Search published articles


Showing 2 results for Money Laundering

Manizheh Bratzadeh, Javad Harati, Mohammad Lashkari,
Volume 9, Issue 33 (10-2018)
Abstract

Money laundering is an illegal practice that legitimizes the income from illegal activities during a legitimate process.Trade-based money laundering (TBML) as one of the newest and most complicated types of money laundering has negative effects on economic, social and political aspect of a society.The most important objective of the present study is to investigate the effect of various factors on trade based money laundering in Iran using the Ferwerda Gravity model.For this purpose the effective factors on trade base money laundering between iran and some selected trade partners  are investigated by the use of a random effect model during the period 1999-2012. The results indicate that a great significant part of the trade based money laundering flow between Iran and selected trade partners can be explained by the the Ferwerda Gravity model. Accordingly, gorss doimestic product(GDP), trade volume, geographical, cultural, population and attractiveness variables have a significant effect on the amount of trade based money laundering in Iran.This means that with the increase in trade flow, money laundering opportunities resulted from the trade channel, that is hidden in it, will also increase. These results can be used by policy makers for designing policies to combat money laundering particularly coming from trade channel.

Majid Maddah, Mahla Sinaeyan,
Volume 11, Issue 40 (6-2020)
Abstract

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.


Page 1 from 1     

© 2024 CC BY-NC 4.0 | Journal of Economic Modeling Research

Designed & Developed by : Yektaweb