Shining a Brighter Light: Comprehensive Evidence on Adoption and Diffusion of CGIAR-Related Innovations in Ethiopia

In recent decades the agricultural sector in Ethiopia has seen a sustained period of growth, which is believed to have contributed in turn to economic growth and poverty reduction. The country is undergoing a structural transformation and a gradual process of modernization in agriculture, supported by government programs.

In this context, this report, provides new nationally representative micro-level evidence of the adoption and diffusion of agricultural innovations, focusing on those innovations that can be linked to CGIAR research. The report, published in October 2020, presents an unprecedented stocktaking of all CGIAR-related innovations in a given country as well as new estimates of adoption of those innovations from a nationally representative dataset. It was made possible through a partnership among the Ethiopian Central Statistics Agency (CSA), the World Bank Living Standards Measurement Study (LSMS) team, and the CGIAR Standing Panel on Impact Assessment (SPIA).

Read the report and the executive summary here

Watch the Webinar held in November 2020 to learn more 

SPIA Chair Karen Macours presents the recent report followed by a discussion with a panel comprising Alan Tollervey (FCDO), Kundhavi Kadiresan (CGIAR), Doug Gollin (University of Oxford) and Mandefro Nigussie (Former Director-General of EIAR, now State Minister in the Ethiopian Ministry of Agriculture).


Read news reports and blogs about the report


Frequently Asked Questions (FAQs) on the report

Download the FAQs as a PDF.



Q1: Why is the adoption of wheat and bean improved varieties not considered in the report?

CIMMYT carried out a wheat DNA fingerprinting study with CSA two years before our work, so CSA did not want to integrate a protocol for sampling wheat again. CIAT has also been working on DNA fingerprinting of common beans in a separate sample. The data from these two studies and those of the crops we did include (maize, barley, sorghum, sweet potatoe, chickpea) are therefore not directly comparable.

Q2: How do you separate out the influence of CGIAR versus the influence of other actors (national systems, NGOs, …)?

The report shows the reach of innovations to which the CGIAR research has contributed. In all cases, other actors also contributed to the research leading to the innovations or to the dissemination of those innovations. The intent is not to attribute the wide-spread adoption of innovations to CGIAR’s efforts relative to other actors – a task that is arguably impossible.

Q3: The most widely adopted innovation, SWC practices, does not have a clear observable feature that would link adoption to CGIAR research. Should the adoption of SWC practices in Ethiopia be considered a CGIAR success?

CGIAR research has informed major donor-funded programs on soil and water conservation practices in Ethiopia. The impact pathway is fundamentally different from, for example, crop germplasm improvement where there are "embodied" technologies that emerge from CGIAR research partnerships.

Q4: Can these data be used to calculate the cost-benefit of the innovations documented in the report?

The report documents 'reach', which together with careful causal estimates of the impact of selected innovations, can be used for a new way of calculating rates of return or cost-benefit ratios to CGIAR investments as a whole. See “SPIA approach to impact assessment for CGIAR (2020)” and the work of Michael Kremer at USAID’s Development Innovation Ventures for an exposition. Such an exercise is outside the scope of this report.

Q5: In some cases, the diffusion of innovations has gone remarkably fast. What can we learn in terms of enabling factors for research design and implementation?

The answer is innovation-specific and the report highlights some factors that deserve further investigation. For example, for crossbred poultry, the role of  the policy framework of the Livestock Master Plan, as well as the public-private partnerships boosting private sector investment, is worth understanding better. Improved barley varieties that were recently released yet found in farmers’ fields are another example that deserve more investigation for their relatively rapid diffusion.

Q6: Beyond the breadth of the adoption, what were the effects at the household level?

We only covered the reach of innovations in this report and did not document the impact on household-level outcomes. This would require combining survey data with a causal research design. SPIA’s approach to impact assessment is exposed in this Technical Note.

Q7: Did the study look at the relationship between the characteristics of the innovation and adoption, time-frame, and the role of extension services?

We did consider extension services efforts in the stocktake, in order to identify innovations that should be collected in the ESS. We did not make the role of extension an explicit focus in the report but it is an excellent candidate for further analysis with the ESS data.

Q8: Does the report document CGIARs capacity development?

Capacity development was not part of the Stocktaking exercise, in part because it is often less well documented. Linking capacity development to adoption of specific innovations as measured in household surveys would also be challenging. 

Q9: Some innovations are not reaching some target groups which raises que question how important targeting is and how we can do an effective targeting for CGIAR innovations?

This is an important question, but one that is hard to answer with the ESS data. Targeted studies considering the impact of specific targeting efforts could be designed to analyze this directly.

Q10: To what degree does this report argue for a unified theory of change that One CGIAR is proposing vs recognizing that each innovation may have its own scaling dynamic?

The report certainly does not intend to make a case for a unified ToC [1]. Instead, it proposes that the information on the types of households that are chosing to adopting a specific innovation (and equally important those that are chosing not to adopt) can be compared with the assumptions made in the ToC of that specific innovation. This allows documenting whether the specific innovation is reaching the type of households it intended to target.  


[1] Indeed, studies of SPIAs adapted strategies call specifically aim to test the impact of scaling strategies that are adjusted to the specific characteristics of an innovation (and the related ToC).