Integrating Anticipatory Governance and Causal Layered Analysis: A Novel Theoretical Framework for Long-Term Socioeconomic Development Forecasting

Abstract

This research advances the theoretical foundation of futures studies by developing an innovative methodological framework that integrates anticipatory governance (AG) and causal layered analysis (CLA). Contemporary challenges in long-term Socioeconomic development forecasting necessitate more sophisticated analytical approaches capable of addressing increasing complexity and uncertainty. Through systematic synthesis of AG's governance mechanisms with CLA's multi-layered analytical framework, this study establishes a comprehensive methodology for understanding and shaping future trajectories. The research employs a sophisticated mixed-methods approach, combining quantitative economic analysis with qualitative societal assessment across multiple analytical layers. The findings reveal significant theoretical and practical implications through the framework's enhanced capability for simultaneous consideration of immediate governance requirements and deeper societal transformations. The integrated framework demonstrates particular utility in scenario development, yielding four distinct future trajectories ranging from low growth to transformative change. The preferred scenario, characterized by adaptive change, projects substantial economic advancement whilst maintaining social cohesion and environmental sustainability. This research contributes to both theoretical advancement and practical application in futures studies, providing policymakers with sophisticated tools for navigating complex socioeconomic challenges. The framework's emphasis on combining systematic governance approaches with deep cultural analysis establishes a foundation for more nuanced understanding of development trajectories in emerging economies.