The Effect of Money Laundering and Shadow Economy in a Global Panel Analysis

This paper examines the relationship between money laundering (ML) as well as the shadow economy (SE) with the help of a panel of data from 154 countries, spanning the years 2002 through 2022. The data includes variables about SE, ML and a wide range of socioeconomic and governance indicators (Tax revenue - Percentage of GDP, WGIs, GDP Per Capita, Financial Deposit to GDP, Export to GDP, Import to GDP, Unemployment, Gini index), providing an extensive global coverage. This study examines the bidirectional connection with ML as well as SE and also examines the moderating function of World Governance Indicators (WGIs) to examine how the quality of governance impacts the relationship. Control factors like taxes and GDP per capita, transparency in trade, financial depth, unemployment, income inequality and quality of governance are incorporated based on previous research. The results show a strong two-way connection: ML drives growth in the informal economy, whereas an increased SE assists ML activities. The moderated effect of WGIs is further evidence that strong governance could thwart this illegal cycle. This study fills in a major gap by jointly modeling the relationship with ML and SE across a broad sample and a long period of time instead of treating these two issues in isolation. These findings have significant implications for policy making, suggesting that coordination of fiscal and regulatory or institutional initiatives is necessary in order to defeat both.