms through which at least one technological or institutional innovations developed by each IP can be successfully ―put into use‖ identified and documented

Target 2010: Practices

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Outputs

Intended Users

Outcome

Impact

Output 3

Lessons learned from the innovation platforms evaluated and documented

Internal as an input into output 1 and 2 as well as the Meta-Analysis project.

1. Knowledge and information flows among IP members and between IP members and community improved; 2. Awareness among IP members and between IP members and communities about potential technological and institutional innovations increased; 3. Awareness about sustainable NRM among farmers increased; 4. Adoption of technological and institutional innovations by farmers, agribusiness and other players in the value chains increased; and 5. Efficiency along the targeted value chains increased...

Improved food and nutrition security, increased household incomes, reduced poverty, and sustainable natural resource management.

Target 2009: Practices

Lessons learned on setting up and sustaining the functioning of IPs documented Model for assessing the efficiency and benefits of IAR4D developed;

Target 2009: Practices

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SSA-04: Lake Kivu Pilot Learning Site
Project Overview and Rationale
The Lake Kivu pilot learning site (LKPLS) sits on the border region between Uganda, Rwanda and the DR Congo. It is a highland agro-ecological zone (AEZ) characterized by steep slopes, deep good volcanic soils and ample rainfall that offers good potential for agriculture growth. The area receives mean annual rainfall ranging between 900 to 2,200 mm and has medium to long length growing periods (180-270 days). The principal crops grown include food (sorghum, millet, potatoes, sweet potatoes, peas, maize, beans, bananas), some cash crops (tea, coffee) and other tree species for fruit and forestry products. Despite the apparent rich natural resource endowment, the LK region is considered one of the poorest and most densely populated areas of Africa, with densities ranging from 400 to 700 persons per km2. This has led to over-exploitation of the natural resource wealth. Over 90% of the population derives their livelihood from agriculture and other enterprises based on natural resources on less than 0.6 ha per family of six. Nearly 60% of the land area is intensively cultivated and poverty in the region is directly linked to the low and deteriorating productivity and profitability of these enterprises. The region has also experienced recurrent volatility of conflicts with sporadic conflict still continuing in some parts of DR Congo and climate change. Smallholder farming in the LKPLS is characterized by unsustainable agricultural practices including: (i) over cropping using inferior germplasm and very little or no inputs; (ii) poor control of diseases and pests; and (iii) poor management and husbandry of land. Steep slopes give rise to high runoff rates and severe soil erosion leading to limited benefits accruing from past and on-going NRM programs. Other forms of land degradation include off-site siltation and nutrient mining through crop removal, leaching, and runoff water. Agro-ecosystems and biological resources in the PLS are therefore rapidly degrading, largely due to mismanagement of steep cultivated slopes and wetland valleys, related in part to inadequacy of old methods to cope with the new food demands of a growing population. Deforestation, soil erosion, nutrient depletion, and flooding of valley bottoms are major processes of land degradation Assessment of the market linkages reveals that many households still do not produce enough for food security and income generation. This situation is exacerbated by limited entrepreneurial skills for adding value to staple commodities, and especially production and marketing of high value products. However, while often presented as a key development constraint, the high population presents a growing internal market for a number of products. The three countries offer a market of 50 million potential consumers, and can supply a large portion of the 150 million potential consumers in the eastern and central Africa region. Enhancing the ability of smallholder, resourcepoor farmers to access market opportunities, and diversify their links with markets is one of the most pressing development challenges in the PLS. Without well functioning markets, farmers have no incentives for investments in agriculture. The problem is that, until recently, most R&D approaches have largely focused on increasing productivity, but have largely neglected linking farmers to markets. Growing evidence and experience indicates that sustaining success in productivity growth as result of research will not lead to economic growth and wealth creation without expansion of market opportunities. Information is available to indicate that there are different strategies for improving market access in the Lake Kivu PLS (Table 11). What is lacking, however, is how to link productivity-enhancing research to market opportunities, and how to develop methods and approaches that effectively integrate productivity-enhancing research with marketing and agro-enterprise development.

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Table 11: Strategies for Diversifying Agro-Enterprises in the Lake Kivu PLS
Existing Markets Market Penetration Examples: potatoes, beans, banana, vegetables, maize, and sorghum Market development &expansion Examples: zero grazing, fish farming, soybean products, dairy products New Markets Product development Examples: honey, passion fruit, wheat, dairy products, soybean, grain, , chili, apple, banana Diversification into higher value crops Examples: temperate fruits, garlic, French beans, chili, ginger, cosmetics, medicines and handicrafts

Existing Products

New Products

Other constraints in the region include poor infrastructure, energy deficits, and lack of appropriate policies to govern the use of important common pool resources and weak extension and research systems to address the farmer‘s problems. There are also deficiencies in agriculture-related institutions, organizations and policies, and farmers receive limited support from research and development organizations. Besides these disincentives to innovate, the population has limited entrepreneurial skills for adding value to staple commodities, especially related to the production and marketing of high value products (and even of major staple crops such as bananas, potatoes and tree crops). The principal challenge in LKPLS is thus to contribute to improved food and nutrition security, increased household incomes and improved quality of the PLS natural resource base by applying Integrated Agricultural Research for Development (IAR4D) to develop, test and promote technological, institutional and policy innovations based on integrated watershed management concept. To overcome the challenges in the PLS, three subprojects by three taskforces were integrated into a single project around three complementary entry points. Instead of using conventional R&D approaches that look at productivity, sustainable natural resource management or efficient markets in isolation, more emphasis is placed on their linkages and interactions to create the desired impact across the landscape. The integrated project will address research questions at interfaces of productivity-sustainable NRM-efficient markets and policy, using robust analytical tools.

Outputs Description
Changes from Previous MTP Output 1: Innovation platforms introduced and functioning Description: This output is about developing methodologies and approaches for establishing functional innovation platforms. In the LKPLS 12 IPs will be established. The IP actors consist of the traditional and non-traditional partners. The actors broadly fall into 6 categories, namely: (1) farmers, (2) researchers, (3) extension agents, (4) middle-agents (agro-processors and traders), (5) policy makers, and (6) consumers. Stakeholder analyses will be used to identify relevant actors for IPs. Communication systems and institutional capacity support learning and sharing of knowledge among IP partners will ensure continuous information flow, knowledge sharing and creation. Alignment to CGIAR Priorities : 5A: Improving science and technology policies and institutions; 5C: Improving rural institutions and their governance; 5D: Improving research and development options to reduce rural poverty and vulnerability;
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Output 2: Potential technological, market, policy and institutional innovations identified, developed and mechanisms for putting them into use analyzed Description: This output will enable relevant members of the IP to generate and test technological and institutional innovations for tackling complex NRM-productivity –market-policy barriers to enhanced delivery of benefits to end users from R&D efforts. In the LKPLS there are vast opportunities for the rural poor to induce changes in the dynamics of poverty and asset accumulation while conserving the environment using the integrated watershed management approach. These broadly fall into four market-product domains, namely: (1) market penetration, (2) market development and expansion, (3) product development, and (4) diversification into higher value crops. The most relevant market-product domain for each of the 12 IP action sites will be determined and addressed by relevant combinations of taskforces. For example, in the market penetration domain, focus on existing key staples (e.g. beans and potatoes) may involve increase in market share through intensification of production and diversification of new products for different socio-ecological niches. The critical issue here is at the NRM-Productivity interface and engenders identification and testing of technological innovations that increase yields while at the same time conserving the natural resources (including reduction of C-footprint). This requires involvement of the relevant 2 taskforces (productivity enhancement and sustainable NRM) using robust trade-off and decision-support analytical tools to facilitate the processes of identification and testing of differentiated technical and institutional innovations at the interfaces. Alignment to CGIAR Priorities : 3B: Increasing income from livestock; 4A: Promoting integrated land, water and forest management at landscape level; 4D: Promoting sustainable agro-ecological intensification in low- and high-potential areas; 5B: Making international and domestic markets work for the poor; Output 3: Lesson learned with innovation platforms evaluated and documented Description: This output will clarify whether and how IAR4D works in terms of its ability to deliver benefits to end users and in a cost effective manner. The research also seeks to clarify the advantage of using IAR4D over other conventional participatory approaches. The central thesis of this research is that it is possible to speed up processes of innovation for pro-poor growth using an IAR4D approach in Africa. The acceleration of innovation will take place in such multistakeholder, heterogeneous contexts through structured learning processes around the principles and forms of organization of those stakeholders in response to changes in their contexts. The output will extract lessons (thus generating IPGs) from the process of action research into these IAR4D processes that are sufficiently robust as to warrant being termed as principles and guidelines for structuring such forms and processes of organization. Alignment to CGIAR Priorities : 5A: Improving science and technology policies and institutions; 5C: Improving rural institutions and their governance; 5D: Improving research and development options to reduce rural poverty and vulnerability;

