All CGIAR Research Programs (CRPs) and Platforms integrate monitoring, evaluation, learning and impact assessments to test their assumptions, learn and improve their work. In 2018 the CGIAR Communities of Practice (CoPs) on monitoring, evaluation and learning (MEL) and impact assessment (IA) held a joint meeting. The meeting covered discussions on strengthening a shared understanding of MEL and IA roles and responsibilities; continuing to build CGIAR quality standards and guidelines for MEL and IA work undertaken at the project, Program, Platform, Center and System levels; exchanging and sharing the MEL and IA work of the CRPs, Platforms, Centers, and at System level; and reviewing the MEL and IA work plans and Terms of References.


An example of MELIA work in 2018 was a program evaluation of remote weather stations (RWSs) in Sri Lanka, a project implemented by IWMI. The risk information technology used in this project was subsequently the focus of a Challenge Fund project, also implemented by IWMI. The Challenge Fund is a joint initiative of the Global Facility for Disaster Reduction and Recovery (GFDRR) and UK Aid and aims to bridge the gap between technology and on-the-ground user needs in the field of disaster risk identification to build greater disaster resilience. The scope of the evaluation included the IWMI Challenge Fund project and broader efforts involving this technology in Sri Lanka.


The evaluation found that the RWSs were continually developed and improved from their innovation to the time of the evaluation; partnerships with six local organizations were formed or strengthened; the tool was co-developed with ten beneficiaries; the project was gender-informed because a gender analysis was conducted and gender gaps were identified and communicated; 144 beneficiaries were trained; and USD 741,900 was leveraged (WLE, 2018).


An example of an ex-post impact assessment in 2018 was IFPRI’s study on the impact of their decentralization strategy on country development indicators in Africa and Asia. The study used country-level panel data on 57 countries in Africa and Asia from 1981 to 2014 to assess the relationships between IFPRI’s in-country presence (as measured by staff present) and various policy and outcome indicators in those countries.


An econometric model with country fixed-effects, year fixed-effects, and country-specific time trends was used, controlling for several factors deemed to affect the different policy and outcome indicators such as the country’s research capacity, production environment and resources, political economy and institutions, and complementary investments.


It was found that IFPRI’s presence and intensity of its policy-oriented research in a country is positively and significantly associated with most of the policy and outcome variables analyzed. Estimated benefit-cost ratios were moderate to high in the range of 8.4–25.4 for land productivity, 9.6–17.3 for labor productivity, and 5.5–75.3 for GDP per capita. These translate into internal rates of return of 101–207 percent for land productivity, 101–161 percent for labor productivity, and 75–383 percent for GDP per capita (PIM, 2018).


Also in 2018, an ex-post impact assessment of the livelihood impacts of improved cassava varieties in Nigeria was published in the Journal of Agricultural Economics. The assessment found that adoption of improved cassava varieties has led to a 4.6 percentage point reduction in poverty, though this is sensitive to the measurement of adoption status. Therefore, accurate measurement of adoption is crucial for a more credible estimate of the poverty reduction effect of adoption. The analysis also suggested that farmers who are more likely to be adopters are also likely to face higher structural costs. Therefore, addressing structural barriers that make improved technologies less profitable for the poor would be important to increase the poverty reduction effect of improved cassava varieties (RTB, 2018).


A list of the status of evaluations, impact assessments and learning exercises in 2018 can be found in Annex 8.



Photo by M. Cooperman/IFPRI