Dynamics of corruption: Theoretical explanatory model and empirical results

Domenico Marino

Physica A: Statistical Mechanics and its Applications, 2025, vol. 658, issue C

Abstract: Corruption silently distorts markets and diverts resources from the public good. This paper explores the cyclical nature of corruption, analyzing corruption from a microeconomic perspective and identifying a relationship between the intensity of state repressive action and the level of corruption. This research offers new insights into the cyclical behavior of corruption, addressing issues relevant to economic policy. An important aspect for understanding corruption dynamics lies in its cyclical behavior. The concept of the corruption cycle has been sufficiently explored at the theoretical level, but empirical evidence remains limited. This paper attempts to fill this gap by constructing a robust theoretical model that elucidates the interaction between sanctions and bribes and between the level of corruption and state intervention as a cause of corruption cyclicality and validating the theoretical findings through empirical analysis using spectral analysis and data mining techniques. The empirical verification of the theoretical hypothesis of cyclicality of corruption opens up interesting scenarios for developing anti-corruption policies.

Keywords: Corruption; dynamical models; data mining (search for similar items in EconPapers)
JEL-codes: K14 K42 R58 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:658:y:2025:i:c:s0378437124007982

DOI: 10.1016/j.physa.2024.130288

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