Structural Equation Modeling of Judicial Efficiency Under Asymmetric Information Constraints: A Bayesian Regularization Framework for Contract Enforcement Optimization

Abstract

This study develops a Bayesian regularization framework integrated with structural equation modeling (SEM) to quantify judicial efficiency losses attributable to asymmetric information in contract enforcement proceedings across common law and civil law jurisdictions. Drawing on longitudinal panel data from 47 jurisdictions spanning 2008–2023, the model incorporates endogeneity corrections, hierarchical latent variable decomposition, and adaptive shrinkage priors to isolate procedural bottlenecks from substantive legal uncertainty. Empirical results indicate that information asymmetry accounts for 34–41% of variance in enforcement duration, with significant heterogeneity across dispute resolution mechanisms. The framework yields jurisdiction-specific efficiency indices that outperform conventional OLS-based benchmarks in predictive validity. Policy implications encompass targeted procedural reform calibration and evidentiary disclosure standardization across transnational commercial arbitration systems.