A Survey on Causal Discovery and Estimation: Theory, Methods, and Applications

The ability to understand and leverage causality separates true intelligence from mere pattern recognition. This survey examines recent advances in causal discovery and estimation techniques, their theoretical foundations, computational implementations, and cross-domain applications. Causal discovery has evolved from a theoretical construct into a practical toolkit for reliable decision-making across diverse domains. We present a comprehensive overview of modern approaches to causal structure identification and effect estimation, emphasizing both methodological innovations and real-world applications in finance, supply chain management, and healthcare.