Alignment to CGIAR Priorities
Table 12 summarizes how the three subprojects that constitute the MTP project contribute to the CGIAR system priorities. Table 12: CGIAR System Priorities Targeted by the Lake Kivu PLS Project
MTP project outputs 1. Functioning innovation platforms created CGIAR system priorities 5a, 5c, 5d

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MTP project outputs 2. Potential technological and institutional innovations identified, developed, tested and promoted 3. Experience with innovation platforms documented and evaluated

CGIAR system priorities 3b, 4a, 4d, 5b

5a, 5c, 5d

Description of Impact Pathway
The conditioning factors include (1) resource availability, skills levels, staff time and human and institutional capacity; (2) partnership commitment, NARS staff turnover, research facilities and vehicles, and NGOs investments; (3) favorable weather, macroeconomic conditions, transportation and communications systems, institutional structures, policy regimes and socioeconomic and political stability; and (4) political will and buy-in from strategic government decision-makers and political leaders. Some of these will be internalized in forming the Innovation Platforms. Some of these will be internalized in forming the Innovation Platforms. Given the conditioning factors, the research will generate impact through both direct and indirect pathways. The direct pathway involves members of the innovation platforms including representatives of farmers‘ organizations, NGOs, NARS extension organizations, agribusiness firms, and policy makers transforming the technological and institutional innovations into outcomes by carrying information to other stakeholders. This will result in uptake of technological and institutional innovations for sustainable intensification and diversification of staple cerealsgrain legumes and vegetable production systems. The indirect pathway comprises two paths: i. by contributing to the impact pathway of the Meta-Analysis project since it (the Meta-Analysis project) draws on the data generated by the Lake Kivu PLS project to produce its IPGs and create impact ii. Through the participating CGIAR research organizations, NARS research and extension organizations, NGOs, agribusiness organizations learning lessons and adopting IAR4D to improve the efficiency of staple food cereals-grain legumes value chains, thereby increasing impact through spillovers. This path also includes other voluntary organizations and NGOs more directly involved in development seeing the benefits of IAR4D, adopting and scaling out the approach, especially the elements concerning putting research into use.

International Public Goods
The research approach to develop IPGs from the Lake Kivu PLS project is similar to the approach for the KKM PLS project outlined in B2.5. Using an innovation systems approach, existing technologies will be screened and adapted and recommendations made for various farmer typologies. The IP will be leveraged as a key action research instrument for developing and testing policy, market and institutional innovations. Strategies for accelerating the putting of research outputs into use will also be investigated The principal IPGs that this project will generate include: (i) a set of methods, (for setting up IPs, and their functionality, the framework for tracking and evaluating IPs, ―putting research into use‖)
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(ii) technological, institutional, policy and market innovations at the interface of productivity, sustainable natural resource management, markets and policies. Furthermore, data from this project along with data from other PLS project will be pooled by the Meta-Analysis project to generate the SSA CP‘s principal IPGs (see B1.5). In this way, this project will contribute to establishing proof of the IAR4D concept and the definition of guidelines for implementing IAR4D.

Elaboration of Partners Roles
Table 13 gives an overview of the various partners involved in the Lake Kivu PLS project and their roles. Table 13: Partners and their Roles in the Lake Kivu PLS Project
Partner type Farmer Organizations Name FOPAC (DRC), Fédération Imbaraga (Rwanda), SYDIP (DRC), Uganda National Seed Potato Producers Role These will participate in value addition and marketing research activities. They will also be tasked with mobilizing their farmermembers to participate in designing, testing, adapting, verifying and transferring technologies. They will partly be responsible for identifying and evaluating market opportunities, selecting and developing agro-enterprise options; and experimenting with technology options to support their enterprises (innovation platforms). These will lead research into (1) crop/livestock interactions and production (2) farmer organization and training, (3) integrated watershed management. They will be responsible for training in IAR4D skills and management of multi-stakeholder processes in addition to information/technology dissemination. They will provide overall co-ordination of project activities at the country level. They will lead value addition and human nutrition. They will provide supervision for graduate student research and provide scientific and technical support in modeling. They will actively participate in policy reviews and reforms to support the relevant technical and institutional innovations including byelaws. They will also participate in scaling up project innovations.

NARS

NARO, INERA, ISAR

Universities

Government ministries

Makerere University, National University of Rwanda, Wageningen University Rural Sector Support Project, Rwanda; NAADS and the local Government of Kabale, Uganda CIAT, ICIPE, IFPRI, IWMI, and ICRISAT.

IARCs

Private Sector

NGOs

Urwibutso Entreprise, Pharmakina s.c.a.r.l.; Huntex Industries (Uganda), Mecrego (DRC) Platform Diobass, SYDIP, BAIR, CAREUganda, IGCP, HPIRwanda

They will drive the science and development of regional and international public goods, will be responsible for providing expertise to support innovations scaling-up/out. Will be responsible for facilitation of the Learning Alliance. These will participate in value addition and marketing research activities. They will facilitate access to domestic, regional and international markets. They will also provide advisory and mentoring services on entrepreneurship, support technology development and input supply. These will play leading roles in information dissemination and scaling up and out of the technologies. They will also help in selecting, managing and running of the innovation platforms sites. Will be responsible for managing social processes and strengthening local innovation systems that enable rural communities to benefit from the technologies and market opportunities MTP 2010-12 47

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Partner type Networks

Name AHI, ECABREN, ECAPAPA

Role Will be responsible for alliance and network building, monitoring and evaluation as well as knowledge management and capacity building

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Logical Framework
Outputs Output 1 Innovation platforms introduced and functioning Intended Users Innovation platform members such as farmers, farmer organizations, input suppliers, traders, processors, agricultural research and extension agencies, credit institutions, NGOs, CBOs, Government Departments, local government, etc Researchers in national and international institutions Advisory service provider Outcome 1. Knowledge and information sharing among IP members improved; 2. Awareness among IP members about potential technical and institutional innovations increased; 3. Awareness among IP members about potential market opportunities increased; 4. Awareness of IP members about sustainable NRM increased; 5. Access of farmers to quality inputs improved; and 6. Technological and institutional innovations adopted by farmers and other stakeholders in the production chain. Target 2009: Practices Approaches for strengthening the innovation capacity of IPs documented Impact Improved food and nutrition security, increased household incomes, reduced poverty, and sustainable natural resource management.

Output 2

Potential technological, market, policy and institutional innovations

Farmers and other actors along the value chain.

