Nonlinear causal asymmetries in income inequality, corruption, and market power: evidence from OECD nations using symbolic transfer entropy

This paper examines nonlinear asymmetries in the causal relationships among income inequality, corruption, and market power in OECD countries between 1984 and 2024. It employs a symbolic transfer entropy (STE) framework to overcome limitations inherent in conventional econometrics models. It uses quantile-based binning to represent income inequality, corruption, and market power, ensuring robust performance in the presence of nonnormality and structural variability. Our pooled longitudinal analysis reveals two dominant asymmetric information flows: first, market power exerts directional causal influence on income inequality through corruption as a facilitating mechanism; second, corruption exhibits feedback effects that reinforce inequality dynamics. These findings demonstrate that corruption functions as a critical structural mediator linking competitive conditions to distributional outcomes. Beyond its methodological contribution, this study illustrates how information-theoretic approaches can uncover complex, nonlinear interdependencies that are often obscured by traditional methods. Our results show the importance of integrated policy reforms addressing competition policy and governance simultaneously, offering evidence-based guidance for fostering equitable economic growth in developed economies. The discovery that asymmetric and nonlinear feedback are useful for uncovering and decoding complex interdependencies in the economy, the study shows that symbolic transfer entropy can be helpful in policymaking for combined reforms in governance and competition, which can foster more equitable growth.

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