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Can AI help to optimize infrastructure planning in Africa?

The Africa’s public infrastructure deficit is widely recognized by economic literature and policy discourse. The 2018 African Economic Outlook published by the African Development Bank estimated the Africa’s road infrastructure needs in $130-170 billion per year, with a financing gap in the range of $68-108 billion. In August this year, the Bank revised this estimation, noting that such needs have now reached levels between $181 and $221 billion per year. But Large gaps also remain in other areas, like electricity, internet, and basic sanitation services. If on one side these deficits reveal a development path in Africa that is still long to be traveled, on the other hand also suggest that public infrastructure investments in Africa are an opportunity for high returns for economic activity and wealth generation. But at one condition: that the development of infrastructure projects is correctly planned so to become attractive for investors. Nobody invests in transport infrastructure, electricity or water supply projects whose operational efficiency, cost-effectiveness, and overall competitiveness have not been carefully evaluated. Infrastructure needs to be located where its economic effects are mostly felt, that’s the point.

Last year, a policy research working paper of the World Bank pointed out how improvements in infrastructure play a vital role in supporting the development process. Not only roads, but public infrastructure in general, foster development. The paper cited as an example broadband internet coverage, which boosts firm productivity and leads to higher levels of employment (particularly of high-skill workers), and electrification, which supports the process of structural transformation, by allowing migration to higher value-added activities beyond agriculture. Regarding transport infrastructure, the paper argues that railways have a long-term impact on development. Let’s think to the arrival of railroads in Africa in rural areas during the colonial period, which enhanced agricultural trade and improved food security. But it took time. Ports, when they operate efficiently, they can reduce the effect of geographical distance, so contributing to the development of geographically isolated countries, like in the case of small island economies. Conversely, the role that roads play in development is different, the World Bank notes. It depends on the territorial areas these roads they link. Those connecting rural localities to main urban centers and international transport hubs (e.g., ports and airports) generally stimulate agricultural production as well as agricultural output and exports expansion. On the other hand, national highway networks contribute to boost manufacturing output and associated exports. Moreover, they facilitate greater industrial specialization and enhancing competition.

The World Bank paper concludes that in the latest years, the academic research analyzing the impacts of infrastructure on development has grown exponentially, fueled by the availability of geospatial data, among others. This data allows today a much richer and more granular understanding on how different kinds of infrastructure can contribute to development.

working paper just issued from the Kiel Institute for the World Economy tries to go beyond this concept. It analyses the potential economic benefits that can arise from incremental investments in all major types of public and economic infrastructure across Africa by using geospatial data from different sources and causal machine learning. One of the main finding of the paper is that, in much of sub-Saharan Africa, infrastructure is allocated inefficiently. In other words, it is frequently disconnected from economically significant areas that would deserve to be linked to each other to promote beneficial trade both within these States and among different African nations. These findings confirm those of a landmark study concluded a few years ago, which pointed out how countries with higher levels of spatial efficiency have higher average levels of development, a stronger business environment and greater logistics performance. Which suggests that infrastructure interventions in Africa must be calibrated with a surgical precision, one might say.

The big question is: how this level of efficiency in the spatial planning of infrastructures could be improved? Maybe, where the man has not succeeded, the machine could. Especially now that artificial intelligence and machine learning methods are available to the humankind. These technologies could help to better determine the optimal positioning of infrastructure in Africa by conducting accurate analysy of a wide range of data and information (including geospatial data), by conducting cost-profit analysis, center of gravity analysis, transportation model analysis, all together to identify their optimal location.

But we are only at the beginning of this path. And this approach presents a promising path for future infrastructure planning...

Read the abridged version on the Habari Network

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