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Saeedi Goraghani, Mahsa, Yavari, Kazem. (1403). Assessing the volume of money laundering in Iran’s economy using the capital flight approach. نشریه علمی دانشگاه سیستان و بلوچستان, 16(2), 203-219. doi: 10.22111/ijbds.2024.50417.2174
Mahsa Saeedi Goraghani; Kazem Yavari. "Assessing the volume of money laundering in Iran’s economy using the capital flight approach". نشریه علمی دانشگاه سیستان و بلوچستان, 16, 2, 1403, 203-219. doi: 10.22111/ijbds.2024.50417.2174
Saeedi Goraghani, Mahsa, Yavari, Kazem. (1403). 'Assessing the volume of money laundering in Iran’s economy using the capital flight approach', نشریه علمی دانشگاه سیستان و بلوچستان, 16(2), pp. 203-219. doi: 10.22111/ijbds.2024.50417.2174
Saeedi Goraghani, Mahsa, Yavari, Kazem. Assessing the volume of money laundering in Iran’s economy using the capital flight approach. نشریه علمی دانشگاه سیستان و بلوچستان, 1403; 16(2): 203-219. doi: 10.22111/ijbds.2024.50417.2174

Assessing the volume of money laundering in Iran’s economy using the capital flight approach

International Journal of Business and Development Studies
مقاله 9، دوره 16، شماره 2، اسفند 2024، صفحه 203-219    اصل مقاله (996.34 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22111/ijbds.2024.50417.2174
نویسندگان
Mahsa Saeedi Goraghani1؛ Kazem Yavari* 2
1PhD Student at the Department of Economics, Yazd University. Email: mahsa.saeedi@stu.yazd.ac.ir.
2Professor of Economics, Department of Economics, Yazd University. Email: kyavari@yazd.ac.ir.
چکیده
Money laundering refers to the concealment of the illegal origin of proceeds obtained from criminal activities, making it appear as if they stem from legal sources. This phenomenon has numerous negative impacts on various economic and social spheres; thus, the countries` authorities - alongside international bodies - have sought to combat it by enacting the necessary laws and regulations and enforcing them. This collaboration occurs to prevent the establishment of a free zone for money laundering and ensures that the efficiency of enforcing these regulations is not disrupted. Iran, due to being in the financial Action Task Force (FATF) blacklist, is considered a free zone from this perspective. This makes the research on evaluating money laundering methods applicable to this country and also makes selecting suitable methods significant and appealing. Therefore, this study utilized the findings of the study by Hendriyetty and Grewal (2017) and, considering the information limitations in Iran, employed a combination method using capital flight approach as an index for measuring money laundering. The results of the research indicate that over a 28-year period, from 1995 to 2022, approximately 553 billion dollars have been laundered in Iran, averaging about 20 billion dollars annually. The highest amount of money laundering in Iran occurred in 2011, during which nearly 55 billion dollars was laundered in the country. Additionally, the observations show the lowest amount of money laundering at around 4.8 billion dollars in 2001.
کلیدواژه‌ها
money laundering؛ capital flight approach؛ combination method
مراجع
  1. Carton, Ch., Slim, S. (2018). Trade mis invoicing in OECD countries: what can we learn from bilateral trade intensity indices? COLECH, Cemafi-International. Online at https://mpra.ub.uni-muenchen.de/85703/ MPRA Paper No. 85703.
  2. Ardabili, H (2003). Money laundering, Methods, and Its Effects in Iran and the World. Economic Research Journal, 3(10), 177-198.
  3. Central Bank of Iran Website. https://cbi.ir/page/8086.aspx.
  4. Claessens, S. and Naude, D. (1993). Recent Estimates of Capital Flight, The World Ban. Debt and international finance. New York, NY.
  5. Eulaiwi, B., Shareef Khalaf, N., Al-Hadi, A., Duong, L., Taylor, G. (2024). Money laundering governance and income shifting: Evidence from Australian financial institutions. Economic Modelling. 132(2):106653. https://doi.org/10.1016/j.econmod.2024.106653.
