Evaluating the Impact of the African Continental Free Trade Area Agreement on Sustainable Intra‐African Trade and Development: A Differences‐in‐Differences, Propensity Score Matching and Causality Approach

Olajide Oyadeyi and Gbadebo Odularu

Review of Development Economics, 2026, vol. 30, issue 4, 2397-2423

Abstract: The study examined the effects of the ratification of the AfCFTA agreement on the economies of 54 African countries using the Differences‐in‐Differences (Diff‐in‐Diff) regression, the quantile Diff‐in‐Diff regression, propensity score matching (PMS) and Dumitrescu and Hurlin's panel non‐Granger causality tests. The purpose of the study was to understand how the implementation and ratification of the AfCFTA have impacted economic growth, unemployment and migration across the continent, thereby contributing to the AfCFTA literature. Using annual data from 2004 to 2023, the study found that the AfCFTA agreement had significant, positive effects on real GDP across the continent, as evidenced by the treatment and time dummy variables. Furthermore, the findings revealed that the ratification of the agreement led to a reduction in unemployment and an increase in migration on the continent. In quantifying these numbers, the findings demonstrated that the agreement's ratification improved real GDP by $23 billion in Africa post‐implementation, reduced unemployment by 1% post‐implementation and increased the net level of migration on the continent by roughly 2000 migrants. These findings were robust across alternative specifications using the quantile Diff‐in‐Diff method. Regarding the direction of causality, the findings indicate that a bi‐directional relationship exists between real GDP and the regressors, including trade, institutional quality, exchange rates, inflation, lending interest rates, population, investments, foreign direct investments and financial development. As a result, policymakers should prioritise these variables in economic planning and forecasting to achieve sustainable growth, while investors can use them as signals for decision‐making.

Date: 2026
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