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on Africa |
| By: | Krantz, Sebastian |
| Abstract: | Using rich geospatial data and causal machine learning (ML), this paper maps potential economic benefits from incremental investments in all major types of public and economic infrastructure across Africa. These 'infrastructure potential maps' cover all African populated areas at a spatial resolution of 9.7km (96km2). They show that the local returns to infrastructure are highly variable and context-specific. For example 'hard infrastructure' such as paved roads and communications is more beneficial in cities, whereas 'social infrastructure' such as education, health, public services and utilities is more critical in rural areas. Market access and agglomeration effects largely govern these returns. The open Africa Infrastructure Database built for this project provides granular data in 54 economic categories/sectors. It reveals that Africa's infrastructure is concentrated in urban areas, with cities exhibiting marked heterogeneity in infrastructure, public services, and economic activities. Spatial inefficiency is common. The findings are consistent with economic literature, highlighting causal ML and explainable AI's potential to generate insights from geospatial data and assist spatial planning. |
| Keywords: | Africa, infrastructure, investment potential, geospatial big data, causal ML, explainable AI |
| JEL: | O18 R11 R40 C14 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:ifwkwp:305261 |
| By: | Mukashov, Askar; Robinson, Sherman; Thurlow, James; Arndt, Channing; Thomas, Timothy S. |
| Abstract: | This paper uses machine learning, simulation, and data mining methods to develop Systematic Risk Profiles of three developing economies: Kenya, Rwanda, and Malawi. We focus on three exogenous shocks with implications for economic performance: world market prices, capital flows, and climate-driven sectoral productivity. In these and other developing countries, recent decades have been characterized by increased risks associated with all these factors, and there is a demand for instruments that can help to disentangle them. For each country, we utilize historical data to develop multi-variate distributions of shocks. We then sample from these distributions to obtain a series of shock vectors, which we label economic uncertainty scenarios. These scenarios are then entered into economywide computable general equilibrium (CGE) simulation models for the three countries, which allow us to quantify the impact of increased uncertainty on major economic indicators. Finally, we utilize importance metrics from the random forest machine learning algorithm and relative importance metrics from multiple linear regression models to quantify the importance of country-specific risk factors for country performance. We find that Malawi and Rwanda are more vulnerable to sectoral productivity shocks, and Kenya is more exposed to external risks. These findings suggest that a country’s level of development and integration into the global economy are key driving forces defining their risk profiles. The methodology of Systematic Risk Profiling can be applied to many other countries, delineating country-specific risks and vulnerabilities. |
| Keywords: | climate; computable general equilibrium models; machine learning; risk; uncertainty; Africa; Eastern Africa; Sub-Saharan Africa; Kenya; Rwanda; Malawi |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:fpr:ifprid:2286 |
| By: | Moritz Goldbeck; Valentin Lindlacher |
| Abstract: | We investigate the impact of early internet availability at basic speeds on local economic development in remote areas of developing countries by analyzing nighttime light emissions across towns in Sub-Saharan Africa. Using a difference-in-differences approach, we exploit submarine cable arrivals, which established countrywide internet connections, and the rollout of the national backbones, which defines internet access within countries. Estimating on incidentally connected mid-sized towns, we find that early internet availability increases nighttime light intensity by 10 percent. We consider increased employment as the main explanation. Our findings highlight the importance of closing the digital divide for regional development. |
| Keywords: | ICT, economic development nighttime lights, Sub-Saharan Africa, cybercafé, internet access, employment, submarine cables |
| JEL: | O18 R11 L96 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11308 |
| By: | Qasim Ajao; Lanre Sadeeq; Oluwatobi Oluwaponmile Sodiq |
| Abstract: | Electric vehicles (EVs) represent a significant advancement in automotive technology, utilizing electricity as a power source instead of traditional fossil fuels, while incorporating sophisticated navigation and autopilot systems. These vehicles align with multiple Sustainable Development Goals (SDGs) by offering a more environmentally sustainable alternative to internal combustion engine vehicles (ICEVs). Despite their potential, the adoption of EVs in developing nations such as Nigeria remains constrained. This study expands the Unified Theory of Acceptance and Use of Technology (UTAUT) framework by incorporating key enablers, including poor infrastructure, affordability issues, and government support, within the broader category of facilitating conditions. Additionally, it examines factors such as trust, performance expectations, social influences, and network externalities to identify the primary determinants influencing Nigerian consumers' propensity to adopt EVs. Results show that the percentage increase of H6 (facilitating conditions - behavioral intentions) compared to H5 (network externalities - behavioral intentions) is approximately 32.35%, indicating that traditional drivers significantly influence individuals' willingness to purchase EVs and are particularly strong factors in adoption decisions. The paper concludes with a discussion of these findings and proposes strategies for future research to further explore the barriers and drivers of EV adoption in Nigeria. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2410.17282 |
| By: | Tekilu Tadesse Choramo; Jemal Abafita; Yerali Gandica; Luis E C Rocha |
| Abstract: | Global and regional integration has grown significantly in recent decades, boosting intra-African trade and positively impacting national economies through trade diversification and sustainable development. However, existing measures of economic integration often fail to capture the complex interactions among trading partners. This study addresses this gap by using complex network analysis and dynamic panel regression techniques to identify factors driving economic integration in Africa, based on data from 2002 to 2019. The results show that economic development, institutional quality, regional trade agreements, human capital, FDI, and infrastructure positively influence a country's position in the African trade network. Conversely, trade costs, the global financial crisis, and regional overlapping memberships negatively affect network based integration. Our findings suggest that enhancing a country's connectivity in the African trade network involves identifying key economic and institutional factors of trade partners and strategically focusing on continent-wide agreements rather than just regional ones to boost economic growth. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2410.21019 |
| By: | Abdelmonim AMACHRAA |
| Abstract: | Nothing better illustrates the positive contribution of the integration of national economies into global value chains than the fact that in the 1990s, the automotive sector barely existed in Morocco. Now, it is the leading export sector, with a production and assembly capacity of 700, 000 vehicles, making it an attractive and competitive hub linking Africa and Europe in the automotive value chain. However, the automotive industry is on the cusp of change, with advances in electric and autonomous vehicles, and transformations in mobility, lowering the barriers to entry in car assembly, and increasing the need for labor- intensive products such as wiring harnesses. We have identified two trends. First, vehicle manufacturers are engaging in the supply of raw materials. Second, the reorientation of investment flows and the organization of the location of production units will allow Western countries to reduce their dependence on foreign suppliers, particularly China. Upstream integration, semiconductors, clean energy, and batteries are at the center of decoupling negotiations. In an uncertain context, this research is intended to conceptualize an adaptive integration strategy for middle-income countries in global automotive value chains. |
| Date: | 2023–05 |
| URL: | https://d.repec.org/n?u=RePEc:ocp:rpaeco:pp_09-23 |