1. Knowledge and information sharing among IP members improved;

Improved food and nutrition security, increased household incomes, 49

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Outputs identified, developed and mechanisms for putting them into use analyzed

Intended Users

Outcome 2. Awareness among IP members about potential technical and institutional innovations increased; 3. Awareness among IP members about potential market opportunities increased; 4. Awareness of IP members about sustainable NRM increased; 5. Access of farmers to quality inputs improved; and 6. Technological and institutional innovations adopted by farmers and other stakeholders in the production chain.

Impact reduced poverty, and sustainable natural resource management.

Target 2009: Policy strategies

Strategies for policy dialogue for linking production-markets-NRM developed At least 2 best-bet options for sustainable intensification and diversification of NRMProductivity-Markets-Policy interfaces identified and tested. The mechanisms through which at least one technological or institutional MTP 2010-12 50

Target 2009: Practices

Target 2010: Practices

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Outputs innovations developed by each IP can be successfully ―put into use‖ identified and documented

Intended Users

Outcome

Impact

Output 3

Lesson learned with innovation platforms evaluated and documented Model for assessing the efficiency and benefits of IAR4D developed;

Target 2009: Practices

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Annexes
Implementation of EPMR/CPER Recommendations
Dates of External Evaluation Report Presentation and Discussion: (a) Science Council: 11-13 September 2006; (b) Executive Council: 17-18 October 2006; and (c) CGIAR Annual General Meeting: 6-7 December 2006.

Recommendation As listed in the EPMR report

Center’s Response Accepted or not accepted

Implementation

Milestones 1. Program 1a. The SSA-CP should be allowed to continue for a three-year period during which the proof of the IAR4D concept will be established, appropriate lessons learnt, and IPGs shared. This implementation phase should occur only at the current three PLSs, and adequate funding channeled to allow this continuation in a manner that avoids the possibility of fatigue and fragmentation of the newly formed and still delicate partnerships. Accepted Research design for IAR4D proof of concept elaborated (including metaanalysis) Medium Term Plans (where the CP‘s outputs and financing plans are presented)

Progress Achieved Research design elaborated and approved by the SSA CP governance body. The first MTP (2008-10) was submitted in June 2007. The SC commentary on this MTP recommended revision of the research design. Revision of the research design was completed in December 2007 and is summarized in the 2009-10 MTP. A framework for capturing and synthesizing lessons has been developed as part of the M&E frame. None yet. Progress to be registered on this milestone after at least one year of research (July 2009 onwards) None yet. Activities for this milestone to start towards end of the current research

Target Date of Completion March 2008

In June of every year up to the final year of the current CP phase

December 2010

Synthesis of lessons learned documented

December 2010

IPGs from SSA CP research shared 1b. At the end of the three years, the SC should commission another Accepted Preparations for the next external review by the SC in place

December 2010

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review to determine whether the IAR4D concept works and can generate deliverable IPGs/RPGs, and whether the SSA CP should merit continued endorsement by the SC and CGIAR. Establishment of an exit strategy is necessary to determine future funding options. Once valuable lessons are learnt and the IAR4D concept proven, additional sites then can be logically added and scalingup and out done. 1c. The SSA CP PCU must now give serious attention to defining and consolidating key priority PLS projects so they can help provide proof that the IAR4D concept works. The PCU should review currently selected PLS projects and allow them to be integrated and consolidated to ensure they adequately address critical linkages between productivity, market, policy and natural resource management issues. Each PLT should provide joint project proposals that show specific and realistic outputs have ways to test the IAR4D approach and include adequate M&E measurements. Traditional ex-ante M&E profiles may Accepted

phase. SSA CP Exit Strategy in place Discussion on the exit strategy initiated during revision of the research design. None yet. Activities for this milestone to start towards the end of the current research phase. June 2009

Proposal for phase II including strategy for expansion to additional sites

December 2010

Revised PLS project proposals aimed at providing a proof of the IAR4D concept basing on research that addresses the interfaces of productivity, market, policy and natural resource management developed. A summary of these proposals will be presented in the CP‘s MTPs. Missing skills in IPs and project teams identified.

PLS project proposals revised to align them to the research design.

March 2008

Stakeholder analysis has been conducted to identify skill gaps in project teams. Similar gaps for IPs will be identified after the IPs have been established. The expertise required to conduct cross-site analysis was identified during the revision of the CP‘s research design (December

March 2008 for project teams; June 2008 for IPs

The expertise required to conduct the cross-site analysis defined.

December 2007

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not be applicable in the innovation platforms. If necessary, missing skills and expertise should be co-opted or commissioned from among ARIs and other institutions. But this outsourcing must be weighed against resource availability and utilization efficiency.

2007) A cross-site research support team (CRST), postdoctoral fellows engaged to bridge skills gaps. The composition of the CRST is expected to change with the changing skill requirements of the CP as its implementation progresses. The initial cross site research support team has been assembled. The team is drawn from CG centers and ARIs. The first group of postdoctoral fellows has been recruited. December 2007

April 2008 for first group of postdoctoral fellows August 2008 for second group of postdoctoral fellows

1d. Gained knowledge and experience from implementing the inception phase, including preparing a joint MTP, must be well documented and shared amongst partners and collaborators. Such knowledge should be reviewed to determine whether it constitutes IPGs/RPGs, and an effective method used to disseminate the same.

Accepted

Synthesis of lessons learned during the inception phase documented Lessons learned during the inception phase disseminated.

A draft report on lessons learned during the inception phase is in place. Three papers on lessons gained during inception phase published. Packaging on the report on lessons learned by the SSA CP during the inception phase is ongoing. It will be mainly disseminated through the FARA website, via email, and the FARA General Assembly.

December 2007

December 2008

1e. Capacity building is critical to effective implementation of the SSA-CP mandate. Once specific PLS projects are formulated, the PCU must work with its collaborators to determine the specific skills required and skill sources that need to be approached in order to enhance the capacity of various stakeholders to effectively

Accepted

SSA CP stakeholders (taskforces, lead institutions and management committees) trained in IAR4D—the principles and their application.

Several knowledge leveling and training events have been undertaken to bring all SSA CP stakeholders on the same page with regard to their understanding of IAR4D. These events include: IAR4D methodology review workshop organized at the FARA secretariat in September 2006 IAR4D training workshops

December 2006

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implement their projects in a timely and efficient manner. Sourcing of such skills must not be random, and sometimes may be embedded within members of the various committees. Revealed inconsistencies among various stakeholders on what constitutes an ―innovation platform‖ should be dealt with and a more practical approach used to bring everyone on the same page to avoid further confusion.

conducted for all three PLS: ZMM in November 2006; Lake Kivu in December 2006; and KKM in January 2007. Taskforce teams and PLS coordinators have all been acquainted with requirements of the revised research design through workshops. ZMM PLS in November 2007; Lake Kivu PLS in December 2007; and KKM PLS also in December 2007. Taskforce teams have also been trained on developing indicators and tracking them throughout the lifetime of the CP (February – March 2008) Taskforce teams have been trained on integrating their data at PLS and program levels to facilitate analysis at these two levels (February – March 2008) Training is organized to respond to identified skill gaps as the program progresses

SSA CP research stakeholders equipped with lacking skills necessary to implement the proof of IAR4D concept research.

Ongoing until June 2010

Also see responses to recommendation 1b for additional milestones and progress to date on securing missing skills.

