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A sustainable future for Africa through continental free trade and agricultural development

Abstract

Developing and integrating agricultural markets may be key to addressing Africa’s sustainability challenges. By modelling trade costs from farm gate to potential import markets across eight African regions, we investigate the impact of individual components of continental free trade and the complementary role of domestic agricultural development through increased market access for farmers and agricultural intensification. We find that free trade would increase intra-African agricultural trade sixfold by 2030 but—since it does not address local supply constraints—outside food imports and undernourishment would reduce only marginally. Agricultural development could almost eliminate undernourishment in Africa by 2050 at only a small cost of increased global greenhouse gas emissions. While continental free trade will be enabled in Africa through the African Continental Free Trade Area, aligning this with local agricultural development policies is crucial to increase intra-African trade gains, promote food security and achieve climate objectives.

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Fig. 1: Trade costs under free trade and agricultural development and regional aggregation.
Fig. 2: Impact of free trade and agricultural development and individual scenario elements in 2050.
Fig. 3: Impact of free trade and agricultural development across African regions in 2050.
Fig. 4: Impact of prioritization strategies (connect, food, export) in 2050.

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Data availability

The main data supporting the findings of this study are available in the article and the supplementary information. Source data are provided with this paper. Additional data are available from the corresponding author upon reasonable request.

Code availability

The code used for the figures and statistical analyses is available from the corresponding author upon reasonable request.

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Acknowledgements

We acknowledge research funding from Research Foundation Flanders (Fonds voor Wetenschappelijk Onderzoek (FWO) (FWO contract/180956/SW)). This research was also supported by the European Union’s Horizon 2020 Research and Innovation programme (grant no. 820712).

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Authors

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C.J., P.H. and M.M. developed the concept and designed the scenarios. C.J., A.M., J.B., D.L. and P.H. provided the code and model simulations. C.J., P.H., E.B., A.P. and M.M. analysed and interpreted the data. All authors edited and approved the manuscript.

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Correspondence to Charlotte Janssens.

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Nature Food thanks Liesbeth Colen, Thom Jayne and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Impact of Free Trade and Agricultural Development scenarios (a) and decomposition (b,c) on African trade, undernourishment, GHG emissions and production in 2030.

GHG emissions present annual emissions in 2030. Total effect = combined effect of all scenario elements; individual effect = sole effect of the specific scenario element; final effect = [total effect – effect without the specific scenario element], that is the effect of adding a specific component when all the others are present. A large difference between the individual effect and final effect indicates interaction among the scenario elements.

Extended Data Fig. 2 Impact of Free Trade and Agricultural Development across African regions in 2030.

Impact of Free Trade and Agricultural Development scenarios on undernourishment, GHG emissions, production, land use and crop trade across African regions in 2030. GHG emissions present the annual emissions in 2030.

Extended Data Fig. 3 Decomposition of the impact of Agricultural Development scenario on GHG emissions, land use, and production across African regions in 2050.

Total effect = combined effect of all scenario elements, individual effect = sole effect of the specific scenario element, final effect=[total effect – without effect of the specific scenario element].

Extended Data Fig. 4 The impact of the Free Trade and Agricultural Development scenarios on intra-African trade pattern of maize, rice, wheat and barley in 2050.

The size of the individual flows reflects the magnitude of the trade flows (kton) and the color of the flow corresponds to the exporting region.

Extended Data Fig. 5 The impact of the Free Trade and Free Trade + Agricultural Development (FT + AD) scenarios on intra-African trade pattern of oil palm, sugarcane, cotton and soybeans in 2050.

The size of the individual flows reflects the magnitude of the trade flows (kton) and the color of the flow corresponds to the exporting region.

Extended Data Fig. 6 Net trade across African regions under the baseline, Free Trade and Agricultural Development scenarios for key commodities imported outside Africa in 2050 (maize, oil palm, rice, soybeans, sugarcane and wheat).

For 2000 and 2020, the GLOBIOM model output compared to the net trade in 2000 and 2018 in CEPII’s BACI trade database (country-level trade aggregated to trade at GLOBIOM region level).

Extended Data Fig. 7 Impact of Agricultural Development prioritization strategies on the risk of hunger, GHG emissions, land use and crop and livestock production, imports and exports by 2050 across African regions.

GHG emissions present the average annual emissions in the period 2030–2050. FT + AD: combined Free Trade + Agricultural Development scenario.

Extended Data Fig. 8 Impact of Agricultural Development and Connect scenario on local trade costs averaged across crops in Africa in 2030 (weighted average by baseline production).

Impact of Agricultural Development and Connect scenario on local trade costs averaged across crops in Africa in 2030 (weighted average by baseline production). Local trade costs consist of local transport and marketing costs. Trade cost values are split according to deciles. Areas without trade costs have no cropland area in the model input data. In the Agricultural Development scenario, farm-gate to market transport costs are reduced to an international benchmark of 0.05 USD/ton-km by 2030. The Connect scenario represents the local transport cost reduction that can be achieved by switching to high load capacity transport vehicles (load capacity = 12.5 ton) in the first 55 km beyond farm-gate by 2030, and this only in areas connected to the current primary road network in Africa (Supplementary Fig. 10).

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Supplementary Methods, Figs. 1–28, Tables 1–12 and References.

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Janssens, C., Havlík, P., Boere, E. et al. A sustainable future for Africa through continental free trade and agricultural development. Nat Food 3, 608–618 (2022). https://doi.org/10.1038/s43016-022-00572-1

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