FISCAL CAPACITY AND MONEY LAUNDERING RISK: THE ROLE OF FISCAL TRANSPARENCY IN STRENGTHENING ANTI-MONEY LAUNDERING FRAMEWORKS

Abstract

The study aims to analyze the relationship between fiscal capacity and money-laundering risk in G20 economies, covering the period from 2012 to 2025. It also investigates the potential to improve fiscal capacity to limit financial crime through better institutional governance and reduced asymmetric information. To provide robust and reliable estimation, empirical analysis involves various tests and methods, including the Cross-Sectional Dependency (CD) test, Second Generation Panel Unit Root Tests, Pooled Ordinary Least Squares (POLS), the Hausman Specification Test, the Driscoll-Kraay Standard Error Fixed Effects Model, and the Generalized Method of Moments (GMM) Estimator. The empirical results consistently show a negative and statistically significant relationship between fiscal capacity and money laundering risk across all estimation techniques. The results show that higher fiscal capacity increases financial accountability and the effectiveness of tax regulation and decreases the room for illicit financial transactions. The high robustness of the results is achieved with OLS, Fixed Effects, Driscoll–Kraay, and GMM, ensuring that the relationship remains stable after controlling for heterogeneity, cross-sectional dependence, and endogeneity. The research provides empirical evidence for Institutional Theory and Information Asymmetry Theory, as the results show that the greater the development of the institutional framework, the lower the information asymmetry and the more efficient the anti-money laundering measures. The study emphasizes the importance of strengthening of fiscal administrative capacity, strengthening international information exchange between tax authorities, and increasing tax regulatory enforcement to address money laundering and financial integrity. The outcome reflects the lack of research on the economic impact of money laundering on developing nations and sheds light on the work of policymakers, tax authorities, financial market regulators, and international bodies to create effective anti-money laundering measures. The study applies robust panel econometric methods, such as the Driscoll–Kraay Fixed Effects Model and GMM estimation, to provide robust empirical evidence that builds on prior research on the relationship among governance, fiscal capacity, and financial crime.