1f. A Competitive Grant System was used to select concept notes that led to development of the current approved PLS projects. This system has its limitation,

Accepted

Report on lessons learned from the SSA CP CGS process in place

A paper reporting lessons learned from the SSA CP CGS process prepared and presented at Tropag 2007. See recommendation 1d

December 2007

Capacity of taskforce research MTP 2010-12

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especially within the IAR4D approach which emphasizes co-operation and team building. According to the SSA-CP, ―the competitive grants process highlighted important lessons where IAR4D elements have either not been internalized by PLTs or are poorly understood, namely organizational and institutional change, capacity building, knowledge management, M/E, log-frames and project impacts on the environment and on gender. It was also clear from this exercise that the IARC-led proposals were far stronger than the NARS-led ones highlighting the need for change involving awareness raising capacity building‖. This being the case, the review team recommends that future concept notes and project proposals be sought using a combination of CGS and commissioned research that allows for synergistic cooperation among bidders and a more consolidated project proposal that addresses all the valid issues. The CGS alone might be detrimental to the desired partnership building needed for the SSA-CP development 1g. The SSA-CP should critically Accepted

actors enhanced so they attain same level of understanding about IAR4D concepts and principles Gaps in PLS project formulation attributed to the CGS process bridged including establishment of a cross-site research support team Draft strategy for formulating projects and identifying their implementers in Phase II of the SSA CP in place

(knowledge leveling and training events organized)

The revision of projects (see recommendation 1b) eliminated gaps in their formulation which were created by the CGS.

March 2008

None yet. Activities leading to achievement of this milestone will commence in the final year of the current phase

December 2010

Articulation of the comparative MTP 2010-12

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identify its comparative advantage and strategic role vis-àvis other stakeholders in the agricultural research and development process. This will allow a clear formulation of activities that complement rather than duplicate existing research activities. According to the MTP, the SSA-CP strategy would be to work at the interfaces of productivity, markets, policy and natural resource management issues, and be a leader, facilitator, advocate, capacity builder and knowledge synthesizer on these dynamic issues. To be effective in these roles, the SSA-CP must be empowered to be flexible, network with others and respond promptly to new opportunities and cutting-edge issues

advantage and strategic role of the SSA CP in relation to other ARD actors.

elaborated in the research design and MTP 2008-10. Comparative advantage of FARA to coordinate the SSA CP also articulated in the same MTP. The SSA CP project proposals have been formulated to focus the action research on the interfaces among productivity with markets, policy and natural resource management. The IPs are the mechanisms through which research priorities on the interfaces above will be identified and progress continuously reviewed The innovation platforms and the SSA CP‘s M&E framework are designed to facilitate adaptation of the SSA CP‘s research plan to enable the CP respond to problems and opportunities that will emerge after commencement of its research Concept note for developing the white paper has been prepared. A search for experts that will be commissioned to conduct the exercise is underway FARA has reviewed

Ensure that the SSA CP‘s action research is targeted on the interfaces among productivity with markets, policy and natural resource management.

March 2008

36 IPs established

June 2008

Flexibility built into the design of the SSA CP‘s research

December 2007

A white paper on IAR4D developed as an advocacy tool aimed at stimulate debate on IAR4D among policy makers and scientists 2. Governance Not Accepted Governance and MTP 2010-12

December 2008

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2a. The direct management role, including staff and routine management issues, of the SSA CP should be gradually devolved to the SSA CP Coordinator, who must work in consultation with the FARA Secretariat. This will relieve the FARA Secretariat of the implementation burden so that it can carry out the oversight role envisaged in Article 5.0 of the FARA Constitution. Further, it is suggested that the Program Steering Committee (PSC) be renamed the Program Advisory Committee (PAC), since the steering role is mostly the function of the SSA CP leadership and FARA.

management of the SSA CP reviewed

the governance and management structure of the SSA CP in order to increase its efficiency and effectiveness and to cut transaction costs. The review recommended: (i) Phasing out of the PLS lead institutions and management committees by transferring their functions to relevant SRO structures; and (ii) Dissolving the PSC and transferring its functions to the Program subcommittee of FARA‘s Executive Board. The latter will be reinforced with at least two experts to serve as technical advisors for the SSA CP. Recommendations concerning the PLS management committees and the PSC have been fully implemented. Implementation of recommendations concerning PLS lead institutions is ongoing The CRST has been established. Its composition will vary depending on the gaps that will emerge as implementation of the program progresses.

Recommendations of the governance and management of the SSA CP implemented. 2b. The SSA CP PCU must be given more authority to steer the direction in which programs at the PLSs evolve. To this end, the PCU should develop a more efficient and interactive communication system between the various teams, taskforces, and management committees. This will improve performance, Partially Accepted Establish a crosssite research support team (CRST) as a mechanism for assuring coherency among projects and facilitating their integration.

December 2008

December 2007

Develop and implement a communication strategy.

The SSA CP‘s communication strategy is now in place. It is expected that as implementation of

December 2007 for development of the initial strategy Implementation to 58

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monitoring and decision-making, and reduce transaction costs throughout the CP. In addition, the PCU should have discretionary funds to consolidate different PLS projects so that these, where deemed necessary, can provide proof of the IAR4D concept and context. 3. Partnership 3a. The SSA-CP has invested great resources to establish a diverse group of stakeholders and to energize their participation in the CP. But there remains a great institutional and disciplinary imbalance. Most current participants are from research institutions, particularly IARCs and NARS. This should not be allowed to skew research and project interests. The SSA CP must reach out to representatives from the private sector (PS), civil society (CS) and farmer association (FA), and engage them at project identification and prioritization stage. Clearly, the success of scaling out and up is nested with these stakeholders. Current links, particularly with PS, CS and FA, are weak. The SSA CP may benefit from expertise of Accepted Achieve a more balanced representation of non-research CP actors (farmers, NGOs and private sector players) in the SSA CP‘s research partnerships.

the program progresses and its communication demands become clearer this strategy will require to be continuously updated.

commence immediately

Stakeholder analysis conducted by taskforces identified gaps in representation and action has been taken to address the weak representation of non-research actors. However sufficient involvement of the private sector remains a challenge. Strategies for attracting private sector participation have become part of the research. Taskforce planning and research implementation has ensured adequate participation of all groups pf actors. Innovation platforms are designed to ensure adequate participation of all ARD actors and genders in defining priorities and reviewing progress. Gender balance has been adopted as a cross-cutting consideration for all the SSA CP activities. FARA is

March 2008

Adequately involve the non-research CP actors at relevant stages of project planning and implementation

Ongoing up to end of the current phase of the CP.

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someone who understands Africa‘s and multinational PS, CS and FA, including their entry, participation requirements, expectations and incentives. In addition, more gender balance is needed within the CP. Many agricultural projects have failed in the past because of such gender insensitivity 3b. A lucrative and untapped source of new skills, opportunities and innovations is Africans in the Diaspora. Many of these are well linked to public, private, civil and international institutions in developed countries, and provide new avenues of funds, technology and information to stimulate productivity growth in Africa. The SSA CP should explore these linkages and start by commissioning a survey of Diaspora resources available ―out there‖ that can be harnessed for ―business unusual‖ investments in Africa. In effect the SSA CP could create an innovative reversal of what has been termed as Brain Drain for Africa to Brain Gain. 4. Clarity from the Science Council/CGIAR Accepted

At least 30% increase in the participation of women in all aspects of the SSA CP‘s research.

implementing a gender mainstreaming initiative that will benefit all its programs including the SSA CP

June 2008

Diaspora resources mobilized to support implementation of the SSA CP‘s research

The development of a strategy for mobilizing diaspora resources to support the implementation of the SSA CP‘s research has been initiated in consultation with the Initiative to end poverty and hunger. Contacts have been initiated with leaders of diaspora groups in Europe. This work is ongoing.

December 2009

Accepted

SC to clarify its expectations to FARA. MTP 2010-12

SC articulated its expectations of the SSA CP‘s research

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The SC should work closely with the SSA-CP leadership to clarify its expectations of the program. Further, the Panel suggests that proof that the IAR4D approach works and will deliver research outputs effectively to the African farmer and business community, and the shared knowledge from this experience, be considered as an IPG. Subsequent delivery of RPGs and NPGs will be desirable additional outcomes

to FARA and recommended resource persons to assist the SSA CP in developing a research plan Research plan emphasizing proof of the IAR4D concept already in place.

