Agricultural innovations are inclusive when they are used by any member of society who wants to use them. Conversely, agricultural innovations that can only be used by a specific privileged group within society can be characterized as “exclusive”. The first objective of this paper is to examine the inclusivity of agricultural innovations in Ethiopia, using national representative data and considering a wide portfolio of innovations resulting from the collaborative research between CGIAR and its national partners. Second, we also examine how measurement error may affect how we characterize the inclusivity of agricultural innovations. We use nationally-representative survey data from Ethiopia (collected in 2018/19) in which best-practice measures of the adoption of a large number of agricultural innovations were embedded, including the adoption of CGIAR-related improved maize varieties measured using two different approaches: subjective, self-reported survey data; and objective DNA fingerprinting of crop samples taken from the same farmers' plots. A rich set of household variables is also collected in the survey, which allows characterizing the types of farmers that are adopting different innovations, and the extent to which conclusions regarding the inclusivity of innovations depends on the measurement of the latter. Many innovations are not disproportionately more likely to be adopted by male, larger, richer, or more connected farmers. When using self-reported data on adoption of improved maize varieties, adoption appears positively correlated with having larger landholdings and households with lower female participation in agriculture, and negatively correlated with poorer households (being among the bottom 40% of consumption distribution). Substituting survey responses with the results of DNA fingerprinting these correlations disappear, with farm size, gender and poverty status no longer predictive of adoption. The results suggest the potential value of offering a menu of innovations to farmers to increase inclusivity, as it allows each farmer to be a critical consumer of potential innovations and select those that best correspond to their own needs and constraints. We also highlight how important data quality is in ensuring we have correct information about inclusive innovation.

中文翻译：

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用正确的数据研究包容性创新：来自埃塞俄比亚的实证例证


当农业创新被任何想要使用它们的社会成员所使用时，它就具有包容性。相反，只能由社会中特定特权群体使用的农业创新可以被描述为“排他性”。本文的第一个目标是利用国家代表性数据并考虑 CGIAR 与其国家合作伙伴之间合作研究产生的广泛创新组合，研究埃塞俄比亚农业创新的包容性。其次，我们还研究了测量误差如何影响我们如何描述农业创新的包容性。我们使用埃塞俄比亚的全国代表性调查数据（2018/2019年收集），其中包含采用大量农业创新的最佳实践措施，包括采用两种不同方法测量的与CGIAR相关的改良玉米品种：主观、自我报告的调查数据；对取自同一农民地块的农作物样本进行客观 DNA 指纹分析。调查中还收集了丰富的家庭变量，这可以描述采用不同创新的农民类型，以及有关创新包容性的结论在多大程度上取决于后者的衡量。许多创新技术被男性、体型较大、较富有或关系较密切的农民采用的可能性并不高。当使用有关改良玉米品种采用情况的自我报告数据时，采用情况似乎与拥有较大土地和女性参与农业程度较低的家庭呈正相关，与较贫困家庭（消费分布中处于底部 40% 的家庭）呈负相关。 用 DNA 指纹识别结果代替调查结果后，这些相关性就消失了，农场规模、性别和贫困状况不再能预测采用情况。结果表明，为农民提供一系列创新以提高包容性具有潜在价值，因为它使每个农民都成为潜在创新的关键消费者，并选择最适合自己需求和限制的创新。我们还强调数据质量对于确保我们获得有关包容性创新的正确信息的重要性。