Insights on Agricultural Productivity and Challenges for Developing Countries
Explore the role of growth diagnostics in identifying agricultural challenges, the significance of low agricultural productivity in Africa, and the constraints affecting returns in agriculture. Delve into the need for addressing key questions on productivity improvement and potential sector movement for economic development.
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Presentation Transcript
Agriculture in MCC Analytics & Program Design Will Martin 25 September 2020
Growth Diagnostics & Agriculture Hausmann, Rodrik & Velasco diagnostics play a key role at MCC Very useful for identifying problems and responses Is the problem one of inability to access finance, or of low returns?
But Africa is poor because agricultural productivity is so low 70 60 50 40 % 30 20 10 0 Ag Share Ag vs Non ag Productivity
Even more extreme in Mozambique 90 80 70 60 50 % 40 30 20 10 0 Ag Lab Shr Ag/NonAg Y
Why is Measurement or real? Are barriers to movement policy-induced or real costs? productivity so much lower in agriculture? Is the best approach to raise returns in agriculture? If so, what are the constraints there? Low adoption of improved varieties? High input costs? Vanishingly small plots? Raises key questions not examined in HRV Or is it better to encourage movement to other sectors? If so, which ones?
Conclusions Basic HRV insight of looking for binding constraints important But agricultural challenges are central for poor countries Is it worth using the constraints approach within & between agric & non- agriculture?