A research plan focusing on proof of IAR4D

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Annex 1: IAR4D Proof of Concept Research Methodology
1. Evaluation Design In order to test the three hypotheses above in a statistically robust fashion and empirically determine whether IAR4D works and whether it delivers more benefits than conventional approaches, a multiple treatments experimental design is proposed. This design compares household and community level outcomes under: (i) IAR4D; (ii) the conventional approach; and (iii) no intervention. In other words, the SSA CP experiment will comprise three treatments carried out in three blocks (the three pilot learning sites) and nine repetitions (three per block— the taskforces). The evaluation entailed in the proof of the IAR4D concept is designed to compare outcomes under IAR4D and under two other possible states, namely: the conventional approach and under nonintervention. Only one of these three possible states gets realized in any given site. The realized state will then be the factual and the unrealized ones the counterfactuals. Thus, the evaluation design will involve a set of three states where is the non-intervention state consisting of having neither IAR4D nor the conventional approach in operation, is the state consisting of having the conventional approach in operation, and is the state consisting of having IAR4D in operation. The effectiveness and impact of IAR4D will be assessed throughout the impact pathway from the IP to the community and to the farmer. The hypothesis about whether IAR4D works will be tested by comparing the values of relevant knowledge, behavioral, efficiency, welfare, equity and environmental outcomes under and under . Similarly, the hypothesis about whether IAR4D delivers more benefits than the conventional approach will be tested by comparing the values of relevant knowledge, behavioral, efficiency, welfare, equity and environmental outcomes under and under . The ―with‖ and ―without‖ IAR4D comparison will be made by comparing the values of the same outcomes as above under and under the composite possible state ― or ‖. 2. Characterization of Treatment and Counterfactual Sites The SSA CP research design proposes to allocate research sites (districts/communes/ local government areas) to IAR4D and non-IAR4D treatments through stratified random sampling. The strata within which the randomization is to be carried out consist of four development domains delineating the combination of market access potential and agro-climatic potential (see table in Figure 1). Each IAR4D treatment site (district/commune/ local government area) is associated with a corresponding counterfactual site also randomly selected from the same stratum as the IAR4D site (for example, see Figure 1). Taskforces will spread IAR4D treatment sites across various strata in order to investigate the performance of the approach across a wide range of conditions.

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Figure 5: Illustration of stratification of a PLS by four development domains IAR4D will be introduced in ―clean‖ villages within the IAR4D sites. The SSA CP‘s hypotheses will be tested by comparing outcomes realized by households within the IAR4D, ―clean‖ villages against outcomes realized by households within conventional ARD villages. The treatment communities consist of IPs and farm households in areas where IAR4D is practiced. The non-treatment communities consist of similar organizations and households in other sites— the non-IAR4D sites. The district/local government area/commune level was adopted as the scale at which the hypothesis testing will be carried out based on the presumption that the innovation process is best organized at this level since it is the lowest level at which a critical mass of IP actors is clustered. 4. Sampling Method and Sample Sizes The SSA CP proposes to employ multistage stratified random sampling within the selected districts (IAR4D and counterfactual) to select the villages where IAR4D will be introduced, study village communities where conventional approaches are in operation, and study villages where no agricultural interventions have been carried out over the last 2-5 years (see Figure 2). Each taskforce will establish four separate IPs. Each IP will be associated with the two counterfactuals described above.

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The program further proposes to use the Miguel and Kremer (2004) methodology of randomizing treatments across schools (districts and village communities) and not individual farm households because this method captures spillovers and externalities benefits that would be underestimated if a treatment is only randomized at the individual level. At least 5 focal villages will be randomly selected from each IAR4D district. These villages will become the theatres for action research aimed at developing innovations on interface between productivity, care of the environment, policies and markets. Within the focal IAR4D village communities, at least 10 households per village will be randomly selected for monitoring and evaluation. For each ―clean‖ counterfactual site matching an IAR4D site, 5 focal villages will be randomly selected. Similarly, 5 focal villages will be randomly sampled from each conventional approach site matching an IAR4D site. In each of the selected villages (clean or conventional approach), 10 households will be will be randomly selected for monitoring and impact evaluation. 5. Sample sizes at Taskforce, PLS and SSA CP scales Sample size for taskforces: Each taskforce will establish 4 IPs and conduct its research in 4x15=60 villages and 4x15x10=600 households. Sample size for PLS projects and SSA CP: Since the research in each PLS is carried out by three taskforces, the PLS sample size is triple the sample size of the taskforces, that is, 3x4=12 IPs, 3x60=180 villages and 3x600=1,800 households. And since the program comprises three PLS projects, its sample size is three times the PLS project size, that is, 3x12=36 IPs, 3x180=540 villages, and 3x1,800=5,400 households. The latter consists of 1,800 IAR4D, 1,800 conventional ARD, and 1,800 non-treated (i.e., non-IAR4D & non-conventional ARD treatment) households.
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The sample sizes at the four scales (IP, taskforce, PLS and program) are summarized in table 1. Table 14 Sample sizes at IP, taskforce, PLS and program scales
No. of IPs IP Taskforce PLS SSA CP 1 4 12 36 No. of IAR4D villages 5 20 60 180 No of conventional ARD villages 5 20 60 180 No. of non-treated villages 5 20 60 180 Total number of households 150 600 1800 5400

The site-to-site variation of IAR4D treatment effects is evaluated by pooling observations and results across the taskforces using meta-modeling (see Figure 3). Similarly, the effect of IAR4D across the nine program sites and the assessment of its replicability will be evaluated by pooling and integrating observations from all the nine program sites. The pooling of data at PLS and program levels is respectively carried out by PLS lead institutions and the cross-site research support (CRST). The CRST comprises a team of experts largely drawn from CGIAR centers and advanced research institutes that the program has engaged to provide backstopping in implementing the research and to conduct, jointly with the taskforces and lead institutions, the cross site analysis and comparisons.

Figure 7: The levels at which SSA CP data will be collected and pooled. 6. Testing the Research Hypotheses Joint hypothesis testing will be carried to evaluate whether or not IAR4D works, that is, whether IPs with hypothesized characteristics can be established and sustained and by comparing the outcomes traceable to IAR4D with corresponding indicators at the counterfactual sites. Testing the first hypothesis The first hypothesis states that: ―If an innovation platform is created and is functional with the 5 components characterizing IAR4D then it will lead to increased interactions and better outcomes among partners in the IP compared to where there is no IP and among farm households in communities where IAR4D is in operation compared to communities where IAR4D is not in
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operation‖. This hypothesis will be tested at the first level of analysis by analyzing if implementation of IAR4D results in:     non-linear collaborative interaction among IP actors; research plans to address key constraints and opportunities agreed by the IP in the context of entire value chains; multidisciplinary and participatory research; and skills to effectively participate in innovation processes.

And whether this in turn leads to the following outcomes for the IPs, communities, and households:       increased sharing of knowledge among IP members and communities; number and composition of disciplines involved in the research; level of congruence between research conducted and constraints and opportunities identified by the IP; congruence between the training conducted and the needs identified; innovations on interfaces of processes driving productivity, efficient use of resources, care of environment, policies and markets, and behavioral change including adoption of the innovations indicated above.