  6. Ferweda, J., Saase, A.K., Unger, B., Getzner, M. (2020). Estimating money laundering flows with a gravity model‑based simulation. Scientific reports. https://doi.org/10.1038/s41598-020-75653-x.
  7. Frunza, M.Ch. (2016). Money Laundering in Financial Markets. Introduction to the Theories and Varieties of Modern Crime in Financial Markets, 153-164. https://doi.org/10.1016/B978-0-12-801221-5.00011-7.
  8. Hendriyetty., N., Grewal S., (2017). Macroeconomics of money laundering: effects and measurements. Journal of Financial Crime. 24(1). 65 – 81. DOI: 10.1108/JFC-01-2016-0004.
  9. International transport and insurance costs of merchandise trade (ITIC) (2024).https://www.oecd.org/en/data/datasets/international-transport-and-insurance-costs-of-merchandise-trade itic.html.
  10. Kar, D. and LeBlanc, B. (2014). Illicit Financial Flows to and from the Philippines: A Study in Dynamic Simulation, 1960-2011. Global Financial Integrity. available at: http://philippines.gfintegrity.org/index.html.
  11. Khajavi, M., Rezayi, E., Khodaveisi, H. )2010). Estimating dirty money and investigating its consequences in Iran's economy: the approach of the Bound Test. Quarterly Journal of Quantitative Economics. 7(4), 81-99.
  12. Madah, M. & Sinanian, M. (2020). Empirical Analysis of the Trend of Money Laundering in Iran (An Approach Based on Partial Least Squares Structural Equation Modeling). Journal of Economic Modeling Research, Issue 40, 99-122.
  13. Marini, M., Dippelsman, R., Stanger, M. (2018). New Estimates for Direction of Trade Statistics. International Monetary Fund.
  14. Maximilian, F. and Teichmann, J. (2017). Twelve methods of money laundering. Journal of Money Laundering Control. 20(2), 130-137. http://dx.doi.org/10.1108/JMLC-05-2016-0018.
  15. Moreira, T., Sachsida, A., Loureiro, P.R. (2012). A Dynamic Model of Organized Crime and Money Laundering. Economics and Finance Review. 1(11) pp. 42 – 47. http://www.businessjournalz.org/efr.
  16. Quirk, P.J. (1996). Macroeconomic implications of money laundering. Trends in Organized Crime. 2(3), 10-14.
  17. Shiva, R. & Mikaeili-Pour, H. (2007). The Negative Economic Effects of Money Laundering on Economic Development. Journal of Knowledge and Development (Scientific-Research), Issue 21.
  18. Unger, B. (2009). Measuring Global Money Laundering: "The Walker Gravity Model". Review of Law & Economics.5(2). DOI:2202/1555-5879.1418.
  19. Veiga, L., Andrade, J., Oliveira, A. (2006). MONEY LAUNDERING, CORRUPTION AND GROWTH: AN EMPIRICAL RATIONALE FOR A GLOBAL CONVERGENCE ON ANTI-MONEY LAUNDERING REGULATION. Latin American and Caribbean Law and Economics Association (ALACDE) Annual Papers, Berkeley Program in Law and Economics, UC Berkeley. https://www.researchgate.net/deref/http%3A%2F%2Fescholarship.org%2Fuc%2Fitem%2F33f4z9x6?_tp=eyJjb250ZXh0Ijp7ImZpcnN0UGFnZSI6InB1YmxpY2F0aW9uIiwicGFnZSI6InB1YmxpY2F0aW9uIn19.
  20. Walker, J. (1999). How Big is Global Money Laundering? Journal of Money Laundering Control. 3(1), 25-37. https://doi.org/10.1108/eb027208.
  21. Website of International monetary Funds. Exports to Counterpart Countries - IMF Data. https://data.imf.org/regular.aspx?key=61726508
  22. Website of International monetary Funds. Imports from Counterpart Countries - IMF Data. Imports from Counterpart Countries - IMF Data.
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