<![CDATA[This paper investigates whether cash circulation and counterfeit money can be used to predict money laundering activity, proxied by the number of Suspicious Transaction Reports (STRs) filed by reporting institutions. Using a balanced provincial monthly panel dataset covering 34 provinces in Indonesia from January 2022 to December 2024 (1,224 observations), we examine the predictive role of cash inflows, cash outflows, and counterfeit money using panel count models with two-way fixed effects. The results show that contemporaneous and one-month lagged cash variables do not significantly explain STR volumes. However, predictive effects emerge with a delay: at a two-month lag, cash inflows significantly increase the number of STRs, while at a three-month lag both inflows and outflows become robust and economically meaningful predictors. Specifically, a doubling of cash inflows three months earlier is associated with a 41 percent increase in STR counts, and a doubling of cash outflows with a 28 percent increase. By contrast, counterfeit money circulation is consistently insignificant across all specifications and lags. These findings highlight the importance of adopting a medium-term (two- to three-month) monitoring horizon when using cash circulation as an early-warning indicator for money laundering risks. They also suggest that while counterfeit money remains relevant for currency integrity, it does not directly translate into suspicious reporting. The study contributes to the literature by demonstrating the delayed but predictive role of cash movements in shaping money laundering detection.]]>
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