Testing the second hypothesis The second hypothesis states that ―IAR4D delivers more benefits to end users compared to conventional approaches (if the conventional ARD approaches have access to the same resources)‖. It will be tested by comparing outcomes of the three treatments (IAR4D, conventional, and nonIAR4D-non-conventional). The comparison will use established and emerging methods for comparing treatment outcomes. It will control for the costs of delivering services under IAR4D and conventional approaches. Because there may not be enough cost/benefit data per approach, the hypothesis testing will also use cost/benefit per farmer reached or served in the community or cost/benefit per farmer who benefits from IAR4D, say, through adoption of IAR4D-derived innovations. Testing the third hypothesis The third hypothesis states that ―If the design and estimation shows that IAR4D works in different contexts then it can be extrapolated outside its test environments.‖ It will be tested by implementing the frameworks developed by Heckman (2005) and Dehejia (2003). Heckman (2005) posits that using structural models permits interpretability in terms of theory and recognition of missing variables (unobservables), which provides the basis for forecasting the impacts of interventions implemented in one environment, to other environments, including their impact in terms of welfare. Structural models of how treatment effects differ by households, village community and area will be developed using the results on how impacts vary along these dimensions. These models will be applied to forecast the effects of IAR4D in new contexts. The data to be collected will include household, farming community and area characteristics that can be used with the conditional independence assumption to do matching and to identify structural models for extrapolation. The structural models will be complemented by the following methods:  hierarchical modeling (Dehejia, 2003);
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 

linear parameterization models for extrapolating and generalizing the observed effects of IAR4D to larger contexts; and synthetic control matching (Abadie, 2007).

Testing this hypothesis will also entail an analysis of adoption and diffusion of IAR4D by organizations more directly involved in development, including national research and extension programs, farmers‘ organizations, NGOs and agribusiness firms. The SSA CP will conduct surveys to identify organizations taking up IAR4D interventions, and to establish the organizational determinants and constraints to the adoption of IAR4D. 7. Data Required to Test the Hypotheses The data required to test the three hypotheses is derived from indicators of the impacts, outcomes and outputs expected from the program‘s research. A benchmark of pre-treatment characteristics of innovation platforms as well as site, community and household characteristics in the research sites is to be established upon commencement of the research. This data is being collected through baseline surveys, field observations and focus group discussions. It includes:         IP, site (at district and village level), community and household characteristics; Innovation process characteristics (level of interaction, information and technology diffusion and innovation spillovers); number of endogenously developed innovations, their variety, the time taken to develop them, and costs; knowledge and behavioral outcomes (adoption, input supply, input demand, volume of sales); market outcomes (output supply and consumption demand); productivity outcomes (yields, technical and allocative efficiency, and profit); environmental and welfare outcomes; and community and household impacts (incomes, livelihood assets and equity).

After the benchmarking, follow-up evaluation surveys and qualitative assessments will be conducted to measure changes in outcomes at the levels of the IP, household, community, and market. These surveys will also assess the participants‘ subjective reactions to IAR4D and identify subgroups experiencing a greater or lesser impact than the sample as a whole. 8. Data Analysis Methods and Issues The data analysis entailed in testing the hypothesis will involve both quantitative and qualitative methods. 8.1 Quantitative Analysis The fundamental evaluation problem in estimating the effects of the IAR4D approach is the attribution problem and constructing counterfactuals. It may be recalled that the counterfactuals, i.e. what would have happened to participants and non-participants without the program, are never observed. In Figure 7, A and D and B and E can be observed but not C and F. The challenge lies in estimating B-C in the absence of measurements for C. An assumption often made is that E=F, that is, there is no self-selection among program participants, scale effects, and spillovers. Potential spillovers and scale effects determine selection of ―with and without‖ program analytical approaches. The estimation methods the SSA CP proposes to use in estimating the effects of IAR4D are outlined below followed by a brief description of the circumstances under which each method will be used.
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  

   

Longitudinal comparisons of participants‘ outcomes (B-A), that is the ―before and after treatment; Cross-sectional comparisons of participants‘ outcomes versus those realised by the nonparticipants (B-E); Social experiments (B-E, with A=D and C=F); i.e. random assignment assures treatment households participating in the program and non-treatment households are statistically equivalent. The key assumption here is: E=F, that is, there are no effects of the program on non-participants; Difference-in-differences estimator ((B-E)-(A-D)), which accounts for fixed differences between outcomes of participants and non-participants; Matching (B-E|A(X)=D(X)); i.e., compare outcomes of participants and non-participants who are similar in observed characteristics; Econometric methods (B-E|X), which account for impacts of observable and unobservable confounding factors (X) on outcomes; and Combinations of the above (e.g., difference-in-difference with econometrics: (B-E|X1)(A-D|X0)).

Longitudinal comparisons of participants‘ outcomes will be used to impute missing counterfactual outcomes for participants and to complement estimates derived using other methods. The SSA CP recognizes that longitudinal comparisons are likely to produce biased estimates of treatment effects because they do not separate such effects from possible confounding factors (A≠C) such as bad or good weather, prices of crops, and long-term trends. Cross-sectional comparisons of participating and non-participating households can improve attribution to treatments since they involve using data on a comparison group of non-participants to impute the counterfactual outcomes for participants. This estimator has the added advantage of demanding minimal data. However, its estimates are also likely to be biased if participants and non-participants are very different (presence of selection bias, e.g. poor and rich households) because the estimated cross-sectional differences will not be only due to the program (A≠D, E≠C). Thus estimates from cross-sectional comparisons will be used to complement estimates derived using other methods. Social experiment methods overcome selection bias by randomizing placement so that all
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observational units within a defined set have the same probability ex-ante of receiving the treatment. If the treatment assignment is random and there is full compliance, i.e. focal villages in IAR4D sites cannot reject treatment and focal villages in control approach and non-IAR4Dnonconventional site cannot implement IAR4D, then the assessment of the effect of IAR4D on outcomes such as yield at the household level can be done by taking the difference in means. Random assignment ensures that observed and unobserved characteristics of treatment and nontreatment households have the same distribution i.e. A = D and C=F. Statistically B-C=E-F=F-C. Thus it resolves the problem of purposive placement based on unobserved factors. The assumption of no spillover and scale effects is very important for social experiments: large spillovers invalidate the purpose of counterfactuals. The randomized design proposed for this study seeks to minimize the spillover problem by assigning the IAR4D treatment at the district/local government areas/communes level instead of individual treatment (using control village communities at sufficient distance from treatment village communities). However, randomized social experiments can alter the way the program works in practice, institutional and political factors may delay randomized assignment and randomization only yields mean outcomes for the counterfactuals rather than distribution of outcomes and gainers and losers. The difference-in-differences estimator nets out pre-project differences between participants and non-participants such as initial differences in wealth, from the final difference. This measures the pure effect of the program ((B-E)-(A-D)). The approach can be generalized to multiple periods. The double difference method has the advantage that it removes selection bias if the effects of selection bias are additive and time invariant and outcomes are not affected by expectations of participation. Therefore the method can be used even if purposive sampling is employed to select households. But double differencing has several shortcomings, namely selection bias that may not be time invariant such as differential growth rates due to different initial endowments; and sensitivity to data quality since measurement errors are more serious in comparing changes in variables than comparing levels. Propensity score matching methods involve identifying a sample of comparator non-participants that are as similar as possible to participants in their predicted likelihood of participation and then comparing mean outcomes. For example baseline data can be used to select participants and nonparticipants who are similar in observed characteristics and to compare differences across space or over time. The strengths of the approach are reduced dependence on parametric assumptions and reduced bias from comparing non-comparable observations. The weaknesses are that: selection is based on observables only and selection bias resulting from unobservables may still remain; reliance on the parametric model to predict participation; heavy reliance on extent and quality of data to predict participation; and difficulties in finding comparable non-participants, which in turn results in sample truncation. Other weaknesses with the approach are that it requires a larger baseline survey since non-comparable participating and non-participating households are dropped which therefore affects the population upon whom the assessment of impacts is based. Econometric methods account for predictive effects of other factors, that is, the impact of observable and unobservable confounding factors (X) on outcomes across individuals or over time. Consequently, they are often used in studies of impacts. Econometric modeling has the advantage that it can control for selection biases by accounting for observable differences between program participants and non-participants (―selection on observables‖ and ―selection on unobservables‖). However econometric approaches suffer from several problems, such as:    parametric approaches depend on valid parametric assumptions; non-parametric approaches rely on large sample size and good data; identification of suitable instrumental variables (IVs) is often difficult;

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 

estimation based on instrumental variables only evaluates impacts due to variation in IVs; and biases may result from comparing non-comparable observations.

