Analyzing the Influence of Corruption on Economic Growth: a Static and Dynamic Panel Approach

The main objective of this article is to analyze the impact of corruption on economic growth in 15 countries in the Middle East and North Africa (MENA) over the period 2003–2022. The originality of this article lies in its rigorous methodology, which employs various econometric techniques. Specifically, we use static and dynamic panel data and study stationarity and cointegration between variables. Unlike previous studies that rely on classical econometric models, this study employs a variety of multivariate econometric tools for static panel data, such as Ordinary Least Squares (OLS), Fixed Effects (FE), and Random Effects (RE), as well as recent dynamic panel data techniques. To assess model robustness, we also apply the Generalized Method of Moments (Difference GMM and System GMM). The findings support the “sand in the wheels” hypothesis and highlight the challenges faced by countries in this region. The model’s findings have important policy implications, suggesting the need for anti-corruption efforts and regional economic cooperation. Policymakers can use these insights to develop effective measures to reduce corruption, attract investments, and foster economic growth. However, certain limitations should be acknowledged, including potential issues with data availability and quality. These limitations underscore the need for cautious interpretation and further research to develop a more comprehensive understanding of the relationship between corruption and economic growth.