Toward a Statistical Framework for Structural Indivisibility

This project introduces the concept of structural indivisibility as a theoretical and methodological challenge to conventional causal inference in complex institutional systems. It argues that key institutional variables—such as policy roadmaps, administrative capacity, and institutional trust—often form co-constitutive configurations that resist decomposition into independent causal components. Through theoretical analysis and empirical illustration using OECD data, the study demonstrates how standard regression-based approaches may obscure rather than clarify causal relationships in such contexts. The project proposes a shift from decomposition to structural recognition and outlines alternative modeling strategies, including network-based and configurational methods. Implications for policy evaluation, comparative institutional analysis, and methodological innovation are discussed.