Recent advances in the field of econometric modeling aimed specifically at evaluating treatment effects (e.g., Heckman (2005)), have generated very valuable approaches for analyzing evaluation problems akin to the one presented by proof the IAR4D concept. Since no single evaluation method can claim to be ideal in all circumstances, different combinations of quantitative approaches will be used to improve the robustness of evaluation, including:     Multiple methods will be used to increase confidence in conclusions, since each method has different strengths and weaknesses; Econometrics or propensity score matching will be used with double-difference estimator to limit or account for effects of pre-project differences between participants and nonparticipants; Econometrics will be used with social experiments to address potential biases caused by selective participation; and Propensity score matching will be combined with econometrics to limit sample analyzed econometrically to comparable units.

8.2 Qualitative assessment approaches While the quantitative methods address the question of what is the impact, their qualitative counterparts address the question of why and how impact is or is not being achieved. The two methods therefore reinforce each other. Qualitative assessments enable better understanding of program theory and context which provides knowledge on what is working well and not, thereby making the overall evaluation more relevant to decision makers. By improving understanding about IAR4D processes qualitative assessments provide valuable insights about how to manage selection issues and the identification of instrumental variables for the econometric modeling. Further, these assessments provide tools for establishing how to apply lessons learnt elsewhere and therefore resolve external validity. The SSA CP proposes to use the following qualitative assessment approaches, which complement one another:     impact pathway analysis; outcome mapping; participatory monitoring evaluation; and developmental evaluation.

Qualitative approaches are especially useful for organizational learning and change, and understanding the determinants and constraints of IA4D adoption and diffusion. Understanding the diffusion of information will be essential in assessing spillover effects that be revealed by quantitative baselines. The main shortcoming of qualitative approaches is that by themselves, they are unable to attribute impacts to interventions. They are also prone to sampling and interviewer biases. Owing to the reasons enumerated above, a combination of quantitative and qualitative evaluation approaches is proposed for monitoring, evaluation and impact assessment of IAR4D.

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Annex 2: Innovation and Learning Process

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Financing Plan
SSA-Table 1: Allocation of Project Costs by Priority Area and Priorities, 2010 in $millions
Priority Area 3 Project Meta- Analysis Project PLS - Kano/Katsina/Maradi Project PLS - Lake Kivu Project PLS - Malawi/Mozambique/Zimbabwe Project Total 0.061 0.069 0.083 0.213 0.281 0.460 0.212 0.069 0.163 0.297 0.078 0.061 0.083 0.222 0.335 0.276 0.409 1.020 3A 3B 4A Priority Area 4 4C 4D 5A 1.402 0.380 0.358 0.533 2.673 0.280 0.135 0.222 0.637 Priority Area 5 5B 5C 0.702 0.213 0.374 0.139 1.428 5D 1.402 0.366 0.449 0.619 2.836 Total 3.506 2.088 2.088 2.088 9.770

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SSA-Table 2: Allocation of Project Costs to CGIAR Priorities, 2008-2012 in $millions
Projects Priorities Meta- Analysis Project 5A 5C 5D Total Project PLS - Kano/Katsina/Maradi Project 3A 3B 4A 4C 4D 5A 5B 5C 5D Total Project PLS - Lake Kivu Project 3A 3B 4A 4C 4D 5A 5B 5C 5D 0.047 0.047 0.199 0.041 0.186 0.240 0.091 0.250 0.302 0.066 0.066 0.281 0.058 0.262 0.339 0.128 0.353 0.425 0.069 0.069 0.297 0.061 0.276 0.358 0.135 0.374 0.449 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.026 0.093 0.071 0.034 0.146 0.167 0.123 0.093 0.160 0.913 0.057 0.201 0.154 0.074 0.317 0.360 0.265 0.202 0.348 1.978 0.061 0.212 0.163 0.078 0.335 0.380 0.280 0.213 0.366 2.088 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.315 0.158 0.315 0.788 1.153 0.578 1.153 2.884 1.402 0.702 1.402 3.506 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Actual 2008 Estimated 2009 Proposal 2010 Plan 1 2011 Plan 2 2012

Projects Priorities Total Project PLS - Malawi/Mozambique/Zimbabwe Project 3A 4C 4D 5A 5B 5C 5D Total Project Total

Actual 2008

Estimated 2009

Proposal 2010

Plan 1 2011

Plan 2 2012

1.403

1.978

2.088

0.000

0.000

0.058 0.058 0.286 0.373 0.155 0.097 0.432 1.459 4.563

0.079 0.079 0.386 0.505 0.210 0.131 0.586 1.976 8.816

0.083 0.083 0.409 0.533 0.222 0.139 0.619 2.088 9.770

0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

SSA-Table 3: Summary of Project Costs, 2008-2012 in $millions
Project Actual 2008 Estimated 2009 Proposal 2010 Plan 1 2011 Plan 2 2012

Meta- Analysis Project PLS - Kano/Katsina/Maradi Project PLS - Lake Kivu Project PLS - Malawi/Mozambique/Zimbabwe Project Total

0.788 0.913 1.403 1.459 4.563

2.884 1.978 1.978 1.976 8.816

3.506 2.088 2.088 2.088 9.770

0.000 0.000 0.000 0.000 0.000

0.000 0.000 0.000 0.000 0.000

SSA-Table 4: Summary of Priority Costs, 2008-2012 in $millions

Priorities 3A 3B 4A 4C 4D 5A 5B 5C 5D Total

Actual 2008 0.131 0.140 0.270 0.133 0.618 1.095 0.369 0.598 1.209 4.563

Estimated 2009 0.202 0.267 0.435 0.211 0.965 2.357 0.603 1.264 2.512 8.816

Proposal 2010 0.213 0.281 0.460 0.222 1.020 2.673 0.637 1.428 2.836 9.770

Plan 1 2011

Plan 2 2012

SSA-Table 5: Investments by Undertaking, Activity and Sector, 2008-2012 in $millions
Actual 2008 Increasing Productivity Germplasm Enhancement & Breeding Production Systems Development & Management Cropping systems Livestock systems Tree systems Fish systems Protecting the Environment Saving Biodiversity Improving Policies Strengthening NARS Training and Professional Development Documentation, Publications, Info. Dissemination Organization & Management Couselling Networks Total 2.702 1.351 1.351 0.826 0.505 0.020 0.000 0.431 0.098 0.979 0.353 0.076 0.069 0.125 0.083 4.563 Estimated 2009 5.219 2.609 2.610 1.596 0.976 0.038 0.000 0.832 0.190 1.892 0.683 0.147 0.133 0.242 0.161 8.816 Proposal 2010 5.784 2.892 2.892 1.768 1.082 0.042 0.000 0.922 0.210 2.097 0.757 0.163 0.148 0.268 0.178 9.770 Plan 1 2011 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Plan 2 2012 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

