1932

Abstract

We take stock of the major changes in methodology for studying the impacts of international agricultural research, focusing on the period 2006–2020. Impact assessment of agricultural research has a long and recognized tradition. Until the mid-2000s, such assessments were dominated by a model of demand for and supply of agricultural products in partial equilibrium. The basic ideas for this approach were sketched out by Griliches more than half a century ago. We describe the implications of heightened standards of evidence for good practice in three domains of research design: causal inference, valid measurement, and statistical representativeness. We document advances in each of these domains and review recent evidence that demonstrates the lessons that can be learned from adopting these practices, emphasizing the importance of evidence at-scale, the need to consider portfolios of innovations at a national level, and the challenges of accounting for innovations that are promoted as bundles.

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2023-10-05
2024-06-16
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