Terrorism in Africa; Economic Origins, Spillover, and Economic Resilience

The thesis consists of three principal chapters that collectively analyse the complex interplay between terrorism and economics in Africa, highlighting the essential role of institutional quality and offering policy implications and recommendations for stakeholders, including government officials, policymakers, investors, and private individuals. The first chapter examines the drivers of terrorism in African regions, reviewing issues such as poverty, political instability, and institutional quality. This chapter's novelty lies in examining various ideologies of terrorism, including political, religious (both Muslim and Christian), and ethnic ideologies within Africa. Instead of treating terrorism as a homogeneous entity, it is analysed as a multifaceted phenomenon, offering a thorough and detailed examination of the factors influencing terrorism across the continent. The chapter also incorporates other factors, like institutional quality, inequality, and health expenditure, which are not addressed in the current research on terrorism in Africa. This methodology expands the examination of factors that may affect terrorism, classifying them into macroeconomic, social, political, demographic, and institutional categories. To do this, the chapter employs Negative Binomial and Poisson models with fixed effects. The econometric technique was selected for its capacity to precisely address over-dispersed count variables, unobserved heterogeneity, and endogeneity. The findings indicate that corruption is a major catalyst of terrorism in Africa. Conversely, economic progress, trade liberalisation, employment opportunities, robust healthcare systems, and comprehensive democracy have been shown to reduce terrorism. It emphasises how poor institutional quality amplifies the occurrence of terrorism, underscoring the need for more robust governance structures. Moreover, the findings indicate that the overall ideology and classifications of terrorism in Africa do not markedly vary in their drivers from those in other countries or globally. The second chapter examines the spillover of terrorism across several areas in Africa, highlighting the interdependence of states and the transnational characteristics of terrorist threats. This study is innovative in its thorough examination of how terrorism might spread from one region to other regions, especially those with common cultural, linguistic, and economic connections. The chapter utilises Vector Autoregression Analysis (VAR) with Generalized Impulse Response Function (GIRFs) to analyse the possible spillover effects of terrorism across different Africa regions. The study employs the Phillips and Sul (2007) club convergence method to categorise countries with similar terrorism characteristics. Given that our dataset comprises 32 countries, the club convergence estimation is essential, as executing the Generalised Impulse Response Function would necessitate numerous matrices, resulting in 400 impulse response functions. The club convergence technique facilitates a more systematic examination by categorising nations according to common terrorist features or patterns. The chapter employs Principal Component Analysis (PCA) to reduce the dimensionality of these groupings, hence enhancing the usefulness of time series analysis for Vector Autoregression Analysis and Generalized Impulse Response Function estimation (VAR/GIRFs). The findings indicate substantial regional impacts on terrorism dynamics, specifically that terrorism shocks from highly terrorised regions can affect moderately terrorised regions, while shocks within low terrorised areas lead to increased terrorism in the short term, which eliminates over the long term. The chapter emphasises the significance of joint initiatives, like as the Accra Initiative, in curbing terrorism and promoting regional stability. This chapter enhances comprehension of terrorism's international effects and provides critical insights for policymakers in formulating focused counter-terrorism tactics. The third chapter explores the notion of economic resilience, evaluating the recovery of African economies following terrorist attacks. This chapter has three novel contributions; firstly, it proposes the notion of economic resilience concerning terrorism, examining how African economies might recover from the disturbances induced by terrorist actions. Secondly, the chapter incorporates institutional quality into its econometric model, demonstrating how the efficacy and stability of institutions may substantially influence the effect of terrorism on economic resilience. This methodology tackles an important gap in the literature by emphasising the need of robust governance and legal frameworks. The chapter adopts a rigorous methodological framework, employing dynamic panel data estimation using First Difference GMM, System GMM, and Corrected Least Square Dummy Variable (CLSDV) estimators. This approach ensures robust and reliable results, offering a clear understanding of the complex relationships among globalization, economic resilience, institutional quality, and terrorism in Africa. The chapter concludes that good institutional quality is significantly correlated with enhanced economic resilience against terrorism in African nations. The Corrected Least Square Dummy Variable (CLSDV) estimator is recognised as the most dependable and effective technique for assessing the influence of terrorism on economic resilience, providing accurate and consistent results. Collectively, these chapters provide a thorough examination of the intricate relationship among terrorism, economic, and institutional quality in Africa.