Impact of geopolitical dynamics on global trade: The case of the African automotives sector
Bibliographic record
Abstract
The global economic landscape has undergone significant transformation since the 2008 financial crisis, marked by rising protectionism, intensifying competition between major powers, and disruptions to trade and investment flows. These changes present both challenges and opportunities for Africa, particularly as the continent seeks to leverage the African Continental Free Trade Area (AfCFTA) for economic transformation. This report provides a crucial analysis of these evolving dynamics, focusing on their impact on Africa's automotive sector-a key industry for the continent's industrialisation strategy and at the core of the transformation of global value chains in the last 30 years. Key insights: - A changing global economic order: The past 15 years have witnessed a shift in global trade. This includes the increased importance of semiconductors and services in trade. The rise of East and Southeast Asia, coupled with evolving trade flows and FDI patterns, demands a reassessment of Africa's position in the global economy. - Geopolitical dynamics and value chains: Protectionist policies and trade disputes are disrupting global supply chains and investment patterns, posing challenges for African economies that are deeply integrated into global value chains. Moreover, a global conflict is emerging among economic powers aiming to boost industrial development while disrupting their partners. - Focus on the automotive sector: The automotive industry, a key driver of global economic growth, is undergoing a significant transformation due to the energy transition. Africa's automotive industry faces longstanding challenges. However, emerging opportunities driven by the EV revolution and increasing consumer demand can foster growth. - Case studies - South Africa and Morocco: Two distinct models of automotive development in Africa are examined: South Africa's pursuit of a continental production hub and Morocco's integration into European value chains. Policy recommendations: To harness geopolitical opportunities, the report advocates enhancing regional trade integration through the AfCFTA, diversifying investment sources and fostering a coordinated approach among African policymakers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".