SSA-Table 6: Project Investments by Developing Region, 2008-2012 in $millions
Project Meta- Analysis Project SSA Total Project PLS - Kano/Katsina/Maradi Project SSA Total Project PLS - Lake Kivu Project SSA Total Project PLS - Malawi/Mozambique/Zimbabwe Project SSA Total Project Total Region Actual 2008 0.788 0.788 0.913 0.913 1.403 1.403 1.459 1.459 4.563 Estimated 2009 2.884 2.884 1.978 1.978 1.978 1.978 1.976 1.976 8.816 Proposal 2010 3.506 3.506 2.088 2.088 2.088 2.088 2.088 2.088 9.770 Plan 1 2011 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Plan 2 2012 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

SSA-Table 7: Summary of Investments by Developing Region, 2008-2012 in $millions
Region SSA Total Actual 2008 4.563 4.563 Estimated 2009 8.816 8.816 Proposal 2010 9.770 9.770 Plan 1 2011 0.000 0.000 Plan 2 2012 0.000 0.000

SSA-Table 8: Expenditure by Object, 2008-2012 in $millions
Actual 2008 Estimated 2009 Proposal 2010 Plan 1 2011 Plan 2 2012

Object of Expenditure

Personnel Supplies and services Collaboration/ Partnerships Operational Travel Depreciation Total

0.443 0.108 3.904 0.106 0.002 4.563

0.545 0.269 7.899 0.092 0.011 8.816

0.627 0.309 8.715 0.106 0.013 9.770

0.000 0.000 0.000 0.000 0.000 0.000

0.000 0.000 0.000 0.000 0.000 0.000

SSA-Table 9: Member and Non-Member Unrestricted Grants, 2008-2010 in $millions NC = National Currency
Member Unrestricted Grants Member Denmark European Commission France Italy Netherlands Norway Sweden United Kingdom World Bank GBP USD Subtotal Total Unrestricted EURO EURO 0.000 1.638 0.000 0.142 0.000 0.000 0.000 2.748 0.035 4.563 4.563 0.000 1.269 0.000 0.110 0.000 0.000 0.000 1.184 0.035 0.000 2.650 0.000 1.800 0.000 0.000 0.000 3.776 0.590 8.816 8.816 0.000 2.052 0.000 1.394 0.000 0.000 0.000 1.627 0.590 0.000 3.111 0.000 0.000 0.000 0.000 0.000 1.420 5.239 9.770 9.770 0.000 2.412 0.000 0.000 0.000 0.000 0.000 0.612 5.239 Type NC Actual 2008 (US$) Actual 2008 (NC) Estimated 2009 (US$) Estimated 2009 (NC) Proposal 2010 (US$) Proposal 2010 (NC)

SSA-Table 9a: Member and Non-Member Unrestricted and Restricted Grants, 2008-2010 in $millions
Member / Non-Member Unrestricted Grants Member Denmark European Commission France Italy Netherlands Norway Sweden United Kingdom World Bank Subtotal Total Unrestricted Total Grants 0.000 1.638 0.000 0.142 0.000 0.000 0.000 2.748 0.035 4.563 4.563 4.563 0.000 2.650 0.000 1.800 0.000 0.000 0.000 3.776 0.590 8.816 8.816 8.816 0.000 3.111 0.000 0.000 0.000 0.000 0.000 1.420 5.239 9.770 9.770 9.770 Actual 2008 Estimated 2009 Proposal 2010

Summary and Statement of Activities Total Grants Center Income Revenue Total Investment Surplus (Deficit)

Actual 2008 4.563 0.000 4.563 4.563 0.000

Estimated 2009 8.816 0.000 8.816 8.816 0.000

Proposal 2010 9.770 0.000 9.770 9.770 0.000

SSA-Table 10: Allocation of Member, Non-Member Grants and Other Sources to Projects, 2008-2010 in $millions
Actual 2008 0.788 Project Total PLS - Kano/Katsina/Maradi Project Unrestricted + Other sources Project Total PLS - Lake Kivu Project Unrestricted + Other sources Project Total PLS - Malawi/Mozambique/Zimbabwe Project Unrestricted + Other sources Project Total Total Resticted Total Unrestricted + Other sources Total 0.788 0.913 0.913 1.403 1.403 1.459 1.459 0.000 4.563 4.563 Estimated Proposal 2009 2010 2.884 2.884 1.978 1.978 1.978 1.978 1.976 1.976 0.000 8.816 8.816 3.506 3.506 2.088 2.088 2.088 2.088 2.088 2.088 0.000 9.770 9.770

Project

Member

Meta- Analysis Project

Unrestricted + Other sources

S

SSA-Table 11: Internationally and Nationally Recruited Staff, 2008-2012 in $millions

Actual 2008 NRS IRS Total 3 3 6

Estimated 2009 3 3 6

Proposal 2010 3 3 6

Plan 1 2011 0 0 0

Plan 2 2012 0 0 0

SSA-Table 12: Currency Structure of Expenditure, 2008-2010 in millions of units and percent
Actual 2008 Currency USD Total Amount 4.563 $ Value 4.563 4.563 % Share 100 100 % Amount 8.816 Estimated 2009 $ Value 8.816 8.816 % Share 100 100 % Amount 9.770 Proposal 2010 $ Value 9.770 9.770 % Share 100 100 %

SSA - Table 13: Statement of Financial Position (SFP), 2008-2010 in $millions
Assets, Liabilities and Net Assets Current Assets
Cash and Cash Equivalents Investments Accounts Receivable - Donor - Employees - Other CGIAR Centers - Others Inventories Pre-paid Expenses Total Current Assets 1.938 0.037 2.839 0.000 0.000 0.000 9.057 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 4.243 0.000 0.000 0.000 0.000 0.000

2008

2009

2010

Non-Current Assets
Net Property, Plan and Equipment Investments Other Assets Total Non-Current Assets Total Assets 0.000 0.000 0.000 0.000 9.057 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Current Liabilities
Overdraft/Short Term Borrowings Accounts Payable - Donor - Employees - Other CGIAR Centers - Others Accruals and Provisions Total Current Liabilities 0.000 0.019 1.945 0.000 0.000 1.964 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Non-Current Liabilities
Accounts Payable - Employees - Deferred Grant Revenue - Others Total Non- Current Liabilities Total Liabilities 0.000 0.000 0.000 0.000 1.964 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Net Assets
Unrestricted - Fixed Assets - Unrestricted Net Assets Excluding Fixed Assets Total Unrestricted Net Assets 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Restricted Total Net Assets Total Liabilities and Net Assets

7.093 7.093 9.057

0.000 0.000 0.000

0.000 0.000 0.000

SSA-Table 14: Statement of Activities (SOA), 2008-2010 in $millions
Restricted Unrestricted Temporary Revenue and Gains Grant Revenue Other revenue and gains Total revenue and gains Expenses and Losses Program related expenses Management and general expenses Other losses expenses Sub Total expenses and losses Indirect cost recovery Total expenses and losses Net Operating Surplus / (Deficit) Extraordinary Items NET SURPLUS / (DEFICIT) Object of Expenditure Personnel Supplies and services Collaboration/ Partnerships Operational Travel Depreciation Total 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Challenge Programs 4.563 0.000 4.563 4.563 0.000 0.000 4.563 0.000 4.563 0.000 0.000 0.000 0.443 0.108 3.904 0.106 0.002 4.563 2008 4.563 0.000 4.563 4.563 0.000 0.000 4.563 0.000 4.563 0.000 0.000 0.000 0.443 0.108 3.904 0.106 0.002 4.563 2009 8.816 0.000 8.816 8.816 0.000 0.000 8.816 0.000 8.816 0.000 0.000 0.000 0.545 0.269 7.899 0.092 0.011 8.816 2010 9.770 0.000 9.770 9.770 0.000 0.000 9.770 0.000 9.770 0.000 0.000 0.000 0.627 0.309 8.715 0.106 0.013 9.770 Total


				
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