Attribution Among Multiple Partners
Establishment of the counterfactual relative to a specific programme is the same as “attribution,” or the identification of the specific causal pathway from the specific actions of a particular institution, relative to other drivers of change. The counterfactual at this level should identify the “next best” technologies or policies that would have been developed and adopted without the assessed research programme, and should analyse how farmers would adjust their practices so as to make best use of the tools consequently available. The timeframe of the development of these alternative technologies should also be established, as impact may be derived from faster delivery of similar outputs to those that would happen in the counterfactual conditions.
During attribution, the issue of “fungibility,” or whether an alternative source, such as the private sector, would have produced a similar research product to that of the assessed public programme, becomes important. If the private sector has been displaced by a public-sector programme with similar research products, the impact at the level of the specific organization may be little, even though the impact relative to a no-research counterfactual is considerable. In this case, the latter scenario is clearly not realistic, and hence is not a plausible basis for claiming impact. For those cases where public sector research is providing outputs that compete with those of the private sector, displacement effects need to be assessed in the counterfactual. Similarly, if the CGIAR has merely substituted for something that a NARS organization would have done in the absence of the CGIAR, then that needs to be brought out in the counterfactual assessment.
At the same time, it is clearly not always feasible or desirable to attribute results to the actions of partners in collaborative research efforts with complementary products. In many cases, the actions of each partner in isolation would not produce an adoptable output without the contributions of the other. Any attempt to “partition” the credit among these actors would hence be ad hoc and would risk offending the partners involved. In these cases, the only viable solution is to consider the collaborative efforts as a single programme and adopt joint attribution.
Identifying the use and application of agricultural and related research outputs may often be less than simple, especially in the case of research programmes that do not directly produce finalised tools or improved physical inputs. Much, if not most, agricultural research results in information embedded in documents, management recommendations, or policies. In such cases uptake is not a binary decision, and may not necessarily lead to full adoption or implementation. Furthermore, there is no distinct empirical marker of use, and other drivers of change may produce influence that is difficult to distinguish from that of the research output. For these forms of research, interview and case study approaches will often be necessitated to identify influence and trace impact from the new information, as opposed to other factors causing change.