The Empirical Analysis of Money Laundering Trend in Iran (by Using PLS-SEM Method )

Money Laundering (ML) reduces the confidence of investors to the financial market, worsen political instability and deviates resources allocation to unproductive sectors by weakening of financial institutions credit. In the ML, illegal resources are entered into the legal economy secretly and outside formal control whereby it has hidden nature. The aim of this paper is to study the different sizes ML and its changes in Iranian economy in the context of latent variables literature using Partial Least Squares Structural Equation Modeling (PLS-SEM) over the period 1360 to 1396. According to the results from paper firstly, drug trafficking and theft crimes have a positive and significant effect on ML trend. Besides that, economic conditions influence an individual’s motivation to enter illegal activities. Secondly, ML growth is associated with decreasing economic growth and increasing the volume of cash that waste economic stability. Thirdly, ML has an upward trend which based on it can be anticipated that in spite of crimes growth, especially drug trafficking, the increasing trend of ML will continue.