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Moderated conference on impact assessment of agricultural research: May 2014

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Wed, 21 May 2014 13:53:24 +0200
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My name is Hailemichael Taye from Ethiopia. I am Results Based Monitoring and Evaluation Expert in a R4D project, at International Livestock Research Institute (ILRI). This is very interesting topic and discussion where I expect to learn a lot. I have got information about this program lately and this is my first email.



There are some issues that need more attention while we think of impact evaluation (IE) in agricultural research. The first important thing we need to clarify is how we define impact. This is because how we define the term dictates the IE methods and designs to be employed, the type of data to be collected, the analysis and conclusions to be drawn. 



There are various definitions of impact. One of the definitions of ‘impact’ refers to the final outcome level of the causal chain. This could be increased income, improved nutritional status, improved wellbeing etc. In this case, impact evaluation is about identifying the changes in terms of these impact variables. Here we can use both quantitative and qualitative (mixed) method for IE. On the other hand, others working in impact evaluation define impact as the difference in the indicator of interest (Y) with the intervention (Y1) and without the intervention (Y0). That is, impact = Y1 − Y0. In this sense, impact evaluation is a study which tackles the issue of attribution by identifying the counterfactual value of Y (Y0) in a rigorous manner. This requires rigorous quantitative data and needs the application of sophisticated statistical analysis (quantitative IE method). Some argue that these two definitions should overlap and impact evaluation should be about attributing the impact indicator (the final outcome in the results chain), like income, to the intervention by using rigorous methods. 



The other challenging issue in impact evaluation of agricultural research is disentangling the impact of research and extension. If agriculture research should bring impact, the research results should first reach the farmer and be applied. For this, the extension system has a huge task which by itself requires resources, methods and interventions and needs to be monitored and evaluated (including impact evaluation) by its own. A good research result may have poor impact due to poor extension system. Therefore, it is difficult to differentiate the impact of research and extension. To add an insult to the injury, there are lots of literature detailing the difficulty of capturing the impact of extension itself due to various factors.   



In terms of the quantitative approach of evaluating impact, it assumes a linear and rigid way of relationship along the results chain from input to output to outcome to impact. However, in agricultural research and extension there are a lot of actors (multi-institutionalism and plurality), sources of information and technology etc. (beside the formal intervention) with complex interactions and inputs. Agricultural development in general is not linear; rather it is a dynamic and complex process that requires the contribution of multiple stakeholders at various levels along with the necessary mix of technical, socio-economic, institutional and policy conditions. This questions the possibility and importance of attribution studies in agricultural research and extension IE. 



We need to consider these issues while developing impact evaluation tools for agricultural research. 



Hailemichael Taye

Results Based Monitoring and Evaluation Expert 

Livestock and Irrigation Value chains for Ethiopian Smallholders (LIVES)

International Livestock Research Institute

Box 5689, 

Addis Ababa, 

Ethiopia 

www.ilri.org 

Tel: +251 11 617 2417

Email: h.taye (at) cgiar.org    

Skype: hailaat1 



 [To contribute to this conference, send your message to [log in to unmask] For further information, see http://www.fao.org/nr/research-extension-systems/res-home/news/detail/en/c/217706/ ].



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