Abstract
Most countries that have undergone economic structural transformation (Structural Transformation 1.0) have done so first using low wage, export-oriented labor-intensive manufacturing as a driving force to absorb labor, first because there was no competition (the West) and then because productivity-adjusted wages were much lower than other places (East Asia). We first argue this structural transformation is unlikely in Africa, because labor productivity is lower and in general is less densely populated, limiting conditions for labor specialization. Instead we argue for a structural transformation based in part on agricultural processing (Structural Transformation 2.0). We suggest four paths by which Structural Transformation 2.0 could be catalyzed: Bundling interventions to alleviate multiple agricultural constraints; some farm consolidation; infrastructure investments, including but not exclusively roads; and by increasing demand and improving regional trade.
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Notes
- 1.
In addition to perceived differences in productivity growth, there are other reasons why industrial jobs are sometimes seen as “good jobs” by policy makers, compared to “bad jobs” in agriculture or the (informal) service sector. These reasons have to do with collective bargaining and unionization (increasing the share of the value added accruing to workers), and the idea that manufacturing jobs are more visible (resulting in more effective state monitoring and enforcement). However, Gollin (2018) argues that these characteristics could be extended to other sectors, including the formal service sector, and that these characteristics should not be misconstrued as an argument in favor of manufacturing per se.
- 2.
That is: unless countries can import both manufactures and food—an unlikely scenario for most African countries, except the ones exporting natural resources in large quantities.
- 3.
A linked intervention in Senegal increased livestock holdings after two years among households for whom multiple constraints were alleviated, but that intervention did not isolate the liquidity constraint due to sample size limitations (Ambler et al., 2020).
- 4.
The origins of the inverse relationship between farm size and productivity can be traced back further in time, all the way to Chayanov (1926).
- 5.
However, rather than leveraging this inefficiency and push smallholders to further raise land productivity, a more sensible path forward would be to reduce transaction costs, improve market participation and raise rural welfare by enabling rural families to rent out part of their labor or rent in more land—both of which should attenuate and perhaps eliminate the inverse relationship.
- 6.
The evidence for biased reporting of farm or plot size is weak. If smaller farmers systematically underreport land area, compared to larger farmers, then their yields would be artificially inflated. However, the empirical basis for such claims is not strong. Carletto et al. (2013) find that replacing farmer estimates of land size by GPS-based measurements only strengthens the empirical basis for the IR.
- 7.
Some outgrower schemes also exist in cereal production. For example, large beer brewers sometimes contract local farmers for a steady supply of grains meeting certain specifications.
- 8.
For example, Blimpo et al. (2013) find that, after controlling for the economic importance of areas and other factors, politically marginalized areas have fewer roads.
- 9.
Evidence from Asia on the effects of infrastructure is a bit more mixed. For example, Asher and Novosad (2020) study the effect of rural road construction in India and find that the main effect of new roads is facilitating the movement of workers out of agriculture. They do not document effects on ownership of agricultural equipment, input use, crop choice, production levels, income, or assets, and conclude that, even with improved market access, remote areas still face disadvantages that impede development.
- 10.
Input usage in the most remote villages is about one-third of that in the least remote villages, and maize sales are only 45% as high.
- 11.
Green box policies are considered non-distortionary to international trade and so are unlimited, while amber box policies (including direct subsidies) are limited to 10% of total value of agricultural production for LMICs that are WTO members.
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de Brauw, A., Bulte, E. (2021). Structural Transformation 2.0: The Rocky Road Ahead…. In: African Farmers, Value Chains and Agricultural Development. Palgrave Studies in Agricultural Economics and Food Policy. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-88693-6_9
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