Testing the Economic Costs of Money Laundering

• In Event: Global Rules and Illicit Economic Flows

Abstract

Scholars argue that money laundering causes significant economic harm – including decreased foreign investment, financial instability, and poor economic growth – and identify these economic costs as a potential mechanism driving countries to enforce anti-money laundering laws. Despite this, there is little documented evidence that money laundering causes economic harm. Another potential mechanism behind anti-money laundering enforcement is the risk of sanctioning by the Financial Action Task Force (FATF), an international organization dedicated to combating money laundering. In this research project, I test the effect of two types of money laundering events – FATF blacklisting and news coverage of major money laundering cases drawn from a new dataset – on three potential sources of economic harm: gross domestic product (GDP) per capita, financial instability, and foreign investment. I use the robust synthetic control method, which creates a synthetic control unit from a weighted average of all control units based on key national characteristics in the period before a money laundering event. This method allows for causal inference by creating a counterfactual estimate of economic outcomes in the absence of a money laundering event. I show that FATF blacklisting contributed to a significant decrease in GDP per capita, while major money laundering cases did not significantly affect economic outcomes. This research contributes to the international political economy literature by providing the first quantitative estimates of the economic consequences of two types of money laundering events, and these findings hold important implications for understanding the mechanisms driving international cooperation in anti-money laundering enforcement.

Author

• Karen Nershi, Stanford University